management science approach to problem solving example

As indicated in the previous section, management science encompasses a logical, systematic approach to problem solving, which closely parallels what is known as the for attacking problems. This approach, as shown in Figure 1.1, follows a generally recognized and ordered series of steps: (1) observation, (2) definition of the problem, (3) model construction, (4) model solution, and (5) implementation of solution results. We will analyze each of these steps individually.

The first step in the management science process is the identification of a problem that exists in the system (organization). The system must be continuously and closely observed so that problems can be identified as soon as they occur or are anticipated. Problems are not always the result of a crisis that must be reacted to but, instead, frequently involve an anticipatory or planning situation. The person who normally identifies a problem is the manager because the managers work in places where problems might occur. However, problems can often be identified by a management scientist , a person skilled in the techniques of management science and trained to identify problems, who has been hired specifically to solve problems using management science techniques.

Once it has been determined that a problem exists, the problem must be clearly and concisely defined . Improperly defining a problem can easily result in no solution or an inappropriate solution. Therefore, the limits of the problem and the degree to which it pervades other units of the organization must be included in the problem definition. Because the existence of a problem implies that the objectives of the firm are not being met in some way, the goals (or objectives) of the organization must also be clearly defined. A stated objective helps to focus attention on what the problem actually is.

A management science is an abstract representation of an existing problem situation. It can be in the form of a graph or chart, but most frequently a management science model consists of a set of mathematical relationships. These mathematical relationships are made up of numbers and symbols.

As an example, consider a business firm that sells a product. The product costs $5 to produce and sells for $20. A model that computes the total profit that will accrue from the items sold is

Z = $20 x - 5 x

In this equation x represents the number of units of the product that are sold, and Z represents the total profit that results from the sale of the product. The symbols x and Z are variables . The term is used because no set numeric value has been specified for these items. The number of units sold, x , and the profit, Z , can be any amount (within limits); they can vary. These two variables can be further distinguished. Z is a dependent variable because its value is dependent on the number of units sold; x is an independent variable because the number of units sold is not dependent on anything else (in this equation).

The numbers $20 and $5 in the equation are referred to as . Parameters are constant values that are generally coefficients of the variables (symbols) in an equation. Parameters usually remain constant during the process of solving a specific problem. The parameter values are derived from (i.e., pieces of information) from the problem environment. Sometimes the data are readily available and quite accurate. For example, presumably the selling price of $20 and product cost of $5 could be obtained from the firm's accounting department and would be very accurate. However, sometimes data are not as readily available to the manager or firm, and the parameters must be either estimated or based on a combination of the available data and estimates. In such cases, the model is only as accurate as the data used in constructing the model.

The equation as a whole is known as a (also called function and relationship) . The term is derived from the fact that profit, Z , is a function of the number of units sold, x , and the equation relates profit to units sold.

Because only one functional relationship exists in this example, it is also the model . In this case the relationship is a model of the determination of profit for the firm. However, this model does not really replicate a problem. Therefore, we will expand our example to create a problem situation.

Let us assume that the product is made from steel and that the business firm has 100 pounds of steel available. If it takes 4 pounds of steel to make each unit of the product, we can develop an additional mathematical relationship to represent steel usage:

4 x = 100 lb. of steel

This equation indicates that for every unit produced, 4 of the available 100 pounds of steel will be used. Now our model consists of two relationships:

We say that the profit equation in this new model is an , and the resource equation is a . In other words, the objective of the firm is to achieve as much profit, Z , as possible, but the firm is constrained from achieving an infinite profit by the limited amount of steel available. To signify this distinction between the two relationships in this model, we will add the following notations:

This model now represents the manager's problem of determining the number of units to produce. You will recall that we defined the number of units to be produced as x . Thus, when we determine the value of x , it represents a potential (or recommended) decision for the manager. Therefore, x is also known as a . The next step in the management science process is to solve the model to determine the value of the decision variable.

Once models have been constructed in management science, they are solved using the management science techniques presented in this text. A management science solution technique usually applies to a specific type of model. Thus, the model type and solution method are both part of the management science technique. We are able to say that a model is solved because the model represents a problem. When we refer to model solution, we also mean problem solution.

For the example model developed in the previous section,

the solution technique is simple algebra. Solving the constraint equation for x , we have

Substituting the value of 25 for x into the profit function results in the total profit:

Thus, if the manager decides to produce 25 units of the product and all 25 units sell, the business firm will receive $375 in profit. Note, however, that the value of the decision variable does not constitute an actual decision; rather, it is information that serves as a recommendation or guideline, helping the manager make a decision.

Some management science techniques do not generate an answer or a recommended decision. Instead, they provide descriptive results : results that describe the system being modeled . For example, suppose the business firm in our example desires to know the average number of units sold each month during a year. The monthly data (i.e., sales) for the past year are as follows:

A management science solution can be either a recommended decision or information that helps a manager make a decision .

Monthly sales average 40 units (480 · 12). This result is not a decision; it is information that describes what is happening in the system. The results of the management science techniques in this text are examples of the two types shown in this section: (1) solutions/decisions and (2) descriptive results.

Implementation

The final step in the management science process for problem solving described in Figure 1.1 is implementation. Implementation is the actual use of the model once it has been developed or the solution to the problem the model was developed to solve. This is a critical but often overlooked step in the process. It is not always a given that once a model is developed or a solution found, it is automatically used. Frequently the person responsible for putting the model or solution to use is not the same person who developed the model and, thus, the user may not fully understand how the model works or exactly what it is supposed to do. Individuals are also sometimes hesitant to change the normal way they do things or to try new things. In this situation the model and solution may get pushed to the side or ignored altogether if they are not carefully explained and their benefit fully demonstrated. If the management science model and solution are not implemented, then the effort and resources used in their development have been wasted .

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Explain the Management Science Approach

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Developed during World War II to find solutions to warfare issues, the management science approach uses mathematical models to solve problems. Also known as a quantitative approach, the approach analyzes a mix of feasibilities, constraints and cost to enable management to make decisions. The management science approach is a type of organizational environment theory. It combines rational thought with intuitive insight to resolve management concerns such as cost, production and service levels.

What is Management Science Theory?

As reported in Cleverism , management science is primarily concerned with exploring how a business can manage itself with the aim to maximize productivity. Through adopting a system that allows assimilation of scientific thought, the managers and owners solve or prevent the range of problems and issues arising from managerial weaknesses, which can be primary reasons small firms are viewed as marginal or unprofitable businesses.

The core function of the management science approach is to compare possible outcomes. Businesses that don't apply quantitative management perspectives run the risk of remaining small in terms of the number of employees, production ratio and market share.

Importance of Management Science for Business

Small-business owners and mangers can use the management science approach to design specific measures that identify and evaluate the effectiveness of certain processes or decisions. For example, they can develop basic computer applications that can help predict and analyze some management issues that may arise at various levels of the organization.

The Management Study Guide recommends that managers use the techniques and tools of this quantitative approach to management to plan, organize, lead and control operations within the workplace. For the company, the approach can result in increased production, industrial peace and benefits of specialization.

Conversely, workers might be more motivated and experience improved working conditions because the approach focuses on maintaining clean and safe work environments and involves differential wage systems.

Is It the Only Answer?

Employees play an integral role in any organization, and they are the ones most affected by the management science approach. One drawback of this approach is that employees have little say in the management process. Decisions are handed down after a recommendation from the analysis phase is selected. Also, the fragmentation of work by giving out individual tasks may not work for small businesses, because it hinders any team-building interventions.

Another disadvantage is that the issues involved in some scenarios can't be quantified; therefore, managers might quantify the pieces that they can and draw conclusions. The decisions they arrive at may not produce optimum results because all issues were not considered.

The Way Forward

To gain the best from the management science process, managers gather and process information about the target market. For emerging businesses, the management science approach is an effective model that can be used to direct facilities, marketing, purchasing, personnel allocation, research and development. Business owners who select and use the proper tools and techniques place themselves in a position to maximize profitability.

However, the ultimate test of this approach is based on whether better decisions are made regarding the overall management of the organization.

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management science

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management science , any application of science to the study of management. Originally a synonym for operations research , the term management science (often used in the plural) now designates a distinct field. Whereas operations research affords analytical data, statistics , and methods to increase the efficiency of management systems, management science applies these tools in such fields as data mining , engineering , economic forecasting , and logistics .

Management science initially included any application of science to management problems or to the process of management itself; it thus encompassed operations research, systems analysis , and the study of management-information systems. This broad understanding of the scope of the field was reflected in the constitution of the Institute of Management Sciences (TIMS), founded in 1953 as an outgrowth of the Operations Research Society of America (ORSA). It stated that “the objects of the Institute shall be to identify, extend, and unify scientific knowledge that contributes to the understanding and practice of management.” In 1995 ORSA and TIMS merged to form the Institute for Operations Research and the Management Sciences (INFORMS).

Although management science could include the study of all activities of groups that entail a managerial function, it generally entails the following: (1) discovering, developing, defining, and evaluating the goals of the organization and the alternative policies that will lead toward the goals, (2) getting the organization to adopt the policies, (3) scrutinizing the effectiveness of the policies that are adopted, and (4) initiating steps to change policies that are ineffective or inadequately effective. Management science often has drawn its concepts and methods from the older disciplines of economics , business administration, psychology , sociology , and mathematics .

• Management Science – The Definitive Guide

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Management is a core function of every business and a number of theories try to explain how the processes of management can be best utilized to help the organization to succeed. Management science is one such approach and in this guide, we’ll explore the history of this approach.

We’ll explain the definition and core elements of the style, as well as compare the benefits and disadvantages of implementing this strategy.

Finally, we’ll look into the different ways it has been applied in the past and the steps you need to take to implement it in your organization.

THE HISTORY OF MANAGEMENT SCIENCE

Management science has an interesting history and the approach has evolved over the years to its current concept, which we’ll explore further in the next section. The roots of management science can be found in a concept of operations research , which was a system developed during World War II. The War, like other wars before and after it, involved plenty of operations outside of the traditional fighting on the battlefield. Warfare changed from the First World War and scientists from different fields were part of the effort to gain the upper hand on both sides of the war.

Operation research or operational research saw the scientists trying to apply analytical methods in order to enhance the decision-making processes. The approach was highly used by the Allied forces, with Britain engaging nearly 1,000 men and women in operation research during the war. The basis of operation research was on different mathematical models, which were used to make predictions that would improve military operations.

One example of the operation research use was the application of ‘ effectiveness ratios ’, which compared the flying hours of Allied planes with enemy U-boat sightings in a given area. By studying these numbers, the military was able to distribute the planes to productive patrol areas and map out enemy positions more efficiently.

After the war, the operation research model became implemented in the corporate sector. As businesses and other organizations begun using analytical research as part of the decision-making process, the term management science was coined. In 1967, Stafford Beer said the field of management science is essentially “ the business use of operations research ”.

At this initial stage, management science involved around the application of different scientific methods and findings in order to solve management problems and streamline the processes of management. The broad approach meant the system used operation research, system analysis as well as the study of management-information systems as part of the implementation. Since then, the definition and scope of management science has become more defined.

THE CORE CONCEPTS OF MANAGEMENT SCIENCE

Now that we’ve looked into the history of management science, we can move on to exploring the current definition of the practice together with its core concepts.

The definition of management science

According to Lancaster University , management science can be defined as a concept that is “ concerned with developing and applying models and concepts that help to illuminate issues and solve managerial problems ”. The approach is essentially interested in looking at an organization and finding ways it can manage itself better and improve its productivity.

The core aim of the approach is to use scientific concepts and methods in order to solve management-related issues. It does this by focusing on analyzing different management approaches, comparing them with existing possibilities and offering possible outcomes of which the organization can pick to improve productivity.

While management science is mainly a mathematical approach to solving problems, the application of it requires the examination of different fields. Management science uses analytical data, statistics and methods for increasing efficiency of management systems and it finds the tools from fields like:

• Business Administration
• Mathematics

The key to management science is the visualization of management as a logical action. Since the approach views management through this lens, it means the process can be quantified and described with the help of symbols, measurements and relationships. The approach basis its theory on the decision theory approach and rational decision-making models and it can provide organizations with a model that helps identify goals and the roadmap for achieving them.

Management science makes a few general assumptions of management , which are the basis for its framework. The assumptions are:

• Management is a problem-solving mechanism, which can be boosted by mathematical tools and techniques.
• Problems in management can be quantified and described in mathematical terms. This includes areas such as system analysis, but also human behavior.
• Managerial problems can best be resolved through mathematical tools, simulations and models.

If you’re interested in the future of management science, then watch the video of Andrew McAfee discussing the possibilities future improvements in Information Technology can provide to management science.

The four core areas of research

The management science approach relies on four core areas of research. These four are the steps an organization must take in order to properly implement management science and they are the four core elements defining the system.

The first one is about discovering, developing, defining, and evaluating the goals and policies that lead to these objectives . This requires the organization to examine the goals it has set, the goals it could set and the current and possible methods and processes it could use in order to achieve them. This is about the initial step of understanding what the company wants to do, what the company is doing, and what the company could be doing.

The second core element is about ensuring the organization adopts those policies . Once the processes and policies have been chosen from the selection of options, science management requires the company to enforce them. This might require additional policy decisions and changes in the way the organization operates, but the key is to implement the processes as identified during the initial phase.

After the policies are being implemented, management science calls for scrutinizing the effectiveness of the policies . Management science doesn’t just provide the tools for making better decisions and streamlining the management procedures within the organization. It can also help with monitoring of the viability of these approaches and decisions.

Finally, the fourth element is about initiating changes to the policies in case they are found ineffective . If the processes are not working as intended and the organization is not achieving the predicted outcomes, management science provides the framework for figuring out the failing parts. The analytical approach doesn’t just measure how things might be, but it can help identify why certain outcomes weren’t achieved. This will help make changes on the go and shift the focus to the processes that will guarantee the achievement of the objectives.

In the final section, we’ll return to examining how the above can be implemented in the most effective manner.

THE BENEFITS OF MANAGEMENT SCIENCE

When it comes to the benefits of implementing a management science approach, organizations can expect a number of advantages. Management science can reduce the overall efficiency of the organization and make decision-making easier and more defined .

The broad advantage of the approach is its ability to design measures that can be used to identify and evaluate the effectiveness of the processes currently in use. Management science looks at the current situation and compares it with other possibilities, creating measurable predictions.

The analysis of processes and decision-making can help the organization identify the problem areas, as well as the systems that are already working efficiently. The identification of these will guarantee the organization is using processes and decision-making approaches that provide the best results in terms of the achieving the organization’s objectives.

Furthermore, the management science approach can help more specifically in the following core areas of any business:

• Planning – The management science approach can be used in the planning because it identifies and predicts the results of certain processes. The approach makes it easier to understand the future needs of the organization based on the current and future models, as well as the objectives the organization is looking to fulfill.
• Organizing – Creating systems that efficiently focus on the specifically defined processes and tasks. Furthermore, it makes it easier to direct resources to their right places.
• Leading and controlling operations – Since the approach focuses on management, it can boost the way the organization leads. It can help individual managers focus on the most important aspects of the organization and improve their decision-making skills.

Efficiency in the following core areas of business will provide boosts in productivity, industrial peace and enhance the organization’s ability to specialize its products and services . Productivity results from the efficiency in planning, organizing and leading, as the processes are streamlined and different parts of the organization focus on the areas that maximize their efficiency.

Furthermore, the higher productivity can result in increased wages as well, since the organization doesn’t need to worry about time-wasting and inefficient workforce. As wages improve, employee motivation is likely to improve, creating a system of reinforced productivity.

In terms of industrial peace, management science enforces better co-operation between the management and the labor. The enhanced processes create an environment of clarity in the workplace and provide more security to the workforce in terms of knowing their position and the health and safety of the employee. If relations between the management and the labor are harmonious and built on trust and respect, industrial disputes are less likely to take place.

Employee motivation and productivity are also boosted through the safer work environment, as alluded above. The approach identifies the most efficient and the safest ways to produce products and services. This can have a meaningful impact on the working conditions and thus increase industrial peace further.

Specialization is improved through enhanced understanding of the strengths and weaknesses of the organization. Management science helps identify the processes, which work, notice the areas of weakness, and realize the future possibilities and needs of the organization’s consumer base. The approach makes the utilization of resources easier, since the framework can notice the availability of resources and the proper use of them.

As the above shows, management science can be beneficial for the organization by improving the way it operates, but also guaranteeing better relations between the different stakeholders. With improved efficiency, productivity will increase and further create a situation for higher profits.

Here is a great talk of how data will transform businesses .

THE DISADVANTAGES OF MANAGEMENT SCIENCE

What about the downside to management science? Despite the above advantages, certain drawbacks need to be taken into account before an organization starts using the approach. The disadvantages should be taken seriously, even though many of these drawbacks can be limited and controlled with proper implementation and planning.

Management science controls the decision-making process within the organization. Decisions are made based on the findings of the framework, using analysis of different factors and implementing a variety of methodologies. This can lead to reduced employee-involvement in decision-making , as the process is not controlled by discussion and opinion, but focus is on numbers and scientific predictions.

In its essence, management science supports a top-down decision-making process. If you read management expert opinions, many champion the opposite to the traditional top-down approach. Author Peter Diamandis is among the proponents of collective decision-making, stating, “ collective management will build companies – not top-down decision-making ”.

The problem with transferring the decision-making completely away from employee input is how it creates situations where people feel disengaged. Since you don’t have any voice, you can more easily feel uncomfortable with the decisions. Even if you wouldn’t get your way with the decisions, the ability to influence or discuss the decision can be enough to make you feel more engaged.

Management science also requires an understanding of the process, which is something the employee doesn’t necessarily have. The employees might not have a good grasp of how the decisions were made and the justification behind the conclusion, which can make the management’s approach seem further disengaging and confusing.

The framework also looks at individual components and therefore breaks down the tasks into smaller objectives. This can create fragmentation throughout the organization , which can have a few defining impacts. First, the fragmentation of objectives means each employee is closely associated with a single unit of action. In short, employees have a task and the instructions on how to do it.

The employee just needs to fulfill the objective and the task is done. Since each person is in charge of their own objective, tasks don’t have much spill over. This can lead to a situation where teamwork is non-existent . Employees are only focused on the specific tasks they’ve been given, without the need to discuss or co-operate with others. While this might suit certain types of employees, others might find it disengaging again. The second problem of fragmentation follows directly from the lack of teamwork.

If team-building and co-operation are diminished, creativity within the organization can suffer . People don’t communicate with each other in the same way, creating a system where the team starts relying on the feedback from the management science framework. Ideas are not thrown around, but rather people wait for the management science framework to come up with the best approaches.

The above points deal with the disadvantages in terms of employee engagement and creativity. But management science can have a few drawbacks on a more practical, operational sense as well. First, the approach generalizes that things can be quantified. For the model to work and make effective predictions, things should be quantifiable and easily measured. If they are, then mathematical calculations will work accurately and the outcomes can be analyzed with care.

But certain issues and problems won’t be easily quantified or standardized . For example, while resources and equipment can be standardized, human behavior is much harder to generalize, as certain people can perform well in specific conditions in which someone else might fail. Therefore, by creating artificial generalization and standardization, the management will reduce the effectiveness of the predictions. If the set of processes analyzed is not correctly quantified, the outcomes might not be the most accurate. In effect, this means the resulting decisions might not yield the optimum results.

In addition to the above, management science has a problem with scaling . Since the framework requires plenty of data and the data has to be as accurate as possible, the implementation process can be much easier for smaller organizations. Creating a process for data collection, analysis and prediction is easier when you have only a limited number of data available with a small organization. The process can be easier to establish and the results can be faster to achieve since analyzing won’t take forever. On the other hand, the cost of establishing an efficient management science system can be high and the expensive element of the framework can make it unattractive for smaller firms.

Watch this interesting case study on how management science could be applied to understanding mobile users (warning: only for super nerds like me)

APPLICATION OF MANAGEMENT SCIENCE

Management science has a number of benefits, which has meant that different fields have started using it to enhance operational and managerial efficiency. Since its early start as part of a core approach to the military, the application has found its way to industries as varied as medical, political, public administration and business. Management science has provided solutions and identified deeper insights into the industries in a number of ways. The following examples are among the best examples of how management science can be applied in a meaningful manner:

• The airline industry has used management science to create the scheduling systems for airlines. This has created the system for ensuring the planes are utilized more efficiently, together with guaranteeing the crew is rotated in the most efficient way.
• A number of information systems currently in use by organizations are a result of management science. The approach has been used to identify and understand the correct information system strategies.
• Public administrations have also used management science to identify the flow of water from water reservoirs. The process identifies the most efficient routes and cost-effective ways to manage the flow.

As the examples show, there are different ways to utilize management science. The application of the framework helps organizations create enhanced efficiency in areas such as cost, production and the level of service by solving the different managerial problems.

In terms of applying management science in business, there is a six-step formula for making the most of it. The steps will help streamline business operations and create a process-based environment for the organization.

Source and Copyrights: World Health Organisation website

1. Identifying business processes in use

The organization must first identify the different management processes it currently has in place. By identifying each process, it’s also possible to notice the strengths and weaknesses of the individual management operation.

For example, you’ll identify all the management teams and understand its positive impact on the workforce. As you identify the processes, you’ll start noticing the patterns of management and the specific aspects that require changing or tweaking.

2. Analyze the individual processes

As you’ve identified the problem areas, as well as the management processes that are working effectively, you can start using management science to modify the process. By implementing the analytical approach, you will notice which processes need scaling, implementation or adjustment.

This step is the key part of management science; it is about diagnosis and the identification of the solution. In some instances, it can even help with creating systems that prevent future problems.

3. Redesign the processes

With the analysis done, the focus should move to identifying the right process for achieving the right results. Management science tends to present a number of solutions and predictions, which means the organization has to identify the most effective processes for its needs.

4. Ensure the right resources are in place to improve the processes

Once you’ve identified the processes and the solutions to the management problems, you need to ensure the organization has the right resources at hand. Redesigning of the processes might require additional resources, either in terms of money or labor. Ensure the appropriate amount and type of resources is identifying to guarantee the newly established processes work as planned.

5. Implement the identified processes

The fifth step is about implementation of the above processes. As mentioned in the section about the disadvantages of management science, the system can easily cause fragmentation if the organization is not careful.

Therefore, at this step, you must ensure there’s a community wide buy-in and proper information available for people to understand the changes, the reasoning behind them, as well as the new processes themselves.

6. Review and analyze the effectiveness of the new processes

Finally, the implemented processes require constant analysis and review. Management science will provide answers and prediction, but just like any other approach to management, it’s not a magic pill to fix everything.

Therefore, you must make sure you continue to collect data and analyze the effectiveness of the processes in place. Only this will guarantee they are working as intended and will provide the organization better chances of tweaking the approach as you go.

THE BOTTOM LINE

Management science is a logical and analytical approach to management and how it impacts an organization. The approach has been used in a variety of industries since its inception during World War II. By using the approach, an organization is able to identify different management processes and whether they are working as efficiently as they could.

It can provide new ways to approach management issues and it helps streamline the decision-making process by creating models the organization can use. While management science can provide plenty of benefits in terms of improvements in productivity and cutting costs, the implementation can also have drawbacks on the workplace.

Employee satisfaction can suffer and the organization has to deal with the fragmentation of processes. The approach is not a quick remedy for solving issues, but when it is applied correctly, the results can lead to success.

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How to master the seven-step problem-solving process

In this episode of the McKinsey Podcast , Simon London speaks with Charles Conn, CEO of venture-capital firm Oxford Sciences Innovation, and McKinsey senior partner Hugo Sarrazin about the complexities of different problem-solving strategies.

Podcast transcript

Simon London: Hello, and welcome to this episode of the McKinsey Podcast , with me, Simon London. What’s the number-one skill you need to succeed professionally? Salesmanship, perhaps? Or a facility with statistics? Or maybe the ability to communicate crisply and clearly? Many would argue that at the very top of the list comes problem solving: that is, the ability to think through and come up with an optimal course of action to address any complex challenge—in business, in public policy, or indeed in life.

Looked at this way, it’s no surprise that McKinsey takes problem solving very seriously, testing for it during the recruiting process and then honing it, in McKinsey consultants, through immersion in a structured seven-step method. To discuss the art of problem solving, I sat down in California with McKinsey senior partner Hugo Sarrazin and also with Charles Conn. Charles is a former McKinsey partner, entrepreneur, executive, and coauthor of the book Bulletproof Problem Solving: The One Skill That Changes Everything [John Wiley & Sons, 2018].

Charles and Hugo, welcome to the podcast. Thank you for being here.

Hugo Sarrazin: Our pleasure.

Charles Conn: It’s terrific to be here.

Simon London: Problem solving is a really interesting piece of terminology. It could mean so many different things. I have a son who’s a teenage climber. They talk about solving problems. Climbing is problem solving. Charles, when you talk about problem solving, what are you talking about?

Charles Conn: For me, problem solving is the answer to the question “What should I do?” It’s interesting when there’s uncertainty and complexity, and when it’s meaningful because there are consequences. Your son’s climbing is a perfect example. There are consequences, and it’s complicated, and there’s uncertainty—can he make that grab? I think we can apply that same frame almost at any level. You can think about questions like “What town would I like to live in?” or “Should I put solar panels on my roof?”

You might think that’s a funny thing to apply problem solving to, but in my mind it’s not fundamentally different from business problem solving, which answers the question “What should my strategy be?” Or problem solving at the policy level: “How do we combat climate change?” “Should I support the local school bond?” I think these are all part and parcel of the same type of question, “What should I do?”

I’m a big fan of structured problem solving. By following steps, we can more clearly understand what problem it is we’re solving, what are the components of the problem that we’re solving, which components are the most important ones for us to pay attention to, which analytic techniques we should apply to those, and how we can synthesize what we’ve learned back into a compelling story. That’s all it is, at its heart.

I think sometimes when people think about seven steps, they assume that there’s a rigidity to this. That’s not it at all. It’s actually to give you the scope for creativity, which often doesn’t exist when your problem solving is muddled.

Simon London: You were just talking about the seven-step process. That’s what’s written down in the book, but it’s a very McKinsey process as well. Without getting too deep into the weeds, let’s go through the steps, one by one. You were just talking about problem definition as being a particularly important thing to get right first. That’s the first step. Hugo, tell us about that.

Hugo Sarrazin: It is surprising how often people jump past this step and make a bunch of assumptions. The most powerful thing is to step back and ask the basic questions—“What are we trying to solve? What are the constraints that exist? What are the dependencies?” Let’s make those explicit and really push the thinking and defining. At McKinsey, we spend an enormous amount of time in writing that little statement, and the statement, if you’re a logic purist, is great. You debate. “Is it an ‘or’? Is it an ‘and’? What’s the action verb?” Because all these specific words help you get to the heart of what matters.

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Simon London: So this is a concise problem statement.

Hugo Sarrazin: Yeah. It’s not like “Can we grow in Japan?” That’s interesting, but it is “What, specifically, are we trying to uncover in the growth of a product in Japan? Or a segment in Japan? Or a channel in Japan?” When you spend an enormous amount of time, in the first meeting of the different stakeholders, debating this and having different people put forward what they think the problem definition is, you realize that people have completely different views of why they’re here. That, to me, is the most important step.

Charles Conn: I would agree with that. For me, the problem context is critical. When we understand “What are the forces acting upon your decision maker? How quickly is the answer needed? With what precision is the answer needed? Are there areas that are off limits or areas where we would particularly like to find our solution? Is the decision maker open to exploring other areas?” then you not only become more efficient, and move toward what we call the critical path in problem solving, but you also make it so much more likely that you’re not going to waste your time or your decision maker’s time.

How often do especially bright young people run off with half of the idea about what the problem is and start collecting data and start building models—only to discover that they’ve really gone off half-cocked.

Hugo Sarrazin: Yeah.

Charles Conn: And in the wrong direction.

Simon London: OK. So step one—and there is a real art and a structure to it—is define the problem. Step two, Charles?

Charles Conn: My favorite step is step two, which is to use logic trees to disaggregate the problem. Every problem we’re solving has some complexity and some uncertainty in it. The only way that we can really get our team working on the problem is to take the problem apart into logical pieces.

What we find, of course, is that the way to disaggregate the problem often gives you an insight into the answer to the problem quite quickly. I love to do two or three different cuts at it, each one giving a bit of a different insight into what might be going wrong. By doing sensible disaggregations, using logic trees, we can figure out which parts of the problem we should be looking at, and we can assign those different parts to team members.

Simon London: What’s a good example of a logic tree on a sort of ratable problem?

Charles Conn: Maybe the easiest one is the classic profit tree. Almost in every business that I would take a look at, I would start with a profit or return-on-assets tree. In its simplest form, you have the components of revenue, which are price and quantity, and the components of cost, which are cost and quantity. Each of those can be broken out. Cost can be broken into variable cost and fixed cost. The components of price can be broken into what your pricing scheme is. That simple tree often provides insight into what’s going on in a business or what the difference is between that business and the competitors.

If we add the leg, which is “What’s the asset base or investment element?”—so profit divided by assets—then we can ask the question “Is the business using its investments sensibly?” whether that’s in stores or in manufacturing or in transportation assets. I hope we can see just how simple this is, even though we’re describing it in words.

When I went to work with Gordon Moore at the Moore Foundation, the problem that he asked us to look at was “How can we save Pacific salmon?” Now, that sounds like an impossible question, but it was amenable to precisely the same type of disaggregation and allowed us to organize what became a 15-year effort to improve the likelihood of good outcomes for Pacific salmon.

Simon London: Now, is there a danger that your logic tree can be impossibly large? This, I think, brings us onto the third step in the process, which is that you have to prioritize.

Charles Conn: Absolutely. The third step, which we also emphasize, along with good problem definition, is rigorous prioritization—we ask the questions “How important is this lever or this branch of the tree in the overall outcome that we seek to achieve? How much can I move that lever?” Obviously, we try and focus our efforts on ones that have a big impact on the problem and the ones that we have the ability to change. With salmon, ocean conditions turned out to be a big lever, but not one that we could adjust. We focused our attention on fish habitats and fish-harvesting practices, which were big levers that we could affect.

People spend a lot of time arguing about branches that are either not important or that none of us can change. We see it in the public square. When we deal with questions at the policy level—“Should you support the death penalty?” “How do we affect climate change?” “How can we uncover the causes and address homelessness?”—it’s even more important that we’re focusing on levers that are big and movable.

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Simon London: Let’s move swiftly on to step four. You’ve defined your problem, you disaggregate it, you prioritize where you want to analyze—what you want to really look at hard. Then you got to the work plan. Now, what does that mean in practice?

Hugo Sarrazin: Depending on what you’ve prioritized, there are many things you could do. It could be breaking the work among the team members so that people have a clear piece of the work to do. It could be defining the specific analyses that need to get done and executed, and being clear on time lines. There’s always a level-one answer, there’s a level-two answer, there’s a level-three answer. Without being too flippant, I can solve any problem during a good dinner with wine. It won’t have a whole lot of backing.

Simon London: Not going to have a lot of depth to it.

Hugo Sarrazin: No, but it may be useful as a starting point. If the stakes are not that high, that could be OK. If it’s really high stakes, you may need level three and have the whole model validated in three different ways. You need to find a work plan that reflects the level of precision, the time frame you have, and the stakeholders you need to bring along in the exercise.

Charles Conn: I love the way you’ve described that, because, again, some people think of problem solving as a linear thing, but of course what’s critical is that it’s iterative. As you say, you can solve the problem in one day or even one hour.

Charles Conn: We encourage our teams everywhere to do that. We call it the one-day answer or the one-hour answer. In work planning, we’re always iterating. Every time you see a 50-page work plan that stretches out to three months, you know it’s wrong. It will be outmoded very quickly by that learning process that you described. Iterative problem solving is a critical part of this. Sometimes, people think work planning sounds dull, but it isn’t. It’s how we know what’s expected of us and when we need to deliver it and how we’re progressing toward the answer. It’s also the place where we can deal with biases. Bias is a feature of every human decision-making process. If we design our team interactions intelligently, we can avoid the worst sort of biases.

Simon London: Here we’re talking about cognitive biases primarily, right? It’s not that I’m biased against you because of your accent or something. These are the cognitive biases that behavioral sciences have shown we all carry around, things like anchoring, overoptimism—these kinds of things.

Both: Yeah.

Charles Conn: Availability bias is the one that I’m always alert to. You think you’ve seen the problem before, and therefore what’s available is your previous conception of it—and we have to be most careful about that. In any human setting, we also have to be careful about biases that are based on hierarchies, sometimes called sunflower bias. I’m sure, Hugo, with your teams, you make sure that the youngest team members speak first. Not the oldest team members, because it’s easy for people to look at who’s senior and alter their own creative approaches.

Hugo Sarrazin: It’s helpful, at that moment—if someone is asserting a point of view—to ask the question “This was true in what context?” You’re trying to apply something that worked in one context to a different one. That can be deadly if the context has changed, and that’s why organizations struggle to change. You promote all these people because they did something that worked well in the past, and then there’s a disruption in the industry, and they keep doing what got them promoted even though the context has changed.

Simon London: Right. Right.

Hugo Sarrazin: So it’s the same thing in problem solving.

Charles Conn: And it’s why diversity in our teams is so important. It’s one of the best things about the world that we’re in now. We’re likely to have people from different socioeconomic, ethnic, and national backgrounds, each of whom sees problems from a slightly different perspective. It is therefore much more likely that the team will uncover a truly creative and clever approach to problem solving.

Simon London: Let’s move on to step five. You’ve done your work plan. Now you’ve actually got to do the analysis. The thing that strikes me here is that the range of tools that we have at our disposal now, of course, is just huge, particularly with advances in computation, advanced analytics. There’s so many things that you can apply here. Just talk about the analysis stage. How do you pick the right tools?

Charles Conn: For me, the most important thing is that we start with simple heuristics and explanatory statistics before we go off and use the big-gun tools. We need to understand the shape and scope of our problem before we start applying these massive and complex analytical approaches.

Simon London: Would you agree with that?

Hugo Sarrazin: I agree. I think there are so many wonderful heuristics. You need to start there before you go deep into the modeling exercise. There’s an interesting dynamic that’s happening, though. In some cases, for some types of problems, it is even better to set yourself up to maximize your learning. Your problem-solving methodology is test and learn, test and learn, test and learn, and iterate. That is a heuristic in itself, the A/B testing that is used in many parts of the world. So that’s a problem-solving methodology. It’s nothing different. It just uses technology and feedback loops in a fast way. The other one is exploratory data analysis. When you’re dealing with a large-scale problem, and there’s so much data, I can get to the heuristics that Charles was talking about through very clever visualization of data.

You test with your data. You need to set up an environment to do so, but don’t get caught up in neural-network modeling immediately. You’re testing, you’re checking—“Is the data right? Is it sound? Does it make sense?”—before you launch too far.

Simon London: You do hear these ideas—that if you have a big enough data set and enough algorithms, they’re going to find things that you just wouldn’t have spotted, find solutions that maybe you wouldn’t have thought of. Does machine learning sort of revolutionize the problem-solving process? Or are these actually just other tools in the toolbox for structured problem solving?

Charles Conn: It can be revolutionary. There are some areas in which the pattern recognition of large data sets and good algorithms can help us see things that we otherwise couldn’t see. But I do think it’s terribly important we don’t think that this particular technique is a substitute for superb problem solving, starting with good problem definition. Many people use machine learning without understanding algorithms that themselves can have biases built into them. Just as 20 years ago, when we were doing statistical analysis, we knew that we needed good model definition, we still need a good understanding of our algorithms and really good problem definition before we launch off into big data sets and unknown algorithms.

Simon London: Step six. You’ve done your analysis.

Charles Conn: I take six and seven together, and this is the place where young problem solvers often make a mistake. They’ve got their analysis, and they assume that’s the answer, and of course it isn’t the answer. The ability to synthesize the pieces that came out of the analysis and begin to weave those into a story that helps people answer the question “What should I do?” This is back to where we started. If we can’t synthesize, and we can’t tell a story, then our decision maker can’t find the answer to “What should I do?”

Simon London: But, again, these final steps are about motivating people to action, right?

Charles Conn: Yeah.

Simon London: I am slightly torn about the nomenclature of problem solving because it’s on paper, right? Until you motivate people to action, you actually haven’t solved anything.

Charles Conn: I love this question because I think decision-making theory, without a bias to action, is a waste of time. Everything in how I approach this is to help people take action that makes the world better.

Simon London: Hence, these are absolutely critical steps. If you don’t do this well, you’ve just got a bunch of analysis.

Charles Conn: We end up in exactly the same place where we started, which is people speaking across each other, past each other in the public square, rather than actually working together, shoulder to shoulder, to crack these important problems.

Simon London: In the real world, we have a lot of uncertainty—arguably, increasing uncertainty. How do good problem solvers deal with that?

Hugo Sarrazin: At every step of the process. In the problem definition, when you’re defining the context, you need to understand those sources of uncertainty and whether they’re important or not important. It becomes important in the definition of the tree.

You need to think carefully about the branches of the tree that are more certain and less certain as you define them. They don’t have equal weight just because they’ve got equal space on the page. Then, when you’re prioritizing, your prioritization approach may put more emphasis on things that have low probability but huge impact—or, vice versa, may put a lot of priority on things that are very likely and, hopefully, have a reasonable impact. You can introduce that along the way. When you come back to the synthesis, you just need to be nuanced about what you’re understanding, the likelihood.

Often, people lack humility in the way they make their recommendations: “This is the answer.” They’re very precise, and I think we would all be well-served to say, “This is a likely answer under the following sets of conditions” and then make the level of uncertainty clearer, if that is appropriate. It doesn’t mean you’re always in the gray zone; it doesn’t mean you don’t have a point of view. It just means that you can be explicit about the certainty of your answer when you make that recommendation.

Simon London: So it sounds like there is an underlying principle: “Acknowledge and embrace the uncertainty. Don’t pretend that it isn’t there. Be very clear about what the uncertainties are up front, and then build that into every step of the process.”

Hugo Sarrazin: Every step of the process.

Simon London: Yeah. We have just walked through a particular structured methodology for problem solving. But, of course, this is not the only structured methodology for problem solving. One that is also very well-known is design thinking, which comes at things very differently. So, Hugo, I know you have worked with a lot of designers. Just give us a very quick summary. Design thinking—what is it, and how does it relate?

Hugo Sarrazin: It starts with an incredible amount of empathy for the user and uses that to define the problem. It does pause and go out in the wild and spend an enormous amount of time seeing how people interact with objects, seeing the experience they’re getting, seeing the pain points or joy—and uses that to infer and define the problem.

Simon London: Problem definition, but out in the world.

Hugo Sarrazin: With an enormous amount of empathy. There’s a huge emphasis on empathy. Traditional, more classic problem solving is you define the problem based on an understanding of the situation. This one almost presupposes that we don’t know the problem until we go see it. The second thing is you need to come up with multiple scenarios or answers or ideas or concepts, and there’s a lot of divergent thinking initially. That’s slightly different, versus the prioritization, but not for long. Eventually, you need to kind of say, “OK, I’m going to converge again.” Then you go and you bring things back to the customer and get feedback and iterate. Then you rinse and repeat, rinse and repeat. There’s a lot of tactile building, along the way, of prototypes and things like that. It’s very iterative.

Simon London: So, Charles, are these complements or are these alternatives?

Charles Conn: I think they’re entirely complementary, and I think Hugo’s description is perfect. When we do problem definition well in classic problem solving, we are demonstrating the kind of empathy, at the very beginning of our problem, that design thinking asks us to approach. When we ideate—and that’s very similar to the disaggregation, prioritization, and work-planning steps—we do precisely the same thing, and often we use contrasting teams, so that we do have divergent thinking. The best teams allow divergent thinking to bump them off whatever their initial biases in problem solving are. For me, design thinking gives us a constant reminder of creativity, empathy, and the tactile nature of problem solving, but it’s absolutely complementary, not alternative.

Simon London: I think, in a world of cross-functional teams, an interesting question is do people with design-thinking backgrounds really work well together with classical problem solvers? How do you make that chemistry happen?

Hugo Sarrazin: Yeah, it is not easy when people have spent an enormous amount of time seeped in design thinking or user-centric design, whichever word you want to use. If the person who’s applying classic problem-solving methodology is very rigid and mechanical in the way they’re doing it, there could be an enormous amount of tension. If there’s not clarity in the role and not clarity in the process, I think having the two together can be, sometimes, problematic.

The second thing that happens often is that the artifacts the two methodologies try to gravitate toward can be different. Classic problem solving often gravitates toward a model; design thinking migrates toward a prototype. Rather than writing a big deck with all my supporting evidence, they’ll bring an example, a thing, and that feels different. Then you spend your time differently to achieve those two end products, so that’s another source of friction.

Now, I still think it can be an incredibly powerful thing to have the two—if there are the right people with the right mind-set, if there is a team that is explicit about the roles, if we’re clear about the kind of outcomes we are attempting to bring forward. There’s an enormous amount of collaborativeness and respect.

Simon London: But they have to respect each other’s methodology and be prepared to flex, maybe, a little bit, in how this process is going to work.

Hugo Sarrazin: Absolutely.

Simon London: The other area where, it strikes me, there could be a little bit of a different sort of friction is this whole concept of the day-one answer, which is what we were just talking about in classical problem solving. Now, you know that this is probably not going to be your final answer, but that’s how you begin to structure the problem. Whereas I would imagine your design thinkers—no, they’re going off to do their ethnographic research and get out into the field, potentially for a long time, before they come back with at least an initial hypothesis.

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Hugo Sarrazin: That is a great callout, and that’s another difference. Designers typically will like to soak into the situation and avoid converging too quickly. There’s optionality and exploring different options. There’s a strong belief that keeps the solution space wide enough that you can come up with more radical ideas. If there’s a large design team or many designers on the team, and you come on Friday and say, “What’s our week-one answer?” they’re going to struggle. They’re not going to be comfortable, naturally, to give that answer. It doesn’t mean they don’t have an answer; it’s just not where they are in their thinking process.

Simon London: I think we are, sadly, out of time for today. But Charles and Hugo, thank you so much.

Charles Conn: It was a pleasure to be here, Simon.

Hugo Sarrazin: It was a pleasure. Thank you.

Simon London: And thanks, as always, to you, our listeners, for tuning into this episode of the McKinsey Podcast . If you want to learn more about problem solving, you can find the book, Bulletproof Problem Solving: The One Skill That Changes Everything , online or order it through your local bookstore. To learn more about McKinsey, you can of course find us at McKinsey.com.

Charles Conn is CEO of Oxford Sciences Innovation and an alumnus of McKinsey’s Sydney office. Hugo Sarrazin is a senior partner in the Silicon Valley office, where Simon London, a member of McKinsey Publishing, is also based.

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Explanation of the Management Science Approach

by Jacquelyn Jeanty

Published on 8 May 2019

The scientific method works as an objective, fact-based method for making new discoveries and learning new ways of doing things. Management science attempts to apply this same approach in dealing with problems that arise within business operations. Its use as a problem-solving approach finds applications in areas such as decision-making, design processes and strategic planning.

History of the Management Science Approach

The management science approach originated during World War II as a means for making the best use of available resources within military operations, according to the Encyclopedia of Business. By studying existing strategies and tactics, the military hoped to gain a better perspective on where resources could best be used.

The success of this approach soon found its way into the business world after World War II. Technological advances and economic growth saw business managers wanting to make the most of their available resources. The management science approach proved an effective means for maximizing resources and reframing large operational problems into manageable scenarios.

Components of Management Science Theory

Management science also goes by the name operations research, which pretty much explains the approach management scientists take when working in a business setting. Just like the scientific method, the management science approach identifies a problematic issue or process within a business’ operations. It then develops possible theories for how the problem developed and designs possible solutions. Scientists develop models from which to test proposed theories and gather data from the results. Analysis of the data then provides practical solutions for solving a problem.

Integral Use of Mathematical Models 

The management science approach uses mathematical models of analysis to apply the scientific method to business operations or processes. Mathematical models uncover relationships between related and unrelated variables, such as number of employees versus number of products produced within a manufacturing environment. A mathematical model can uncover unknown problem areas, such as equipment designs that slow the overall production process.

The results obtained from mathematical models enable decision-makers to develop solutions based on the resulting data.

Applications for the Management Science Method

The use of management science within business operations can translate systems and processes into measurable terms. In effect, the approach brings a new and practical perspective on how different areas of an organization work together and affect its overall output or effectiveness.

Measurable results provide opportunities for decision-makers – who work in seemingly unrelated processes, systems or departments – to work toward a common end goal. As a result, the management science approach plays a vital role within large, complex operations such as government organizations, mass transit planning and criminal analysis and investigations.

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Management Science

Management Science: this short article explains Management Science in a practical way. Next to what it is, this article also highlights the theory and bacgroend, and it’s applications. Enjoy reading!

What is Management Science?

Management science is a broad, interdisciplinary study of decision making and problem solution within an organisation. The interdisciplinary study has strong ties to economics, engineering, management, business administration and other fields.

Various scientific principles such as mathematical models, algorithms, and statistics are implemented. The objective is to increase and better a company’s capital and to take more precise and rational decisions. Management science helps organisations reach their goals using scientific principles and methods.

Management science can be defined as a problem-solving process used by an interdisciplinary team to develop models that represent simple and complex functional relationships and provide management guidance for decision-making.

Management scientific theory and background

The founder of management science is Frederick Taylor . He is known as the father of scientific management. Taylor developed four management principles; research, standardisation, monitoring, and co-working. He is also the founder of the rational goal model .

Examples of other pioneers when it comes to scientific management are Carl Barth, Henry Gantt , and Hathaway. Gantt contributed to the acknowledgement of work psychology, bonus plans, and the use of charts in production planning. Later, these all birthed the term industrial engineering.

In the years after the second world war, management science was more commonly known as operations research.

Applications

The analysis of business and decision-making processes helps organisations identify problems. Additionally, a management science approach helps assist in the following core areas within a company:

Management science is applied in planning because it predicts the results of certain processes. This approach makes it easier to understand future needs, instead of waiting for developments.

Organisation

Management sciences make it easier to create systems that work efficiently and focus on specific tasks.

Additionally, this also makes it easier to assign resources to the right place.

Because this scientific approach focuses on management, it can boost the way the organisation is run.

It helps individual managers focus on the key elements of leadership and improve their decision-making skills.

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Mastering problem solving and decision making.

© Copyright Carter McNamara, MBA, PhD, Authenticity Consulting, LLC .

Sections of This Topic Include

• Test – What is Your Personal Decision-Making Style?
• Guidelines to Rational Problem Solving and Decision-Making
• Rational Versus Organic Approach to Problem Solving and Decision Making
• General Guidelines to Problem Solving and Decision-Making
• Various Methods and Tools for Problem-Solving and Decision Making
• General Resources for Problem-Solving and Decision Making

Also, consider

• Related Library Topics
• (Also see the closely related topics Decision Making , Group-Based Problem Solving, and Decision Making and Planning — Basics .)

What is Your Personal Decision-Making Style?

There are many styles of making decisions, ranging from very rational and linear to organic and unfolding. Take this online assessment to determine your own style.

Discover Your Decision-Making Style

Do you want to improve or polish your style? Consider the many guidelines included below.

Guidelines to Problem-Solving and Decision Making (Rational Approach)

Much of what people do is solve problems and make decisions. Often, they are “under the gun”, stressed, and very short of time. Consequently, when they encounter a new problem or decision they must make, they react with a decision that seemed to work before. It’s easy with this approach to get stuck in a circle of solving the same problem over and over again. Therefore, it’s often useful to get used to an organized approach to problem-solving and decision-making.

Not all problems can be solved and decisions made by the following, rather rational approach. However, the following basic guidelines will get you started. Don’t be intimidated by the length of the list of guidelines. After you’ve practiced them a few times, they’ll become second nature to you — enough that you can deepen and enrich them to suit your own needs and nature.

(Note that it might be more your nature to view a “problem” as an “opportunity”. Therefore, you might substitute “problem” for “opportunity” in the following guidelines.)

1. Define the problem

This is often where people struggle. They react to what they think the problem is. Instead, seek to understand more about why you think there’s a problem.

Define the problem: (with input from yourself and others). Ask yourself and others, the following questions:

• What can you see that causes you to think there’s a problem?
• Where is it happening?
• How is it happening?
• When is it happening?
• With whom is it happening? (HINT: Don’t jump to “Who is causing the problem?” When we’re stressed, blaming is often one of our first reactions. To be an effective manager, you need to address issues more than people.)
• Why is it happening?
• Write down a five-sentence description of the problem in terms of “The following should be happening, but isn’t …” or “The following is happening and should be: …” As much as possible, be specific in your description, including what is happening, where, how, with whom and why. (It may be helpful at this point to use a variety of research methods.)

Defining complex problems:

If the problem still seems overwhelming, break it down by repeating steps 1-7 until you have descriptions of several related problems.

Verifying your understanding of the problems:

It helps a great deal to verify your problem analysis for conferring with a peer or someone else.

Prioritize the problems:

If you discover that you are looking at several related problems, then prioritize which ones you should address first.

Note the difference between “important” and “urgent” problems. Often, what we consider to be important problems to consider are really just urgent problems. Important problems deserve more attention. For example, if you’re continually answering “urgent” phone calls, then you’ve probably got a more “important” problem and that’s to design a system that screens and prioritizes your phone calls.

Understand your role in the problem:

Your role in the problem can greatly influence how you perceive the role of others. For example, if you’re very stressed out, it’ll probably look like others are, too, or, you may resort too quickly to blaming and reprimanding others. Or, you are feel very guilty about your role in the problem, you may ignore the accountabilities of others.

2. Look at potential causes for the problem

• It’s amazing how much you don’t know about what you don’t know. Therefore, in this phase, it’s critical to get input from other people who notice the problem and who are affected by it.
• It’s often useful to collect input from other individuals one at a time (at least at first). Otherwise, people tend to be inhibited about offering their impressions of the real causes of problems.
• Write down your opinions and what you’ve heard from others.
• Regarding what you think might be performance problems associated with an employee, it’s often useful to seek advice from a peer or your supervisor in order to verify your impression of the problem.
• Write down a description of the cause of the problem in terms of what is happening, where, when, how, with whom, and why.

3. Identify alternatives for approaches to resolve the problem

At this point, it’s useful to keep others involved (unless you’re facing a personal and/or employee performance problem). Brainstorm for solutions to the problem. Very simply put, brainstorming is collecting as many ideas as possible, and then screening them to find the best idea. It’s critical when collecting the ideas to not pass any judgment on the ideas — just write them down as you hear them. (A wonderful set of skills used to identify the underlying cause of issues is Systems Thinking.)

4. Select an approach to resolve the problem

• When selecting the best approach, consider:
• Which approach is the most likely to solve the problem for the long term?
• Which approach is the most realistic to accomplish for now? Do you have the resources? Are they affordable? Do you have enough time to implement the approach?
• What is the extent of risk associated with each alternative?

(The nature of this step, in particular, in the problem solving process is why problem solving and decision making are highly integrated.)

5. Plan the implementation of the best alternative (this is your action plan)

• Carefully consider “What will the situation look like when the problem is solved?”
• What steps should be taken to implement the best alternative to solving the problem? What systems or processes should be changed in your organization, for example, a new policy or procedure? Don’t resort to solutions where someone is “just going to try harder”.
• How will you know if the steps are being followed or not? (these are your indicators of the success of your plan)
• What resources will you need in terms of people, money, and facilities?
• How much time will you need to implement the solution? Write a schedule that includes the start and stop times, and when you expect to see certain indicators of success.
• Who will primarily be responsible for ensuring the implementation of the plan?
• Write down the answers to the above questions and consider this as your action plan.
• Communicate the plan to those who will involved in implementing it and, at least, to your immediate supervisor.

(An important aspect of this step in the problem-solving process is continual observation and feedback.)

6. Monitor implementation of the plan

Monitor the indicators of success:

• Are you seeing what you would expect from the indicators?
• Will the plan be done according to schedule?
• If the plan is not being followed as expected, then consider: Was the plan realistic? Are there sufficient resources to accomplish the plan on schedule? Should more priority be placed on various aspects of the plan? Should the plan be changed?

7. Verify if the problem has been resolved or not

One of the best ways to verify if a problem has been solved or not is to resume normal operations in the organization. Still, you should consider:

• What changes should be made to avoid this type of problem in the future? Consider changes to policies and procedures, training, etc.
• Lastly, consider “What did you learn from this problem-solving?” Consider new knowledge, understanding, and/or skills.
• Consider writing a brief memo that highlights the success of the problem-solving effort, and what you learned as a result. Share it with your supervisor, peers and subordinates.

Rational Versus Organic Approach to Problem Solving

A person with this preference often prefers using a comprehensive and logical approach similar to the guidelines in the above section. For example, the rational approach, described below, is often used when addressing large, complex matters in strategic planning.

• Define the problem.
• Examine all potential causes for the problem.
• Identify all alternatives to resolve the problem.
• Carefully select an alternative.
• Develop an orderly implementation plan to implement the best alternative.
• Carefully monitor the implementation of the plan.
• Verify if the problem has been resolved or not.

A major advantage of this approach is that it gives a strong sense of order in an otherwise chaotic situation and provides a common frame of reference from which people can communicate in the situation. A major disadvantage of this approach is that it can take a long time to finish. Some people might argue, too, that the world is much too chaotic for the rational approach to be useful.

Some people assert that the dynamics of organizations and people are not nearly so mechanistic as to be improved by solving one problem after another. Often, the quality of an organization or life comes from how one handles being “on the road” itself, rather than the “arriving at the destination.” The quality comes from the ongoing process of trying, rather than from having fixed a lot of problems. For many people, it is an approach to organizational consulting. The following quote is often used when explaining the organic (or holistic) approach to problem solving.

“All the greatest and most important problems in life are fundamentally insoluble … They can never be solved, but only outgrown. This “outgrowing” proves that further investigation to require a new level of consciousness. Some higher or wider interest appeared on the horizon and through this broadening of outlook, the insoluble lost its urgency. It was not solved logically in its own terms, but faded when confronted with a new and stronger life urge.” From Jung, Carl, Psychological Types (Pantheon Books, 1923)

A major advantage of the organic approach is that it is highly adaptable to understanding and explaining the chaotic changes that occur in projects and everyday life. It also suits the nature of people who shun linear and mechanistic approaches to projects. The major disadvantage is that the approach often provides no clear frame of reference around which people can communicate, feel comfortable and measure progress toward solutions to problems.

Additional Guidelines for Problem-Solving and Decision Making

Recommended articles.

• Ten Tips for Beefing Up Your Problem-Solving Tool Box
• Problem Solving Techniques (extensive overview of various approaches)
• Key Questions to Ask Before Selecting a Solution to a Business Problem

Additional Articles

• Problem-solving and Decision-Making:
• Top 5 Tips to Improve Concentration
• Problem Solving and Decision Making – 12 Great Tips!
• Powerful Problem Solving
• Creative Problem-Solving
• Leadership Styles and Problem Solving (focus on creativity)
• Forget About Causes, Focus on Solutions
• Ten Tips for Beefing Up Your Problem-Solving ToolBox
• Coaching Tip: Four-Question Method for Proactive Problem Solving
• Coaching Tip — How to Bust Paralysis by Analysis
• Appreciative Inquiry
• Powerful Problem-Solving
• Problem-Solving Techniques
• Guidelines for Selecting An Appropriate Problem-Solving Approach
• Factors to Consider in Figuring Out What to Do About A Problem
• A Case for Reengineering the Problem-Solving Process (Somewhat Advanced)
• Courseware on Problemistics (The art & craft of problem dealing)
• Adapt your leadership style
• Organic Approach to Problem Solving
• Make Good Decisions, Avoid Bad Consequences
• Priority Management: Are You Doing the Right Things?

General Guidelines for Decision Making

• Decision-Making Tips
• How We Sometimes Fool Ourselves When Making Decisions (Traps We Can Fall Into)
• More of the Most Common Decision-Making Mistakes (more traps we can fall into)
• When Your Organization’s Decisions Are in the Hands of Devils
• Flawed Decision-making is Dangerous
• Five Tips for Making Better Decisions
• Study Says People Make Better Decisions With a Full Bladder
• What Everyone Should Know About Decision Making

Various Tools and Methods for Problem Solving and Decision Making

(Many people would agree that the following methods and tools are also for decision-making.)

• Cost Benefit Analysis (for deciding based on costs)
• De Bono Hats (for looking at a situation from many perspectives
• Delphi Decision Making (to collect the views of experts and distill expert-based solutions)
• Dialectic Decision Making (rigorous action planning via examining opposite points of view) Fishbone Diagram —
• 5 Steps to build Fishbone Diagram
• Fishbowls (for groups to learn by watching modeled behaviors)
• Grid Analysis (for choosing among many choices)
• Pareto Principle (for finding the options that will make the most difference — (20/80 rule”)
• For solving seemingly unsolvable contradictions
• Rational Decision Making
• SWOT Analysis (to analyze strengths, weaknesses, opportunities, and threats)
• Work Breakdown Structure (for organizing and relating many details)

General Resources for Problem Solving and Decision Making

• The Ultimate Problem-Solving Process Guide: 31 Steps and Resources
• list of various tools
• long list of tools
• Decision Making Tools
• Decision Making
• Group Decision Making and Problem Solving
• Inquiry and Reflection
• Mental Models (scan down to “Mental Models”)
• Questioning
• Research Methods
• Systems Thinking

Learn More in the Library’s Blogs Related to Problem Solving and Decision Making

In addition to the articles on this current page, also see the following blogs that have posts related to this topic. Scan down the blog’s page to see various posts. Also, see the section “Recent Blog Posts” in the sidebar of the blog or click on “Next” near the bottom of a post in the blog. The blog also links to numerous free related resources.

• Library’s Career Management Blog
• Library’s Coaching Blog
• Library’s Human Resources Blog
• Library’s Spirituality Blog

For the Category of Innovation:

To round out your knowledge of this Library topic, you may want to review some related topics, available from the link below. Each of the related topics includes free, online resources.

Also, scan the Recommended Books listed below. They have been selected for their relevance and highly practical nature.

• Recommended Books

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7 Problem-Solving Skills That Can Help You Be a More Successful Manager

Discover what problem-solving is, and why it's important for managers. Understand the steps of the process and learn about seven problem-solving skills.

1Managers oversee the day-to-day operations of a particular department, and sometimes a whole company, using their problem-solving skills regularly. Managers with good problem-solving skills can help ensure companies run smoothly and prosper.

If you're a current manager or are striving to become one, read this guide to discover what problem-solving skills are and why it's important for managers to have them. Learn the steps of the problem-solving process, and explore seven skills that can help make problem-solving easier and more effective.

What is problem-solving?

Problem-solving is both an ability and a process. As an ability, problem-solving can aid in resolving issues faced in different environments like home, school, abroad, and social situations, among others. As a process, problem-solving involves a series of steps for finding solutions to questions or concerns that arise throughout life.

The importance of problem-solving for managers

Managers deal with problems regularly, whether supervising a staff of two or 100. When people solve problems quickly and effectively, workplaces can benefit in a number of ways. These include:

Greater creativity

Higher productivity

Increased job fulfillment

Satisfied clients or customers

Better cooperation and cohesion

Improved environments for employees and customers

7 skills that make problem-solving easier

Companies depend on managers who can solve problems adeptly. Although problem-solving is a skill in its own right, a subset of seven skills can help make the process of problem-solving easier. These include analysis, communication, emotional intelligence, resilience, creativity, adaptability, and teamwork.

1. Analysis

As a manager , you'll solve each problem by assessing the situation first. Then, you’ll use analytical skills to distinguish between ineffective and effective solutions.

2. Communication

Effective communication plays a significant role in problem-solving, particularly when others are involved. Some skills that can help enhance communication at work include active listening, speaking with an even tone and volume, and supporting verbal information with written communication.

3. Emotional intelligence

Emotional intelligence is the ability to recognize and manage emotions in any situation. People with emotional intelligence usually solve problems calmly and systematically, which often yields better results.

4. Resilience

Emotional intelligence and resilience are closely related traits. Resiliency is the ability to cope with and bounce back quickly from difficult situations. Those who possess resilience are often capable of accurately interpreting people and situations, which can be incredibly advantageous when difficulties arise.

5. Creativity 

When brainstorming solutions to problems, creativity can help you to think outside the box. Problem-solving strategies can be enhanced with the application of creative techniques. You can use creativity to:

Approach problems from different angles

Improve your problem-solving process

Spark creativity in your employees and peers

6. Adaptability

Adaptability is the capacity to adjust to change. When a particular solution to an issue doesn't work, an adaptable person can revisit the concern to think up another one without getting frustrated.

7. Teamwork

Finding a solution to a problem regularly involves working in a team. Good teamwork requires being comfortable working with others and collaborating with them, which can result in better problem-solving overall.

Steps of the problem-solving process

Effective problem-solving involves five essential steps. One way to remember them is through the IDEAL model created in 1984 by psychology professors John D. Bransford and Barry S. Stein [ 1 ]. The steps to solving problems in this model include: identifying that there is a problem, defining the goals you hope to achieve, exploring potential solutions, choosing a solution and acting on it, and looking at (or evaluating) the outcome.

1. Identify that there is a problem and root out its cause.

To solve a problem, you must first admit that one exists to then find its root cause. Finding the cause of the problem may involve asking questions like:

Can the problem be solved?

How big of a problem is it?

Why do I think the problem is occurring?

What are some things I know about the situation?

What are some things I don't know about the situation?

Are there any people who contributed to the problem?

Are there materials or processes that contributed to the problem?

Are there any patterns I can identify?

2. Define the goals you hope to achieve.

Every problem is different. The goals you hope to achieve when problem-solving depend on the scope of the problem. Some examples of goals you might set include:

Gather as much factual information as possible.

Brainstorm many different strategies to come up with the best one.

Be flexible when considering other viewpoints.

Articulate clearly and encourage questions, so everyone involved is on the same page.

Be open to other strategies if the chosen strategy doesn't work.

Stay positive throughout the process.

3. Explore potential solutions.

Once you've defined the goals you hope to achieve when problem-solving , it's time to start the process. This involves steps that often include fact-finding, brainstorming, prioritizing solutions, and assessing the cost of top solutions in terms of time, labor, and money.

4. Choose a solution and act on it.

Evaluate the pros and cons of each potential solution, and choose the one most likely to solve the problem within your given budget, abilities, and resources. Once you choose a solution, it's important to make a commitment and see it through. Draw up a plan of action for implementation, and share it with all involved parties clearly and effectively, both verbally and in writing. Make sure everyone understands their role for a successful conclusion.

5. Look at (or evaluate) the outcome.

Evaluation offers insights into your current situation and future problem-solving. When evaluating the outcome, ask yourself questions like:

Did the solution work?

Will this solution work for other problems?

Were there any changes you would have made?

Would another solution have worked better?

As a current or future manager looking to build your problem-solving skills, it is often helpful to take a professional course. Consider Improving Communication Skills offered by the University of Pennsylvania on Coursera. You'll learn how to boost your ability to persuade, ask questions, negotiate, apologize, and more. 

You might also consider taking Emotional Intelligence: Cultivating Immensely Human Interactions , offered by the University of Michigan on Coursera. You'll explore the interpersonal and intrapersonal skills common to people with emotional intelligence, and you'll learn how emotional intelligence is connected to team success and leadership.

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Article sources

Tennessee Tech. “ The Ideal Problem Solver (2nd ed.) , https://www.tntech.edu/cat/pdf/useful_links/idealproblemsolver.pdf.” Accessed December 6, 2022.

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This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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15 Top Management Science Books to Read

By: Grace He | Updated: August 25, 2023

Here is our list of management science books .

Management science books are guides, reference materials, and textbooks that use scientific methods to solve complex management issues. Examples of management science books are Introduction to Management Science by Bernard W. Taylor III and The Tyranny of Metrics by Jerry Z. Muller. The purpose of management science books is to provide leaders with a decision-making framework based on analysis, data, and mathematical models. The techniques covered in management science books offer a structured approach to decision-making in management.

Management science books are similar to office management books , training and development books , and operations management books . These resources help readers learn about management tips , management styles , and management by objectives .

This list includes:

• management science books for beginners
• management science textbooks
• best selling management science books

Let’s begin!

List of management science books

Management science books help readers develop problem-solving and critical-thinking skills essential in management. Here is a list of books you should consider reading to develop your management science techniques.

1. Introduction to Management Science (What’s New in Operations Management) by Bernard W. Taylor III

Introduction to Management Science is one of the management science textbooks that offers an all-encompassing initiation into this field. Authored by Bernard W. Taylor III, the book uses a clear and succinct writing approach, catering to beginners. Readers will find insights into linear programming, decision analysis, network models, and simulation. For newcomers grappling with unfamiliar scenarios, the book incorporates a dedicated chapter on navigating decisions amidst uncertainty. Additionally, readers can enjoy end-of-chapter challenges and exercises for self-assessment of each segment. Taylor skilfully constructs an intelligent progression of concepts and techniques, making the book an intelligible and well-structured resource.

Notable quote: “A management science solution can be either a recommended decision or information that helps a manager make a decision.”

Check out Introduction to Management Science .

2. Small Giants: Companies That Choose to be Great Instead of Big by Bo Burlingham

In Small Giants , Bo Burlingham takes a close look at 14 remarkable private companies, such as a music label and a brewery. Burlingham challenges the idea that achieving success requires constant aggressive growth. Instead, he highlights how businesses can flourish by concentrating on top-notch customer service and fostering a lasting culture rather than pursuing rapid expansion.

The book delves into how these companies effectively pursued their business objectives through diligent and clever approaches. The resource offers a fresh and motivating handbook on business and management tactics. Burlingham reveals the special factors that set these companies apart and led to their accomplishments.

Notable quote: “If you constantly hear about the need to grow or die, if everybody seems to be trying to get to the next level, if the only companies being celebrated—or even taken seriously—are the biggest, you may never even think to ask about options other than growing your business as much as you can and as quickly as you can.”

Check out Small Giants .

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3. What Your Employees Need and Can’t Tell You: Adapting to Change with the Science of Behavioral Economics by Melina Palmer

In What Your Employees Need and Can’t Tell You , you will gain valuable insight into how behavioral economics influences management strategies. Melina Palmer dives into frameworks that shed light on how employees react to changes. The book revolves around three key themes. These themes include comprehending the brain’s workings in response to change, uncovering the subconscious processes behind decision-making, and putting this newfound knowledge into action. Moreover, the book equips readers with tactics for employers to meaningfully connect with their employees.

Notable quote: “If you approach change properly, it can be quite easy. People naturally and happily embrace change all the time, but we tend to ignore its signs.”

Check out What Your Employees Need and Can’t Tell You .

4. Leadership and Management Development by Jeff Gold, Richard Thorpe, and Alan Mumford

Authored by Jeff Gold, Richard Thorpe, and Alan Mumford, Leadership and Management Development offers practical strategies and guidance for enhancing management and leadership skills. Drawing on research from psychology, organizational behavior, and sociology, the authors offer valuable insights into effective leadership practices. The revised edition features a wider spectrum, including ethics, ecology, SMEs, and diversity. Readers will also benefit from the diverse perspectives of international case studies. This book is a valuable resource for individuals pursuing studies in leadership and management development as part of their CIPD qualification.

Notable quote: “Through talk, argument, and persuasion, a manager creates meaning with others, providing clarity as the conversations unfold.”

Check out Leadership and Management Development .

5. Business Analytics: The Art of Modeling with Spreadsheets, 5th Edition by Stephen Powell and Kenneth Baker

Stephen Powell and Kenneth Baker’s book uses the power of Excel spreadsheets to share the fundamentals of management science. The Art of Modeling with Spreadsheets centers around optimization, data visualization, simulation, and regression. In its fifth edition, the book discusses management science, adept modeling techniques, and proficient spreadsheet usage. Readers will learn the essential skills and technical acumen required for effective business modeling. Notably concise and easily approachable, this book is a fitting choice for departments or courses that prioritize modeling as a vital competency.

Notable quote: “Models are not useful only in the business world, but also in the academic world where business analysts are educated.”

Check out Business Analytics .

6. The Tyranny of Metrics by Jerry Z. Muller

The Tyranny of Metrics scrutinizes the impact of performance measurement and metrics on decision-making and organizational dynamics. Authored by Jerry Z. Muller, the book delves into how metrics contribute to enhancing performance and fostering accountability. Nonetheless, Muller cautions against the potential misapplication of these metrics, leading to unintended repercussions. Employing an interdisciplinary stance, The Tyranny of Metrics draws insights from history, psychology, sociology, and political science. This method offers a comprehensive grasp of the topic. The book adopts a progressive structure, with each chapter building upon the preceding one to construct a compelling and coherent argument.

Notable quote: “When numbers, standardized measurement of performance, and big data are seen as the wave of the future, professional judgment based upon experience and talent are seen as retrograde, almost anachronistic.”

Check out The Tyranny of Metrics .

7. Leading for Change: How to Thrive in Uncertain Times by Kathryn Simpson

Leading for Change is among the best selling management science books, offering valuable guidance for leaders maneuvering through periods of change and unpredictability. Guiding a team amidst an ever-shifting business management landscape can be a difficult task. To tackle this dilemma, Kathryn Simpson dissects eight pivotal success factors, offering a blueprint for all leaders to follow. Within these pages, readers will gain insights into adept change leadership, strategies to involve stakeholders, and a lasting route to success.

Notable quote: “As a leader, it is important to understand your role—when you are going to be a content expert (someone who knows what needs to be done) or a facilitator (who focuses on how the work needs to get done), or a combination of both roles.”

Check out Leading for Change .

8. A Guide to the Project Management Body of Knowledge by The Project Management Institute

The Guide to Project Management Basics offers a clear plan for successful project management. The book explains the steps needed to make projects work well, including planning, doing the work, keeping things on track, and checking progress. The resource also talks about how to talk with colleagues about the project, manage those who are interested, and handle potential problems.

This guide helps you see how your project is doing and make it better. By using the information, you can finish projects on time, with the money you planned, and at a good quality level. The Project Management Institute updates this guide annually to include the latest and best ways to manage projects. This step makes the guide a great help for project managers.

Notable quote: “Project managers are expected to deliver projects that create value for the organization and stakeholders within the organization’s system for value delivery.”

Check out A Guide to the Project Management Body of Knowledge .

9. High Output Management by Andrew Groove

In High Output Management , Andrew Grove shares practical insights on effectively leading a new business. He spotlights the critical role managers play in a company’s success, highlighting the value of setting clear goals and offering helpful feedback to employees. Grove underscores the importance of being proactive, foreseeing potential issues, and addressing them ahead of time. The book promotes making decisions based on data, urging managers to gather information and use it to guide choices for their teams and the organization. Given the current era of abundant data, prioritizing data and analysis is crucial. The concepts within this book are beneficial for both experienced and aspiring managers, accountants, consultants, CEOs, and educators.

Notable quote: “When products and services become largely indistinguishable from each other, all there is by way of competitive advantage is time.”

Check out High Output Management .

10. The Making of a Manager: What to Do When Everyone Looks to You by Julie Zhuo

The Making of a Manager offers down-to-earth guidance on tackling the hurdles of managerial roles and triumphing over them. The book zeros in on fundamental management domains, like making decisions, communicating effectively, recruiting, and leading teams. Within each chapter, Julie Zhuo weaves in her own experiences and practical advice tailor-made for novice and future managers. Zhuo places a premium on nurturing a positive workplace atmosphere and cultivating robust staff bonds. This approach nurtures inventiveness and ingenuity and elevates employee spirits and loyalty. Presented in Zhuo’s friendly and immersive prose, the book is a user-friendly resource that readers can readily absorb and integrate into their daily professional lives.

Notable quote: “The management aspect has nothing to do with employment status and everything to do with the fact that you are no longer trying to get something done by yourself.”

Check out The Making of a Manager .

11. Project Management for the Unofficial Manager by Kory Kogan, Suzette Blakemore, and James Wood

Project Management for the Unofficial Manager is tailored for those who lack formal project management training but often find themselves responsible for projects in different roles. This book encompasses the entire project journey, from starting a project to wrapping it up. Insights address aspects like managing risks, defining project boundaries, and engaging stakeholders. Moreover, the resource offers guidance on handling project communications and overseeing virtual teams. The book breaks down project management into five core parts, which are beginning, planning, doing, keeping track, and concluding. With its clear, step-by-step approach, this book enables any reader to oversee a project from its inception to completion effectively.

Notable quote: “If most of your work time is spent on projects and you have never been exposed to formal project management training, you are an unofficial project manager.”

Check out Project Management for the Unofficial Manager .

12. The First-Time Manager by Loren Belker, Jim Mccormick, and Gary Topchik

Transitioning from an employee to a manager can be daunting, so The First-Time Manager is an excellent read for new leaders. Loren Belker, Jim Mccormick, and Gary Topchik help readers set necessary boundaries and decide what type of manager they want to be. This book focuses on motivation, remaining calm under pressure, listening, hiring, and leading meetings. The First-Time Manager touches on tackling every possible management problem. Also, the book is action-oriented and comes with checklists, exercises, and templates to help readers apply the techniques in their work.

Notable quote: “Being a manager requires skills beyond those of being an excellent technician. Managers need to focus on people, not just tasks. They need to rely on others, not just be self-reliant.”

Check out The First-Time Manager .

13. The Effective Executive: The Definitive Guide to Getting the Right Things Done by Peter Drucker

The Effective Executive is a valuable resource for enhancing managerial and leadership skills, concentrating on the vital aspects of prioritization and decision-making. Written by the eminent Peter Drucker, a luminary in management science, the book is a treasure trove of actionable advice. Drucker underscores the cornerstones of effectiveness, including a shift toward outcome-driven approaches instead of routine activities. He claims it is important to focus on pivotal tasks, employ data-backed analysis for sound decisions, and embrace communication responsibilities. Drucker asserts that being a productive executive hinges on accomplishing the right tasks by steering clear of unproductive endeavors and attending to often-overlooked matters.

Notable quote: “Intelligence, imagination, and knowledge are essential resources, but only effectiveness converts them into results.”

Check out The Effective Executive .

14. New Managers: Mastering the Big 3 Principles of Effective Management—Leadership, Communication, and Team Building by Paul Falcone

Paul Falcone equips new managers with indispensable skills for excelling in their roles in his book New Managers . The book zeroes in on leadership, effective communication, and the principles of building cohesive teams. Falcone argues that skilled management is not an inherent trait but is instead a learned ability. He underscores the importance of crafting an environment that nurtures the capabilities of every employee while creating a robust team. Additionally, the book dissects the key challenges that often confound new managers and presents practical, actionable remedies.

Notable quote: “You need to not only manage performance but also demonstrate the soft skills of listening, empathy, and genuine concern for your employees.”

Check out New Managers .

15. The 80/20 Principle: Achieving More with Less by Richard Koch

The 80/20 Principle is a top-tier choice among management science books for beginners. This principle asserts that 80 percent of outcomes stem from 20 percent of efforts. Richard Koch deftly uses this concept in the book to unveil strategies for enhancing efficiency and advancing one’s career. Koch imparts the wisdom of prioritizing seemingly minor actions to unlock substantial achievements. The crux lies in directing your energy toward recognizing tasks that yield the most impactful results.

Notable quote: “Everything in life is a tussle between effort and results, inputs and outputs, causes and consequences.”

Check out The 80/20 Principle .

Management science books are relevant in various fields, including business, healthcare, government, and engineering. These books help decision-makers and managers make effective and informed decisions. By providing practical examples and case studies, management science books help develop readers’ critical thinking and problem-solving skills and drive success in the business environment. A management science book is suitable for every reader regardless of professional status, from introductory to more advanced.

For more management resources, check out these articles on management training programs , project management skills , and management podcasts .

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FAQ: Management science books

Here are frequently asked questions about management science books.

What is management science?

Management science is a field that adopts mathematical modeling and quantitative analysis to aid decision-making and problem-solving in different management areas. Additionally, management science aims to identify effective ways to manage resources and optimize processes through data and analytical methods. This principle applies to various industries, including healthcare, finance, and logistics.

What are management science books?

Management science books are guides and textbooks that provide practical problem-solving approaches in various management areas. These books cover topics like finance, strategy, marketing, and operations. With the help of management science books, organizations and individuals can solve management problems and make better decisions.

What are the best books about management science?

The best management science books include The Making of a Manager by Julie Zhuo, The Tyranny of Metrics by Jerry Muller, and  The First-Time Manager by Loren Belker, Jim Mccormick, and Gary Topchik.

Author: Grace He

People & Culture Director at teambuilding.com. Grace is the Director of People & Culture at teambuilding.com. She studied Industrial and Labor Relations at Cornell University, Information Science at East China Normal University and earned an MBA at Washington State University.

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People & Culture Director at teambuilding.com.

Grace is the Director of People & Culture at teambuilding.com. She studied Industrial and Labor Relations at Cornell University, Information Science at East China Normal University and earned an MBA at Washington State University.

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Crafting an effective problem statement

Aug 31, 2024

Posted by: Regine Fe Arat

Crafting a clear and concise problem statement is an essential skill in project management. It’s a powerful tool that you can use for effective problem-solving as it guides teams toward innovative solutions and measurable outcomes.

Whether you’re a seasoned project manager or a newcomer to the field, being able to write problem statements can significantly enhance your ability to tackle complex challenges and drive meaningful change.

A problem statement concisely describes an issue or challenge that needs to be addressed. An effective problem statement frames the issue in a way that facilitates a deeper understanding and guides the problem-solving process.

At its core, a well-crafted problem statement should capture the essence of the challenge at hand, providing enough context for stakeholders to grasp the issue’s significance. It helps you find the most appropriate solution and ensures that all team members are aligned in their understanding of the problem’s scope and implications.

In this comprehensive guide, you’ll find out what problem statements are and what types you can use. You’ll also find practical examples and actionable tips to help you create impactful problem statements of your own.

What are the key components of a problem statement?

Here are the three key components of a problem statement:

The problem

You should clearly state the core issue or challenge to be addressed. This is the heart of your problem statement. Articulate it in a way that’s easy to understand and free from ambiguity.

The method used to solve the problem

While the problem statement itself shouldn’t propose specific solutions, it can outline the general approach or methodology you’ll use to address the issue. For example, you might mention the type of research, analysis or problem-solving techniques your team will employ.

The purpose, statement of objective and scope

This component outlines why addressing the problem is important and what the desired outcome looks like. It should clarify the goals of the problem-solving effort and define the boundaries of what you’ll address. This helps focus efforts and set clear expectations for what the project or initiative aims to achieve.

When to use a problem statement

A problem statement is a versatile tool that you can use across various scenarios in both professional and personal contexts. They are particularly valuable in the following cases:

• Initiating new projects: a problem statement helps define the project’s purpose and sets clear objectives from the outset.
• Addressing organizational challenges: it provides a structured approach to tackling complex issues within a company or team.
• Conducting research: researchers use problem statements to focus their investigations and define the scope of their studies.
• Presenting ideas to stakeholders: a well-formulated problem statement can effectively communicate the need for change or investment to decision-makers.
• Personal goal-setting: even in individual pursuits, problem statements can help clarify objectives and motivate action.

Types of problem statements

Understanding different types of problem statements can help you choose the best approach for your specific situation.

Let’s explore three common types:

The status quo problem statement

This type of problem statement focuses on the current state of affairs and highlights the gap between the existing situation and the desired outcome.

It’s particularly effective when you are addressing ongoing issues or systemic problems within an organization.

Example: “Our customer support team currently handles 150 tickets, on average, per day with a resolution time of 48 hours. This prolonged response time has led to a 15% decrease in customer satisfaction scores over the past quarter, potentially impacting our retention rates and brand reputation.”

Destination problem statement

A destination problem statement emphasizes the desired future state or goal.

It’s ideal for situations where you want to inspire change and motivate teams to work toward a specific vision.

Example: “We aim to create a seamless onboarding experience for new employees that reduces the time to full productivity from 12 to six weeks while increasing new hire satisfaction scores by 25% within the next fiscal year.”

The stakeholder problem statement

This type of problem statement focuses on the impact of an issue on specific individuals or groups.

It’s particularly useful when you need to highlight the human element of a problem and garner support for change.

Example: “Junior software developers in our organization report feeling overwhelmed and unsupported, with 60% expressing dissatisfaction with their professional growth opportunities. This has resulted in a 30% turnover rate among this group in the past year, leading to increased recruitment costs and knowledge loss.”

How to write a problem statement

Crafting an effective problem statement takes practice and attention to detail. Follow these steps to create impactful problem statements:

Understand the problem

Before putting pen to paper, invest time in thoroughly understanding the issue at hand. Gather data, conduct interviews with stakeholders and observe the problem in action if possible. This deep understanding will form the foundation of your problem statement.

Articulate the problem in simple, straightforward language. Avoid jargon or overly technical terms that might confuse readers. Your goal is to ensure that anyone reading the statement can quickly grasp the core issue.

Provide context

Include relevant background information that helps readers understand the problem’s significance. This might include historical data, industry benchmarks or organizational goals that the issue is affecting.

Identify the root cause

Dig deeper to uncover the underlying reasons for the problem. Avoid focusing on symptoms. Instead, strive to identify the fundamental issues that need to be addressed. Tools like the “5 whys” technique can be helpful in this process.

Be specific

Use concrete details and quantifiable metrics whenever possible. Instead of saying, “Customer satisfaction is low,” specify, “Customer satisfaction scores have dropped by 15% in the past quarter.” This precision helps create a clear picture of the problem’s scope and impact.

Use measurable criteria

Incorporate measurable elements that can be used to track progress and determine when the problem has been resolved. This might include specific metrics, timeframes or benchmarks.

Make it feasible

Ensure the problem statement describes an issue the organization can actually address. You’ll need to be realistic.

Consider your organization’s resources and constraints. While ambition is important, an overly broad or unattainable goal can be demotivating and unhelpful.

Avoid solution language

Resist the temptation to propose solutions in the problem statement. The goal is to clearly define the problem, not to prescribe how it should be solved. This approach encourages creative thinking and enables you and your team to consider a range of potential solutions.

Consider the audience

Tailor your problem statement to the intended audience. The level of detail and technical language may vary depending on whether you’re presenting to executives, team members or external stakeholders.

Seek feedback

Share your draft problem statement with colleagues or stakeholders to gather their input. Fresh perspectives can help identify blind spots or areas that need clarification.

Revise and refine

Refine your problem statement based on the feedback you receive. Don’t be afraid to go through multiple iterations to achieve the most clear and impactful statement possible.

Test for objectivity

Review your problem statement to ensure it remains objective and free from bias. Avoid language that assigns blame or makes assumptions about causes or solutions.

Challenges of writing a problem statement

While problem statements can be a powerful tool for problem-solving, you may face several common challenges when writing yours. Being aware of these pitfalls can help you avoid them and create more effective problem statements.

Making it too complicated and lacking detail

One of the most frequent issues in problem statement writing is finding the right balance between detail and clarity.

Oversimplifying the problem can lead to a statement that’s too vague to be actionable. On the other hand, including too much detail can obscure the core issue and make the statement difficult to understand.

To overcome this challenge, focus on the essential elements of the problem. Start with a clear, concise statement about the issue, then add only the most relevant contextual details. Use specific, measurable criteria to define the problem’s scope and impact, but avoid getting bogged down in excessive technical jargon or minute, unhelpful details.

Ignoring stakeholders’ perspectives

Another common pitfall is failing to consider the diverse perspectives of all the stakeholders the problem affects. This can result in a problem statement that doesn’t fully capture the issue’s complexity or fails to resonate with key decision-makers.

To address this challenge, make an effort to gather input from a wide range of stakeholders before finalizing your problem statement. This might include conducting interviews, surveys or focus groups with employees, customers, partners or other relevant parties.

Incorporate these diverse viewpoints into your problem statement to create a more comprehensive and compelling representation of the issue.

Misalignment with organizational goals

Sometimes, problem statements can be well-crafted but fail to align with broader organizational objectives. This misalignment can lead to wasted resources and efforts on issues that, while important, may not be critical to the company’s overall success.

To ensure your problem statement aligns with the organization’s goals, review your company’s mission statement, strategic plans and key performance indicators before you get started. Consider how the problem you’re addressing relates to these broader objectives.

If possible, explicitly link the problem and its potential resolution to specific goals or metrics in your statement.

Failing to review and revise

An effective problem statement often requires multiple iterations and refinements. Many project managers make the mistake of treating their first draft as the final version, missing opportunities to improve clarity, precision and impact.

To overcome this challenge:

• Build time for revision into your problem statement writing process.
• After crafting your initial draft, step away from it for a short period.
• Return with fresh eyes to critically evaluate and refine your statement.
• Share it with colleagues or mentors for feedback. Be open to making substantive changes based on their input.

The last card

Being able to write problem statements is a valuable skill that can significantly enhance your problem-solving capabilities and drive meaningful change within your organization. They enable you to set the stage for innovative solutions and improved processes – but to do this, you’ll need to clearly articulate challenges, provide context and focus on measurable outcomes.

A well-crafted problem statement is a powerful tool for aligning teams, securing resources and guiding decision-making. It’s the foundation for effective problem-solving strategies. As you get better at writing problem statements, you’ll find that complex challenges become more manageable and your ability to drive positive change increases.

At Pip Decks, we’re passionate about equipping professionals with the tools and knowledge they need to excel in their roles. Whether you’re looking to improve your problem-solving skills, enhance team collaboration or develop your leadership abilities, you’ll find the answers you need in our expert-written card decks.

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