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Research Ops 101: Using the Research Ops Framework to Build a Thriving Research Practice

Learn how to effectively intercept users for research without disrupting their workflow using ethnio's targeting features and incentives in this comprehensive guide., why is research ops important.

Research Ops helps organizations make more informed decisions, improve the user experience of their products or services, and drive business growth by aligning research efforts with strategic objectives.

The aim is to optimize research efforts' efficiency, quality, and impact while enabling better collaboration and knowledge sharing among researchers, facilitating cross-functional teams to access and leverage research findings.

re+ops, the world's biggest Research Ops community, outlined several core reasons why the practice is essential :

Protecting participant privacy

Making research easier to do (i.e., democratizing research )

Operationalizing respect for the people who participate in our research

Magnifying the impact of our research (knowledge sharing)

Research Operations uncovers tensions, bridges communication gaps, and helps teams be more effective. Elham Ali Design Researcher at Beeck Center for Social Impact & Innovation The Research Ops Framework

The re+ops community created a framework to define Research Ops, its functions, and its responsibilities within an organization. The initiative used survey data and outcomes from 33 #WhatisResearchOps workshops worldwide to highlight twelve key Research Ops elements.

This framework can enhance your understanding of Research Ops and enable you to structure operational systems and procedures using global best practices.

Knowledge management

Internal communications

Asset management, budget management, research spaces, participant recruitment, event management, team building and care, capability & opportunity, guidelines and templates.

The DIKW Pyramid — image credit: Ontotext

Knowledge management is the strategic and systematic approach of capturing, organizing, and leveraging research insights and information within an organization. It involves creating processes, tools, and systems that enable researchers —and other team members— to effectively store, share, and access knowledge generated through research activities.

Knowledge management aims to facilitate collaboration, knowledge sharing, and reuse of research insights across teams and projects, ultimately enhancing the organization's ability to make informed decisions based on user-centric data.

Some core components of knowledge management include:

Content management systems

Documentation of research findings

Research roadmaps

Centralized data repositories

Sharing— research, tools, findings, etc.

Best practices

Packaging research

Universal research vocabulary

Data gardening—retention schedule & archiving

The internal communications element is directly linked to knowledge management and involves establishing effective channels and processes for communication within the research team and across the organization. It ensures smooth information flow, collaboration, and alignment among researchers, stakeholders, and other teams.

Effective internal communications enable Research Ops to enhance collaboration, reduce duplication of efforts, and promote a shared understanding of research goals and outcomes within the organization.

Some core components of internal communications include:

Reporting—quarterly, customer, etc.

Information architecture

Platforms for socializing research

Asset management includes organizing and maintaining a centralized repository of raw and processed data, including research-related assets, such as research reports, participant data, interview recordings, and design artifacts. UXRs must make this data accessible, findable, and useful for team members while adhering to security and permissions.

Some core components of asset management include:

Findable assets

Security & privacy

Centralized storage and distribution

Effective storage for RAW data—i.e., unedited A/V

Managing personal identifiable information

Permissions

Tools are the software and platforms that facilitate various research activities, such as participant recruitment , data collection and analysis, collaboration, and knowledge management.

Research Ops tools fall into five primary categories:

Participant recruitment platforms streamline finding , recruiting participants , scheduling , and paying for research studies, ensuring representative and diverse user samples.

Research management platforms help manage and track research projects, participant recruitment, scheduling, and logistics, streamlining the end-to-end research process.

Data collection and analysis tools enable researchers to collect and analyze qualitative and quantitative data, such as surveys, interviews, usability testing, and analytics, providing valuable insights for decision-making.

Collaboration and communication tools facilitate seamless collaboration among researchers, stakeholders, and team members, enabling efficient knowledge sharing, feedback exchange, and project management.

Knowledge management systems assist in organizing, storing, and retrieving research assets, such as reports, insights, and design artifacts, making them easily accessible and reusable across the organization.

Some core components of tooling include:

Help me find the right tools

Tool sets—hardware, software, A/V equipment

Management—permissions, licenses, users, staff onboarding

Procurement

Planning of tools

Ethnio— a user research CRM to solve common UXR pain points

Before Ethnio, many customers:

Managed an Amazon account to send individual incentives—a lot of wasted time and resources

Didn’t do any live/in-the-moment participant recruiting—enter Intercepts

Manually created each calendar event for their sessions, which Ethnio’s Scheduling automates for both Google Calendar and Outlook.

Managed a participant database in a tool like Airtable, which is fine, but doesn’t have the complexity of Ethnio Pool with rules and governance, tracking, and automations.

Budget management is the planning, allocating, and tracking financial resources for research activities. It ensures that research projects are executed within budgetary constraints while maximizing the impact and value of the research investments.

Effective Research Ops budget management must consider these five factors:

Budget planning: Research Ops teams collaborate with stakeholders to define the research goals, objectives, and scope to estimate the required resources and associated costs.

Cost estimation: Based on the research requirements, Research Ops teams assess the costs involved in participant recruitment, research tools, technology, travel expenses, incentives, and other research-related expenses.

Budget allocation: Once the budget is determined, Research Ops teams allocate funds to various research projects, ensuring an appropriate distribution of resources based on priorities and strategic objectives.

Expense tracking: Research Ops teams monitor and track expenses throughout research projects, ensuring that spending aligns with the budget. They also identify potential cost overruns or variances and take necessary measures to mitigate them.

Reporting and analysis: Research Ops teams provide regular budget reports to stakeholders, outlining the utilization of funds, highlighting any significant variances, and providing insights into the return on investment from research activities.

Some core components of budget management include:

Tracking operational spend

Synching with broader budgetary processes

Budget approvals

Budget allocations per project

Research spaces are the physical or virtual environments where research activities take place. UXRs must design spaces that foster high-quality research, support seamless collaboration, and enhance the research experience for researchers and participants.

Researchers must consider procedures and protocols for these five essential research space components:

Physical research spaces: are dedicated rooms or facilities equipped with appropriate tools and equipment for conducting in-person research sessions, such as usability tests, interviews, or focus groups. Research Ops teams ensure these spaces are well-designed, comfortable, and equipped with the necessary technology and recording capabilities.

Virtual research spaces: include online platforms, video conferencing tools, and collaboration software that enable researchers to conduct remote studies, engage with participants, and facilitate remote collaboration among research team members.

Lab management: UXRs must manage and maintain physical research spaces, including scheduling, resource allocation, and ensuring the spaces are appropriate for each research session, including coordinating with facilities management, IT/AV support, and other stakeholders to ensure a smooth research environment.

Participant management: coordinate with participants, providing them with necessary instructions, directions, and any required equipment or technology to ensure a seamless research session.

Accessibility and inclusivity: Research Ops teams consider accessibility and inclusivity when designing and managing research spaces. They ensure that spaces and tools are accessible to participants with different abilities and accommodate diverse user needs.

Research Ops teams ensure research studies have the right participants , leading to more accurate insights and informed decision-making. They streamline the recruitment process, optimize participant selection, and create a positive experience for participants, enhancing the overall research operations within an organization.

Here are some of the key UXR responsibilities of participant recruitment:

Participant sourcing: Research Ops teams collaborate with researchers and stakeholders to define the target audience for research studies. They employ various methods to source participants , such as intercepts , recruiting from existing user databases , utilizing recruitment agencies, or leveraging online platforms and communities.

Screening and qualification: Research Ops teams must screen participants to determine their suitability for specific research studies. Screening involves assessing participants' demographics, background, experience, or any specific criteria defined for the study.

Consent and incentives: the administrative tasks related to participant recruitment, such as obtaining informed consent from participants, managing confidentiality agreements, and facilitating the provision of incentives or compensation for their time and effort.

Scheduling and logistics: UXRs coordinate with participants, team members, and stakeholders to schedule research sessions , ensuring their availability aligns with the research timeline. They handle logistics, such as sharing session details, preparing participants for the research process, and addressing any questions or concerns they may have.

Participant database management: a participant database captures and stores relevant information about participants, their preferences, and their history of participation. This database helps streamline future recruitment efforts and enables efficient participant management for ongoing research initiatives.

Some core components of participant recruitment include:

Quality for the price

Manage both internal and outsourced recruitment

Engaging with external recruiters

Managing recruitment tools

Incentive management

Need to understand design and research

Managing a secure database of consent forms

Thanking respondents

Developing and maintaining a diverse customer panel

Governance refers to establishing and implementing frameworks, processes, and policies that ensure research activities are conducted effectively, ethically, and in alignment with organizational objectives.

Clear governance procedures are especially critical for research democratization because they provide non-researchers with the frameworks, guardrails, oversight, tools, and processes to conduct proper research.

Here is a high-level overview of Research Ops governance and what UXRs must consider for effective implementation:

Research standards and guidelines: establish and communicate research standards and guidelines to maintain consistency and quality across research projects, including research methodologies, ethical considerations, data privacy regulations, and reporting requirements.

Compliance and ethics: standards related to research, such as obtaining informed consent from participants, protecting participant privacy and data, and adhering to industry regulations and guidelines.

Documentation and reporting: Ensure findings, insights, and recommendations are adequately recorded and shared with relevant stakeholders. UXRs establish templates and guidelines for research documentation, making it easier for teams to capture and communicate their work effectively.

Stakeholder alignment: UXRs facilitate communication channels, such as regular research meetings or reporting mechanisms, to share research insights, validate findings, and gather feedback.

Process optimization: Identify bottlenecks, streamline workflows, and implement best practices to optimize the research operations and enable researchers to focus on generating valuable insights.

Risk management: Identifying potential biases, ensuring data security and privacy, and implementing safeguards to protect participants and intellectual property.

London based research team in a UXR workshop. Image credit: Dave Hora .

Researchers are responsible for event management, including planning, coordination, and execution of research-related events, such as user research sessions, workshops, conferences, or training programs. UXRs ensure that sessions and activities run smoothly, participants have a positive experience, and they meet event objectives.

Some core components of event management include:

Arranging distinguished speakers

Social events

Company events

Team meetings

According to re+ops findings, "Research Ops is as much about people and forging relationships and connections as it is about efficiency, support, and data." This framework element celebrates team members, helping to recruit and retain them longer— especially in remote organizations where team members are more likely to feel disconnected .

Some core components of team building and care include:

Celebrations

Pre-approved counseling service

Secondment opportunities

Onboarding new staff

Image credit: re+ops community .

Developing researcher career progression is essential for growing the research team's experience, skill sets, confidence, and opportunities. This personal and team growth enhances their professional development and contributes to the overall success and effectiveness of the research operations within the organization.

Some core components of capability & opportunity include:

Professional development opportunities

Research skills and maturity matrix

Mentoring opportunities

Training opportunities

Book or reading club

Peer review sessions

Sparring sessions

Image credit: Rodrigo Dalcin .

Guidelines and templates help maintain consistency, efficiency, and quality in research activities. They enable researchers—and non-researchers—to focus more on the research rather than reinventing processes or struggling with documentation. These guidelines lead to improved research outcomes and better-informed decision-making within the organization.

Some core components of guidelines and templates include:

Database of methods

Shared templates & methodology = shared understanding

Research briefing and reporting templates

Maintaining the content

Platform for sharing guidelines and templates

Clear guidelines and rules

How-to guides

Recruitment guidelines

Ethics guidelines

Customer contact guidelines

The Eight Pillars of Scaling Research Ops

The re+ops community has also devised the eight pillars of Research Ops . The community-driven initiative created a strategy for scaling research and ResearchOps. Once you have a research operations practice, you can use this framework as a checklist to identify problem areas, bottlenecks, and inefficiencies and implement effective solutions.

User Experience Research and Design Leader at Meta, Emma Boulton, summarized the eight pillars of Research Ops in a Medium article.

Environment: Why does research happen, and who engages with what I do?  

People silos

Value of research

Internally focused

Stakeholders

Scope: How and when does research happen? What methods?

Cadence 

Sharing insights

Prioritization

Integrating insights

Research as a team sport—democratization

Recruitment and admin: How do I manage all the project and participant admin?

Panel management

Participant coordination

Data and knowledge management: What happens to the findings, data, and insights?

Research library

Data gardening

Document templates

People: Who is responsible for carrying out research?

Community of practice

Professional development

Mature career paths

Organizational context: What are the internal and external constraints?  

Business constraints

Market forces

Org maturity

Governance: What are the legal and ethical considerations?

Risk assessments

Tools and infrastructure: What systems and tools do I need for my projects?

Building a research ops team.

Building a Research Ops team will vary depending on the organization's maturity, market, products, and other factors.

Hiring a Research Ops Manager or Research Operations Specialist first is often recommended. These roles are responsible for establishing the foundation of research operations, defining processes, and ensuring the smooth execution of research activities. 

Once the core team members are in place, the Ops manager or specialist can consider additional roles such as Knowledge Manager, Tools and Technology Specialist, and Training and Development Specialist based on the organization's specific needs and priorities.

Here are several Research Ops positions:

Research Ops Manager : oversees the overall operations of the Research Ops team, manages resources, and aligns the team's activities with organizational goals. They play a crucial role in developing strategies, establishing processes, and driving continuous improvement in research operations.

Research Operations Specialist : responsible for executing and managing day-to-day research operations. They handle various administrative tasks, such as participant recruitment, scheduling research sessions, managing research tools and platforms, and ensuring smooth logistics for research activities. They work closely with researchers to provide support and ensure research activities run efficiently.

Knowledge Manager : focuses on managing research knowledge and insights within the organization. They develop systems and processes for organizing, storing, and sharing research findings, ensuring that knowledge is easily accessible to relevant stakeholders. They also facilitate knowledge transfer and collaboration among researchers, enabling the efficient reuse of research assets and insights.

Technology Specialist : responsible for evaluating, implementing, and maintaining research tools and technologies. They stay updated on the latest research tools and methodologies, identifying opportunities to enhance research capabilities and efficiency. They provide technical support, train researchers on tool usage, and explore ways to optimize research workflows through technology.

Training and Development Specialist : focuses on building the research skills and capabilities of the team. They develop training programs, conduct workshops, and coach researchers to enhance their research methodologies, techniques, and soft skills. They also stay informed about industry trends and best practices, keeping the team up-to-date with the latest advancements in research methodologies.

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Home / Books / Research That Scales

Research That Scales

The research operations handbook.

By  Kate Towsey

For the most part, the battle of establishing research teams in organizations is won. For leaders of research, design and product teams, there’s a new challenge: How do you support and scale your research activities to meet the ever-increasing demand and deliver on the promised impact? Around the world, leaders are turning to Research Operations for help.

Research At Scale: the Research Operations Handbook will help you find your operational muscle – even if you don’t think you have one. Within these pages, you’ll find the information you need to confidently deliver operations that will help you build a research practice that is scalable, ethical, efficient and impactful, whether you’re a team of five or five hundred.

Table of Contents

Chapter 1: Mistakes and Master Strokes

Section 2: Setting Foundations and Fundamental Concepts

Chapter 2: Research Ops Isn’t Research Strategy Chapter 3: Self-service vs. Full-service Operations Chapter 4: The Three Bs of Operations: Build, Buy, Broker

Section 3: Research Maturity and Ops

Chapter 5: When to Operationalize: A Maturity Map Chapter 6: Find Your Place on the Map

Section 4: The Twelve Elements of Research Ops

Chapter 7: Participant Recruitment Chapter 8: Data Governance Chapter 9: Knowledge Management Chapter 10: Research Spaces Chapter 11: Guidelines and Templates Chapter 12: Tools and Technology–Implementation and Management Chapter 13: Finances: Getting the Money Right Chapter 14: Capability and Opportunity Chapter 15: Impact and Engagement Chapter 16: Event Management Chapter 17: Team Care

Section 5: Common Pitfalls

Chapter 18: Underestimate at Your Peril Chapter 19: Professionalizing Unprofessional Research Chapter 20: Goldilocks Ops

Section 6: Ready. Set. Go. And keep going.

Chapter 21: Get Buy-in to Get Going (and Keep Going) Chapter 22: Grow Your Team Right: Skilling up for Operations Chapter 23: Measure your Ops Chapter 24: Build for Organizational Resilience

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Research Ops: What it is, why it’s so important, and how to get started

Table of contents

1. Research Ops: What it is? 2. Research Ops: Why it’s so important? 3. Research Ops: How to get started? 4. Final Words

1. Research Ops: What it is? 

First of all, ResearchOps are relevant in different industries, from It and software to the space business . It is the shorter version of Research Operations. It is similar to DevOps, SalesOps, and DesignOps, which are used to operationalise specific departments of the company, as can be understood from their names. Even though related, the job roles similar to the Ops Research Assistant are still too new to have a descriptive research report as yet. However, the closest definition describes the term as anything that supports researchers by easing their shoulders off operational work. It can be anything from people, strategy to software. If it causes researchers to save time from data collection and processing for data analysis, it can be considered Research Ops.

1.1 Research Ops: Purpose in a company

Research Ops aims not to help a single scientist or analyst, but to make the department reach its optimum efficiency and effectiveness in a company. The goal is achieved in the following ways:

• Automating tasks
• Taking care of the logistics behind quantitative research
• Creating a framework for both quantitative & qualitative research
• Establishes a workflow and process
• Initiating repeatable methods
• Ensuring that the process and implementation matches the strategy

2. Research Ops: Why it’s so important? 

With the increase in competition in the consumer world, customer centricity is gaining more and more importance. Businesses and entrepreneurs are increasingly moving towards niche marketing and customisation. The importance of a unique selling proposition has reached newer heights. But where does Research Ops fit in all this? With companies focusing on consumer insights, which is a changing phenomenon, quicker access to reports or the research paper outline has become almost mandatory. The emergence of this requirement sheds light on the pressure created on the Research & Development department and the need for operationalisation for faster processing.

To put it into simpler words, the following are the main requirements of a company’s R&D department that the Research Ops helps in meeting:

Usability : Research Ops makes it possible for different departments to access any research data needed by them from a central operating system or software. As a result, everything from a research proposal, research paper outline, status, and analysis to reports becomes accessible to anyone within the company. In addition, it makes usability very easy, thereby improving the quality of the product and changing the overall focus and vision of the company.

Productivity : Research Ops promotes developing a framework, templates like research proposal example, workflow, and repeatability methods to ensure saving maximum time on operational work. It is an umbrella with several components that manage to reduce the processing time to a large extent, hence optimising efficiency. Here you can find some valuable tips on how to scale UX research.

Cost-Efficiency : The same factors affecting the efficiency of the R&D team of a company also helps in cost-cutting. A proper strategy, well-researched, and experimented method makes Research Ops responsible for saving budget and managing many other factors controlling and affecting the smooth operation of the department.

Quick reports : The automatisation and workload division with Research Ops helps the team produce quick and almost dynamic reports matching the spontaneously changing consumers. It allows companies to evolve with incredible speed and enjoy a competitive edge over others in the same industry.

With the growth and scaling of companies, the operationalisation of departments becomes necessary. The reason being, increase in sales affects each department, impacting the workload exponentially. Therefore, efficiency, resource-saving, and smart work become the ultimate goal in the growth stage of startups. And why not?! The management of several departments becomes an unknown territory for companies going through a sudden transition from a one-room startup to a multi-departmental corporation. Hence, the emergence of systems like DesignOps, DevOps, SalesOps, and now ResearchOps, for easy management of several departments. It also signifies that these Operational Practices are responsible for more than one component in a department, and so is the case with Research Ops as well.

2.1 Research Ops: The eight pillars or components

A R&D department has eight areas of operation which need the attention of the team. These areas, from time to time, cause hindrances in smooth and fast report delivery. Research Ops makes the process and delivery of consumer insights reports seamless, irrespective of the research question, team requirements, and challenges, making them the eight pillars of the practice.

2.1.1 Budget management

Similar to any other department, R&D also has its own expenses, which need proper planning and management. For example, some standard heads in a budget include salaries or fees to recruiting participants, travel expenses for outdoor research, regular costs of licenses, online tools and software, etc. The Research Ops solves the budgeting challenges by bringing a proper structure where the outflow is tracked and accounted for. In addition, allocating the budget for new research paper topics by negotiating with the company’s finance team for approval also falls under the responsibility of the Research Ops.

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2.1.2 Tools and infrastructure

Analysing and evaluating user data, both quantitative and qualitatively, requires maintaining a lab with software and other IT tools. Since IT may not be the forte of researchers, the team may need to coordinate with the responsible departments for smooth functioning. Besides being a liaison between departments, Research Ops also takes care of the lab infrastructure over time.

Toolbox with templates for measuring UX KPIs

The free toolbox reliably supports UX researchers with user experience evaluations. It allows a valid, trustworthy and objective measurement of user perception. The three relevant KPIs—Single Ease Question (SEQ), Net Promoter Score (NPS) and System Usability Scale (SUS)—help you to better assess risks and derive improvements based on them.

2.1.3 Data and knowledge management

With the growing size of data and topics, data management and reports become increasingly difficult. Hence, forming a data repository becomes a significant role of the Research Ops to make the data accessible to the entire company from a central system. The emergence of operative practice also introduces structure into the R&D department. One of the first activities of the practice is to create a strategy for data collection, analysis, archiving, and sharing. The standardisation of a framework process makes a systematic direction for the R&D team, helping them to increase efficiency in their delivery.

2.1.4 Documentation

Scaling in a team indicates an increase in people, which instantly reveals the need for a system. A more significant number of people not only requires management but they are easily lost and confused. Thus, it becomes the Research Ops’ responsibility to develop a framework for processing, analysis, and reporting of the people in the R&D team. The documentation of frameworks like how to write a research paper, guidelines, etc., makes it easy for any new member to learn the process and quickly fit into the role. An adequately documented framework ensures consistent, high-quality reports without compromising on efficiency.

2.1.5 Internal communication

The R&D department is one area that every department uses, which indicates the role of internal communication. Research Ops takes the responsibility of socialising within the organisation in emails, newsletters, blogs, etc., to share monthly reports, latest findings from the department.

2.1.6 Sample pooling

User insights always require sample subjects for participation; however, attracting these participants for data collection from the desired demography is a massive task. Therefore, Research Ops strategies incentives based on the demography and then builds a pool of subjects for participation and aid in the data collection.

2.1.7 People

Again, human resource management and recruitment are needed in every department. Research Ops monitors the team’s requirements in terms of hires, training, skill learning, mentorship, conducting off-site or on-site meetings, etc.

2.1.8 Governance

Today, the privacy and security of user data is a sensitive topic. The Governance section of Research Ops assures that the collection, processing, and storing of information is ethically abiding by the legislation. In this article, you can find all the information you need to know about UX research.

3. Research Ops: How to get started

The scope of Research Ops can seem overwhelming in the beginning. Despite its possibilities, one of the most common worries surrounding the practice comes from companies asking how to get started? Since it covers eight pillars and each of the eight areas has a department of its own in a company, it can seem like a massive task. However, the key to a successful Research Ops team is taking it slow. Similar to a business idea, one of the first steps to starting the operative function requires finding its necessity through communication within the team.

Leading companies like Microsoft, Spotify, and Deliveroo pointed out that their R&D team became good at multitasking with the growth of the company. While it sounded great to the ears, the reality was that the team was giving away time from the job that they were hired to do, like studying customer needs, developing strategy, etc. Some even realised the blurry lines between their job requirements, noting that there was no ending to the list of jobs, while they knew where they had to start. Another big challenge that Microsoft said was the absence of documentation could cost the R&D team making similar expensive mistakes again in the future. Finding the challenges to the respective team became the first step to developing Research Ops in the companies described above.

3.1 Steps to build Research Ops

Following the footsteps of the well-known organisations with successful Research Ops, mentioned below are the four easy steps on how to get started:

3.1.1 Communication

Follow the format of a feedback form to ask your team the challenges they face. If the unit cannot find any obstacles, take a detour and ask about their tasks during the day. Suppose they have any suggestions for improvement. If forming questions is a difficulty, then concentrate on how the four areas mentioned below affect the respective team in the questionnaire:

• Environment: What is the process? How are the participants found? Any constraints in the data collection or processing.
• Scope: Frequency, methods, how and when of the research process.
• People: Strengths and weaknesses of the team.
• Organisation: Questions regarding task division, structure, internal communication.

3.1.2 Audit and analysis

Similar to data processing, after the collection of responses, audit and analyse to find the significant challenges faced by the team. Create a spreadsheet with the report of the findings for the next step in developing Research Ops. However, before moving forward, classify the challenges into areas, for example:

• Human Resource Management & Recruitment
• Data Archiving & Knowledge Management
• Tools & Infrastructure

3.1.3 Start small

Post classification, it becomes much easier for a company to start Research Ops. However, again, it is best to not concentrate on all challenges in one go. Instead, it is best to begin by focusing on one area, solving the challenges, and moving to the next.

3.1.4 Grow and evolve

Once the Research Ops gets started, similar to other company departments, let it proceed and evolve to find continual challenges the R&D team faces. Then, with regular communication and feedback from the team and auditing responses, the Research Ops can grow and get a comprehensive structure for itself.

4. Final Words

It is interesting how certain companies can’t have enough Research Ops, while others are yet to realise its need. The bandwidth of the practice is so large that in larger companies where research is an integral part of the company practices, they have already started crossing interdisciplinary ops for better integration. However, before jumping to conclusions and following the trend, it is necessary to lay out the challenges of the R&D and scopes of Research Ops. The absence of planning and rushing can lead to budget wasting, says Spotify Research Ops lead. She made the mistake of giving away tasks to Research Ops that the researchers couldn’t have handled, and thus emphasises planning before execution.

Maggy Mächler

Maggy is a Senior B2B Marketing Manager with a background in Business Psychology. She’s passionate about driving software products and exploring user behaviour. Maggy contributes to the UX Research community through various content formats, from long-form articles to social media takeaways. She organizes user research talks, always seeking new angles and providing valuable input.

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Research Ops

What is Research Ops: The Complete Guide to UX Research Ops

Written by: Phil Hesketh

Published on: 28 Feb, 2023

The term and the role of research ops encompasses everything that's needed to set a user research project in motion.

Learn everything there is about research ops, and find out how to create a research ops program within your organization.

What is Research Ops?

Research Operations (also known as Research Ops, or ReOps) is an emerging field, and one that is rapidly being adopted by companies who rely on UX research to grow their business.

As described by the  ResearchOps Community :

“ResearchOps is the people, mechanisms, and strategies that set user research in motion. It provides the roles, tools and processes needed to support researchers in delivering and scaling the impact of the craft across an organization”

The community also created the  visual framework  below, which defines the elements of Research Ops to help shape this emerging practice.

Image source: ResearchOps Community

A ReOps program manages both the people, roles, tools, and processes that carry out user research. It can function alongside other similar operations teams, such as DevOps and Design Ops.

Kate Towsey , Research Ops Manager at Atlassian defines it as:

“Offering support and infrastructure to ‘people who do research’. This is because in a lot of bigger organizations like Atlassian, it’s not just researchers doing research, there’s also PMs and designers doing research”

User research has, up until recently, been a part of a UX designer role. But organizations have realized the impact of quality research on their growth, and now have teams dedicated solely to the pursuit of UX research.

As these teams scale, it becomes difficult to manage the people, tools, costs, and processes involved in UX research, which is how the role of Research Ops evolved.

Research Ops enables busy UX researchers to plan, conduct, report on, and apply the findings of their research at scale—while at the same time improving their productivity and helping them to overcome the many roadblocks and challenges they face in their daily work.

So if you’re looking for a way to identify opportunities to grow, improve efficiency, and make faster and better informed business decisions, creating a Research Ops program to support your UX researchers can help you reach these goals faster.

What are the benefits of Research Ops?

Although Research Ops is still in its infancy, it’s a powerful advantage for growing businesses who want to scale their research initiatives (and keep their UX researchers sane).

UX as a discipline has grown exponentially around the world since the 1950s. The Nielsen Norman Group predicts that there will be over 100,000,000 UX professionals by 2050.

So with more companies getting on board with UX research, and more people choosing UX research as a career, finding ways to scale research practices to ensure high quality research and keep up with demand is essential. And that’s where Research Ops comes in.

The key benefits of implementing a ReOps program for your business include:

Your UX researchers will be able to breathe a huge sigh of relief once Research Ops is up and running.

With the support of this program, researchers can focus directly on the tasks that move the needle to enhance user experience. They’ll also reach their goals faster and be able to maintain higher research standards.

A ReOps team will analyze all of your current research processes, create operational strategies to ensure that future research is more efficient and consistent, and help to action those steps.

This can significantly reduce repetitive admin tasks, save time, and create smooth, efficient, and repeatable processes for your researchers.

The growing and changing global laws around data consent and compliance means many organizations could find themselves in a sticky legal situation if they don’t have systems in place for managing personal data.

A Research Ops program can give you peace of mind by ensuring that research teams aren’t overlooking consent and compliance.

Appointing somebody who is responsible for creating processes and workflows to ensure you’re adhering to rules and regulations like GDPR and CPRA means you’ll significantly reduce your risk of non-compliance.

Cost savings

Tired of having those awkward conversations about budget blowouts?

UX Research Ops can streamline all the moving parts of your research studies, and eliminate many of the software tools and expenses that are dragging you down.

As part of your Research Ops program, you should ensure you have a manager who is:

Responsible for approving research-related expenses

Able to establish that any current paid software tools are worthwhile

Able to source the most cost-friendly hardware and software items for your use cases

Customer experience

Your business can use Research Ops as a means to get deeper research insights on customers, action their feedback, and enhance the user experience.

Decision making

UX research teams often collect data that isn’t accessible to other teams in your organization, and may be stored in many different places. The same goes for data collected by your sales, marketing, and products teams.

ReOps can collate and manage all of this data and keep it in a central location. This ensures your organization has the information it needs on demand to inform decision making and achieve company goals in the most efficient way.

Stakeholder buy-in

Many UX teams can’t (or don’t know how to) accurately measure the performance of their research initiatives, which makes it tricky to get executives to buy into future research rounds.

ReOps can help create standardized systems for things like:

Deciding which metrics need to be captured

How to apply these metrics to business goals

Consistent data collection and reporting

A Research Ops program can help gather historical data and deliver all the juicy metrics that stakeholders want to see to sign off on new research—and (hopefully!) approve the budget that will be needed to deliver an excellent outcome.

Brand building

Research Ops can help you make key decisions that align with your goals and values as a brand, which can lead to a stronger brand reputation, better user experience, and increased customer loyalty.

UX research advocacy

Your Research Ops team should love what they do—as they will play a key role in your organization to share information and advocate for the value and importance of UX research, and the many powerful advantages it gives your business.

They will help to socialize and democratize your research so that teams across your organization can access information, collaborate on initiatives, and make more informed decisions based on research insights.

How to create and implement a Research Ops program

If your company is undertaking more UX research, and your research team is expanding, you’ll need to start thinking about ways to  operationalize research  as your business scales.

Research requires a lot of additional work outside of the actual research bit, including  preparing an initial brief , managing participants, analysis, reporting…and the list goes on.

If you find that your UX researchers are spending less and less time on actual research work, it’s time to consider implementing Research Ops to keep things organized, and to give your UX team the support they need to do their best work.

Here’s a simple Research Ops  framework  to help you get started.

1. Appoint a manager for your Research Ops program

Your starting point is to choose the right person to manage things like workflows, data control, and budget. They’ll need to create systems and guides that can be rolled out across your organization.

This person should ideally have plenty of experience with:

UX planning, research, project management, and reporting

Creating and managing budgets

Leading and management teams

Liaising with various teams and communicating with stakeholders at executive levels

2. Decide what Research Ops will be responsible for

When you’re considering Research Ops for your organization, you’ll need to begin by pinpointing the biggest problems and roadblocks faced by your UX research team. These should guide how your Research Ops program operates.

For most companies, the UX research team’s pain points will take the form of admin tasks that are tying up all their time and slowing their progress.

Talk with your researchers and ask them which specific tasks and processes they’d love to hand over to someone else so they can concentrate on what they’re best at.

These jobs can be dealt with more efficiently and effectively by a dedicated Research Ops team, who can focus on:

ReOps will do the heavy lifting for data governance, and for creating ethical guidelines around data and consent management for your company.

This includes data collection, storage, and processing, and ensuring sensitive personal information is compliant with all relevant rules and legislation.

Knowledge management

As your business scales and your UX research initiatives increase, you need to have scalable systems in place for capturing research data, analyzing it, sharing it, and archiving it.

Research Ops are usually responsible for knowledge management, and for ensuring data is stored in a centralized place that is secure, compliant, and accessible to whoever needs it.

Participant management

Recruiting participants can be one of the most time-consuming tasks for UX researchers. And it’s one of the key tasks that Research Ops can easily take off their hands.

Your ReOps team can manage all the complex needs of participant recruitment, including:

Building a database or research panel of potential participants

Researching recruitment channels

Defining ideal participants

Recruiting participants for field studies, surveys, and interviews

Screening participants

Managing communication and data throughout the participant lifecycle

Booking venues

Collecting and analyzing data

Gathering and reporting on insights

Creating frameworks for fair and ethical incentives for participants

Managing the necessary budgets for recruitment

Hardware and software management

Depending on the type of research carried out by your organization, your Research Ops team might be responsible for:

Booking appropriate venues for conducting research

Sourcing audio or recording equipment

Finding lab space

Using specialized software to analyze data

Whatever your teams require to ensure a successful research study, it’s Research Ops’ job to ensure they have what they need, when they need it.

Documentation creation and management

As we mentioned earlier, Research Ops is all about improving efficiency. If your UX research is scaling, you need templates, processes, guides, and manuals to ensure that everyone is on the same page, and is producing work that’s consistent and of high quality.

In most organizations, it’s Research Ops who are in charge of creating and updating these documents.

Training and support

ReOps should also be in charge of producing documents, guides, and templates that help to train and upskill researchers. They might work on creating specific trainings for things like:

Ensuring ethics are applied and upheld by individual researchers

Standardizing your organization’s research methods

Consent forms, consent management, types of consent

Data governance

Recruiting participants

Customer contact guides

It might also be beneficial to let your Research Ops team support research managers by:

Pinpointing new opportunities for coaching and training

Screening and onboarding new research hires

Streamlining internal and offsite meetings

Educating research partners and stakeholders about the value of UX research

Making sure research data and success stories are accessible to people who need it

Ensuring the impact of your UX research is understood across your organization

Internal communications

Depending on the size of your organization, your Research Ops team might be responsible for tasks such as:

Communicating with other departments and stakeholders about research

Content production (e.g. blogs and newsletters)

Budget management

You can hand over some budgeting responsibilities to Research Ops too. These can include items such as allocating budget for research studies, tracking spend, and allocating resources for research projects.

Research Ops will also be in charge of negotiations when it’s time to get budgets approved for research studies and participant incentives.

3. Create standardized workflows

Once you’ve decided what your Research Ops team will be responsible for in your organization, you’ll need to create a standardized workflow for their respective activities.

Decide how you can:

Automate repetitive and time consuming tasks

Delegate specific tasks to team members

Create templates and how-to guides to save time

You’ll then need to set an achievable timeframe to complete these workflows and nail down your new Research Ops processes.

Decide on essential tools

Research Ops teams typically rely on a multitude of hardware and software tools to get work done efficiently.

When you’re developing your ReOps program, you’ll need to consider the types of tools you might need for things like compliance, project management, data collection, and reporting—and the budget you have for these essential tools each month.

Depending on your organization, you might need software to help manage:

Team communication

Collaboration

Research panels

Polling and surveys

Recording equipment for audio and/or video

Transcription

Collecting and organizing research

Participant database

Informed consent

Mockups and prototypes

Design collaboration

User journey mapping

Data analytics and tracking

As you can see, this is a fairly lengthy list—and these only scratch the surface of the potential tools that your team might need.

It’s important to set a firm budget, and then narrow down the must-have and nice-to-have tools to help you launch your Research Ops program.

5. Take action

Once all of your Research Ops people and processes are in place, it’s time to put everything into action.

Create an action plan that sets out each step you’ll be taking to increase efficiency and improve specific parts of the research process. It’s important to place an initial focus on the things that will give you the best shot at scaling the impact for your research team—and for your customers.

Make sure you include a timeline for your plan, and an approximate budget for working through everything.

It’s important to track all of the changes and results (good and bad) so your ReOps team can iterate and improve upon their systems over time.

6. Measure results

One of Research Ops’ key roles is to be able to provide relevant metrics that can be tied to both specific and overall business goals.

They can use these results at stakeholder meetings, to get buy-in for new research studies, and to help organizations make smarter business decisions.

What qualities do you need as an individual to succeed in Research Ops?

Research Ops involves tasks like recruiting people for interviews and surveys, scheduling research, creating research processes and programs, and undertaking various other admin tasks to help deliver better results for companies.

It’s a career path that is ideal for a variety of people. As it’s still an emerging discipline, you don’t need to have any specialized experience to get started—but it will be beneficial if you have a background in general business operations, UX, marketing, or research.

If you’re thinking of getting involved in Research Ops, here are some of the key qualities you’ll need to succeed in this role:

Attention to detail

You’ll be reviewing and analyzing large amounts of data on a regular basis. This means you’ll need to enjoy working your way through a ton of information and be able to spot trends and patterns.

Analytical skills

You’ll need to have natural analytical thinking skills to help you process research data, and draw meaningful conclusions from it.

Critical and creative thinking

Being a good problem solver is essential. Can you think on your feet and come up with creative solutions to complex problems? If so, you could be a great fit for this role.

Communication

You’ll need to be able to effectively communicate with others, and be able to clearly explain your research findings and solutions to stakeholders and other team members.

Organizational skills

By its very nature, this job demands that you’re efficient and organized in both your thinking and your actions in order to meet deadlines and stay on budget.

If you tick all of these boxes, Research Ops might be the perfect career move for you!

Wrapping up

As companies increasingly rely on UX research operations to grow, there is an overarching need for Research Ops to help organize, deliver, and scale these initiatives.

If you’re interested in learning more, check out the  ResearchOps Community . It’s a global group that has a ton of helpful resources, plus an active Slack channel where you can network with other experts in this field.

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The ReOps Community - ResearchOps Community

ResearchOps Community

Operationalizing research and research design

The ReOps Community

About the researchops community.

If the mission for ResearchOps is to help researchers do their best work, then the mission of the ResearchOps Community is to help research operations people know just how to do that.

In effect, we research the researchers. We talk about and influence the development of tools, repositories, guidelines and templates. Discussing what makes the best lab, what kinds of spaces researchers need to do their work, how to do the best recruitment.

We’re a vibrant, global Community centred around our Slack which is carefully tended and managed by a team of committed board members and organisers of our global projects.

ResearchOps is the people, mechanisms, and strategies that set user research in motion. It provides the roles, tools and processes needed to support researchers in delivering and scaling the impact of the craft across an organisation.

View the map in Mural or Kumu .

Join the ResearchOps Community

Rules of conduct.

Being a community requires a commitment to being respectful of our incredibly diverse and global Community. We have a public Community Guidelines document that includes a Code of Conduct.

Impressively, the community is actually just warm, collegiate and inclusive all by itself. When it isn’t, the Cheese Board are ready to help (better yet, because of the global nature of the group, there’s always one of us on hand, should you need anything).

Outside the Slack, you can contact us at [email protected]

There’s a small waitlist as we like to bring new people into the community as a cohort. This way, we have a chance to get to know you and say hi without getting lost in all our chatter.

The wait is not often longer than 4 weeks, and in the meantime, you can keep up-to-date with us on our Medium articles and other social accounts.

Community Talks

The wonderful thing about all the work we do together, is that people like to ask us to talk about it!

What is ResearchOps:

• ResearchOps Town Hall .
• NUX Manchester 2019 , Emma Boulton.
• Design Research 2019 , Brigette Metzler, Kate Towsey and Ruth Ellison.
• User Research London 2019 , Emma Boulton.
• UX Bristol July 2019 , Emma Boulton.
• Web Directions 2019 ,Brigette Metzler, Benson Low.

Emma Boulton and Chris Spalton ResearchOps Rea collaboration:

• ResearchOps Rea Part 1. .
• ResearchOps Rea Part 2 .
• ResearchOps Rea Part 3 .

Research Skills Framework:

• Skills for the trek , Dave Hora, Tomomi Sasaki.
• Interaction 20 , Dave Hora, Tomomi Sasaki.

Research Repositories:

• Research Repos Town Hall (deck).
• Research Repos Town Hall (Vimeo).
• Advancing Research Community Call (deck).

Pace Layers Matrix*:

• Research Repos Advancing Research 20 (deck).

(*Pace Layers Matrix is not a project, but instead is a framework arising from the 8 Pillars and Research Repositories work).

ResearchOps Events

In addition to maintaining our Slack, our community is committed to facilitating global discussions via local workshops. Our first workshop series helped us better define the discipline. In 2019, we’re running two more.

Conferences

Reopsconf by the researchops.community.

Wednesday 8 June 2022, New York City, NY and Remote

Book for ReOpsConf2022

Our Town Halls are run intermittently throughout the year. You can find previous Town Halls via the ResearchOps Community on Vimeo .

We at ResearchOps really love researching researchers! We are working our way through the core pillars of ResearchOps to understand each facet of delivering and doing ReOps better.

Our workshops tend to be announced so follow us on Twitter and Medium or join in with the Community on Slack.

Introduction to Operations Research

• First Online: 17 June 2022

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In its first section, this introductory chapter first introduces operations research as a discipline. It defines its function and then traces its roots to its beginnings. The second section highlights some of the main elements of operations research and discusses a number of potential difficulties and pitfalls. Finally, the third section of this chapter suggests an eight-step procedure for the modeling process.

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Eiselt, H.A., Sandblom, CL. (2022). Introduction to Operations Research. In: Operations Research. Springer Texts in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-97162-5_1

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World Leaders in Research-Based User Experience

The state of researchops: untapped yet.

March 13, 2022 2022-03-13

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ResearchOps is meant to support people who do research. Support can take so many forms: paving the way for research activities to become commonplace, making it easy for people who do research to increase knowledge, making user recruiting and data management painless and ethical, jump-starting collaborative prioritization exercises, and routinely tagging insights so they may be easily found later. Organizations with advanced ResearchOps teams do all these activities plus many more and provide a solid foundation for sound, effective research.

In December 2021 we conducted a survey with 353 UX professionals in which we asked them about the state of ResearchOps at their organizations. We found that teams do not have the resources or readiness for many ResearchOps elements.

In This Article:

Researchops roles uncommon today, researchops resources present today.

One of the survey questions asked respondents about the presence of various ResearchOps roles at their organization.

While many agree that having well-organized operations for research can save time and money, and increase research quality, 46% of organizations surveyed have no dedicated person doing ResearchOps. Among those who do have a ResearchOps role, the most common roles tend to be administrative-support person (25%) or ResearchOps leader (24%). The more specialized roles (research-participant manager and research-repository manager) are present in only 12% and 8% of organizations, respectively.

Lack of ResearchOps Roles Causes Waste

Not having ResearchOps roles tends to become costly in the long run because it forces other roles to take over ResearchOps responsibilities. These people may not do ResearchOps tasks often and, thus, will take more time to do them. They are often also paid more than some ResearchOps roles. For example, a product manager who rarely does discovery studies may take a long time to draft a screener for recruiting , do recruiting , and create an interview guide . They are also likely paid more than a person in a ResearchOps position. Thus, the absolute cost of a PM recruiting and doing operations-related discovery research could be higher than if a research recruiter managed study participants and interview-guide templates were accessible to the PM.

ResearchOps Administrative-Support Role

25% of organizations have a ResearchOps administrative-support person. Such a role makes good sense as a first ResearchOps role. People who do research need support with managing participants, scheduling sessions, tracking findings, and sharing them with others. An all-around, well-organized administrative person can make a considerable impact in these areas.

ResearchOps Leader

Another role that is likely to be among the first dedicated ResearchOps roles is the ResearchOps leader, which 24% of the respondents report having at their organizations. A leader can strategically kick off the operationalizing process.

Recruiting/ Participant Manager

In fewer cases (12%), organizations have a dedicated role for managing research participants. This number may be low partly because there are many external recruiting resources available to suit various needs and budgets.

Repository Owner

In even fewer cases (8%) organizations have a dedicated role for organizing and managing a research repository . A research repository allows teams to track (and reuse) insights from user research. This number is low because organizations often need to commit to a repository before they will hire someone to manage it. Also, they need to have a lot of insights to deem them worthy of being managed. Finally, they need to believe that finding and using insights is important enough to warrant headcount to manage them.

We also asked teams what ResearchOps tools and elements were present in their organization.

We separately discuss the different types of ResearchOps resources used in organizations.

ResearchOps software has a limited presence in organizations:

• 39% of respondents reported that their organizations have a repository to organize research insights.
• 35% have an online library of recordings from sessions.
• 24% have a research-participant management system.

The field of cloud-based repository software designed for (or at least marketed to) user researchers is bountiful today, and teams are starting to take advantage of these options. Good tools can help teams make research insights accessible to everyone in the organization.

When they adopt new tools, teams should spend time with the initial planning of the research information architecture. A good taxonomy and thoughtful tagging will scale gracefully with your data and with the repository’s user base. In other words, plan for data and user-base growth. And don’t assume that the tool’s out-of-the-box templates will be perfect for your needs. 

Commitment to Research

Subscribing to a cloud-based tool can be a good sign of ResearchOps growth, but it requires a lower level of commitment compared to hiring full-time employees for ResearchOps or allocating ongoing budget for research. It’s concerning that only 56% of respondents feel that their organizations have capable researchers and only 42% have budget allocated to doing research. These percentages should be judged relative to the fact that our respondents were UX professionals: companies without UX specialists on staff will likely have 0% or few capable researchers and close to 0% budget (they could spend a little on consultants), meaning that the percentages across all companies in the world will be lower.

Both numbers should be much higher for good research work to be done effectively. (If I wanted to see the glass half full, I could say that it’s a good thing that more than half of respondents have capable researchers and almost half have a research budget. I’ll leave the optimism or pessimism to you, reader, as well as this important question: do you have capable researchers and money to do research at your organization?)

A mature, thriving, and viable research practice requires setting aside dedicated time to think about it and the best ways to implement it. As we will discus in a subsequent article, lack of time is the biggest obstacle against doing research. Unfortunately, only relatively few of our respondents reported having in place support for research planning and for tracking how and whether research findings were used:

• 29% of respondents report that their organizations use a research roadmap .
• 33% report that time to do research is allocated in the backlog or schedule.
• 17% report that time to respond to research findings is allocated in the backlog or schedule.
• 18% report that their organizations have a system for managing research requests.
• 9% say that their organizations have a system for tracking what happened with research findings.

What do these responses mean in day-to-day design and research work?

• Most development schedules (67%) do not include doing research.

If people can get research done under these circumstances, bravo! But it probably takes a lot of overtime work and it is challenging to convince others to be involved. In short, research is not sustainable if it’s not part of the planned development schedule.

• Most development schedules (83%) do not account for the time needed for changing designs or plans based on research findings.

One may overcome barriers to get research done. Great. But that is just step one. Then research should be analyzed, findings should be prioritized, and a course of action should be determined. Acting upon research findings may involve small or big swerves in product definition and development. For example, in discovery research, a team might learn that it needs to alter the direction of the initial product concept. If the team and schedule are not prepared for this change, the research findings will not be used. In fact, they may be either ignored or looked upon hostilely.

Or, say a team uses iterative usability testing to determine what in a design works well for users and why. But if there is no time to make appropriate changes to the design based on the study, then those research insights are pointless and the design will not reach its potential.

• Research roadmaps do not exist in most (71%) organizations.

I think about planning user research in two ways: strategic and reactive .

With strategic research, the team deliberately derives a list of items that should be researched, then makes it part of the product plan and schedule. The plan often takes the form of a research roadmap.

With reactive research, during product development, a feature is already designed (or even coded and live) and someone requests for it to be researched.

Both kinds of research can bring value, but teams often gravitate toward reactive research. This is perilous because areas that are important to the business and users may never be researched. Even if a lot of research is done, areas related to top tasks , hard-to-design concepts, and the frequent subject of support calls may be overlooked.   

With no research roadmap , 71% of organizations surveyed may be doing only reactive research or no research at all.

• In most (82%) organizations, research requests are not managed and tracked.

Both strategic and reactionary requests can be tracked. Doing so can offer many benefits both before and after research is performed; they include:

• helping researchers prioritize and manage their work
• offering transparency to stakeholders (and research requestors) about the supply and demand of research
• evaluating unmet research demand and better planning for the future
• measuring met demands and assessing the value of research

Tracking and transparency can be especially helpful at organizations in certain situations, like when research capabilities are new at an organization, research is unable to meet demand, or the organization’s research (or design) organization is centralized uses an agency-like model to work with products. The 82% of organizations not tracking requests may be missing out on many benefits.

• Research work results are not tracked in most (91%) organizations.

Many organizations need research to be done quickly. But efficient doesn’t have to equal ephemeral. Taking a beat to track what was learned and how it was acted upon, even if deferred, helps teams to see how much value is being gained from research. For example, imagine a user test uncovers 45 insights: 10 are strengths of the current design, 5 are bugs, and 30 are usability issues of various severity . There are several, complementary ways in which these can be communicated and tracked, as discussed below.

Four Methods for Tracking User Research

Using all four of these methods is recommended:

• Discuss insights with the team.
• Create a report that summarizes all the insights.
• Save each insight (also known as ‘atomic’ insight) with some context as its own item in a research repository.
• For each insight, log the progress the team is making on fixing it.    

There are benefits and costs to each of these, summarized in the table below. Ideally, all these actions should be done with research findings.

Consider the total cost of these tracking methods, calculated simply by multiplying the hours spent per person by the number of people, then multiplied by the average cost per person. Since all employees are not paid that same, it would be more accurate to use actual cost-per-employee data. For our purposes, we assumed a cost of $200,000 per employee per year, 52 work weeks, and 40 hours per week to arrive at $96.15 per hour. The table below uses these numbers to calculate the total cost for each research-tracking activity.

Also remember the opportunity cost — things the workers are not doing and that the business is giving up in order to carry out these activities.

Roles and resources in ResearchOps can elevate the quality of research work, increase productivity, and reduce work duplication. Most organizations today have little infrastructure for doing research efficiently: they have relatively few

ResearchOps tools and even fewer ResearchOps roles. Moreover, there is little time dedicated to strategic planning of research and tracking of research findings and research-resource allocation.

As the ResearchOps arena continues to gain momentum, I am hopeful that teams will see the value in it and purposefully grow their capabilities.

Learn more about ResearchOps in our full-day course .

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Cracking the Code: The 18 Best Operations Management Books

Having immersed myself in the world of operations management for years, both through extensive reading and practical experience, I know the burning desire to stay ahead of the curve. With countless books devoured and a genuine passion for the subject, I’m here to guide you. I understand your needs because I’ve been there. Trust that […]

Having immersed myself in the world of operations management for years, both through extensive reading and practical experience, I know the burning desire to stay ahead of the curve. With countless books devoured and a genuine passion for the subject, I'm here to guide you. I understand your needs because I've been there. Trust that I'll provide you with options worth exploring—they're the real deal! So, let's dive into the realm of operations management together.

Overview of 18 Best Operations Management Books

I've personally curated these 18 top operations management books to help address your specific needs and challenges:

1. The Goal by Eliyahu M. Goldratt

2. lean thinking by james p. womack and daniel t. jones, 3. operations management by william j. stevenson, 4. the toyota way by jeffrey k. liker, 5. the phoenix project by gene kim, kevin behr, and george spafford, 6. operations strategy by nigel slack and michael lewis, 7. the lean startup by eric ries, 8. lean six sigma by michael l. george, 9. the art of strategy by avinash k. dixit and barry j. nalebuff, 10. the lean toolbox by john bicheno, 11. the machine that changed the world by james p. womack, daniel t. jones, and daniel roos, 12. hbr's 10 must reads on operations by harvard business review, 13. operations rules by david simchi-levi, edith simchi-levi, and p. kaminsky, 14. the high-velocity edge by steven j. spear, 15. the gold mine by freddy balle and michael balle, 16. the lean manager by michael ballé and freddy balle, 17. operations and supply chain management by f. robert jacobs and richard b. chase.

• Research Methods for Operations and Supply Chain Management by Taylor & Francis

"The Goal," often regarded as one of the great business books, stands as a testament to the impact of visionary business leaders like those in China who have embraced cutting-edge management strategies. In this groundbreaking business novel, we follow Alex Rogo, a plant manager, on his journey to transform a struggling factory using the Theory of Constraints (TOC). Through this narrative, "The Goal" offers invaluable insights that resonate with business leaders seeking to optimize their operations and stay at the forefront of the ever-evolving business landscape.

What You'll Learn:

In this book, you'll learn how to identify and eliminate bottlenecks in your operations, optimize processes, and improve overall business performance.

Why You Should Read It:

If you're looking to enhance your operations management skills and achieve remarkable results in your organization, "The Goal" offers invaluable insights into the art of process improvement.

About The Author:

Eliyahu M. Goldratt (1947-2011) was an Israeli physicist, business consultant, and author. He was a pioneer in the field of operations management and is best known for his work on the Theory of Constraints. Goldratt's contributions to business management have had a profound impact on industries worldwide.

"Lean Thinking," often hailed as a seminal work in project management, draws inspiration from American companies like Amazon and Apple, known for their exceptional implementation of Lean principles. Authors Womack and Jones emphasize how organizations can eliminate waste, much like Atul Gawande's approach to healthcare optimization, to enhance efficiency and deliver increased value to customers, mirroring the customer-centric strategies of Amazon and the innovation-driven ethos of Apple.

This book will teach you the core principles of Lean thinking, including identifying value from the customer's perspective, mapping value streams, and continuously improving processes.

If you aspire to streamline operations, reduce costs, and enhance customer satisfaction, "Lean Thinking" is an essential guide that provides actionable strategies and real-world examples.

About The Authors:

James P. Womack and Daniel T. Jones are renowned experts in Lean management. They co-founded the Lean Enterprise Institute, a nonprofit research and education organization dedicated to advancing Lean thinking. Their work has had a profound influence on Lean practices worldwide.

"Operations Management" stands as a cornerstone in the list of books addressing production and operations management. This comprehensive textbook, akin to Intel's relentless improvement efforts, delves into the foundational principles of operations management. It offers in-depth insights into topics such as process design, quality management, and supply chain, making it an indispensable resource for students and professionals striving to excel in the field.

In this book, you'll gain a deep understanding of key concepts and techniques in operations management, equipping you with the knowledge to optimize processes and make informed decisions.

Whether you're a student studying operations management or a practitioner seeking to refresh your knowledge, William J. Stevenson's book provides a solid foundation and practical insights.

William J. Stevenson is a leading authority in the field of operations management. He has authored several textbooks and academic publications on the subject and has had a significant impact on the education and understanding of operations management principles.

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"The Toyota Way," much like Michael Hammer's influential ideas, delves into the renowned Toyota Production System, revealing how its principles and practices have been reshaping global markets. This book offers a checklist manifesto of sorts for organizations aiming to get things right, akin to the strategies outlined in Jim Collins' "Good to Great." With its insights, "The Toyota Way" provides a roadmap for businesses in New York and beyond to leverage technologies and cause great firms to thrive in the competitive landscape.

Readers will discover the 14 management principles that underpin the Toyota Way, enabling them to apply these principles to foster continuous improvement and excellence in their own organizations.

If you're eager to understand the foundations of Lean manufacturing and develop a culture of continuous improvement, Jeffrey K. Liker's book is your definitive guide.

Jeffrey K. Liker is a prominent scholar and practitioner of Lean manufacturing and leadership. His extensive research and expertise in the field have made him a respected authority in the world of operations management.

In the realm of business literature, "The Phoenix Project" is regarded as a great book among operations management textbooks, akin to Clayton Christensen's "The Innovator's Dilemma." This gripping novel skillfully weaves together the story of an IT manager facing an operational disaster, showcasing how disruptive technologies can cause great firms to stumble if they do not embrace innovation. Within its pages, "The Phoenix Project" also provides valuable insights into the principles of DevOps, demonstrating how they can be applied effectively to transform IT and business operations, ultimately propelling organizations toward success.

This book offers a unique narrative approach to convey the importance of collaboration, automation, and a systems-thinking mindset in achieving operational excellence.

For those seeking to bridge the gap between IT and business operations, this book provides a compelling and informative journey toward understanding and implementing DevOps practices.

Gene Kim , Kevin Behr , and George Spafford are experts in IT operations and DevOps. Their collective experience and knowledge are reflected in this groundbreaking book.

"Operations Strategy" explores the critical role of operations in an organization's overall strategy. Nigel Slack and Michael Lewis provide insights into aligning operations with business goals to gain a competitive advantage.

This book offers a strategic perspective on operations management, teaching readers how to design and manage operations that contribute directly to an organization's success.

If you aim to enhance your understanding of operations strategy and its impact on business performance, this book offers practical guidance and strategic insights.

Nigel Slack and Michael Lewis are renowned scholars in operations management. Their combined expertise brings a wealth of knowledge to this book, making it an indispensable resource for operations strategists.

"The Lean Startup" introduces a revolutionary approach to launching and managing startups. Eric Ries advocates for a methodology that emphasizes continuous innovation, customer feedback, and adaptive development.

Readers will grasp the principles of lean thinking applied to startups, enabling them to build more sustainable businesses by efficiently validating ideas and evolving products.

For aspiring entrepreneurs and those looking to transform their startup culture, Eric Ries provides actionable insights that can lead to greater success and resilience.

Eric Ries is a prominent entrepreneur and author known for his influential work on Lean Startup principles. His expertise has helped countless startups and established companies navigate the challenges of innovation.

"Lean Six Sigma" is a comprehensive guide to blending Lean and Six Sigma methodologies for process improvement. Michael L. George outlines strategies for eliminating defects, reducing waste, and enhancing efficiency.

This book equips readers with the tools and techniques needed to implement Lean Six Sigma, enabling them to drive operational excellence and deliver superior products and services.

For professionals seeking to improve processes, reduce costs, and enhance quality, Michael L. George's book provides a roadmap for integrating Lean and Six Sigma effectively.

Michael L. George is a recognized expert in Lean Six Sigma and process improvement. His extensive knowledge and practical guidance have made him a trusted resource in the field. You can also find him on his LinkedIn .

"The Art of Strategy" explores the world of game theory and its applications to strategic decision-making in business and beyond. Avinash K. Dixit and Barry J. Nalebuff provide a comprehensive introduction to this powerful tool.

Readers will gain a deeper understanding of strategic thinking, learning how to analyze situations, anticipate rival moves, and make better decisions in competitive environments.

For those looking to enhance their strategic acumen and make more informed choices in operations management, this book offers valuable insights drawn from the world of game theory.

Avinash K. Dixit and Barry J. Nalebuff are esteemed economists and scholars in the field of game theory. Their expertise in strategic thinking and decision-making is reflected in this accessible and informative book.

"The Lean Toolbox" is a practical guide that compiles a wide range of Lean tools and techniques. John Bicheno provides a comprehensive resource for individuals and organizations seeking to implement Lean principles effectively.

Readers will discover a vast array of Lean tools, from value stream mapping to 5S, and gain insights into how to select and apply them to improve processes and reduce waste.

For those looking for a hands-on approach to Lean implementation, this toolbox offers a wealth of practical guidance and actionable tools to drive continuous improvement.

John Bicheno is a recognized authority in Lean thinking and operations management. His practical experience and expertise make "The Lean Toolbox" an invaluable resource for Lean practitioners.

"The Machine That Changed the World" is a seminal work that explores the rise of the Lean production system, often referred to as the Toyota Production System. The book sheds light on how Lean thinking transformed manufacturing worldwide.

Readers will gain a deep understanding of the principles, practices, and impact of Lean manufacturing, as well as insights into how it revolutionized the automotive industry.

If you're interested in the history and global impact of Lean thinking, this book provides a comprehensive and enlightening narrative of its evolution and success.

James P. Womack and Daniel T. Jones , co-authors of "The Machine That Changed the World," are recognized experts in Lean thinking. Daniel Roos, also a contributor, is an esteemed scholar in the field of engineering and operations research.

"HBR's 10 Must Reads on Operations" is a curated collection of Harvard Business Review articles focusing on operations management. It offers a wealth of insights from leading experts in the field.

Readers will access a diverse range of articles covering topics such as supply chain management, process improvement, and operational excellence, providing a well-rounded view of operations strategies.

For professionals seeking concise and thought-provoking insights from a variety of perspectives, this collection is an essential reference for staying informed about the latest trends and practices in operations management.

Harvard Business Review is a globally respected publication known for its high-quality business insights and articles. The collection "HBR's 10 Must Reads on Operations" brings together the expertise of multiple contributors from the world of business and operations management.

"Operations Rules" is a comprehensive guide that delves into the critical principles of operations management. Co-authored by David Simchi-Levi, Edith Simchi-Levi, and P. Kaminsky, this book offers insights into optimizing operations and supply chains.

Readers will learn essential rules and strategies for effective operations management, including demand forecasting, inventory management, and risk mitigation.

If you're looking for actionable strategies and best practices to improve your operations, this book provides a wealth of knowledge from industry experts.

David Simchi-Levi , Edith Simchi-Levi, and P. Kaminsky are respected authorities in the field of operations management and supply chain optimization. Their collective expertise is evident in this valuable resource.

"The High-Velocity Edge" explores the concept of high-velocity organizations that excel in speed, innovation, and quality. Steven J. Spear investigates the principles behind these organizations and how they sustain their competitive edge.

Readers will gain insights into the practices of high-velocity organizations, including the importance of continuous learning, problem-solving, and a culture of excellence.

For those seeking to create a culture of high-performance and innovation within their organizations, Steven J. Spear's book offers a roadmap to achieving sustained success.

Steven J. Spear is a renowned researcher and thought leader in the fields of leadership, innovation, and operations management. His work has had a profound impact on organizations striving for excellence.

"The Gold Mine" is a unique business novel that explores the application of Lean principles in a manufacturing setting. Co-authored by Freddy Balle and Michael Balle, this book tells the story of a plant manager's journey toward Lean transformation.

Readers will follow the protagonist's experiences as he applies Lean thinking, uncovers waste, and works towards creating a Lean culture within his organization.

For those interested in learning about Lean principles through an engaging narrative, this book offers valuable lessons and practical insights on Lean implementation.

Freddy Balle and Michael Balle are recognized experts in Lean thinking and operations management. Their collaborative work in "The Gold Mine" presents a compelling approach to understanding and applying Lean principles in a real-world context.

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"The Lean Manager" by Michael Ballé and Freddy Balle provides a comprehensive guide to Lean leadership. It explores the principles and practices of Lean management and how effective leadership is essential for sustaining Lean transformations.

Readers will gain insights into the role of a Lean manager, including problem-solving, coaching, and creating a culture of continuous improvement within an organization.

For those aspiring to be effective leaders in a Lean environment, this book offers practical advice and real-world examples from experienced Lean practitioners.

Michael Ballé and Freddy Balle are well-known experts in Lean thinking and management. Their combined expertise in Lean leadership and transformation is reflected in this valuable resource.

"Operations and Supply Chain Management" is a comprehensive textbook co-authored by F. Robert Jacobs and Richard B. Chase. It covers a wide range of topics in operations and supply chain management, making it an essential resource for students and professionals.

Readers will gain a deep understanding of key concepts and techniques in operations and supply chain management, equipping them with the knowledge to optimize processes and create efficient supply chains.

Whether you're a student studying operations and supply chain management or a practitioner seeking to enhance your knowledge, this textbook provides a solid foundation and practical insights.

F. Robert Jacobs and Richard B. Chase are respected authorities in the field of operations and supply chain management. Their collaborative work in this textbook reflects their expertise and commitment to educating the next generation of operations professionals.

18. "Research Methods for Operations and Supply Chain Management" by Taylor & Francis

"Research Methods for Operations and Supply Chain Management" is a comprehensive guide that explores various research methodologies essential for studying and improving operations and supply chain management processes. This book equips readers with the knowledge and tools required to conduct effective research in these critical domains.

Within the pages of this book, readers will discover a wide range of research methods, including qualitative and quantitative approaches, case studies, surveys, and data analysis techniques. Each method is explained in detail, allowing readers to choose the most suitable research approach for their specific needs.

For individuals interested in advancing their research skills and making informed decisions in the fields of operations and supply chain management, this book serves as an invaluable resource. It provides a comprehensive understanding of research methodologies tailored to the unique challenges and opportunities within these domains.

Taylor & Francis is a renowned academic publisher known for its contributions to various fields, including operations and supply chain management. This book reflects their commitment to providing high-quality resources that support research and scholarship in these areas.

Which Operations Management Book Do You Recommend?

Feel free to recommend any books we might have overlooked from the list. Your insights are valuable, and we're eager to hear your suggestions!

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The analytics edge.

Dimitris Bertsimas The Analytics Edge provides a unified, insightful, modern and entertaining treatment of analytics. The book covers the science of using data to build models, improve decisions, and ultimately add value to institutions and individuals. The philosophical underpinnings of the book are that real world problems are usually complex and often will defined; they do not come with labels, meaning that they are not necessarily regression problems or optimization problems. The only objective reality is data, which itself may be incomplete and of questionable quality, and the role of models is to facilitate the solution of real world problems. Problems and data play a leading role in this book, while models play an essential but supporting role.  

A Non-Random Walk Down Wall Street 

Andrew Lo For over half a century, financial experts have regarded the movements of markets as a random walk — unpredictable meanderings akin to a drunkard's unsteady gait — and this hypothesis has become a cornerstone of modern financial economics and many investment strategies. Here Andrew W. Lo and A. Craig MacKinlay put the Random Walk Hypothesis to the test In this volume, which elegantly integrates their most important articles, Lo and MacKinlay find that markets are not completely random after all, and that predictable components do exist in recent stock and bond returns. Their book provides a state-of-the-art account of the techniques for detecting predictabilities and evaluating their statistical and economic significance, and offers a tantalizing glimpse into the financial technologies of the future.

The Econometrics of Financial Markets 

Andrew Lo The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory.

The Industrial Organization and Regulation of the Securities Industry (National Bureau of Economic Research Conference Report)

Andrew Lo The regulation of financial markets has for years been the domain of lawyers, legislators, and lobbyists. In this unique volume, experts in industrial organization, finance, and law, as well as members of regulatory agencies and the securities industry, examine the securities industry from an economic viewpoint.

Ten original essays address topics including electronic trading and the "virtual"stock exchange; trading costs and liquidity on the London and Tokyo Stock Exchanges and in the German and Japanese government bond markets; international coordination among regulatory agencies; and the impact of changing margin requirements on stock prices, volatility, and liquidity.  

Market Efficiency: Stock Market Behaviour in Theory and Practice (International Library of Critical Writings in Economics)

Andrew Lo The efficient markets hypothesis is one of the most controversial and hotly contested ideas in all the social sciences. It is disarmingly simply to state, has far-reaching consequences for academic pursuits and business practice, and yet is surprisingly resilient to empirical proof or refutation. Even after three decades of research and literally thousands of journal articles, economists have not yet reached a consensus about whether markets - particularly financial markets - are efficient or not. These two volumes bring together the most influential articles surrounding the efficient markets hypothesis debate, from Paul Samuelson's pathbreaking proof that properly anticipated prices fluctuate randomly to Fischer Black's study of noise traders, from Eugene Fama's empirical implementation of the efficient markets hypothesis to Robert Merton's analysis of stock price volatility.  

Designing & Managing the Supply Chain

David Simchi-Levi, Philip Kaminsky, and Edith Simchi-Levi Supply chain management, both in industry and in academia, has grown rapidly over the past several years mainly due to an increase in corporate goals of reducing manufacturing costs and the savings that come from planning and managing the supply chain effectively. Most textbooks do not include models and decision support systems robust enough for industry. Designing and Managing the Supply Chain: Concepts, Strategies, and Cases, 2/e by Simchi-Levi, Kaminsky and Simchi-Levi discusses the problems, models and concepts derived from issues related to effective supply chain management. This text is suitable for both academic study and practicing professionals. While many core supply chain management issues are interrelated, the authors have tried to make each chapter as self-contained as possible so that the reader can refer directly to chapters covering topics of interest. Each chapter utilizes case studies and numerous examples. Mathematical and technical sections can be skipped without loss of continuity. The accompanying CD-ROM also provides two simulations, the Computerized Beer Game and the Risk Pool Game and a computerized tool, new to this edition, for developing and executing supply chain contracts. These packages help illustrate many of the concepts discussed.

Logic Of Logistics: Theory, Algorithms, And Applications For Logistics Management

David Simchi-Levi, Xin Chen, and Julien Bramel Fierce competition in today's global market provides a powerful motivation for developing ever more sophisticated logistics systems. This book, written for the logistics manager and researcher, presents a survey of the modern theory and application of logistics. The goal of the book is to present the state of the art in the science of logistics management. As a result, the authors have written a timely and authoritative survey of this field that many practitioners and researchers will find makes an invaluable companion to their work.

Managing the Supply Chain: The Definitive Guide for the Business Professional

David Simchi-Levi, Philip Kaminsky, and Edith Simchi-Levi > In today's environment of tight budgets and even tighter turnarounds, effective supply-chain management has become a core business requirement. Managing the Supply Chain adapts the number one supply-chain book on the college market to examine how professionals can consistently turn supply-chain strategy into a competitive advantage. This results-based book examines the experiences of today's most accomplished companies to demonstrate supply-chain innovation at work in the marketplace.

Modern Logistics Management, Linking Marketing, Manufacturing, and Physical Distribution

Donald B. Rosenfield, John Magee, and William Copacino This comprehensive overview of logistics provides a conceptual framework for understanding the logistics system, the integration of its basic elements, and its relationship to the overall firm. Discusses both manufacturing and physical distribution, new technologies in each of these areas, and how they related to each other and to the company. New topics covered range from approaches to strategic logistics planning and multi-location inventory planning, to international logistics issues and future directions.

The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage

Yosef Sheffi >Logistics, argues that a company's survival and prosperity depend more on what it does before such a disruption occurs than on the actions it takes as the event unfolds. In The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage, Sheffi explores high-impact/ low-probability disruptions, focusing not only on security but on corporate resilience the ability to bounce back from such disruptions and how resilience investments can be turned into competitive advantage.

Sheffi provides tools for companies to reduce the vulnerability of the supply chain they live in. And along the way he tells the stories of dozens of enterprises, large and small, including Toyota, General Motors, UPS, Intel, Amazon.com, the US Navy, and others from across the globe. Their successes, failures, preparations, and methods provide a rich set of lessons in preparing for and managing disruptions.

Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods

Yosef Sheffi What happens to a company when the unimaginable occurs? When an earthquake hits its primary contract manufacturer? When labor strikes shut down an entire port? When terrorists cripple a transportation system?

Machine Learning

Machine learning under a modern optimization lens.

Dimitris Bertsimas and Jack Dunn The book provides an original treatment of machine learning (ML) using convex, robust and mixed integer optimization that leads to solutions to central ML problems at large scale that can be found in seconds/minutes, can be certified to be optimal in minutes/hours, and outperform classical heuristic approaches in out-of-sample experiments.

Management Science

Data, models, and decisions.

Dimitris Bertsimas and Robert Freund This book represents a departure from existing textbooks. Rather than covering methodology, the book introduces decision support systems through real world applications, and uses spreadsheets to model and solve problems. It uses management science techniques (statistics, simulation, probabilistic modeling and optimization), but only as tools to facilitate problem solving.

Manufacturing

Manufacturing systems engineering.

Stanley B. Gershwin This book provides quantitative methods for the capacity analysis and real-time scheduling of manufacturing systems. It treats these issues as engineering problems, without slogans, and it faces technical details in an appropriate, useful way.

This book provides a fundamental description of some of the most important phenomena affecting material flow in manufacturing systems: machine failures, starvations, blockages, and set-ups. It has a point of view: that disruptions, while undesirable, are a fact of life in a factory. While effort should be expended to reduce them, or even to eliminate them, some amount of disruption is inevitable, and we should develop ways of predicting and limiting their negative effects. The book describes some potentially disruptive events that affect production, the control actions that managers can take in anticipation of or in response to the disruptions, and the consequences of the control actions. The goal is to contribute to the development of a rigorous, and useful, manufacturing systems science.

The emphasis in the early chapters is a capacity analysis of flow systems. The later chapters deal with the real-time control of manufacturing systems. Mathematical background in Markov processes, linear programming, and dynamic programming is provided.

Optimization

Introduction to linear optimization.

Dimitris Bertsimas and John N. Tsitsiklis The book is a modern and unified introduction to linear optimization (linear programming, network flows and integer programming) at the PhD level. It covers, in addition to the classical material, all the recent developments in the field in the last ten years including the development of interior points, large scale optimization models and algorithms and complexity of linear optimization. It emphasizes the underlying geometry, intuition and applications of large scale systems.

Network Flows: Theory, Algorithms, and Applications

Ravindra K. Ahuja, Thomas L. Magnanti, James B. Orlin Bringing together the classic and the contemporary aspects of the field, this comprehensive introduction to network flows provides an integrative view of theory, algorithms, and applications. It offers in-depth and self-contained treatments of shortest path, maximum flow, and minimum cost flow problems, including a description of new and novel polynomial-time algorithms for these core models. For professionals working with network flows, optimization, and network programming.

Optimization over Integers

Dimitris Bertsimas and Robert Weismantel The purpose of this book is to provide a unified, insightful, and modern treatment of the theory of integer optimization with an eye towards the future. We have selected those topics that we feel have influenced the current state of the art and most importantly we feel will affect the future of the field. We depart from earlier treatments of integer optimization by placing significant emphasis on strong formulations, duality, algebra and most importantly geometry.

OR in the Public Sector

Urban operations research.

Richard C. Larson and Amedeo R. Odoni Richard C. Larson and Amadeo R. Odoni Urban Operations Research Approximately 68 percent of the citizens of the world's developed countries live today in cities or in city-centered metropolitan areas. ¹ The economic and social fabric of these high-density clusters is elaborately interwoven, with the well-being of each citizen intricately enmeshed with the activities of others. Strong interdependencies arise in all areas of human need: food, shelter, safety, clothing, recreation, maintenance, energy provision, and so on. Servicing these needs requires highly structured transportation and communication networks throughout the city for effective provision of a variety of urban services: emergency medical, police, mail collection and delivery, fire protection, street and highway maintenance, utility repair, snowplowing, street cleaning, refuse collection, bus and subway transportation, taxi transportation, and so on. Increasingly, citizens are demanding more urban services, by type, quantity, and quality. Yet the ability of most cities in the United States and elsewhere to pay for additional services has been severely strained during the 1970s. The resulting pressure, between the demands for more and better services, on the one hand, and decreased costs, on the other, has created a strong need for improved management decision making in urban services. It is a primary purpose of this book to provide methods for assisting these decisions.

Probability

Applied probability: models and intuition.

Arnold I. Barnett Applied Probability: Models and Intuition is an introductory textbook in Probability, written from the viewpoint of Applied Mathematics. Under that perspective, theoretical rigor is not denigrated, but the book puts a high premium on offering an intuitive overview of key theorems as well as clear evidence of their usefulness. Beyond teaching specific methods, the book strives to create real comfort with the underlying notions of probabilistic thinking. Grasping such ideas is essential if they are to be used with competence and confidence.

A primary objective of the book is to demonstrate that Probability and Statistics are, more than anything, just crystallizations of common sense. The reader should come away from each lesson understanding not only how a result was obtained but also why the outcome is plausible

Applied Statistics: Models and Intuition

Arnold I. Barnett This introductory textbook on applied statistics supports a one-semester course for graduate and undergraduate students in management, engineering, the natural sciences, and the social sciences.

What distinguishes the book is:

• An exceptionally large inventory of real-life examples drawn from many fields, with hundreds of solved examples and practice exercises, many based on the author’s experiences in industry, law, and government; • An unusually strong emphasis on an intuitive understanding of the material, based on recognition that it isn’t enough for an answer to be correct: it should also make sense; and • A conversational style of presentation, to make the book’s treatment of applied statistics more inviting and easier to grasp.

Part of the mission of the ORC is to generate new knowledge that will be used in educating future generations of students around the world.

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Operations Research: A Practical Introduction (Operations Research Series) 1st Edition

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Students with diverse backgrounds will face a multitude of decisions in a variety of engineering, scientific, industrial, and financial settings. They will need to know how to identify problems that the methods of operations research (OR) can solve, how to structure the problems into standard mathematical models, and finally how to apply or develop computational tools to solve the problems.

Perfect for any one-semester course in OR, Operations Research: A Practical Introduction answers all of these needs. In addition to providing a practical introduction and guide to using OR techniques, it includes a timely examination of innovative methods and practical issues related to the development and use of computer implementations. It provides a sound introduction to the mathematical models relevant to OR and illustrates the effective use of OR techniques with examples drawn from industrial, computing, engineering, and business applications.

Many students will take only one course in the techniques of Operations Research. Operations Research: A Practical Introduction offers them the greatest benefit from that course through a broad survey of the techniques and tools available for quantitative decision making. It will also encourage other students to pursue more advanced studies and provides you a concise, well-structured, vehicle for delivering the best possible overview of the discipline.

• ISBN-10 0849322561
• ISBN-13 978-0849322563
• Edition 1st
• Publisher CRC Press
• Publication date July 28, 2000
• Part of series Operations Research
• Language English
• Dimensions 7.25 x 1.25 x 10.25 inches
• Print length 410 pages
• See all details

Editorial Reviews

"The chapter on heuristics techniques is particularly welcome." Short Book Reviews, Vol. 21, No. 2, August, 2001

About the Author

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• Publisher ‏ : ‎ CRC Press; 1st edition (July 28, 2000)
• Language ‏ : ‎ English
• Hardcover ‏ : ‎ 410 pages
• ISBN-10 ‏ : ‎ 0849322561
• ISBN-13 ‏ : ‎ 978-0849322563
• Item Weight ‏ : ‎ 2 pounds
• Dimensions ‏ : ‎ 7.25 x 1.25 x 10.25 inches
• #13 in Genetic Algorithms
• #25 in Industrial Production & Management
• #45 in Industrial Engineering (Books)

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Michael w. carter.

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ORIGINAL RESEARCH article

This article is part of the research topic.

AI and Robotics for Increasing Disaster Resilience in Modern Societies

Advancing Search and Rescue (SAR) Operations: A Holistic Framework Integrating Gesture-Controlled unmanned ground vehicle (UGV) Operation and Camera-Based Human Detection in Disaster Environments Provisionally Accepted

• 1 University of Agder, Norway

The final, formatted version of the article will be published soon.

This paper introduces a novel approach to enhance search and rescue (SAR) operations in disaster environments by integrating cutting-edge technologies into unmanned ground vehicles (UGVs). A prime example is a quadruped robot tailored for SAR tasks. The methodology consists of two key components: gesture-controlled UGV operation and camera-based human detection.The gesture-controlled UGV operation addresses the challenge of precise control in confined spaces, utilising a deep learning (DL) model to accurately interpret and translate hand gestures into real-time control commands. This intuitive interface empowers human operators to guide UGVs through intricate spaces, improving situational awareness and control precision. The second component focuses on human detection using cameras mounted on the UGV, employing an innovative deep learning architecture to identify individuals amidst disaster-induced debris and chaotic surroundings. Notably, the YOLOv8 network is employed, trained, and tested using a Human Dataset specifically curated for disaster scenarios, ensuring the model's adaptability and effectiveness in real-world SAR operations. The integration of these components forms a holistic framework that significantly advances SAR capabilities. Experimental results in simulated disaster scenarios demonstrate the efficacy and real-world viability of the proposed methodology, showcasing the potential of advanced technologies, including DL and camera-based approaches, in evolving UGV technology for disaster response. This research contributes to the ongoing efforts to improve operational outcomes and ultimately save lives in disaster-stricken areas.

Keywords: Disaster response, unmanned ground vehicles (UGVs), deep learning, Multi-modal fusion, human detection

Received: 15 Dec 2023; Accepted: 17 Apr 2024.

Copyright: © 2024 Hamza Zafar and Sanfilippo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mx. Filippo Sanfilippo, University of Agder, Kristiansand, 4604, Vest-Agder, Norway

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3 Questions: Enhancing last-mile logistics with machine learning

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Across the country, hundreds of thousands of drivers deliver packages and parcels to customers and companies each day, with many click-to-door times averaging only a few days. Coordinating a supply chain feat of this magnitude in a predictable and timely way is a longstanding problem of operations research, where researchers have been working to optimize the last leg of delivery routes. This is because the last phase of the process is often the costliest due to inefficiencies like long distances between stops due to increased ecommerce demand, weather delays, traffic, lack of parking availability, customer delivery preferences, or partially full trucks — inefficiencies that became more exaggerated and evident during the pandemic.

With newer technology and more individualized and nuanced data, researchers are able to develop models with better routing options but at the same time need to balance the computational cost of running them. Matthias Winkenbach, MIT principal research scientist, director of research for the MIT Center for Transportation and Logistics (CTL) and a researcher with the MIT-IBM Watson AI Lab, discusses how artificial intelligence could provide better and more computationally efficient solutions to a combinatorial optimization problem like this one.

Q: What is the vehicle routing problem, and how do traditional operations research (OR) methods address it?

A: The vehicle routing problem is faced by pretty much every logistics and delivery company like USPS, Amazon, UPS, FedEx, DHL every single day. Simply speaking, it's finding an efficient route that connects a set of customers that need to be either delivered to, or something needs to be picked up from them. It’s deciding which customers each of those vehicles — that you see out there on the road — should visit on a given day and in which sequence. Usually, the objective there is to find routes that lead to the shortest, or the fastest, or the cheapest route. But very often they are also driven by constraints that are specific to a customer. For instance, if you have a customer who has a delivery time window specified, or a customer on the 15th floor in the high-rise building versus the ground floor. This makes these customers more difficult to integrate into an efficient delivery route.

To solve the vehicle routing problem, we obviously we can't do our modeling without proper demand information and, ideally, customer-related characteristics. For instance, we need to know the size or weight of the packages ordered by a given customer, or how many units of a certain product need to be shipped to a certain location. All of this determines the time that you would need to service that particular stop. For realistic problems, you also want to know where the driver can park the vehicle safely. Traditionally, a route planner had to come up with good estimates for these parameters, so very often you find models and planning tools that are making blanket assumptions because there weren’t stop-specific data available.

Machine learning can be very interesting for this because nowadays most of the drivers have smartphones or GPS trackers, so there is a ton of information as to how long it takes to deliver a package. You can now, at scale, in a somewhat automated way, extract that information and calibrate every single stop to be modeled in a realistic way.

Using a traditional OR approach means you write up an optimization model, where you start by defining the objective function. In most cases that's some sort of cost function. Then there are a bunch of other equations that define the inner workings of a routing problem. For instance, you must tell the model that, if the vehicle visits a customer, it also needs to leave the customer again. In academic terms, that's usually called flow conservation. Similarly, you need to make sure that every customer is visited exactly once on a given route. These and many other real-world constraints together define what constitutes a viable route. It may seem obvious to us, but this needs to be encoded explicitly.

Once an optimization problem is formulated, there are algorithms out there that help us find the best possible solution; we refer to them as solvers. Over time they find solutions that comply with all the constraints. Then, it tries to find routes that are better and better, so cheaper and cheaper ones until you either say, "OK, this is good enough for me," or until it can mathematically prove that it found the optimal solution. The average delivery vehicle in a U.S. city makes about 120 stops. It can take a while to solve that explicitly, so that's usually not what companies do, because it's just too computationally expensive. Therefore, they use so-called heuristics, which are algorithms that are very efficient in finding reasonably good solutions but typically cannot quantify how far away these solutions are from the theoretical optimum.

Q: You’re currently applying machine learning to the vehicle routing problem. How are you employing it to leverage and possibly outperform traditional OR methods?

A: That's what we're currently working on with folks from the MIT-IBM Watson AI Lab. Here, the general idea is that you train a model on a large set of existing routing solutions that you either observed in a company’s real-world operations or that you generated using one of these efficient heuristics. In most machine-learning models, you no longer have an explicit objective function. Instead, you need to make the model understand what kind of problem it's actually looking at and what a good solution to the problem looks like. For instance, similar to training a large language model on words in a given language, you need to train a route learning model on the concept of the various delivery stops and their demand characteristics. Like understanding the inherent grammar of natural language, your model needs to understand how to connect these delivery stops in a way that results in a good solution — in our case, a cheap or fast solution. If you then throw a completely new set of customer demands at it, it will still be able to connect the dots quite literally in a way that you would also do if you were trying to find a good route to connect these customers.

For this, we're using model architectures that most people know from the language processing space. It seems a little bit counterintuitive because what does language processing have to do with routing? But actually, the properties of these models, especially transformer models, are good at finding structure in language — connecting words in a way that they form sentences. For instance, in a language, you have a certain vocabulary, and that's fixed. It's a discrete set of possible words that you can use, and the challenge is to combine them in a meaningful way. In routing, it's similar. In Cambridge there are like 40,000 addresses that you can visit. Usually, it's a subset of these addresses that need to be visited, and the challenge is: How do we combine this subset — these "words" — in a sequence that makes sense?

That's kind of the novelty of our approach — leveraging that structure that has proven to be extremely effective in the language space and bringing it into combinatorial optimization. Routing is just a great test bed for us because it's the most fundamental problem in the logistics industry. 

Of course, there are already very good routing algorithms out there that emerged from decades of operations research. What we are trying to do in this project is show that with a completely different, purely machine learning-based methodological approach, we are able to predict routes that are pretty much as good as, or better than, the routes that you would get from running a state-of-the-art route optimization heuristic.

Q: What advantages does a method like yours have over other state-of-the-art OR techniques?

A: Right now, the best methods are still very hungry in terms of computational resources that are required to train these models, but you can front-load some of this effort. Then, the trained model is relatively efficient in producing a new solution as it becomes required. 

Another aspect to consider is that the operational environment of a route, especially in cities, is constantly changing. The available road infrastructure, or traffic rules and speed limits might be altered, the ideal parking lot may be occupied by something else, or a construction site might block a road. With a pure OR-based approach, you might actually be in trouble because you would have to basically resolve the entire problem instantly once new information about the problem becomes available. Since the operational environment is dynamically changing, you would have to do this over and over again. While if you have a well-trained model that has seen similar issues before, it could potentially suggest the next-best route to take, almost instantaneously. It's more of a tool that would help companies to adjust to increasingly unpredictable changes in the environment.

Moreover, optimization algorithms are often manually crafted to solve the specific problem of a given company. The quality of the solutions obtained from such explicit algorithms is bounded by the level of detail and sophistication that went into the design of the algorithm. A learning-based model, on the other hand, continuously learns a routing policy from data. Once you have defined the model structure, a well-designed route learning model will distill potential improvements to your routing policy from the vast amount of routes it is being trained on. Simply put, a learning-based routing tool will continue to find improvements to your routes without you having to invest into explicitly designing these improvements into the algorithm.

Lastly, optimization-based methods are typically limited to optimizing for a very clearly defined objective function, which often seeks to minimize cost or maximize profits. In reality, the objectives that companies and drivers face are much more complex than that, and often they are also somewhat contradictory. For instance, a company wants to find efficient routes, but it also wants to have a low emissions footprint. The driver also wants to be safe and have a convenient way of serving these customers. On top of all of that, companies also care about consistency. A well-designed route learning model can eventually capture these high-dimensional objectives by itself, and that is something that you would never be able to achieve in the same way with a traditional optimization approach.

So, this is the kind of machine learning application that can actually have a tangible real-world impact in industry, on society, and on the environment. The logistics industry has problems that are much more complex than this. For instance, if you want to optimize an entire supply chain — let's say, the flow of a product from the manufacturer in China through the network of different ports around the world, through the distribution network of a big retailer in North America to your store where you actually buy it — there are so many decisions involved in that, which obviously makes it a much harder task than optimizing a single vehicle route. Our hope is that with this initial work, we can lay the foundation for research and also private sector development efforts to build tools that will eventually enable better end-to-end supply chain optimization.

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Evolution's recipe book: How 'copy paste' errors cooked up the animal kingdom

A series of whole genome and gene duplication events that go back hundreds of millions of years have laid the foundations for tissue-specific gene expression, according to a new study in the journal Nature Ecology and Evolution . The 'copy paste' errors allowed animals to keep one copy of their genome or genes for fundamental functions, while the second copy could be used as raw material for evolutionary innovation. Events like these, at varying degrees of scale, occurred constantly throughout the bilaterian evolutionary tree and enabled traits and behaviours as diverse as insect flight, octopus camouflage and human cognition.

700 million years ago, a remarkable creature emerged for the first time. Though it may not have been much to look at by today's standards, the animal had a front and a back, a top and a bottom. This was a groundbreaking adaptation at the time, and one which laid down the basic body plan which most complex animals, including humans, would eventually inherit.

The inconspicuous animal resided in the ancient seas of Earth, likely crawling along the seafloor. This was the last common ancestor of bilaterians, a vast supergroup of animals including vertebrates (fish, amphibians, reptiles, birds, and mammals), and invertebrates (insects, arthropods, molluscs, worms, echinoderms and many more).

To this day, more than 7,000 groups of genes can be traced back to the last common ancestor of bilaterians, according to a study of 20 different bilaterian species including humans, sharks, mayflies, centipedes and octopuses. The findings were made by researchers at the Centre for Genomic Regulation (CRG) in Barcelona and are published today in the journal Nature Ecology and Evolution .

Remarkably, the study found that around half of these ancestral genes have since been repurposed by animals for use in specific parts of the body, particularly in the brain and reproductive tissues. The findings are surprising because ancient, conserved genes usually have fundamental, important jobs that are needed in many parts of the body.

When the researchers took a closer look, they found a series of serendipitous 'copy paste' errors during bilaterian evolution were to blame. For example, there was a significant moment early in the history of vertebrates. A bunch of tissue-specific genes first appeared coinciding with two whole genome duplication events. Animals could keep one copy for fundamental functions, while the second copy could be used as raw material for evolutionary innovation. Events like these, at varying degrees of scale, occurred constantly throughout the bilaterian evolutionary tree.

"Our genes are like a vast library of recipes that can be cooked up differently to create or change tissues and organs. Imagine you end up with two copies of a recipe for paella by accident. You can keep and enjoy the original recipe while evolution tweaks the extra copy so that it makes risotto instead. Now imagine the entire recipe book is copied -- twice -- and the possibilities it opens for evolution. The legacy of these events, which took place hundreds of millions of years ago, lives on in most complex animals today," explains Federica Mantica, author of the paper and researcher at the Centre for Genomic Regulation (CRG) in Barcelona.

The authors of the study found many examples of new, tissue-specific functions made possible by the specialisation of these ancestral genes. For example, the TESMIN and tomb genes, which originated from the same ancestor, ended up independently playing a specialised role in the testis both in vertebrates and insects. Their importance is highlighted by the fact that problems with these genes can disrupt sperm production, affecting fertility in both mice and fruit flies.

The specialisation of ancestral genes also laid some foundations for the development of complex nervous systems. For example, in vertebrates, the researchers found genes critical for the formation of myelin sheaths around nerve cells, which are essential for fast nerve signal transmission. In humans they also identified FGF17 , which is thought to play an important role in maintaining cognitive functions into old age.

In insects, specific genes became specialised in muscles and in the epidermis for cuticle formation, contributing to their ability to fly. In the skin of octopuses, other genes became specialised to perceive light stimulI, contributing to their ability to change colour, camouflage and communicate with other octopuses.

By studying the evolution of species at the tissue level, the study demonstrates that changes in the way genes are used in different parts of the body have played a big role in creating new and unique features in animals. In other words, when genes start acting in specific tissues, it can lead to the development of new physical traits or abilities, which ultimately contributes to animal evolution.

"Our work makes us rethink the roles and functions that genes play. It shows us that genes that are crucial for survival and have been preserved through millions of years can also very easily acquire new functions in evolution. It reflects evolution's balancing act between preserving vital roles and exploring new paths," concludes ICREA Research Professor Manuel Irimia, co-author of the paper and researcher at the Centre for Genomic Regulation.

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Materials provided by Center for Genomic Regulation . Note: Content may be edited for style and length.

Journal Reference :

• Federica Mantica, Luis P. Iñiguez, Yamile Marquez, Jon Permanyer, Antonio Torres-Mendez, Josefa Cruz, Xavier Franch-Marro, Frank Tulenko, Demian Burguera, Stephanie Bertrand, Toby Doyle, Marcela Nouzova, Peter D. Currie, Fernando G. Noriega, Hector Escriva, Maria Ina Arnone, Caroline B. Albertin, Karl R. Wotton, Isabel Almudi, David Martin, Manuel Irimia. Evolution of tissue-specific expression of ancestral genes across vertebrates and insects . Nature Ecology & Evolution , 2024; DOI: 10.1038/s41559-024-02398-5

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Participant Shutting Down Operations After 20 Years: Film Studio Was Behind Oscar Winners ‘Spotlight,’ ‘Green Book’ (EXCLUSIVE)

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Participant , the 20-year-old film and television production company whose mission was to inspire social justice and humanitarian action, is shutting down.

Founder Jeff Skoll broke the news to a staff of roughly 100 on Tuesday. Established in 2004, Participant co-produced or co-financed a number of notable movies including best picture Oscar winners “Spotlight” and “Green Book,” as well as Steven Spielberg’s “Lincoln” and the breakthrough documentary “An Inconvenient Truth.”

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As Skoll’s message suggests, Participant and companies like it face an uphill battle in the current media landscape. Amid the ongoing economic downturn, the nightmare of making streaming business models work and the pain from production stoppages after last year’s Hollywood labor strikes, there exists a larger reality: The studios are just not making as many movies for adults, especially ones with a conscience.

More than trophies, Participant served as a model for “do-gooder” content — working with nonprofits and activist groups to make and promote work touching on the environment, human rights, institutional corruption and social justice. Participant’s mission, often referred to as a “double bottom line” of creating premium content with a strong social impact element, has been widely integrated by the legacy studios and streamers (especially on social media platforms).

“Our titles drove tangible real-world change. We got out the vote and championed investigative journalism. From the passage of landmark legislation to enact labor protections for domestic workers in Mexico, to spurring state and federal action to address forever chemicals in the United States and Europe,” the Skoll memo said, “Participant content has made the world a safer, more just place for millions of people. “

Skoll has not actively run Participant for years, having brought in former Universal film executive David Linde as CEO in 2015. Under Linde, Participant became the largest certified B Corp (a designation that means a company meets “social and environmental performance, accountability, and transparency” standards, according to B Lab) in entertainment. He oversaw titles from the likes of Alfonso Cuaron, Ava DuVernay and Taika Waititi.

For about three years, Participant Media also owned the Pivot TV basic cable channel, after acquiring what had been the Documentary Channel in early 2013. Pivot TV was an early experiment in blending short-form content and unscripted programs aimed at the Gen Z audience. The channel, launched by veteran media executive Evan Shapiro, did a handful of scripted originals and brought the Australian series “Please Like Me” and its auteur star Josh Thomas to the U.S. Pivot TV was an early casualty of cable cord-cutting and the rise of streaming. As an independent solo channel operator, Participant had no leverage among the large MVPDs to maintain the channel’s distribution base even with negligible affiliate fees. Pivot TV shut down in 2016.

Participant’s company ethos was focused on effecting change off-screen as well. It become an early adopter of carbon neutral film sets and a provider of carbon offsets for its releases (like “Inconvenient Truth,” an Oscar winner for Best Documentary, which made former Vice President Al Gore a climate action star).

It’s unclear who might take up Participant’s mantle in the industry or if such a mission is sustainable. Social impact has become an amorphous hallmark of talent-driven production labels, like President Barack and Michelle Obama’s Higher Ground. Skoll’s farewell address said it was time for him to “evaluate my next chapter and approach to tackling the pressing issues of our time.”

Now there’s one less player doing just that for Hollywood.

Read Skoll’s full letter to staff:

Dear Participant Team,

As many of you have heard today, after much reflection, I have made the very difficult decision to wind down company operations. This is not a step I am taking lightly, but after 20 years of groundbreaking content and world-changing impact campaigns, it is the right time for me to evaluate my next chapter and approach to tackling the pressing issues of our time.

I founded Participant with the mission of creating world-class content that inspires positive social change, prioritizing impact alongside commercial sustainability. Since then, the entertainment industry has seen revolutionary changes in how content is created, distributed and consumed.

Although I have not been active in the day-to-day management of Participant for some years, this is a farewell to one of the most gratifying ventures of my career and there is much to be proud of. We succeeded in creating something truly one-of-a-kind: an impact media company with a double bottom line. This was intentional, and by all measures, we have been incredibly successful in driving the impact we set out to create. We have achieved the highest levels of critical and commercial success. We have released 135 films and 5 series, won 21 Academy Awards, including 2 Best Pictures, 4 Best Documentaries and 2 Best International Features, won 18 Emmy Awards, earned more than $3.3 billion in global box office revenue and partnered with the greatest storytellers and changemakers of our time. Together, we have built a category-defining media pioneer with an iconic, globally recognized brand whose legacy will live on through our people, our stories and all who are inspired by them.

The global conversations sparked by films and series like “An Inconvenient Truth,” “Contagion,” “Good Night, and Good Luck.,” “Waiting for Superman,” “Lincoln,” “Spotlight,” “Roma,” “Food, Inc.,” “Judas and the Black Messiah,” “RBG,” “Just Mercy,” “American Factory” and “When They See Us” gave all of us a new roadmap to engage – earnestly and meaningfully – in the unending pursuit of a better world. It’s not an overstatement to say that Participant films changed the way we think and talk about impact-driven films, building a new lexicon for the power of transformational storytelling.

Our titles drove tangible real-world change. We got out the vote and championed investigative journalism. From the passage of landmark legislation to enact labor protections for domestic workers in Mexico, to spurring state and federal action to address forever chemicals in the United States and Europe, to driving increased global awareness and willingness to act on climate change – Participant content has made the world a safer, more just place for millions of people.

As this chapter of Participant comes to a close, I am emboldened by the efforts of the next generation of storytellers and content creators who are building upon and reimagining this work. From philanthropists, to producers, to distributors, to social impact agencies, more and more individuals and organizations all over the world are recognizing and adopting impact models as core to their approaches. The ripple effects of Participant can be felt far and wide – what we have started together is just the beginning.

Thank you all for your hard work and unwavering dedication to Participant. I have nothing but respect and admiration for each and every one of you, and I know you will continue to carry the legacy of what we built together far into the future.

Sincerely ,

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Participant, studio behind ‘Spotlight,’ ‘An Inconvenient Truth,’ shutters after 20 years

FILE - Jeff Skoll arrives at the Los Angeles premiere of “An Inconvenient Sequel: Truth to Power” at the Arclight Hollywood, July 25, 2017, in Los Angeles. Participant, the activist film and television studio that has financed Oscar winners like “Spotlight” and socially conscious documentaries like “Food, Inc,” and “Waiting For Superman” is closing its doors after 20 years. Billionaire Skoll told his staff of 100 in a memo shared with The Associated Press on Tuesday, April 16, 2024, that they were winding down company operations. (Photo by Willy Sanjuan/Invision/AP, File)

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Participant, the activist film and television studio that has financed Oscar winners like “Spotlight” and socially conscious documentaries like “Food, Inc,” and “Waiting For Superman” is closing its doors after 20 years.

Billionaire Jeff Skoll told his staff of 100 in a memo shared with The Associated Press Tuesday that they were winding down company operations.

“This is not a step I am taking lightly,” Skoll wrote in the memo. “But after 20 years of groundbreaking content and world-changing impact campaigns, it is the right time for me to evaluate my next chapter and approach to tackling the pressing issues of our time.”

Since Skoll founded the company in 2004, Participant has released 135 films, 50 of which were documentaries and many of which were tied to awareness-raising impact campaigns. Their films have won 21 Academy Awards including best picture for “Spotlight” and “ Green Book ,” best documentary for “An Inconvenient Truth” and “American Factory” and best international feature for “Roma.”

Participant was behind films like “Contagion,” “Good Night, and Good Luck,” “Lincoln” and “Judas and the Black Messiah,” the limited series “When They See Us” and also a sequel to their documentary “Food Inc,” which they rolled out this month. Their films have made over $3.3 billion at the global box office. But the company had a “double bottom line” in which impact was measured in addition to profit.

Skoll stepped back from day-to-day operations of the company years ago. Veteran film executive David Linde has been CEO of Participant since 2015, during which they had their “Green Book” and “Roma” successes.

“I founded Participant with the mission of creating world-class content that inspires positive social change, prioritizing impact alongside commercial sustainability,” Skoll wrote. “Since then, the entertainment industry has seen revolutionary changes in how content is created, distributed and consumed.”

Skoll added that their legacy “will live on through our people, our stories and all who are inspired by them.”