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Decision Support System

What it is, why it matters, and best practices. This guide provides definitions, examples and practical advice to help you understand the topic of decision support systems (DSS).

DECISION SUPPORT SYSTEM GUIDE

What is a decision support system.

Broadly speaking, a decision support system (DSS) is an analytics software program used to gather and analyze data to inform decision making. There are many different types of decision support systems, from modern business intelligence which uses AI and machine learning to suggest insights and analyses for humans to perform, to model-based DSS systems which use predefined criteria to perform automated calculations and deliver best-case decisions. For all types, DSS is used in timely problem solving to improve efficiency and streamline operations, planning and company management.

Traditional vs Modern DSS

Traditional DSS:  Historically, DSS and BI tools relied on preconfigured, historical data with no ability to drive real-time decisions and action. With this approach, decisions are made based on the past.

Modern DSS:  New tools and processes allow for “active intelligence”, a state of continuous intelligence with an end-to-end analytics data pipeline delivering real-time, up-to-date information designed to trigger immediate insights and actions.

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Dss characteristics: 3 key elements.

Prior to decision support systems, organizational leaders relied heavily on a combination of their experience and professional training, and applied those to thoughtful use of the advanced insights generated by a  data analytics  platform. Decision support systems systematize that by taking organizational data, analyzing it, and presenting it for use in company decision making.

This DSS approach enables powerful augmented analytics or modeling to make analysis recommendations and game play the outcomes of different scenarios. By varying considerations, outcomes can be more accurately predicted and business decisions made based on the best available information. In this way, DSS supports both  predictive  and  prescriptive analytics .

Three key elements that characterize a decision support system framework are model management, organizational data (your knowledge base) and user interface. Let’s briefly explore each.

Model Management:  To make effective decisions, especially those made on an ongoing basis, it’s crucial for companies to develop  key performance indicators (KPI’s)  from which to evaluate performance against goals, and measure improvements over time. These KPI’s then form the decision criteria for the information models used to guide decision making. Having models provides the backbone of consistency every business needs to sustain success. Models can be leveraged by formally coded rules in DSS or  prescriptive analytics  software or by analysis using a BI platform.

Organizational Data or Knowledge Base:  Before any DSS can be used, raw data must be transformed into clean, accurate, and up-to-date information. The graphic below illustrates how different types of data are combined, cleaned and transformed into standardized formats. The data is then stored in a repository such as a data lake or data warehouse using a governed data catalog.

User Interface:  You’ve stared at enough dense tables of numbers to appreciate why it’s so necessary to have a more digestible and user-friendly way to consume data. A user interface, complete with  digital dashboards , tables, graphs, widgets or other tools to present information, enables users to better interact with, view, and use the data at their disposal.

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Decision Support System Types

The many types of decision support system software options align to the various forms that data takes.

Communication-Driven DSS: Helps companies manage data that requires more than one person to collaborate on a task.

Model-Driven DSS: These DSS software solutions enable decision makers to access and manage statistical models used to run the business. The information is imported to a decision-making model that will then be used to analyze situations. These are the models mentioned above in the model management section.

Knowledge-Driven DSS: Uses company data, facts, procedures, graphical displays, or pre-coded data rules to deliver informed solutions to specialized company scenarios.

Document-Driven DSS: This type of DSS uses unstructured information available in various electronic formats in company systems, such as share drives, cloud storage, or other data asset management (DAM) solutions.

Data-Driven DSS: Helps companies save, manage, and analyze a combination of data that’s both internal to the company and external to the company.

Decision Support System Examples

Now that we’ve defined what a DSS is, DSS characteristics, and types of decision support system solutions, let’s review decision support system examples to better contextualize DSS benefits across a range of situational applications.

DSS that Use Historical Data:  Historical DSS data tabulates past performance and surfaces areas for improvement and/or provides a baseline metric from which to measure. These can include:

Descriptive analytics : Sales, inventory, revenue-related figures.

Diagnostic analytics: A combination of the “what” and the “why” behind data, providing the rationale from which to make go-forward decisions.

Business Intelligence: A range of useful information used to guide important decisions (as described below).

BI Platform for Decision Making:  Business Intelligence tools are a sub-segment of the larger decision support system definition, offering a range of insights, tools and data literacy benefits to organizations looking to expand data understanding, especially in the age of big data,  AutoML , AI and machine learning. A major benefit of BI systems is that they are far less expensive and time-intensive to develop and implement than other DSS approaches.Augmented analytics refers to AI and machine learning processing and making recommendations on large volumes of data at lightning speed. Here’s a demonstration of how a modern BI platform allows conversational interaction and then suggests relevant insights.

Manual and Hybrid DSS:  Before there were computer analyses, manual calculations, spreadsheets and assessments ruled the day. These drew upon available information and qualitative considerations. SWOT analyses are an example of this, as are analyses that rely on subjective judgment, such as performance reviews or creative/art direction. Hybrid DSS combines manual processes with DSS computational power of software applications to deliver a range of data for decision making.

Modeling DSS for Data-Driven Decision Making:  This DSS example uses predetermined criteria to populate a query, then delivers the optimal solution based on the available data. This process includes the simultaneous evaluation of many different scenarios that are then presented for consideration. The better and more comprehensive the DSS model design, the richer the model outputs. To optimize models, two approaches are typically followed: rules-based and flexible optimization. The rules-based approach follows predetermined, predictable schedules, such as insurance risk tables. The optimization approach adapts to dynamic inputs and multiple constraints.

Using Predictive DSS for Future Decisions:  These DSS tools tap predictive analytics techniques capable of anticipating future trends with a high degree of accuracy. By triangulating past events, current parameters and a range of external data too complex to do manually, predictive DSS can help companies make data-driven decisions about the future.

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From Data and Models to Decision Support Systems: Lessons and Advice for the Future

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Model-based Decision Support Systems (DSSs) employ various types of models, such as statistical, optimization, simulation, or rule-based. Models are used to assess and analyze the given decision situation, and on this basis advise the decision-maker. Generally, the DSS development process involves three steps: (1) model development, (2) implementing the model(s) in a DSS, and (3) using the DSS. In this chapter, we focus on two model development approaches: Data Mining and Expert Modeling. We advocate for combing the two in order to get better models and better DSSs in general. We illustrate some points and potential pitfalls using an example of the PD_manager DSS, which is aimed at supporting medication change decisions in the management of Parkinson’s disease. Based on the experience from PD_manager and some other DSS development projects, we propose the so-called 5C requirements for better DSS models: correctness, completeness, consistency, comprehensibility, and convenience. Finally, we summarize the lessons learned and give advice to DSS developers and researchers.

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Acknowledgments

The author acknowledges the financial support from the Slovenian Research Agency, research core funding P2-0103. The PD_manager project was funded within the EU Framework Programme for Research and Innovation Horizon 2020, under grant number 643706. Data used in the preparation of this article were obtained from the Parkinson’s Progression Markers Initiative (PPMI) database ( www.ppmi-info.org/data ). For up-to-date information on the study, visit www.ppmi-info.org . PPMI—a public–private partnership—is funded by the Michael J. Fox Foundation for Parkinson’s Research and funding partners, including Abbvie, Allergan, Amathus, Avid, Biogen, BioLegend, Bristol-Myers Squibb, Celgene, Jenali, GE Healthcare, Genentech, GlaxoSmithKline, Janssen Neuroscience, Lilly, Lundbeck, Merck, MSD, Pfizer, Piramal, Prevail, Roche, Sanofy Genzyme, Servier, Takeda, Teva, UCB, Verily, and Voyager.

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Bohanec, M. (2021). From Data and Models to Decision Support Systems: Lessons and Advice for the Future. In: Papathanasiou, J., Zaraté, P., Freire de Sousa, J. (eds) EURO Working Group on DSS. Integrated Series in Information Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-70377-6_11

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Decision Support Systems Applications and Uses

Table of Contents

Should you base your business decision-making on hard data or a gut feeling? When developing products, Steve Jobs trusted his judgment above everything else, and he seems to have been right more times than he was wrong. 

Intuition is often the source for new products and business improvement projects. But, for many entrepreneurs, acting on just an instinctive feeling alone is too risky. They want to test their ideas before deciding to take a particular course of action.

One way to do this is with decision support software. Below, we explain how decision support software works and how it can help you run your business better.

What is a decision support system?

A decision support system (DSS) is a computer-based information system that organizes, collects and analyzes business data. This analysis is then used by decision-makers to help them better manage and plan their organization or business. 

The typical types of information that are gathered by a DSS include sales figures, projected revenue and inventory data that has been organized into relational databases. The information it analyzes can come from multiple sources, like documents, raw data, management, business models and personal knowledge from employees.

DSS applications can be used in various fields, including credit loan verification, medical diagnosis, various types of business management , and evaluating bids on engineering, agricultural and rail projects.

Types of decision support systems

While there is a DSS application for nearly every  decision-making process , most of these tools fall into one of five categories.

Document-driven DSSs

Document-driven DSSs are widely used and allow users to search for information in internal and external databases (including the internet) using keywords. They sift through structured and unstructured data in documents, like profiles, ratings and financial spreadsheets. These systems are typically found online and in electronic files. [ Read related article: The Best Spreadsheet Software ]

Data-driven DSSs

Like document-driven DSSs, data-driven DSSs use quality data to determine a course of action based on a systematic process. They strategically break down questions and goals into pieces based on data.

For example, a business owner wanting to purchase additional equipment for operations could use one of these systems by looking at any data that supports this decision. Revenue, how frequently current equipment is used and the efficiency of current operations are some factors the owner could consider. By using a data-driven DSS, the owner can analyze ways to collect data to assess these factors and use the findings to make a decision on purchasing additional equipment.

Knowledge-driven DSSs

Knowledge-driven DSSs are mainly used by managers to find recommendations or suggestions for detailed problem-solving. These computer-based systems use artificial intelligence and human intellect to look at how issues of a problem are connected. They’re capable of making suggestions regarding how to act as well as recommending supporting material on a particular issue to users. They can also employ data-mining methods to make predictions for tests or studies and look at patterns to use for marketing plans.

Model-driven DSSs

Model-driven DSSs help users to make choices and analyze decisions. They use models in areas like finances, simulations and statistics to present possible options in making a decision. Managers and staff use these tools to better understand the potential outcomes of a particular decision.

These systems use databases, but they are typically smaller than the ones used in data-driven DSSs. Simple processes use one model to look at basic decisions.

Combining two or more models often makes a process more complicated but can also help with weighing options for complex decisions.

Communication-driven DSSs

Teams use communication-driven DSSs to work together better. They make it easier for people to communicate and share information during the decision-making process.

Software and technology, such as video conferencing, instant internal messaging , and other network and online platforms are examples of communication-driven DSSs. They allow teams to consider choices and select options while meeting virtually and receiving quick responses from team members.

Specific uses for DSSs in business

There are many different ways managers can use DSS software to their advantage. Typically, business planners will build custom DSSs to evaluate specific operations. These include inventory management, in which DSS applications can provide guidance on establishing supply chain movement, and sales, in which DSS software helps managers predict how changes may affect results.

To manage inventory

DSSs are very helpful in evaluating inventory to help a business’s cash flow and profitability by predicting demand for particular products and itemizing assets.

To aid sales optimization and sales projections

Decision support technology can also analyze sales data, make predictions and monitor existing revenue patterns. Planners can use the technology to tackle sales numbers using a variety of decision support resources.

To optimize industry-specific systems

Other uses for decision support systems include projecting the future of a business or to get a bird’s-eye of a company’s performance. These insights help owners and managers navigate difficult situations better, especially when they have reliable information to predict expenditures and revenues.

Examples of DSSs

We all use DSSs in our personal and business lives every day. For example, every time you use Google, you’re using a highly sophisticated DSS that organizes a massive amount of information in a searchable, retrievable format. It can locate the specific images, videos and text files you need to help your business achieve more.

GPS tracking is another type of DSS. As you can see in our Verizon Connect review , its software allows drivers to determine the best and quickest route between two points while monitoring traffic conditions and helping them avoid congestion.

These are some other uses of DSS, including:

• Agriculture:  Farmers use DSS tools for crop planning to help them determine the best times for planting, fertilization and harvesting.
• Medicine:  Clinical DSS technology has many uses: maintaining research information about chemotherapy protocols, preventive and follow-up care, and monitoring medication orders. DSSs are also used with medical diagnosis software.
• Weather forecasting:  Some states use DSSs to provide information about potential future hazards such as floods. To do this, they factor in real-time weather conditions, floodplain boundaries information and historic county flood data.
• Real estate: Real estate companies use DSSs to manage data on comparable home prices and acreage.
• Education:  Universities and colleges use DSSs to know how many students they currently have enrolled. This helps them predict how many students will register for particular courses or whether the student population is sufficient to meet the university’s costs.

Additional reporting by Shayna Waltower

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What Is a Decision Support System?

• February 15, 2024 Updated

A Decision Support System (DSS) is an interactive information system that helps decision-makers use data and models to solve unstructured or semi-structured problems. These systems assist in making informed and sound decisions by analyzing large amounts of data, providing comprehensive reports, and forecasting future trends.

In this article, we will explain “What is a Decision Support System (DSS)?, its role in AI, key components, and everything you want to know about it in detail. So why wait? Keep reading this article, written by AI Scientists at All About AI .

What Is a Decision Support System?: Not Your Average Superhero’s Sidekick!

Imagine you have a big, smart helper called a Decision Support System (DSS). It’s like a magic computer that helps people make tough decisions by using lots of information and special tools. Think of it as having a super smart friend who can help you solve tricky puzzles by giving you hints and ideas.

What is a Decision Support System (DSS)? – An Overview

Now that you understand the basic concept of “What is a Decision Support System (DSS)?, let’s get started by taking a quick look at it.

Data Integration:

DSS systems integrate data from multiple sources, including internal databases , external data feeds, and manual inputs. This integration allows for a more holistic view of the problem at hand, ensuring that decisions are made based on comprehensive and up-to-date information.

Analytical Tools:

DSS utilizes a range of analytical tools and techniques, such as statistical analysis, optimization models, and forecasting methods. These tools help in identifying patterns , trends, and relationships in the data, which can be crucial for making informed decisions.

User-Driven:

These systems are designed with the end-user in mind, ensuring that they are accessible to decision-makers who may not have extensive technical expertise. This user-centric approach includes intuitive interfaces and the ability to customize reports and analyses.

Interactive:

DSS are interactive, allowing users to manipulate and explore data , test out different scenarios, and see the impact of various decision options. This interactive nature helps in understanding complex problems and evaluating different strategies.

They are adaptable to different business needs and contexts. Whether it’s for financial analysis, marketing strategy, or operational efficiency, a DSS can be customized to address specific challenges and objectives.

DSS is distinct from standard operational applications in several key aspects:

Unlike operational applications that are designed for routine tasks and processes, DSS is specifically geared towards supporting complex decision-making processes.

Flexibility:

DSS is more flexible and adaptable compared to operational applications. They can handle a wider range of data inputs and are designed to provide customized outputs.

User Engagement:

DSS requires active engagement from users, who interact with the system to explore data and generate insights. In contrast, operational systems often run automatically or with minimal user interaction.

Data Analysis:

Operational applications are generally focused on data entry, storage, and retrieval. DSS, on the other hand, places a stronger emphasis on data analysis and interpretation, helping to draw meaningful insights from the data.

The Role of AI in Decision Support Systems

After knowing “What is a Decision Support System (DSS)?” let’s understand its role in the world of AI. The integration of Artificial Intelligence (AI) into Decision Support Systems has led to the creation of Intelligent Decision Support Systems (IDSS).

These systems enhance traditional DSS capabilities with AI-driven insights, predictive analytics, and more sophisticated data processing techniques.

Predictive Analytics:

AI in DSS enables predictive analytics , where the system can forecast future trends and outcomes based on historical data. This capability is particularly useful in areas like market analysis, risk assessment, and demand forecasting.

Machine Learning:

Machine learning algorithms within IDSS can identify patterns and anomalies in large data sets that human analysts might miss. This aspect is crucial for uncovering hidden insights and making data-driven decisions.

Natural Language Processing:

AI-powered DSS often includes natural language processing (NLP) , allowing users to interact with the system using natural language queries. This makes the system more accessible and intuitive to use.

Adaptive Learning:

AI enables the system to learn from past decisions and outcomes, continuously improving its recommendations and insights. This learning capability ensures that the system becomes more effective and accurate over time.

Automation:

AI in DSS can automate certain decision-making processes, especially those that are repetitive or require processing large volumes of data. This automation not only speeds up the decision-making process but also reduces the potential for human error.

Key Components of a Decision Support System

A Decision Support System is typically comprised of three key components: the knowledge base, the software system, and the user interface.

Knowledge Base

The knowledge base is a critical component of a DSS, providing the necessary data and information for decision-making.

Data Repository:

This includes a vast collection of historical data , documents, and other relevant information that the system uses to make decisions.

Model Base:

The model base stores various mathematical and analytical models that the system uses to process data and simulate different scenarios. These models can range from simple statistical tools to complex predictive algorithms.

This consists of a set of rules and algorithms that guide the system in data processing and decision-making. These rules are often based on industry best practices or specific organizational policies.

Update Mechanism:

A crucial aspect of the knowledge base is its ability to update and incorporate new data and information, ensuring that the system’s decisions are based on the most current data.

Integration:

The knowledge base integrates data from both internal and external sources, providing a comprehensive view of the information relevant to the decision-making process.

Software System

The software system is the core of a DSS, performing the necessary computations and processing to generate insights and recommendations.

Processing Engine:

This is the heart of the software system, where data is processed using the models and algorithms stored in the model base. It’s responsible for analyzing the data, running simulations, and generating outputs.

The software system includes a range of analytical tools for data analysis, ranging from simple statistical tools to complex data mining techniques. These tools help in extracting meaningful insights from large and complex datasets.

Customization:

The software system can be customized to suit the specific needs of the organization and the decision-making context. This includes the ability to adjust models, change parameters, and configure outputs.

Scalability:

A key feature of the software system is its scalability, allowing it to handle increasing amounts of data and more complex models as the organization’s needs grow.

Given the sensitive nature of the data and the importance of the decisions being made, the software system includes robust security features to protect data integrity and confidentiality.

User Interface

The user interface is the point of interaction between the decision-maker and the DSS, designed to be intuitive and user-friendly.

Accessibility:

The interface is designed to be accessible to users with varying levels of technical expertise, ensuring that decision-makers can effectively use the system regardless of their background.

Visualization Tools:

It includes various data visualization tools, such as charts, graphs, and dashboards, which help users understand complex data and insights visually.

Interaction:

The interface allows users to interact with the system, inputting data, querying information, and exploring different scenarios. This interactive capability is crucial for effective decision-making.

Users can customize the interface according to their preferences and needs, including the layout, the types of reports generated, and the level of detail presented.

Feedback Mechanism:

The interface often includes a mechanism for users to provide feedback on the system’s performance and outputs, which can be used to improve the system over time.

Types of Decision Support Systems

There are several types of Decision Support Systems, each designed to address different types of decision-making needs.

Data-driven DSS:

Focuses primarily on the processing and analysis of large sets of data. These systems are commonly used in situations where the decision-making process is heavily reliant on data, such as market analysis or operational efficiency studies.

Model-driven DSS:

Relies on mathematical models and simulations to support decision-making. These are often used in scenarios where it’s possible to simulate different options and outcomes, such as financial forecasting or logistics planning.

Communication-driven and Group DSS:

Designed to support decision-making in a group context. These systems facilitate communication and collaboration among team members, helping groups to reach consensus and make collective decisions.

Knowledge-driven DSS:

Provides specialized problem-solving expertise and knowledge. These systems are often used in areas where specific expertise is required, such as medical diagnosis or legal compliance.

Document-driven DSS:

Manages and retrieves large volumes of unstructured data , such as documents and reports. These systems are useful in scenarios where decisions are based on the analysis of text-based information, like legal case analysis or research and development.

Practical Applications of DSS in Various Industries

Now that you completely understand “What is a Decision Support System (DSS)?” let’s learn about its implementation across a wide range of industries, each leveraging its capabilities to address industry-specific challenges.

Healthcare:

In healthcare, DSS is used for diagnosing diseases, planning treatment protocols, and managing hospital resources. For instance, a DSS might analyze patient data to recommend the most effective treatment plan or manage schedules and resources in a hospital.

Agriculture:

In agriculture, DSS helps in crop planning, weather forecasting, and resource management. Farmers can use DSS to decide on the best time to plant or harvest, or how to allocate resources like water and fertilizers most effectively.

Corporate Operations:

In the corporate world, DSS is utilized for financial analysis, strategic planning, and project management. Companies might use a DSS to forecast market trends, analyze financial risks, or manage large, complex projects.

Future of Decision Support Systems

The future of Decision Support Systems is likely to be shaped by several key trends and developments.

Integration with Emerging Technologies:

Future DSS are expected to integrate more closely with emerging technologies like the Internet of Things (IoT), blockchain, and advanced analytics. This integration will enable more real-time data analysis and decision-making.

More Advanced AI Capabilities:

The AI components of DSS are likely to become more sophisticated, with improved capabilities in areas like machine learning, predictive analytics, and natural language processing. This will make DSS even more powerful in terms of their ability to analyze data and generate insights.

Increased Customization and Flexibility:

As businesses and organizations become more diverse and their decision-making needs more specific, DSS will need to offer increased customization and flexibility to meet these varied needs.

Enhanced User Experience:

Future DSS are expected to feature more intuitive and user-friendly interfaces, making them accessible to a wider range of users and decision-making contexts.

Greater Emphasis on Data Privacy and Security:

As DSS become more central to critical decision-making processes, there will be an increased focus on ensuring data privacy and security. This is particularly important given the sensitive nature of the data often involved in these decisions.

Want to Read More? Explore These AI Glossaries!

Dive into the realm of artificial intelligence with our meticulously selected glossaries. Perfect for beginners and advanced learners alike, there’s always a new discovery awaiting!

• What is Anytime Algorithm? : An Anytime Algorithm, in the context of AI, is a computational method that aims to generate progressively better solutions to a problem, even with limited time or resources.
• What is Application Programming Interface? : Application Programming Interface (API) is a crucial component in the realm of software development and AI systems.
• What is Approximate String Matching? : Approximate String Matching (ASM), also known as fuzzy string matching or approximate string searching, is a fundamental concept in the field of Artificial Intelligence (AI) and natural language processing.
• What is Approximation Error? : Approximation error, in the context of AI and mathematics, refers to the discrepancy between the actual value of a parameter or output and the estimated value obtained through an approximation method or algorithm.
• What is an Argumentation Framework? : An argumentation framework is a structured representation of arguments and their relationships, used to model and analyze reasoning processes in AI systems.

Here are some of the most commonly asked questions about the topic other than “What is a Decision Support System (DSS)?”

What is an example of a Decision Support System?

Why is decision support system important in decision-making, how can a decision support system (dss) help make decisions, what are the disadvantages of a decision support system, conclusion:.

Decision Support Systems are powerful tools that have transformed the way organizations make decisions. By leveraging data, advanced analytics, and AI, DSS enhances decision-making processes across various industries. As technology continues to evolve, so too will the capabilities and applications of DSS, further solidifying their role as essential tools in modern decision-making.

Now that you understand “What is Decision Support System (DSS)?” doesn’t mean you know everything about AI. To understand more AI-related concepts, theories, and terms, check out more articles in our AI Terminology Book .

Digital marketing enthusiast by day, nature wanderer by dusk. Dave Andre blends two decades of AI and SaaS expertise into impactful strategies for SMEs. His weekends? Lost in books on tech trends and rejuvenating on scenic trails.

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What Is a Decision Support System Used for?

What is an example of a decision support system, what are the benefits of a decision support system.

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Decision Support System (DSS): What It Is and How Businesses Use Them

Investopedia / Michela Buttignol

What Is a Decision Support System (DSS)?

A decision support system (DSS) is a computerized program used to support determinations, judgments, and courses of action in an organization or a business. A DSS sifts through and analyzes massive amounts of data, compiling comprehensive information that can be used to solve problems and in decision-making .

Typical information used by a DSS includes target or projected revenue, sales figures or past ones from different time periods, and other inventory- or operations-related data.

Key Takeaways

• A decision support system (DSS) is a computerized system that gathers and analyzes data, synthesizing it to produce comprehensive information reports.
• A decision support system differs from an ordinary operations application, whose function is just to collect data.
• Decision support systems allow for more informed decision-making, timely problem-solving, and improved efficiency in dealing with issues or operations, planning, and even management.

Understanding a Decision Support System (DSS)

A decision support system gathers and analyzes data, synthesizing it to produce comprehensive information reports. In this way, as an informational application, a DSS differs from an ordinary operations application, whose function is just to collect data.

The DSS can either be completely computerized or powered by humans. In some cases, it may combine both. The ideal systems analyze information and actually make decisions for the user. At the very least, they allow human users to make more informed decisions at a quicker pace.

The DSS can be employed by operations management and other planning departments in an organization to compile information and data and synthesize it into actionable intelligence. In fact, these systems are primarily used by mid- to upper-level management.

For example, a DSS may be used to project a company's revenue over the upcoming six months based on new assumptions about product sales. Due to a large number of factors that surround projected revenue figures, this is not a straightforward calculation that can be done manually. However, a DSS can integrate all the multiple variables and generate an outcome and alternate outcomes, all based on the company's past product sales data and current variables.

A DSS can be tailored for any industry, profession, or domain including the medical field, government agencies, agricultural concerns, and corporate operations.

Characteristics of a DSS

The primary purpose of using a DSS is to present information to the customer in an easy-to-understand way. A DSS system is beneficial because it can be programmed to generate many types of reports, all based on user specifications. For example, the DSS can generate information and output its information graphically, as in a bar chart that represents projected revenue or as a written report.

As technology continues to advance, data analysis is no longer limited to large, bulky mainframe computers. Since a DSS is essentially an application, it can be loaded on most computer systems, whether on desktops or laptops. Certain DSS applications are also available through mobile devices.

The flexibility of the DSS is extremely beneficial for users who travel frequently. This gives them the opportunity to be well-informed at all times, providing them the ability to make the best decisions for their company and customers on the go or even on the spot.

In organizations, a decision support system (DSS) analyzes and synthesizes vast amounts of data to assist in decision-making . With this information, it produces reports that may project revenue, sales, or manage inventory. Through the integration of multiple variables, a DSS can produce a number of different outcomes based on the company’s previous data and current inputs. 

Many different industries, from medicine to agriculture, use decision support systems. To help diagnose a patient, a medical clinician may use a computerized decision support system for diagnostics and prescriptions. Combining clinician inputs and previous electronic health records, a decision support system may assist a doctor in diagnosing a patient.

Broadly speaking, decision support systems help in making more informed decisions. Often used by upper and mid-level management, decision support systems are used to make actionable decisions, or produce multiple possible outcomes based on current and historical company data. At the same time, decision support systems can be used to produce reports for customers that are easily digestible and can be adjusted based on user specifications. 

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35 problem-solving techniques and methods for solving complex problems

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All teams and organizations encounter challenges as they grow. There are problems that might occur for teams when it comes to miscommunication or resolving business-critical issues . You may face challenges around growth , design , user engagement, and even team culture and happiness. In short, problem-solving techniques should be part of every team’s skillset.

Problem-solving methods are primarily designed to help a group or team through a process of first identifying problems and challenges , ideating possible solutions , and then evaluating the most suitable .

Finding effective solutions to complex problems isn’t easy, but by using the right process and techniques, you can help your team be more efficient in the process.

So how do you develop strategies that are engaging, and empower your team to solve problems effectively?

In this blog post, we share a series of problem-solving tools you can use in your next workshop or team meeting. You’ll also find some tips for facilitating the process and how to enable others to solve complex problems.

Let’s get started! 

How do you identify problems?

How do you identify the right solution.

• Tips for more effective problem-solving

Complete problem-solving methods

• Problem-solving techniques to identify and analyze problems
• Problem-solving techniques for developing solutions

Problem-solving warm-up activities

Closing activities for a problem-solving process.

Before you can move towards finding the right solution for a given problem, you first need to identify and define the problem you wish to solve. 

Here, you want to clearly articulate what the problem is and allow your group to do the same. Remember that everyone in a group is likely to have differing perspectives and alignment is necessary in order to help the group move forward. 

Identifying a problem accurately also requires that all members of a group are able to contribute their views in an open and safe manner. It can be scary for people to stand up and contribute, especially if the problems or challenges are emotive or personal in nature. Be sure to try and create a psychologically safe space for these kinds of discussions.

Remember that problem analysis and further discussion are also important. Not taking the time to fully analyze and discuss a challenge can result in the development of solutions that are not fit for purpose or do not address the underlying issue.

Successfully identifying and then analyzing a problem means facilitating a group through activities designed to help them clearly and honestly articulate their thoughts and produce usable insight.

With this data, you might then produce a problem statement that clearly describes the problem you wish to be addressed and also state the goal of any process you undertake to tackle this issue.  

Finding solutions is the end goal of any process. Complex organizational challenges can only be solved with an appropriate solution but discovering them requires using the right problem-solving tool.

After you’ve explored a problem and discussed ideas, you need to help a team discuss and choose the right solution. Consensus tools and methods such as those below help a group explore possible solutions before then voting for the best. They’re a great way to tap into the collective intelligence of the group for great results!

Remember that the process is often iterative. Great problem solvers often roadtest a viable solution in a measured way to see what works too. While you might not get the right solution on your first try, the methods below help teams land on the most likely to succeed solution while also holding space for improvement.

Every effective problem solving process begins with an agenda . A well-structured workshop is one of the best methods for successfully guiding a group from exploring a problem to implementing a solution.

In SessionLab, it’s easy to go from an idea to a complete agenda . Start by dragging and dropping your core problem solving activities into place . Add timings, breaks and necessary materials before sharing your agenda with your colleagues.

The resulting agenda will be your guide to an effective and productive problem solving session that will also help you stay organized on the day!

Tips for more effective problem solving

Problem-solving activities are only one part of the puzzle. While a great method can help unlock your team’s ability to solve problems, without a thoughtful approach and strong facilitation the solutions may not be fit for purpose.

Let’s take a look at some problem-solving tips you can apply to any process to help it be a success!

Clearly define the problem

Jumping straight to solutions can be tempting, though without first clearly articulating a problem, the solution might not be the right one. Many of the problem-solving activities below include sections where the problem is explored and clearly defined before moving on.

This is a vital part of the problem-solving process and taking the time to fully define an issue can save time and effort later. A clear definition helps identify irrelevant information and it also ensures that your team sets off on the right track.

Don’t jump to conclusions

It’s easy for groups to exhibit cognitive bias or have preconceived ideas about both problems and potential solutions. Be sure to back up any problem statements or potential solutions with facts, research, and adequate forethought.

The best techniques ask participants to be methodical and challenge preconceived notions. Make sure you give the group enough time and space to collect relevant information and consider the problem in a new way. By approaching the process with a clear, rational mindset, you’ll often find that better solutions are more forthcoming.  

Try different approaches  

Problems come in all shapes and sizes and so too should the methods you use to solve them. If you find that one approach isn’t yielding results and your team isn’t finding different solutions, try mixing it up. You’ll be surprised at how using a new creative activity can unblock your team and generate great solutions.

Don’t take it personally 

Depending on the nature of your team or organizational problems, it’s easy for conversations to get heated. While it’s good for participants to be engaged in the discussions, ensure that emotions don’t run too high and that blame isn’t thrown around while finding solutions.

You’re all in it together, and even if your team or area is seeing problems, that isn’t necessarily a disparagement of you personally. Using facilitation skills to manage group dynamics is one effective method of helping conversations be more constructive.

Get the right people in the room

Your problem-solving method is often only as effective as the group using it. Getting the right people on the job and managing the number of people present is important too!

If the group is too small, you may not get enough different perspectives to effectively solve a problem. If the group is too large, you can go round and round during the ideation stages.

Creating the right group makeup is also important in ensuring you have the necessary expertise and skillset to both identify and follow up on potential solutions. Carefully consider who to include at each stage to help ensure your problem-solving method is followed and positioned for success.

Document everything

The best solutions can take refinement, iteration, and reflection to come out. Get into a habit of documenting your process in order to keep all the learnings from the session and to allow ideas to mature and develop. Many of the methods below involve the creation of documents or shared resources. Be sure to keep and share these so everyone can benefit from the work done!

Bring a facilitator 

Facilitation is all about making group processes easier. With a subject as potentially emotive and important as problem-solving, having an impartial third party in the form of a facilitator can make all the difference in finding great solutions and keeping the process moving. Consider bringing a facilitator to your problem-solving session to get better results and generate meaningful solutions!

Develop your problem-solving skills

It takes time and practice to be an effective problem solver. While some roles or participants might more naturally gravitate towards problem-solving, it can take development and planning to help everyone create better solutions.

You might develop a training program, run a problem-solving workshop or simply ask your team to practice using the techniques below. Check out our post on problem-solving skills to see how you and your group can develop the right mental process and be more resilient to issues too!

Design a great agenda

Workshops are a great format for solving problems. With the right approach, you can focus a group and help them find the solutions to their own problems. But designing a process can be time-consuming and finding the right activities can be difficult.

Check out our workshop planning guide to level-up your agenda design and start running more effective workshops. Need inspiration? Check out templates designed by expert facilitators to help you kickstart your process!

In this section, we’ll look at in-depth problem-solving methods that provide a complete end-to-end process for developing effective solutions. These will help guide your team from the discovery and definition of a problem through to delivering the right solution.

If you’re looking for an all-encompassing method or problem-solving model, these processes are a great place to start. They’ll ask your team to challenge preconceived ideas and adopt a mindset for solving problems more effectively.

• Six Thinking Hats
• Lightning Decision Jam
• Problem Definition Process
• Discovery & Action Dialogue

Design Sprint 2.0

• Open Space Technology

1. Six Thinking Hats

Individual approaches to solving a problem can be very different based on what team or role an individual holds. It can be easy for existing biases or perspectives to find their way into the mix, or for internal politics to direct a conversation.

Six Thinking Hats is a classic method for identifying the problems that need to be solved and enables your team to consider them from different angles, whether that is by focusing on facts and data, creative solutions, or by considering why a particular solution might not work.

Like all problem-solving frameworks, Six Thinking Hats is effective at helping teams remove roadblocks from a conversation or discussion and come to terms with all the aspects necessary to solve complex problems.

2. Lightning Decision Jam

Featured courtesy of Jonathan Courtney of AJ&Smart Berlin, Lightning Decision Jam is one of those strategies that should be in every facilitation toolbox. Exploring problems and finding solutions is often creative in nature, though as with any creative process, there is the potential to lose focus and get lost.

Unstructured discussions might get you there in the end, but it’s much more effective to use a method that creates a clear process and team focus.

In Lightning Decision Jam, participants are invited to begin by writing challenges, concerns, or mistakes on post-its without discussing them before then being invited by the moderator to present them to the group.

From there, the team vote on which problems to solve and are guided through steps that will allow them to reframe those problems, create solutions and then decide what to execute on. 

By deciding the problems that need to be solved as a team before moving on, this group process is great for ensuring the whole team is aligned and can take ownership over the next stages. 

Lightning Decision Jam (LDJ)   #action   #decision making   #problem solving   #issue analysis   #innovation   #design   #remote-friendly   The problem with anything that requires creative thinking is that it’s easy to get lost—lose focus and fall into the trap of having useless, open-ended, unstructured discussions. Here’s the most effective solution I’ve found: Replace all open, unstructured discussion with a clear process. What to use this exercise for: Anything which requires a group of people to make decisions, solve problems or discuss challenges. It’s always good to frame an LDJ session with a broad topic, here are some examples: The conversion flow of our checkout Our internal design process How we organise events Keeping up with our competition Improving sales flow

3. Problem Definition Process

While problems can be complex, the problem-solving methods you use to identify and solve those problems can often be simple in design. 

By taking the time to truly identify and define a problem before asking the group to reframe the challenge as an opportunity, this method is a great way to enable change.

Begin by identifying a focus question and exploring the ways in which it manifests before splitting into five teams who will each consider the problem using a different method: escape, reversal, exaggeration, distortion or wishful. Teams develop a problem objective and create ideas in line with their method before then feeding them back to the group.

This method is great for enabling in-depth discussions while also creating space for finding creative solutions too!

Problem Definition   #problem solving   #idea generation   #creativity   #online   #remote-friendly   A problem solving technique to define a problem, challenge or opportunity and to generate ideas.

4. The 5 Whys 

Sometimes, a group needs to go further with their strategies and analyze the root cause at the heart of organizational issues. An RCA or root cause analysis is the process of identifying what is at the heart of business problems or recurring challenges. 

The 5 Whys is a simple and effective method of helping a group go find the root cause of any problem or challenge and conduct analysis that will deliver results. 

By beginning with the creation of a problem statement and going through five stages to refine it, The 5 Whys provides everything you need to truly discover the cause of an issue.

The 5 Whys   #hyperisland   #innovation   This simple and powerful method is useful for getting to the core of a problem or challenge. As the title suggests, the group defines a problems, then asks the question “why” five times, often using the resulting explanation as a starting point for creative problem solving.

5. World Cafe

World Cafe is a simple but powerful facilitation technique to help bigger groups to focus their energy and attention on solving complex problems.

World Cafe enables this approach by creating a relaxed atmosphere where participants are able to self-organize and explore topics relevant and important to them which are themed around a central problem-solving purpose. Create the right atmosphere by modeling your space after a cafe and after guiding the group through the method, let them take the lead!

Making problem-solving a part of your organization’s culture in the long term can be a difficult undertaking. More approachable formats like World Cafe can be especially effective in bringing people unfamiliar with workshops into the fold. 

World Cafe   #hyperisland   #innovation   #issue analysis   World Café is a simple yet powerful method, originated by Juanita Brown, for enabling meaningful conversations driven completely by participants and the topics that are relevant and important to them. Facilitators create a cafe-style space and provide simple guidelines. Participants then self-organize and explore a set of relevant topics or questions for conversation.

6. Discovery & Action Dialogue (DAD)

One of the best approaches is to create a safe space for a group to share and discover practices and behaviors that can help them find their own solutions.

With DAD, you can help a group choose which problems they wish to solve and which approaches they will take to do so. It’s great at helping remove resistance to change and can help get buy-in at every level too!

This process of enabling frontline ownership is great in ensuring follow-through and is one of the methods you will want in your toolbox as a facilitator.

Discovery & Action Dialogue (DAD)   #idea generation   #liberating structures   #action   #issue analysis   #remote-friendly   DADs make it easy for a group or community to discover practices and behaviors that enable some individuals (without access to special resources and facing the same constraints) to find better solutions than their peers to common problems. These are called positive deviant (PD) behaviors and practices. DADs make it possible for people in the group, unit, or community to discover by themselves these PD practices. DADs also create favorable conditions for stimulating participants’ creativity in spaces where they can feel safe to invent new and more effective practices. Resistance to change evaporates as participants are unleashed to choose freely which practices they will adopt or try and which problems they will tackle. DADs make it possible to achieve frontline ownership of solutions.

7. Design Sprint 2.0

Want to see how a team can solve big problems and move forward with prototyping and testing solutions in a few days? The Design Sprint 2.0 template from Jake Knapp, author of Sprint, is a complete agenda for a with proven results.

Developing the right agenda can involve difficult but necessary planning. Ensuring all the correct steps are followed can also be stressful or time-consuming depending on your level of experience.

Use this complete 4-day workshop template if you are finding there is no obvious solution to your challenge and want to focus your team around a specific problem that might require a shortcut to launching a minimum viable product or waiting for the organization-wide implementation of a solution.

8. Open space technology

Open space technology- developed by Harrison Owen – creates a space where large groups are invited to take ownership of their problem solving and lead individual sessions. Open space technology is a great format when you have a great deal of expertise and insight in the room and want to allow for different takes and approaches on a particular theme or problem you need to be solved.

Start by bringing your participants together to align around a central theme and focus their efforts. Explain the ground rules to help guide the problem-solving process and then invite members to identify any issue connecting to the central theme that they are interested in and are prepared to take responsibility for.

Once participants have decided on their approach to the core theme, they write their issue on a piece of paper, announce it to the group, pick a session time and place, and post the paper on the wall. As the wall fills up with sessions, the group is then invited to join the sessions that interest them the most and which they can contribute to, then you’re ready to begin!

Everyone joins the problem-solving group they’ve signed up to, record the discussion and if appropriate, findings can then be shared with the rest of the group afterward.

Open Space Technology   #action plan   #idea generation   #problem solving   #issue analysis   #large group   #online   #remote-friendly   Open Space is a methodology for large groups to create their agenda discerning important topics for discussion, suitable for conferences, community gatherings and whole system facilitation

Techniques to identify and analyze problems

Using a problem-solving method to help a team identify and analyze a problem can be a quick and effective addition to any workshop or meeting.

While further actions are always necessary, you can generate momentum and alignment easily, and these activities are a great place to get started.

We’ve put together this list of techniques to help you and your team with problem identification, analysis, and discussion that sets the foundation for developing effective solutions.

Let’s take a look!

• The Creativity Dice
• Fishbone Analysis
• Problem Tree
• SWOT Analysis
• Agreement-Certainty Matrix
• The Journalistic Six
• LEGO Challenge
• What, So What, Now What?
• Journalists

Individual and group perspectives are incredibly important, but what happens if people are set in their minds and need a change of perspective in order to approach a problem more effectively?

Flip It is a method we love because it is both simple to understand and run, and allows groups to understand how their perspectives and biases are formed. 

Participants in Flip It are first invited to consider concerns, issues, or problems from a perspective of fear and write them on a flip chart. Then, the group is asked to consider those same issues from a perspective of hope and flip their understanding.  

No problem and solution is free from existing bias and by changing perspectives with Flip It, you can then develop a problem solving model quickly and effectively.

Flip It!   #gamestorming   #problem solving   #action   Often, a change in a problem or situation comes simply from a change in our perspectives. Flip It! is a quick game designed to show players that perspectives are made, not born.

10. The Creativity Dice

One of the most useful problem solving skills you can teach your team is of approaching challenges with creativity, flexibility, and openness. Games like The Creativity Dice allow teams to overcome the potential hurdle of too much linear thinking and approach the process with a sense of fun and speed. 

In The Creativity Dice, participants are organized around a topic and roll a dice to determine what they will work on for a period of 3 minutes at a time. They might roll a 3 and work on investigating factual information on the chosen topic. They might roll a 1 and work on identifying the specific goals, standards, or criteria for the session.

Encouraging rapid work and iteration while asking participants to be flexible are great skills to cultivate. Having a stage for idea incubation in this game is also important. Moments of pause can help ensure the ideas that are put forward are the most suitable. 

The Creativity Dice   #creativity   #problem solving   #thiagi   #issue analysis   Too much linear thinking is hazardous to creative problem solving. To be creative, you should approach the problem (or the opportunity) from different points of view. You should leave a thought hanging in mid-air and move to another. This skipping around prevents premature closure and lets your brain incubate one line of thought while you consciously pursue another.

11. Fishbone Analysis

Organizational or team challenges are rarely simple, and it’s important to remember that one problem can be an indication of something that goes deeper and may require further consideration to be solved.

Fishbone Analysis helps groups to dig deeper and understand the origins of a problem. It’s a great example of a root cause analysis method that is simple for everyone on a team to get their head around. 

Participants in this activity are asked to annotate a diagram of a fish, first adding the problem or issue to be worked on at the head of a fish before then brainstorming the root causes of the problem and adding them as bones on the fish. 

Using abstractions such as a diagram of a fish can really help a team break out of their regular thinking and develop a creative approach.

Fishbone Analysis   #problem solving   ##root cause analysis   #decision making   #online facilitation   A process to help identify and understand the origins of problems, issues or observations.

12. Problem Tree 

Encouraging visual thinking can be an essential part of many strategies. By simply reframing and clarifying problems, a group can move towards developing a problem solving model that works for them. 

In Problem Tree, groups are asked to first brainstorm a list of problems – these can be design problems, team problems or larger business problems – and then organize them into a hierarchy. The hierarchy could be from most important to least important or abstract to practical, though the key thing with problem solving games that involve this aspect is that your group has some way of managing and sorting all the issues that are raised.

Once you have a list of problems that need to be solved and have organized them accordingly, you’re then well-positioned for the next problem solving steps.

Problem tree   #define intentions   #create   #design   #issue analysis   A problem tree is a tool to clarify the hierarchy of problems addressed by the team within a design project; it represents high level problems or related sublevel problems.

13. SWOT Analysis

Chances are you’ve heard of the SWOT Analysis before. This problem-solving method focuses on identifying strengths, weaknesses, opportunities, and threats is a tried and tested method for both individuals and teams.

Start by creating a desired end state or outcome and bare this in mind – any process solving model is made more effective by knowing what you are moving towards. Create a quadrant made up of the four categories of a SWOT analysis and ask participants to generate ideas based on each of those quadrants.

Once you have those ideas assembled in their quadrants, cluster them together based on their affinity with other ideas. These clusters are then used to facilitate group conversations and move things forward. 

SWOT analysis   #gamestorming   #problem solving   #action   #meeting facilitation   The SWOT Analysis is a long-standing technique of looking at what we have, with respect to the desired end state, as well as what we could improve on. It gives us an opportunity to gauge approaching opportunities and dangers, and assess the seriousness of the conditions that affect our future. When we understand those conditions, we can influence what comes next.

14. Agreement-Certainty Matrix

Not every problem-solving approach is right for every challenge, and deciding on the right method for the challenge at hand is a key part of being an effective team.

The Agreement Certainty matrix helps teams align on the nature of the challenges facing them. By sorting problems from simple to chaotic, your team can understand what methods are suitable for each problem and what they can do to ensure effective results. 

If you are already using Liberating Structures techniques as part of your problem-solving strategy, the Agreement-Certainty Matrix can be an invaluable addition to your process. We’ve found it particularly if you are having issues with recurring problems in your organization and want to go deeper in understanding the root cause. 

Agreement-Certainty Matrix   #issue analysis   #liberating structures   #problem solving   You can help individuals or groups avoid the frequent mistake of trying to solve a problem with methods that are not adapted to the nature of their challenge. The combination of two questions makes it possible to easily sort challenges into four categories: simple, complicated, complex , and chaotic .  A problem is simple when it can be solved reliably with practices that are easy to duplicate.  It is complicated when experts are required to devise a sophisticated solution that will yield the desired results predictably.  A problem is complex when there are several valid ways to proceed but outcomes are not predictable in detail.  Chaotic is when the context is too turbulent to identify a path forward.  A loose analogy may be used to describe these differences: simple is like following a recipe, complicated like sending a rocket to the moon, complex like raising a child, and chaotic is like the game “Pin the Tail on the Donkey.”  The Liberating Structures Matching Matrix in Chapter 5 can be used as the first step to clarify the nature of a challenge and avoid the mismatches between problems and solutions that are frequently at the root of chronic, recurring problems.

Organizing and charting a team’s progress can be important in ensuring its success. SQUID (Sequential Question and Insight Diagram) is a great model that allows a team to effectively switch between giving questions and answers and develop the skills they need to stay on track throughout the process. 

Begin with two different colored sticky notes – one for questions and one for answers – and with your central topic (the head of the squid) on the board. Ask the group to first come up with a series of questions connected to their best guess of how to approach the topic. Ask the group to come up with answers to those questions, fix them to the board and connect them with a line. After some discussion, go back to question mode by responding to the generated answers or other points on the board.

It’s rewarding to see a diagram grow throughout the exercise, and a completed SQUID can provide a visual resource for future effort and as an example for other teams.

SQUID   #gamestorming   #project planning   #issue analysis   #problem solving   When exploring an information space, it’s important for a group to know where they are at any given time. By using SQUID, a group charts out the territory as they go and can navigate accordingly. SQUID stands for Sequential Question and Insight Diagram.

16. Speed Boat

To continue with our nautical theme, Speed Boat is a short and sweet activity that can help a team quickly identify what employees, clients or service users might have a problem with and analyze what might be standing in the way of achieving a solution.

Methods that allow for a group to make observations, have insights and obtain those eureka moments quickly are invaluable when trying to solve complex problems.

In Speed Boat, the approach is to first consider what anchors and challenges might be holding an organization (or boat) back. Bonus points if you are able to identify any sharks in the water and develop ideas that can also deal with competitors!   

Speed Boat   #gamestorming   #problem solving   #action   Speedboat is a short and sweet way to identify what your employees or clients don’t like about your product/service or what’s standing in the way of a desired goal.

17. The Journalistic Six

Some of the most effective ways of solving problems is by encouraging teams to be more inclusive and diverse in their thinking.

Based on the six key questions journalism students are taught to answer in articles and news stories, The Journalistic Six helps create teams to see the whole picture. By using who, what, when, where, why, and how to facilitate the conversation and encourage creative thinking, your team can make sure that the problem identification and problem analysis stages of the are covered exhaustively and thoughtfully. Reporter’s notebook and dictaphone optional.

The Journalistic Six – Who What When Where Why How   #idea generation   #issue analysis   #problem solving   #online   #creative thinking   #remote-friendly   A questioning method for generating, explaining, investigating ideas.

18. LEGO Challenge

Now for an activity that is a little out of the (toy) box. LEGO Serious Play is a facilitation methodology that can be used to improve creative thinking and problem-solving skills. 

The LEGO Challenge includes giving each member of the team an assignment that is hidden from the rest of the group while they create a structure without speaking.

What the LEGO challenge brings to the table is a fun working example of working with stakeholders who might not be on the same page to solve problems. Also, it’s LEGO! Who doesn’t love LEGO! 

LEGO Challenge   #hyperisland   #team   A team-building activity in which groups must work together to build a structure out of LEGO, but each individual has a secret “assignment” which makes the collaborative process more challenging. It emphasizes group communication, leadership dynamics, conflict, cooperation, patience and problem solving strategy.

19. What, So What, Now What?

If not carefully managed, the problem identification and problem analysis stages of the problem-solving process can actually create more problems and misunderstandings.

The What, So What, Now What? problem-solving activity is designed to help collect insights and move forward while also eliminating the possibility of disagreement when it comes to identifying, clarifying, and analyzing organizational or work problems. 

Facilitation is all about bringing groups together so that might work on a shared goal and the best problem-solving strategies ensure that teams are aligned in purpose, if not initially in opinion or insight.

Throughout the three steps of this game, you give everyone on a team to reflect on a problem by asking what happened, why it is important, and what actions should then be taken. 

This can be a great activity for bringing our individual perceptions about a problem or challenge and contextualizing it in a larger group setting. This is one of the most important problem-solving skills you can bring to your organization.

W³ – What, So What, Now What?   #issue analysis   #innovation   #liberating structures   You can help groups reflect on a shared experience in a way that builds understanding and spurs coordinated action while avoiding unproductive conflict. It is possible for every voice to be heard while simultaneously sifting for insights and shaping new direction. Progressing in stages makes this practical—from collecting facts about What Happened to making sense of these facts with So What and finally to what actions logically follow with Now What . The shared progression eliminates most of the misunderstandings that otherwise fuel disagreements about what to do. Voila!

20. Journalists  

Problem analysis can be one of the most important and decisive stages of all problem-solving tools. Sometimes, a team can become bogged down in the details and are unable to move forward.

Journalists is an activity that can avoid a group from getting stuck in the problem identification or problem analysis stages of the process.

In Journalists, the group is invited to draft the front page of a fictional newspaper and figure out what stories deserve to be on the cover and what headlines those stories will have. By reframing how your problems and challenges are approached, you can help a team move productively through the process and be better prepared for the steps to follow.

Journalists   #vision   #big picture   #issue analysis   #remote-friendly   This is an exercise to use when the group gets stuck in details and struggles to see the big picture. Also good for defining a vision.

Problem-solving techniques for developing solutions 

The success of any problem-solving process can be measured by the solutions it produces. After you’ve defined the issue, explored existing ideas, and ideated, it’s time to narrow down to the correct solution.

Use these problem-solving techniques when you want to help your team find consensus, compare possible solutions, and move towards taking action on a particular problem.

• Improved Solutions
• Four-Step Sketch
• 15% Solutions
• How-Now-Wow matrix
• Impact Effort Matrix

21. Mindspin  

Brainstorming is part of the bread and butter of the problem-solving process and all problem-solving strategies benefit from getting ideas out and challenging a team to generate solutions quickly. 

With Mindspin, participants are encouraged not only to generate ideas but to do so under time constraints and by slamming down cards and passing them on. By doing multiple rounds, your team can begin with a free generation of possible solutions before moving on to developing those solutions and encouraging further ideation. 

This is one of our favorite problem-solving activities and can be great for keeping the energy up throughout the workshop. Remember the importance of helping people become engaged in the process – energizing problem-solving techniques like Mindspin can help ensure your team stays engaged and happy, even when the problems they’re coming together to solve are complex. 

MindSpin   #teampedia   #idea generation   #problem solving   #action   A fast and loud method to enhance brainstorming within a team. Since this activity has more than round ideas that are repetitive can be ruled out leaving more creative and innovative answers to the challenge.

22. Improved Solutions

After a team has successfully identified a problem and come up with a few solutions, it can be tempting to call the work of the problem-solving process complete. That said, the first solution is not necessarily the best, and by including a further review and reflection activity into your problem-solving model, you can ensure your group reaches the best possible result. 

One of a number of problem-solving games from Thiagi Group, Improved Solutions helps you go the extra mile and develop suggested solutions with close consideration and peer review. By supporting the discussion of several problems at once and by shifting team roles throughout, this problem-solving technique is a dynamic way of finding the best solution. 

Improved Solutions   #creativity   #thiagi   #problem solving   #action   #team   You can improve any solution by objectively reviewing its strengths and weaknesses and making suitable adjustments. In this creativity framegame, you improve the solutions to several problems. To maintain objective detachment, you deal with a different problem during each of six rounds and assume different roles (problem owner, consultant, basher, booster, enhancer, and evaluator) during each round. At the conclusion of the activity, each player ends up with two solutions to her problem.

23. Four Step Sketch

Creative thinking and visual ideation does not need to be confined to the opening stages of your problem-solving strategies. Exercises that include sketching and prototyping on paper can be effective at the solution finding and development stage of the process, and can be great for keeping a team engaged. 

By going from simple notes to a crazy 8s round that involves rapidly sketching 8 variations on their ideas before then producing a final solution sketch, the group is able to iterate quickly and visually. Problem-solving techniques like Four-Step Sketch are great if you have a group of different thinkers and want to change things up from a more textual or discussion-based approach.

Four-Step Sketch   #design sprint   #innovation   #idea generation   #remote-friendly   The four-step sketch is an exercise that helps people to create well-formed concepts through a structured process that includes: Review key information Start design work on paper,  Consider multiple variations , Create a detailed solution . This exercise is preceded by a set of other activities allowing the group to clarify the challenge they want to solve. See how the Four Step Sketch exercise fits into a Design Sprint

24. 15% Solutions

Some problems are simpler than others and with the right problem-solving activities, you can empower people to take immediate actions that can help create organizational change. 

Part of the liberating structures toolkit, 15% solutions is a problem-solving technique that focuses on finding and implementing solutions quickly. A process of iterating and making small changes quickly can help generate momentum and an appetite for solving complex problems.

Problem-solving strategies can live and die on whether people are onboard. Getting some quick wins is a great way of getting people behind the process.   

It can be extremely empowering for a team to realize that problem-solving techniques can be deployed quickly and easily and delineate between things they can positively impact and those things they cannot change. 

15% Solutions   #action   #liberating structures   #remote-friendly   You can reveal the actions, however small, that everyone can do immediately. At a minimum, these will create momentum, and that may make a BIG difference.  15% Solutions show that there is no reason to wait around, feel powerless, or fearful. They help people pick it up a level. They get individuals and the group to focus on what is within their discretion instead of what they cannot change.  With a very simple question, you can flip the conversation to what can be done and find solutions to big problems that are often distributed widely in places not known in advance. Shifting a few grains of sand may trigger a landslide and change the whole landscape.

25. How-Now-Wow Matrix

The problem-solving process is often creative, as complex problems usually require a change of thinking and creative response in order to find the best solutions. While it’s common for the first stages to encourage creative thinking, groups can often gravitate to familiar solutions when it comes to the end of the process. 

When selecting solutions, you don’t want to lose your creative energy! The How-Now-Wow Matrix from Gamestorming is a great problem-solving activity that enables a group to stay creative and think out of the box when it comes to selecting the right solution for a given problem.

Problem-solving techniques that encourage creative thinking and the ideation and selection of new solutions can be the most effective in organisational change. Give the How-Now-Wow Matrix a go, and not just for how pleasant it is to say out loud. 

How-Now-Wow Matrix   #gamestorming   #idea generation   #remote-friendly   When people want to develop new ideas, they most often think out of the box in the brainstorming or divergent phase. However, when it comes to convergence, people often end up picking ideas that are most familiar to them. This is called a ‘creative paradox’ or a ‘creadox’. The How-Now-Wow matrix is an idea selection tool that breaks the creadox by forcing people to weigh each idea on 2 parameters.

26. Impact and Effort Matrix

All problem-solving techniques hope to not only find solutions to a given problem or challenge but to find the best solution. When it comes to finding a solution, groups are invited to put on their decision-making hats and really think about how a proposed idea would work in practice. 

The Impact and Effort Matrix is one of the problem-solving techniques that fall into this camp, empowering participants to first generate ideas and then categorize them into a 2×2 matrix based on impact and effort.

Activities that invite critical thinking while remaining simple are invaluable. Use the Impact and Effort Matrix to move from ideation and towards evaluating potential solutions before then committing to them. 

Impact and Effort Matrix   #gamestorming   #decision making   #action   #remote-friendly   In this decision-making exercise, possible actions are mapped based on two factors: effort required to implement and potential impact. Categorizing ideas along these lines is a useful technique in decision making, as it obliges contributors to balance and evaluate suggested actions before committing to them.

27. Dotmocracy

If you’ve followed each of the problem-solving steps with your group successfully, you should move towards the end of your process with heaps of possible solutions developed with a specific problem in mind. But how do you help a group go from ideation to putting a solution into action? 

Dotmocracy – or Dot Voting -is a tried and tested method of helping a team in the problem-solving process make decisions and put actions in place with a degree of oversight and consensus. 

One of the problem-solving techniques that should be in every facilitator’s toolbox, Dot Voting is fast and effective and can help identify the most popular and best solutions and help bring a group to a decision effectively. 

Dotmocracy   #action   #decision making   #group prioritization   #hyperisland   #remote-friendly   Dotmocracy is a simple method for group prioritization or decision-making. It is not an activity on its own, but a method to use in processes where prioritization or decision-making is the aim. The method supports a group to quickly see which options are most popular or relevant. The options or ideas are written on post-its and stuck up on a wall for the whole group to see. Each person votes for the options they think are the strongest, and that information is used to inform a decision.

All facilitators know that warm-ups and icebreakers are useful for any workshop or group process. Problem-solving workshops are no different.

Use these problem-solving techniques to warm up a group and prepare them for the rest of the process. Activating your group by tapping into some of the top problem-solving skills can be one of the best ways to see great outcomes from your session.

• Check-in/Check-out
• Doodling Together
• Show and Tell
• Constellations
• Draw a Tree

28. Check-in / Check-out

Solid processes are planned from beginning to end, and the best facilitators know that setting the tone and establishing a safe, open environment can be integral to a successful problem-solving process.

Check-in / Check-out is a great way to begin and/or bookend a problem-solving workshop. Checking in to a session emphasizes that everyone will be seen, heard, and expected to contribute. 

If you are running a series of meetings, setting a consistent pattern of checking in and checking out can really help your team get into a groove. We recommend this opening-closing activity for small to medium-sized groups though it can work with large groups if they’re disciplined!

Check-in / Check-out   #team   #opening   #closing   #hyperisland   #remote-friendly   Either checking-in or checking-out is a simple way for a team to open or close a process, symbolically and in a collaborative way. Checking-in/out invites each member in a group to be present, seen and heard, and to express a reflection or a feeling. Checking-in emphasizes presence, focus and group commitment; checking-out emphasizes reflection and symbolic closure.

29. Doodling Together  

Thinking creatively and not being afraid to make suggestions are important problem-solving skills for any group or team, and warming up by encouraging these behaviors is a great way to start. 

Doodling Together is one of our favorite creative ice breaker games – it’s quick, effective, and fun and can make all following problem-solving steps easier by encouraging a group to collaborate visually. By passing cards and adding additional items as they go, the workshop group gets into a groove of co-creation and idea development that is crucial to finding solutions to problems. 

Doodling Together   #collaboration   #creativity   #teamwork   #fun   #team   #visual methods   #energiser   #icebreaker   #remote-friendly   Create wild, weird and often funny postcards together & establish a group’s creative confidence.

30. Show and Tell

You might remember some version of Show and Tell from being a kid in school and it’s a great problem-solving activity to kick off a session.

Asking participants to prepare a little something before a workshop by bringing an object for show and tell can help them warm up before the session has even begun! Games that include a physical object can also help encourage early engagement before moving onto more big-picture thinking.

By asking your participants to tell stories about why they chose to bring a particular item to the group, you can help teams see things from new perspectives and see both differences and similarities in the way they approach a topic. Great groundwork for approaching a problem-solving process as a team! 

Show and Tell   #gamestorming   #action   #opening   #meeting facilitation   Show and Tell taps into the power of metaphors to reveal players’ underlying assumptions and associations around a topic The aim of the game is to get a deeper understanding of stakeholders’ perspectives on anything—a new project, an organizational restructuring, a shift in the company’s vision or team dynamic.

31. Constellations

Who doesn’t love stars? Constellations is a great warm-up activity for any workshop as it gets people up off their feet, energized, and ready to engage in new ways with established topics. It’s also great for showing existing beliefs, biases, and patterns that can come into play as part of your session.

Using warm-up games that help build trust and connection while also allowing for non-verbal responses can be great for easing people into the problem-solving process and encouraging engagement from everyone in the group. Constellations is great in large spaces that allow for movement and is definitely a practical exercise to allow the group to see patterns that are otherwise invisible. 

Constellations   #trust   #connection   #opening   #coaching   #patterns   #system   Individuals express their response to a statement or idea by standing closer or further from a central object. Used with teams to reveal system, hidden patterns, perspectives.

32. Draw a Tree

Problem-solving games that help raise group awareness through a central, unifying metaphor can be effective ways to warm-up a group in any problem-solving model.

Draw a Tree is a simple warm-up activity you can use in any group and which can provide a quick jolt of energy. Start by asking your participants to draw a tree in just 45 seconds – they can choose whether it will be abstract or realistic. 

Once the timer is up, ask the group how many people included the roots of the tree and use this as a means to discuss how we can ignore important parts of any system simply because they are not visible.

All problem-solving strategies are made more effective by thinking of problems critically and by exposing things that may not normally come to light. Warm-up games like Draw a Tree are great in that they quickly demonstrate some key problem-solving skills in an accessible and effective way.

Draw a Tree   #thiagi   #opening   #perspectives   #remote-friendly   With this game you can raise awarness about being more mindful, and aware of the environment we live in.

Each step of the problem-solving workshop benefits from an intelligent deployment of activities, games, and techniques. Bringing your session to an effective close helps ensure that solutions are followed through on and that you also celebrate what has been achieved.

Here are some problem-solving activities you can use to effectively close a workshop or meeting and ensure the great work you’ve done can continue afterward.

• One Breath Feedback
• Who What When Matrix
• Response Cards

How do I conclude a problem-solving process?

All good things must come to an end. With the bulk of the work done, it can be tempting to conclude your workshop swiftly and without a moment to debrief and align. This can be problematic in that it doesn’t allow your team to fully process the results or reflect on the process.

At the end of an effective session, your team will have gone through a process that, while productive, can be exhausting. It’s important to give your group a moment to take a breath, ensure that they are clear on future actions, and provide short feedback before leaving the space. 

The primary purpose of any problem-solving method is to generate solutions and then implement them. Be sure to take the opportunity to ensure everyone is aligned and ready to effectively implement the solutions you produced in the workshop.

Remember that every process can be improved and by giving a short moment to collect feedback in the session, you can further refine your problem-solving methods and see further success in the future too.

33. One Breath Feedback

Maintaining attention and focus during the closing stages of a problem-solving workshop can be tricky and so being concise when giving feedback can be important. It’s easy to incur “death by feedback” should some team members go on for too long sharing their perspectives in a quick feedback round. 

One Breath Feedback is a great closing activity for workshops. You give everyone an opportunity to provide feedback on what they’ve done but only in the space of a single breath. This keeps feedback short and to the point and means that everyone is encouraged to provide the most important piece of feedback to them. 

One breath feedback   #closing   #feedback   #action   This is a feedback round in just one breath that excels in maintaining attention: each participants is able to speak during just one breath … for most people that’s around 20 to 25 seconds … unless of course you’ve been a deep sea diver in which case you’ll be able to do it for longer.

34. Who What When Matrix 

Matrices feature as part of many effective problem-solving strategies and with good reason. They are easily recognizable, simple to use, and generate results.

The Who What When Matrix is a great tool to use when closing your problem-solving session by attributing a who, what and when to the actions and solutions you have decided upon. The resulting matrix is a simple, easy-to-follow way of ensuring your team can move forward. 

Great solutions can’t be enacted without action and ownership. Your problem-solving process should include a stage for allocating tasks to individuals or teams and creating a realistic timeframe for those solutions to be implemented or checked out. Use this method to keep the solution implementation process clear and simple for all involved. 

Who/What/When Matrix   #gamestorming   #action   #project planning   With Who/What/When matrix, you can connect people with clear actions they have defined and have committed to.

35. Response cards

Group discussion can comprise the bulk of most problem-solving activities and by the end of the process, you might find that your team is talked out! 

Providing a means for your team to give feedback with short written notes can ensure everyone is head and can contribute without the need to stand up and talk. Depending on the needs of the group, giving an alternative can help ensure everyone can contribute to your problem-solving model in the way that makes the most sense for them.

Response Cards is a great way to close a workshop if you are looking for a gentle warm-down and want to get some swift discussion around some of the feedback that is raised. 

Response Cards   #debriefing   #closing   #structured sharing   #questions and answers   #thiagi   #action   It can be hard to involve everyone during a closing of a session. Some might stay in the background or get unheard because of louder participants. However, with the use of Response Cards, everyone will be involved in providing feedback or clarify questions at the end of a session.

Save time and effort discovering the right solutions

A structured problem solving process is a surefire way of solving tough problems, discovering creative solutions and driving organizational change. But how can you design for successful outcomes?

With SessionLab, it’s easy to design engaging workshops that deliver results. Drag, drop and reorder blocks  to build your agenda. When you make changes or update your agenda, your session  timing   adjusts automatically , saving you time on manual adjustments.

Collaborating with stakeholders or clients? Share your agenda with a single click and collaborate in real-time. No more sending documents back and forth over email.

Explore  how to use SessionLab  to design effective problem solving workshops or  watch this five minute video  to see the planner in action!

Over to you

The problem-solving process can often be as complicated and multifaceted as the problems they are set-up to solve. With the right problem-solving techniques and a mix of creative exercises designed to guide discussion and generate purposeful ideas, we hope we’ve given you the tools to find the best solutions as simply and easily as possible.

Is there a problem-solving technique that you are missing here? Do you have a favorite activity or method you use when facilitating? Let us know in the comments below, we’d love to hear from you! 

thank you very much for these excellent techniques

Certainly wonderful article, very detailed. Shared!

Your list of techniques for problem solving can be helpfully extended by adding TRIZ to the list of techniques. TRIZ has 40 problem solving techniques derived from methods inventros and patent holders used to get new patents. About 10-12 are general approaches. many organization sponsor classes in TRIZ that are used to solve business problems or general organiztational problems. You can take a look at TRIZ and dwonload a free internet booklet to see if you feel it shound be included per your selection process.

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Problem-Solving Approaches in Data Structures and Algorithms

This blog highlights some popular problem-solving strategies for solving problems in DSA. Learning to apply these strategies could be one of the best milestones for the learners in mastering data structure and algorithms.

An Incremental approach using Single and Nested loops

One of the simple ideas of our daily problem-solving activities is that we build the partial solution step by step using a loop. There is a different variation to it:

• Input-centric strategy: At each iteration step, we process one input and build the partial solution.
• Output-centric strategy: At each iteration step, we add one output to the solution and build the partial solution.
• Iterative improvement strategy: Here, we start with some easily available approximations of a solution and continuously improve upon it to reach the final solution.

Here are some approaches based on loop: Using a single loop and variables, Using nested loops and variables, Incrementing the loop by a constant (more than 1), Using the loop twice (Double traversal), Using a single loop and prefix array (or extra memory), etc.

Example problems:   Insertion Sort ,  Finding max and min in an array ,  Valid mountain array ,  Find equilibrium index of an array ,  Dutch national flag problem ,  Sort an array in a waveform .

Decrease and Conquer Approach

This strategy is based on finding the solution to a given problem via its one sub-problem solution. Such an approach leads naturally to a recursive algorithm, which reduces the problem to a sequence of smaller input sizes. Until it becomes small enough to be solved, i.e., it reaches the recursion’s base case.

Example problems:   Euclid algorithm of finding GCD ,  Binary Search ,  Josephus problem

Problem-solving using Binary Search

When an array has some order property similar to the sorted array, we can use the binary search idea to solve several searching problems efficiently in O(logn) time complexity. For doing this, we need to modify the standard binary search algorithm based on the conditions given in the problem. The core idea is simple: calculate the mid-index and iterate over the left or right half of the array.

Example problems: Find Peak Element , Search a sorted 2D matrix , Find the square root of an integer , Search in Rotated Sorted Array

Divide and Conquer Approach

This strategy is about dividing a problem into  more than one subproblems,  solving each of them, and then, if necessary, combining their solutions to get a solution to the original problem. We solve many fundamental problems efficiently in computer science by using this strategy.

Example problems:   Merge Sort ,  Quick Sort ,  Median of two sorted arrays

Two Pointers Approach

The two-pointer approach helps us optimize time and space complexity in the case of many searching problems on arrays and linked lists. Here pointers can be pairs of array indices or pointer references to an object. This approach aims to simultaneously iterate over two different input parts to perform fewer operations. There are three variations of this approach:

Pointers are moving in the same direction with the same pace:   Merging two sorted arrays or linked lists, Finding the intersection of two arrays or linked lists , Checking an array is a subset of another array , etc.

Pointers are moving in the same direction at a different pace (Fast and slow pointers):   Partition process in the quick sort , Remove duplicates from the sorted array , Find the middle node in a linked list , Detect loop in a linked list , Move all zeroes to the end , Remove nth node from list end , etc.

Pointers are moving in the opposite direction:  Reversing an array, Check pair sum in an array , Finding triplet with zero-sum , Rainwater trapping problem , Container with most water , etc.

Sliding Window Approach

A sliding window concept is commonly used in solving array/string problems. Here, the window is a contiguous sequence of elements defined by the start and ends indices. We perform some operations on elements within the window and “slide” it in a forward direction by incrementing the left or right end.

This approach can be effective whenever the problem consists of tasks that must be performed on a contiguous block of a fixed or variable size. This could help us improve time complexity in so many problems by converting the nested loop solution into a single loop solution.

Example problems: Longest substring without repeating characters , Count distinct elements in every window , Max continuous series of 1s , Find max consecutive 1's in an array , etc.

Transform and Conquer Approach

This approach is based on transforming a coding problem into another coding problem with some particular property that makes the problem easier to solve. In other words, here we solve the problem is solved in two stages:

• Transformation stage: We transform the original problem into another easier problem to solve.
• Conquering stage: Now, we solve the transformed problem.

Example problems: Pre-sorting based algorithms (Finding the closest pair of points, checking whether all the elements in a given array are distinct, etc.)

Problem-solving using BFS and DFS Traversal

Most tree and graph problems can be solved using DFS and BFS traversal. If the problem is to search for something closer to the root (or source node), we can prefer BFS, and if we need to search for something in-depth, we can choose DFS.

Sometimes, we can use both BFS and DFS traversals when node order is not required. But in some cases, such things are not possible. We need to identify the use case of both traversals to solve the problems efficiently. For example, in binary tree problems:

• We use preorder traversal in a situation when we need to explore all the tree nodes before inspecting any leaves.
• Inorder traversal of BST generates the node's data in increasing order. So we can use inorder to solve several BST problems.
• We can use postorder traversal when we need to explore all the leaf nodes before inspecting any internal nodes.
• Sometimes, we need some specific information about some level. In this situation, BFS traversal helps us to find the output easily.

To solve tree and graph problems, sometimes we pass extra variables or pointers to the function parameters, use helper functions, use parent pointers, store some additional data inside the node, and use data structures like the stack, queue, and priority queue, etc.

Example problems: Find min depth of a binary tree , Merge two binary trees , Find the height of a binary tree , Find the absolute minimum difference in a BST , The kth largest element in a BST , Course scheduling problem , bipartite graph , Find the left view of a binary tree , etc.

Problem-solving using the Data Structures

The data structure is one of the powerful tools of problem-solving in algorithms. It helps us perform some of the critical operations efficiently and improves the time complexity of the solution. Here are some of the key insights:

• Many coding problems require an effcient way to perform the search, insert and delete operations. We can perform all these operations using the hash table in O(1) time average. It's a kind of time-memory tradeoff, where we use extra space to store elements in the hash table to improve performance.
• Sometimes we need to store data in the stack (LIFO order) or queue (FIFO order) to solve several coding problems. 
• Suppose there is a requirement to continuously insert or remove maximum or minimum element (Or element with min or max priority). In that case, we can use a heap (or priority queue) to solve the problem efficiently.
• Sometimes, we store data in Trie, AVL Tree, Segment Tree, etc., to perform some critical operations efficiently. 

Example problems: Next greater element , Valid Parentheses , Largest rectangle in a histogram , Sliding window maximum , kth smallest element in an array , Top k frequent elements , Longest common prefix , Range sum query , Longest consecutive sequence , Check equal array , LFU cache , LRU cache , Counting sort

Dynamic Programming

Dynamic programming is one of the most popular techniques for solving problems with overlapping or repeated subproblems. Here rather than solving overlapping subproblems repeatedly, we solve each smaller subproblems only once and store the results in memory. We can solve a lot of optimization and counting problems using the idea of dynamic programming.

Example problems: Finding nth Fibonacci,  Longest Common Subsequence ,  Climbing Stairs Problem ,  Maximum Subarray Sum ,  Minimum number of Jumps to reach End ,  Minimum Coin Change

Greedy Approach

This solves an optimization problem by expanding a partially constructed solution until a complete solution is reached. We take a greedy choice at each step and add it to the partially constructed solution. This idea produces the optimal global solution without violating the problem’s constraints.

• The greedy choice is the best alternative available at each step is made in the hope that a sequence of locally optimal choices will yield a (globally) optimal solution to the entire problem.
• This approach works in some cases but fails in others. Usually, it is not difficult to design a greedy algorithm itself, but a more difficult task is to prove that it produces an optimal solution.

Example problems: Fractional Knapsack, Dijkstra algorithm, The activity selection problem

Exhaustive Search

This strategy explores all possibilities of solutions until a solution to the problem is found. Therefore, problems are rarely offered to a person to solve the problem using this strategy.

The most important limitation of exhaustive search is its inefficiency. As a rule, the number of solution candidates that need to be processed grows at least exponentially with the problem size, making the approach inappropriate not only for a human but often for a computer as well.

But in some situations, there is a need to explore all possible solution spaces in a coding problem. For example: Find all permutations of a string , Print all subsets , etc.

Backtracking

Backtracking is an improvement over the approach of exhaustive search. It is a method for generating a solution by avoiding unnecessary possibilities of the solutions! The main idea is to build a solution one piece at a time and evaluate each partial solution as follows:

• If a partial solution can be developed further without violating the problem’s constraints, it is done by taking the first remaining valid option at the next stage. ( Think! )
• Suppose there is no valid option at the next stage, i.e., If there is a violation of the problem constraint, the algorithm backtracks to replace the partial solution’s previous stage with the following option for that stage. ( Think! )

In simple words, backtracking involves undoing several wrong choices — the smaller this number, the faster the algorithm finds a solution. In the worst-case scenario, a backtracking algorithm may end up generating all the solutions as an exhaustive search, but this rarely happens!

Example problems: N-queen problem , Find all k combinations , Combination sum , Sudoku solver , etc.

Problem-solving using Bit manipulation and Numbers theory

Some of the coding problems are, by default, mathematical, but sometimes we need to identify the hidden mathematical properties inside the problem. So the idea of number theory and bit manipulation is helpful in so many cases.

Sometimes understanding the bit pattern of the input and processing data at the bit level help us design an efficient solution. The best part is that the computer performs each bit-wise operation in constant time. Even sometimes, bit manipulation can reduce the requirement of extra loops and improve the performance by a considerable margin.

Example problems: Reverse bits , Add binary string , Check the power of two , Find the missing number , etc.

Hope you enjoyed the blog. Later we will write a separate blog on each problem-solving approach. Enjoy learning, Enjoy algorithms!

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