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What is Managerial Economics? Definition, Types, Nature, Principles, and Scope
- Ritesh Pathak
- Nov 26, 2020
- Updated on: Nov 21, 2023
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Businesses run on various theories that are explained in Economics. Managerial Economics is the stream of management studies that emphasizes solving problems in businesses using the theories in micro and macroeconomics . This branch of economics is used by firms to not only find a solution to problems in daily running but also for long-term planning. We can also say that Managerial economics is a practical application of theories in economics.
“Managerial economics is concerned with the application of economic concepts and economic analysis to the problems of formulating rational managerial decisions.” - Edwin Mansfield, Economics Professor, University of Pennsylvania
We should also look here at What is economics? Economics is an inevitable part of any business. All the business assumptions, forecasting, and investments are based on this one single concept. Investopedia explains “Economics is a social science concerned with the production, distribution, and consumption of goods and services. It studies how individuals, businesses, governments, and nations make choices about how to allocate resources.” So, theories in economics are not just some statements written but rather they act as fuel for a firm. In the broader picture, economics also helps nations in policy formation.
So, in this blog, we will discuss the branch of economics that helps businesses to find a solution to almost every problem they may face. We will discuss the definition of managerial economics, its nature, its scope in businesses, and the principles of managerial economics.
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Definition of Managerial Economics
Managerial economics is defined as the branch of economics which deals with the application of various concepts, theories, methodologies of economics to solve practical problems in business management . It is also reckoned as the amalgamation of economic theories and business practices to ease the process of decision making. Managerial economics is also said to cover the gap between the problems of logic and problems of policy.
Managerial economics is used to find a rational solution to problems faced by firms. These problems include issues around demand, cost, production, marketing, and it is used also for future planning. The best thing about managerial economics is that it has a logical solution to almost every problem that may arise during business management and that too by sticking to the microeconomic policies of the firm.
When we talk of managerial economics as a subject, it is a branch of management studies that emphasizes solving business problems using theories of micro and macroeconomics . Spencer and Siegelman have defined the subject as “the integration of economic theory with business practice to facilitate decision making and planning by management.” The study of managerial economics helps the students to enhance their analytical skills, developing a mindset that enables them to find rational solutions.
Nature of Managerial Economics
We know about managerial economics like what it is and how different people define it. Managerial Economics is an essential scholastic field. It can be termed as a science in the sense that it fulfills the criteria of being a science.
We all know science as a systematic body of knowledge and it is based on methodological observations. Similarly, Managerial Economics is also a science of making decisions and finding alternatives, keeping the scarce of resources in mind.
In science, we arrive at any conclusion after continuous experimentation. Similarly, in managerial economics policies are formed after constant testing and trailing.
In science, principles are universally acceptable and in managerial economics, policies are universally applicable at least partially if not fully.
Nature of Managerial Economics
We will now look at the characteristics of managerial economics in brief.
Art and Science
Managerial Economics requires a lot of creativity and logical thinking to come up with a solution. A managerial economist should possess the art of utilizing his capabilities, knowledge, and skills to achieve the organizational objective. Managerial Economics is also considered as a stream of science as it involves the application of different economic principles, techniques, and methods, to solve business problems.
Microeconomics
In managerial economics, problems of a particular organization are looked upon rather than focusing on the whole economy. Therefore it is termed as a part of microeconomics.
Uses Macroeconomics
Any organization operates in a market that is a part of the whole economy, so external environments affect the decisions within the organization. Managerial Economics uses the concepts of macroeconomics to solve problems. Managers analyze the macroeconomic factors like market conditions, economic reforms, government policies to understand their impact on the organization.
Multi-disciplinary
Managerial Economics uses different tools and principles from different disciplines like accounting, finance, statistics, mathematics, production, operation research, human resource, marketing, etc. This helps in coming up with a perfect solution.
Management oriented and pragmatic
Managerial economics is a tool in the hands of managers that aids them in finding appropriate solutions to business-related problems and uncertainties. As mentioned above, managerial economics also helps in goal establishment, policy formation, and effective decision making. It is a practical approach to find solutions.
Types of Managerial Economics
Everyone has their perceiving ability, so the same goes with managerial economics. All managers perceive the concept of managerial economics differently. For some, customers’ satisfaction can be the priority while some may focus on efficient production. This leads us to different types of managerial economics. So, let us explore the different approaches to managerial economics.
Liberal Managerialism
Market is a free and democratic place in terms of decision making. Customers get a lot many options to choose from. So, companies have to modify their policies according to consumers’ demands and market trends. If not done so, it may result in business failures. This is what we call liberal managerialism.
Normative Managerialism
The normative view of managerial economics means that the decisions taken by the administration would be normal, based on real-life experiences and practices. The decisions reflect a practical approach regarding product design, forecasting, marketing, supply and demand analysis, recruitments, and everything else that is concerned with the growth of a business.
Radical Managerialism
Radical managerialism means to come up with revolutionary solutions. Sometimes, when the conventional approach to a problem doesn’t work, radical managerialism may have the solution. However, it requires the manager to possess some extraordinary skills and thinking to look beyond. In radical managerialism, consumer needs and satisfaction are prioritized over profit maximization.
So, these were the three different types of managerial economics. These are decided based on the different approaches by managers.
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Principles of Managerial Economics
The great macroeconomist N. Gregory Mankiw has given ten principles to explain the significance of managerial economics in business operations which can be further classified into three categories.
Principles of How People Make Decisions
Based on the real-life decision-making processes, four principles are recalled in Managerial Economics.
1. People Face Tradeoffs
There are enormous options in the market. So, people have to make choices among the various options available.
2. Opportunity Cost
Every decision involves an opportunity cost that is the cost of those options which we let go of while selecting the most appropriate one.
3. Rational People Think at the Margin
When we make choices from the various options available and before investing the capital or resources we look at the profit margin we would make in the investment.
4. People Respond to Incentives
It is human nature to look for something extra while purchasing something. Decision-making is affected by the incentives attached to a particular product or service. Positive incentive motivates people to opt for the particular product while negative incentive discourages.
Principles of How People Interact
Communication with the audience plays a vital role in good performance. Over the years, organizations have realized the need to communicate well with their audience. Based on this, three principles are given in Managerial Economics.
1. Trade can Make Everyone Better Off
This principle states that trade is a medium to exchange services and products. Everyone gets a fair chance to offer products and services which they are good at making and also to purchase those products and services. Also Read: The success story of Delhivery
2. Markets Are Usually A Good Way to Organize Economic Activity
Market is a place where buyers and sellers interact with each other. Consumers put in their demands and requirements and the producers decide on the production and supply of those products and services.
3. Government can better the market outcomes
Government intervenes in business operations whenever there are unfavorable market conditions like the current pandemic situation or also for the welfare of society. One example of the latter is deciding the minimum wage for laborers.
Referred Blog | How is India recovering from the economic slowdown .
Principle of How Economy Works as a Whole
Three principles are given to explain the role of the economy in the functioning of an organization.
1. A Country’s Standard of Living Depends on the Goods and Services produced
The role of organizations in the economic growth of a country is one of the major, so, the organizations must be capable enough to produce goods and services for the population. This ultimately raises the standard of living and also contributes to GDP growth.
2. Price Rises When Government Prints Too Much Money
If there is surplus money available with people, their spending capacity increases, ultimately leading to a rise in demand. When the producers are unable to meet the consumer’s demand, inflation takes place. Referred blog : What does the 24% shrink in India’s GDP mean?
3. Society Faces a Short-Run Tradeoff between Inflation and Unemployment
Government bring-in policies to tackle the problem of unemployment and boost the economy in the short run as well. This further leads to inflation.
Scope of Managerial Economics
Managerial Economics has a more narrow scope. It solves a firm’s problem using microeconomics. In the situation of scarce resources, managerial economics ensures that managers make effective and efficient decisions that are equally beneficial to customers, suppliers, and the organization. The fact of scarcity of resources gives rise to three fundamental questions-
What to produce?
How to produce?
For whom to produce?
To answer these questions, a firm makes use of managerial economics principles.
Managerial Economics is not only applicable to profit-making business organizations, but also to non- profit organizations such as hospitals, schools, government agencies, etc.
Read this article to know about the scope of Managerial Economics in detail.
We tried to explain Managerial Economics through this blog. The definition of Managerial Economics says that it is a branch of economics that deals with the application of various theories, concepts, and methodologies to solve business problems. It is said to cover the gap between problem of logic and problem of policy.
For any firm to be successful, it needs to solve its problems logically and rationally. Managerial Economics helps the managers to make effective and efficient decisions using the concepts of microeconomics. One of the top characteristics of Managerial Economics is that it uses the different factors of macroeconomics helping firms to act according to the market trends.
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Managerial Economics: Importance, Significance, Nature, Scope, and Role
Meaning of managerial economics.
Managerial economics refers to the management of business using economic theories, tools, and concepts. It is simply the amalgamation of management principles and economic theories for better problem solving and decision making. It is a branch of economics that applies economic theories for analysis, assumption, and prediction of business conditions.
Managerial economics performs three important roles for business organizations : Demand analysis and forecasting, capital management and profit management. Firms with the application of managerial economics optimally decide what to produce, how to produce and for whom to produce.
Role of Managerial Economics
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Importance of Managerial Economics
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Significance of Managerial Economics
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Nature of Managerial Economics
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Scope of Managerial Economics
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A Managerial Problem Solving Methodology (MPSM)
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- Samir Chakraborty 2
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A managerial problem solving methodology (MPSM) has been developed and extensively used [1–7] to solve Process problems. A Process is defined as an operational combination of man-machine systems which transforms basic (to the organization) inputs ($’s) to primary (to survival) outputs (products/services). A problem is defined by state-space constraints [8] which threaten Process survival. A threat to survival is said to exist when the distance [11] between actual-performance and ideal-performance exceeds a given threshold.
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Chakraborty, S. (1978). A Managerial Problem Solving Methodology (MPSM). In: Klir, G.J. (eds) Applied General Systems Research. NATO Conference Series, vol 5. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-0555-3_54
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Detailed contents
1 | ||||
3 | ||||
1.1 | Introduction 4 | |||
Case study 1.1: Global warming 4 | ||||
1.2 | Definition and relationships with other disciplines 7 | |||
Definition 7 | ||||
Relationship with economic theory 8 | ||||
Relationship with decision sciences 10 | ||||
Relationship with business functions 10 | ||||
1.3 | Elements of managerial economics 11 | |||
Subject areas and relationships 11 | ||||
Presentation of topics 11 | ||||
1.4 | Methods 12 | |||
Scientific theories 12 | ||||
Learning economics 14 | ||||
Case study 1.2: Import quotas on Japanese cars 15 | ||||
Tools of analysis: demand and supply 16 | ||||
Case study 1.3: Equal prize money in tennis 17 | ||||
Summary 18 | ||||
Review questions 19 | ||||
Notes 19 | ||||
20 | ||||
2.1 | Introduction 22 | |||
2.2 | The nature of the firm 23 | |||
Economic organizations 23 | ||||
Transaction cost theory 25 | ||||
Motivation theory 26 | ||||
Property rights theory 29 | ||||
2.3 | The basic profit-maximizing model 32 | |||
Assumptions 32 | ||||
Limitations 35 | ||||
Usefulness 35 | ||||
2.4 | The agency problem 36 | |||
Contracts and bounded rationality 37 | ||||
Hidden information 38 | ||||
Hidden action 39 | ||||
Control measures 40 | ||||
Limitations of the agency model 43 | ||||
Case study 2.1: Corporate governance 44 | ||||
2.5 | Measurement of profit 48 | |||
Nature of measurement problems 48 | ||||
Efficient markets hypothesis 50 | ||||
Limitations of the EMH 51 | ||||
Case study 2.2: Enron 53 | ||||
2.6 | Risk and uncertainty 57 | |||
Attitudes to risk 58 | ||||
Risk and objectives 58 | ||||
Risk and the agency problem 59 | ||||
2.7 | Multiproduct strategies 60 | |||
Product line profit maximization 60 | ||||
Product mix profit maximization 61 | ||||
Case study 2.3: PC World 62 | ||||
2.8 | Conclusion 62 | |||
The public sector and non-profit organizations 63 | ||||
Satisficing 63 | ||||
Surveys of business objectives 64 | ||||
Ethics 64 | ||||
Profit maximization revisited 65 | ||||
Summary 66 | ||||
Review questions 67 | ||||
Notes 68 | ||||
71 | ||||
73 | ||||
3.1 | Introduction 74 | |||
3.2 | Definition and representation 74 | |||
Meaning of demand 74 | ||||
Tables, graphs and equations 75 | ||||
Interpretation of equations 78 | ||||
3.3 | Consumer theory 80 | |||
Assumptions 81 | ||||
Analysis 83 | ||||
Limitations 88 | ||||
Alternative approaches 88 | ||||
Conclusions 90 | ||||
3.4 | Factors determining demand 91 | |||
Controllable factors 92 | ||||
Uncontrollable factors 93 | ||||
Demand and quantity demanded 96 | ||||
Case study 3.1: Marks & Spencer 97 | ||||
3.5 | Elasticity 98 | |||
Price elasticity 99 | ||||
Promotional elasticity 105 | ||||
Income elasticity 107 | ||||
Cross-elasticity 108 | ||||
3.6 | A problem-solving approach 110 | |||
Examples of solved problems 110 | ||||
Case study 3.2: The Oresund bridge 115 | ||||
Case study 3.3: The Texas state bird 116 | ||||
Case study 3.4: Oil production 116 | ||||
Summary 118 | ||||
Review questions 118 | ||||
Problems 119 | ||||
Notes 120 | ||||
122 | ||||
4.1 | Introduction 124 | |||
4.2 | Methods 125 | |||
Consumer surveys 125 | ||||
Market experiments 126 | ||||
Statistical methods 127 | ||||
4.3 | Model specification 127 | |||
Mathematical models 127 | ||||
Statistical models 129 | ||||
4.4 | Data collection 129 | |||
Types of data 129 | ||||
Sources of data 130 | ||||
Presentation of data 131 | ||||
4.5 | Simple regression 133 | |||
The OLS method 133 | ||||
Application of OLS 133 | ||||
4.6 | Goodness of fit 135 | |||
Correlation 135 | ||||
The coefficient of determination 136 | ||||
4.7 | Power regression 137 | |||
Nature of the model 138 | ||||
Application of the model 138 | ||||
4.8 | Forecasting 139 | |||
Nature 139 | ||||
Application 139 | ||||
4.9 | Multiple regression 140 | |||
Nature of the model 140 | ||||
Advantages of multiple regression 141 | ||||
Dummy variables 142 | ||||
Mathematical forms 143 | ||||
Interpretation of the model results 144 | ||||
Selecting the best model 148 | ||||
Case study 4.1: The demand for coffee 149 | ||||
4.10 | Implications of empirical studies 150 | |||
The price–quality relationship 150 | ||||
Lack of importance of price 150 | ||||
Dynamic relationships 151 | ||||
4.11 | A problem-solving approach 151 | |||
Examples of solved problems 152 | ||||
Case study 4.2: Determinants of car prices 155 | ||||
Case study 4.3: The Sports Connection* 155 | ||||
Appendix A: Statistical inference 157 | ||||
Nature of inference in the OLS model 157 | ||||
Assumptions 157 | ||||
Calculations for statistical inference 159 | ||||
Consequences of assumptions 160 | ||||
Estimation 162 | ||||
Hypothesis testing 162 | ||||
Confidence intervals for forecasts 163 | ||||
Appendix B: Problems of the OLS model 165 | ||||
Specification error 165 | ||||
The identification problem 165 | ||||
Violation of assumptions regarding the error term 166 | ||||
Multicollinearity 168 | ||||
Summary 169 | ||||
Review questions 169 | ||||
Problems 170 | ||||
Notes 171 | ||||
175 | ||||
175 | ||||
5.1 | Introduction 176 | |||
5.2 | Basic terms and definitions 177 | |||
Factors of production 177 | ||||
Production functions 178 | ||||
Fixed factors 179 | ||||
Variable factors 179 | ||||
The short run 180 | ||||
The long run 180 | ||||
Scale 180 | ||||
Efficiency 181 | ||||
Input-output tables 181 | ||||
5.3 | The short run 182 | |||
Production functions and marginal product 182 | ||||
Derivation of the short-run input-output table 183 | ||||
Increasing and diminishing returns 185 | ||||
Relationships between total, marginal and average product 186 | ||||
Determining the optimal use of the variable input 188 | ||||
Case study 5.1: Microsoft – increasing or diminishing returns? 191 | ||||
Case study 5.2: State spending 192 | ||||
5.4 | The long run 193 | |||
Isoquants 193 | ||||
The marginal rate of technical substitution 194 | ||||
Returns to scale 194 | ||||
Determining the optimal combination of inputs 198 | ||||
5.5 | A problem-solving approach 203 | |||
Planning 203 | ||||
Marginal analysis 203 | ||||
Example of a solved problem 204 | ||||
Evaluating trade-offs 205 | ||||
Example of a solved problem 206 | ||||
Case study 5.3: Factor Substitution in the National Health Service 207 | ||||
Summary 208 | ||||
Review questions 209 | ||||
Problems 210 | ||||
Notes 211 | ||||
212 | ||||
6.1 | Introduction 213 | |||
Importance of costs for decision-making 213 | ||||
Explicit and implicit costs 214 | ||||
Historical and current costs 214 | ||||
Sunk and incremental costs 215 | ||||
Private and social costs 215 | ||||
Relevant costs for decision-making 216 | ||||
Case study 6.1: Brewster Roofing 216 | ||||
Summary of cost concepts 216 | ||||
6.2 | Short-run cost behaviour 217 | |||
Classification of costs 217 | ||||
Types of unit cost 217 | ||||
Derivation of cost functions from production functions 218 | ||||
Factors determining relationships with output 220 | ||||
Efficiency 223 | ||||
Changes in input prices 223 | ||||
Different forms of cost function 223 | ||||
6.3 | Long-run cost behaviour 226 | |||
Derivation of cost functions from production functions 226 | ||||
Economies of scale 227 | ||||
Diseconomies of scale 229 | ||||
Economies of scope 230 | ||||
Relationships between short- and long-run cost curves 231 | ||||
Strategy implications 234 | ||||
6.4 | The learning curve 235 | |||
6.5 | Cost–volume–profit analysis 236 | |||
Purpose and assumptions 236 | ||||
Break-even output 238 | ||||
Profit contribution 238 | ||||
Operating leverage 239 | ||||
Limitations of CVP analysis 239 | ||||
6.6 | A problem-solving approach 240 | |||
Examples of solved problems 241 | ||||
Case study 6.2: Converting to LPG – is it worth it? 245 | ||||
Case study 6.3: Rescuing Nissan 245 | ||||
Case study 6.4: Earls Court Gym 246 | ||||
Summary 250 | ||||
Review questions 250 | ||||
Problems 251 | ||||
Notes 253 | ||||
254 | ||||
7.1 | Introduction 255 | |||
Importance of cost estimation for decision-making 255 | ||||
Types of cost scenario 256 | ||||
Methodology 256 | ||||
7.2 | Short-run cost estimation 259 | |||
Types of empirical study 260 | ||||
Problems in short-run cost estimation 260 | ||||
Different forms of cost function, interpretation and selection 263 | ||||
Implications of empirical studies 265 | ||||
7.3 | Long-run cost estimation 265 | |||
Types of empirical study 266 | ||||
Problems in long-run cost estimation 266 | ||||
Different forms of cost function 268 | ||||
Implications of empirical studies 268 | ||||
Case study 7.1: Banking 270 | ||||
7.4 | The learning curve 271 | |||
Types of specification 271 | ||||
Case study 7.2: Airlines 272 | ||||
Case study 7.3: Electricity generation 273 | ||||
Application of the learning curve 275 | ||||
Example of a solved problem 275 | ||||
Implications of empirical studies 276 | ||||
7.5 | A problem-solving approach 277 | |||
Examples of solved problems 278 | ||||
Summary 280 | ||||
Review questions 280 | ||||
Problems 281 | ||||
Notes 282 | ||||
285 | ||||
287 | ||||
8.1 | Introduction 288 | |||
Characteristics of markets 289 | ||||
Types of market structure 289 | ||||
Relationships between structure, conduct and performance 290 | ||||
Methodology 291 | ||||
8.2 | Perfect competition 291 | |||
Conditions 291 | ||||
Demand and supply 292 | ||||
Graphical analysis of equilibrium 293 | ||||
Algebraic analysis of equilibrium 296 | ||||
Adjustment to changes in demand 297 | ||||
8.3 | Monopoly 300 | |||
Conditions 300 | ||||
Barriers to entry and exit 300 | ||||
Graphical analysis of equilibrium 304 | ||||
Algebraic analysis of equilibrium 305 | ||||
Pricing and price elasticity of demand 306 | ||||
Comparison of monopoly with perfect competition 309 | ||||
Case study 8.1: Electricity generation 311 | ||||
8.4 | Monopolistic competition 313 | |||
Conditions 313 | ||||
Graphical analysis of equilibrium 313 | ||||
Algebraic analysis of equilibrium 314 | ||||
Comparison with perfect competition and monopoly 316 | ||||
Comparison with oligopoly 316 | ||||
Case study 8.2: Price cuts for medicines 317 | ||||
8.5 | Oligopoly 318 | |||
Conditions 318 | ||||
The kinked demand curve model 319 | ||||
Collusion and cartels 321 | ||||
Price leadership 324 | ||||
Case study 8.3: Mobile phone networks 324 | ||||
Case study 8.4: Private school fees 325 | ||||
8.6 | A problem-solving approach 327 | |||
Summary 328 | ||||
Review questions 328 | ||||
Problems 329 | ||||
Notes 330 | ||||
331 | ||||
9.1 | Introduction 332 | |||
Nature and scope of game theory 333 | ||||
Elements of a game 333 | ||||
Types of game 336 | ||||
9.2 | Static games 338 | |||
Equilibrium 338 | ||||
Oligopoly models 340 | ||||
Property rights 349 | ||||
Nash bargaining 351 | ||||
Case study 9.1: Experiments testing the Cournot equilibrium 352 | ||||
9.3 | Dynamic games 353 | |||
Equilibrium 353 | ||||
Strategic moves and commitment 355 | ||||
Stackelberg oligopoly 358 | ||||
Case study 9.2: Monetary policy in Thailand 361 | ||||
9.4 | Games with uncertain outcomes 361 | |||
Mixed strategies 362 | ||||
Moral hazard and pay incentives 365 | ||||
Moral hazard and efficiency wages 367 | ||||
9.5 | Repeated games 370 | |||
Infinitely repeated games 370 | ||||
Finitely repeated games 375 | ||||
9.6 | Limitations of game theory 375 | |||
Case study 9.3: Credible commitments 376 | ||||
9.7 | A problem-solving approach 378 | |||
Summary 378 | ||||
Review questions 379 | ||||
Problems 379 | ||||
Notes 380 | ||||
382 | ||||
10.1 | Introduction 384 | |||
10.2 | Competitive advantage 385 | |||
Nature of competitive advantage 385 | ||||
Value creation 385 | ||||
Case study 10.1: Mobile phones – Nokia 388 | ||||
10.3 | Market positioning, segmentation and targeting 389 | |||
Cost advantage 390 | ||||
Benefit advantage 390 | ||||
Competitive advantage, price elasticity and pricing strategy 391 | ||||
Segmentation and targeting 392 | ||||
Role of pricing in managerial decision-making 394 | ||||
Case study 10.2: Handheld Computers – Palm 394 | ||||
10.4 | Price discrimination 396 | |||
Definition and conditions 396 | ||||
Types of price discrimination 397 | ||||
Price discrimination in the European Union 399 | ||||
Analysis 401 | ||||
Example of a solved problem 401 | ||||
Case study 10.3: Airlines 403 | ||||
10.5 | Multiproduct pricing 405 | |||
Context 405 | ||||
Demand interrelationships 406 | ||||
Production interrelationships 407 | ||||
Joint products 407 | ||||
Example of a solved problem 408 | ||||
10.6 | Transfer pricing 411 | |||
Context 411 | ||||
Products with no external market 412 | ||||
Example of a solved problem 412 | ||||
Products with perfectly competitive external markets 415 | ||||
Products with imperfectly competitive external markets 415 | ||||
10.7 | Pricing and the marketing mix 416 | |||
An approach to marketing mix optimization 416 | ||||
The constant elasticity model 417 | ||||
Complex marketing mix interactions 420 | ||||
10.8 | Dynamic aspects of pricing 421 | |||
Significance of the product life-cycle 421 | ||||
Early stages of the product life-cycle 421 | ||||
Later stages of the product life-cycle 422 | ||||
10.9 | Other pricing strategies 422 | |||
Perceived quality 423 | ||||
Perceived price 423 | ||||
The price–quality relationship 423 | ||||
Perceived value 424 | ||||
Summary 424 | ||||
Review questions 426 | ||||
Problems 426 | ||||
Notes 428 | ||||
430 | ||||
11.1 | Introduction 431 | |||
The nature and significance of capital budgeting 431 | ||||
Types of capital expenditure 432 | ||||
A simple model of the capital budgeting process 434 | ||||
11.2 | Cash flow analysis 434 | |||
Identification of cash flows 435 | ||||
Measurement of cash flows 435 | ||||
Example of a solved problem 435 | ||||
Case study 11.1: Investing in a corporate fitness programme 439 | ||||
11.3 | Risk analysis 439 | |||
Nature of risk in capital budgeting 439 | ||||
Measurement of risk 440 | ||||
11.4 | Cost of capital 445 | |||
Nature and components 445 | ||||
Cost of debt 446 | ||||
Cost of equity 447 | ||||
Weighted average cost of capital 449 | ||||
11.5 | Evaluation criteria 450 | |||
Net present value 450 | ||||
Internal rate of return 451 | ||||
Comparison of net present value and internal rate of return 452 | ||||
Other criteria 452 | ||||
Decision-making under risk 454 | ||||
Example of a solved problem 455 | ||||
Decision-making under uncertainty 458 | ||||
11.6 | The optimal capital budget 459 | |||
The investment opportunity (IO) schedule 460 | ||||
The marginal cost of capital (MCC) schedule 460 | ||||
Equilibrium of IO and MCC 462 | ||||
11.7 | A problem-solving approach 462 | |||
Case study 11.2: Under-investment in transportation infrastructure 462 | ||||
Case study 11.3: Over-investment in fibre optics 463 | ||||
Summary 465 | ||||
Review questions 466 | ||||
Problems 466 | ||||
Notes 468 | ||||
469 | ||||
12.1 | Introduction 471 | |||
Importance of government policy 471 | ||||
Objectives of government policy 471 | ||||
12.2 | Market failure 473 | |||
Definition and types 473 | ||||
Monopolies 474 | ||||
Externalities 475 | ||||
Public goods 475 | ||||
Imperfect information 476 | ||||
Transaction costs 476 | ||||
12.3 | Monopoly and Competition Policy 477 | |||
Basis of government policy 477 | ||||
The structure–conduct–performance (SCP) model 479 | ||||
Detection of monopoly 480 | ||||
Public ownership 481 | ||||
Privatization and regulation 486 | ||||
Promoting competition 490 | ||||
Restrictive practices 493 | ||||
Case study 12.1: Electricity 499 | ||||
Case study 12.2: Postal services 503 | ||||
12.4 | Externalities 507 | |||
Optimality with externalities 508 | ||||
Implications for government policy 509 | ||||
Implications for management 511 | ||||
Case study 12.3: Fuel taxes and optimality 512 | ||||
12.5 | Imperfect information 513 | |||
Incomplete information 514 | ||||
Asymmetric information 514 | ||||
Implications for government policy 516 | ||||
Implications for management 518 | ||||
Summary 518 | ||||
Review questions 520 | ||||
Notes 520 | ||||
522 |
Solving Managerial Problems Systematically
- Industrial Engineering & Business Information Systems
Research output : Book/Report › Book › Professional
Original language | English |
---|---|
Publisher | |
Number of pages | 135 |
ISBN (Print) | 9789001887957 |
Publication status | Published - 2017 |
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- http://ho.noordhoff.nl/boek/solving-managerial-problems-systematically
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T1 - Solving Managerial Problems Systematically
AU - Heerkens, Hans
AU - van Winden, Arnold
N1 - Translated into English by Jan-Willem Tjooitink
N2 - Solving Managerial Problems Systematically describes the Seven Steps of the Managerial Problem-Solving Method. With this It helps trouble-shooters arrive at solutions by ticking the boxes on a methodological checklist, and teaches them to differentiate between knowledge and action problems. The Language of Variables ensures that researchers remain concrete, helping them to consciously weigh up alternatives and obtain answers to questions they had not yet thought to ask. The MPSM encourages its users to take advantage of their intuition. Solving Managerial Problems Systematically is meant for higher education where students deal with problems in individual courses, and graduate projects.
AB - Solving Managerial Problems Systematically describes the Seven Steps of the Managerial Problem-Solving Method. With this It helps trouble-shooters arrive at solutions by ticking the boxes on a methodological checklist, and teaches them to differentiate between knowledge and action problems. The Language of Variables ensures that researchers remain concrete, helping them to consciously weigh up alternatives and obtain answers to questions they had not yet thought to ask. The MPSM encourages its users to take advantage of their intuition. Solving Managerial Problems Systematically is meant for higher education where students deal with problems in individual courses, and graduate projects.
UR - http://ho.noordhoff.nl/boek/solving-managerial-problems-systematically
SN - 9789001887957
BT - Solving Managerial Problems Systematically
PB - Noordhoff Uitgevers
1.3 The Nature of Management
- What is expected of a manager?
If organizations are to be successful in meeting these challenges, management must lead the way. With effective management, contemporary companies can accomplish a great deal toward becoming more competitive in the global environment. On the other hand, ineffective management dooms the organization to mediocrity and sometimes outright failure. Because of this, we turn now to a look at the nature of management. However, we want to point out that even though our focus is on managers, what we discuss is also relevant to the actions of nonmanagers. On the basis of this examination, we should be ready to begin our analysis of what managers can learn from the behavioral sciences to improve their effectiveness in a competitive environment.
What Is Management?
Many years ago, Mary Parker Follett defined management as “the art of getting things done through people.” A manager coordinates and oversees the work of others to accomplish ends they could not attain alone. Today this definition has been broadened. Management is generally defined as the process of planning, organizing, directing, and controlling the activities of employees in combination with other resources to accomplish organizational objectives. In a broad sense, then, the task of management is to facilitate the organization’s effectiveness and long-term goal attainment by coordinating and efficiently utilizing available resources. Based on this definition, it is clear that the topics of effectively managing individuals, groups, or organizational systems is relevant to anyone who must work with others to accomplish organizational objectives.
Management exists in virtually all goal-seeking organizations, whether they are public or private, large or small, profit-making or not-for-profit, socialist or capitalist. For many, the mark of an excellent company or organization is the quality of its managers.
![](http://writinghelp.online/777/templates/cheerup/res/banner1.gif)
Managerial Responsibilities
An important question often raised about managers is: What responsibilities do managers have in organizations? According to our definition, managers are involved in planning, organizing, directing, and controlling. Managers have described their responsibilities that can be aggregated into nine major types of activities. These include:
- Long-range planning . Managers occupying executive positions are frequently involved in strategic planning and development.
- Controlling . Managers evaluate and take corrective action concerning the allocation and use of human, financial, and material resources.
- Environmental scanning . Managers must continually watch for changes in the business environment and monitor business indicators such as returns on equity or investment, economic indicators, business cycles, and so forth.
- Supervision . Managers continually oversee the work of their subordinates.
- Coordinating . Managers often must coordinate the work of others both inside the work unit and out.
- Customer relations and marketing . Certain managers are involved in direct contact with customers and potential customers.
- Community relations . Contact must be maintained and nurtured with representatives from various constituencies outside the company, including state and federal agencies, local civic groups, and suppliers.
- Internal consulting. Some managers make use of their technical expertise to solve internal problems, acting as inside consultants for organizational change and development.
- Monitoring products and services . Managers get involved in planning, scheduling, and monitoring the design, development, production, and delivery of the organization’s products and services.
As we shall see, not every manager engages in all of these activities. Rather, different managers serve different roles and carry different responsibilities, depending upon where they are in the organizational hierarchy. We will begin by looking at several of the variations in managerial work.
Variations in Managerial Work
Although each manager may have a diverse set of responsibilities, including those mentioned above, the amount of time spent on each activity and the importance of that activity will vary considerably. The two most salient perceptions of a manager are (1) the manager’s level in the organizational hierarchy and (2) the type of department or function for which they are responsible. Let us briefly consider each of these.
Management by Level. We can distinguish three general levels of management: executives, middle management , and first-line management (see Exhibit 1.6 ). Executive managers are at the top of the hierarchy and are responsible for the entire organization, especially its strategic direction. Middle managers, who are at the middle of the hierarchy, are responsible for major departments and may supervise other lower-level managers. Finally, first-line managers supervise rank-and-file employees and carry out day-to-day activities within departments.
Exhibit 1.7 shows differences in managerial activities by hierarchical level. Senior executives will devote more of their time to conceptual issues, while first-line managers will concentrate their efforts on technical issues. For example, top managers rate high on such activities as long-range planning , monitoring business indicators, coordinating, and internal consulting. Lower-level managers, by contrast, rate high on supervising because their responsibility is to accomplish tasks through rank-and-file employees. Middle managers rate near the middle for all activities. We can distinguish three types of managerial skills: 8
- Technical skills . Managers must have the ability to use the tools, procedures, and techniques of their special areas. An accountant must have expertise in accounting principles, whereas a production manager must know operations management. These skills are the mechanics of the job.
- Human relations skills . Human relations skills involve the ability to work with people and understand employee motivation and group processes. These skills allow the manager to become involved with and lead his or her group.
- Conceptual skills . These skills represent a manager’s ability to organize and analyze information in order to improve organizational performance. They include the ability to see the organization as a whole and to understand how various parts fit together to work as an integrated unit. These skills are required to coordinate the departments and divisions successfully so that the entire organization can pull together.
As shown in Exhibit 1.7 , different levels of these skills are required at different stages of the managerial hierarchy. That is, success in executive positions requires far more conceptual skill and less use of technical skills in most (but not all) situations, whereas first-line managers generally require more technical skills and fewer conceptual skills. Note, however, that human or people skills remain important for success at all three levels in the hierarchy.
Management by Department or Function. In addition to level in the hierarchy, managerial responsibilities also differ with respect to the type of department or function. There are differences found for quality assurance, manufacturing, marketing, accounting and finance, and human resource management departments. For instance, manufacturing department managers will concentrate their efforts on products and services, controlling, and supervising. Marketing managers, in comparison, focus less on planning, coordinating, and consulting but more on customer relations and external contact. Managers in both accounting and human resource management departments rate high on long-range planning, but will spend less time on the organization’s products and service offerings. Managers in accounting and finance are also concerned with controlling and with monitoring performance indicators, while human resource managers provide consulting expertise, coordination, and external contacts. The emphasis on and intensity of managerial activities varies considerably by the department the manager is assigned to.
At a personal level, knowing that the mix of conceptual, human, and technical skills changes over time and that different functional areas require different levels of specific management activities can serve at least two important functions. First, if you choose to become a manager, knowing that the mix of skills changes over time can help you avoid a common complaint that often young employees want to think and act like a CEO before they have mastered being a first-line supervisor. Second, knowing the different mix of management activities by functional area can facilitate your selection of an area or areas that best match your skills and interests.
In many firms, managers are rotated through departments as they move up in the hierarchy. In this way they obtain a well-rounded perspective on the responsibilities of the various departments. In their day-to-day tasks they must emphasize the right activities for their departments and their managerial levels. Knowing what types of activity to emphasize is the core of the manager’s job. In any event, we shall return to this issue when we address the nature of individual differences in the next chapter.
The Twenty-First Century Manager
We discussed above many of the changes and challenges facing organizations in the twenty-first century. Because of changes such as these, the managers and executives of tomorrow will have to change their approaches to their jobs if they are to succeed in meeting the new challenges. In fact, their profiles may even look somewhat different than they often do today. Consider the five skills that Fast Company predicts that successful future managers, compared to the senior manager in the year 2000, will need. The five skills are: the ability to think of new solutions, being comfortable with chaos, an understanding of technology, high emotional intelligence, and the ability to work with people and technology together.
For the past several decades, executive profiles have typically looked like this: The person started out in finance with an undergraduate degree in accounting, then methodically worked their way up through the company from the controller’s office in a division, to running that division, to the top job. The military background shows. They are used to giving orders—and to having them obeyed. As head of the philanthropic efforts, they are important in the community. However, the first time the individual traveled overseas on business was as chief executive. Computers, which became ubiquitous, make them nervous. 9
Now compare this with predictions about what a twenty-first-century executive will look like:
Their undergraduate degree might be in French literature, but they also have a joint MBA/engineering degree. The individual started in research and was quickly picked out as a potential CEO. They are able to think creatively and thrives in a chaotic environment. They zigzagged from research to marketing to finance, are comfortable with technology and people, and have a high degree of emotional intelligence. The executive proved valuable in Brazil by turning around a failing joint venture. This person speaks multiple languages and is on a first-name basis with commerce ministers in half a dozen countries.
Clearly, the future holds considerable excitement and promise for future managers and executives who are properly prepared to meet the challenges. How do we prepare them? One study suggested that the manager of the future must be able to fill at least the following four roles: 10
Global strategist. Executives of the future must understand world markets and think internationally. They must have a capacity to identify unique business opportunities and then move quickly to exploit them.
Master of technology. Executives and managers of the future must be able to get the most out of emerging technologies, whether these technologies are in manufacturing, communications, marketing, or other areas.
Leadership that embraces vulnerability. The successful executive of the future will understand how to cut through red tape to get a job done, how to build bridges with key people from highly divergent backgrounds and points of view, and how to make coalitions and joint ventures work.
Follow-from-the-front motivator. Finally, the executive of tomorrow must understand group dynamics and how to counsel, coach, and command work teams and individuals so they perform at their best. Future organizations will place greater emphasis on teams and coordinated efforts, requiring managers to understand participative management techniques.
Great communicator. To this list of four, we would add that managers of the future must be great communicators. They must be able to communicate effectively with an increasingly diverse set of employees as well as customers, suppliers, and community and government leaders.
Whether these predictions are completely accurate is difficult to know. Suffice it to say that most futurists agree that the organizational world of the twenty-first century will likely resemble, to some extent, the portrait described here. The task for future managers, then, is to attempt to develop these requisite skills to the extent possible so they will be ready for the challenges of the next decade.
Concept Check
- Define management.
- How does the nature of management change according to one’s level and function in the organization?
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Managerial Problem Definition: A Descriptive Study of Problem Definers
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Description
This research examines problem definition as the first step in a sequential problem solving process. Seventy-seven managers in four diverse organizations were studied to determine common characteristics of problem definers. Among the variables considered as differentiating problem definers from non-problem definers were cognitive style, personal need characteristics, preference for ideation, experience, level of management, and type and level of education. Six hypotheses were tested using the following instruments: the Problem Solving Inventory, the Myers-Briggs Type Indicator Schedule, the Preference for Ideation Scale, the Edwards Personal Preference Schedule, a Problem Definition Exercise, and a Personal Data Questionnaire. Among the managers studied, … continued below
Physical Description
ii, 136 leaves : ill.
Creation Information
Phillips Danielson, Waltraud August 1985.
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People and organizations associated with either the creation of this dissertation or its content.
- Phillips Danielson, Waltraud
- Powell, James Don Major Professor
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- Starling, Jack Minor Professor
- Glass, James J. Minor Professor
- North Texas State University Publisher Info: www.unt.edu Place of Publication: Denton, Texas
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Degree Information
- Department: College of Business
- Discipline: Organization Theory and Policy Analysis
- Level: Doctoral
- Name: Doctor of Philosophy
- PublicationType: Doctoral Dissertation
- Grantor: North Texas State University
This research examines problem definition as the first step in a sequential problem solving process. Seventy-seven managers in four diverse organizations were studied to determine common characteristics of problem definers. Among the variables considered as differentiating problem definers from non-problem definers were cognitive style, personal need characteristics, preference for ideation, experience, level of management, and type and level of education. Six hypotheses were tested using the following instruments: the Problem Solving Inventory, the Myers-Briggs Type Indicator Schedule, the Preference for Ideation Scale, the Edwards Personal Preference Schedule, a Problem Definition Exercise, and a Personal Data Questionnaire. Among the managers studied, only twelve were found to be problem definers. Such small numbers severely limit the ability to generalize about problem definers. However, it is possible that problem definers are scarce in organizations. In terms of cognitive style, problem definers were primarily thinking types who preferred evaluation to ideation in dealing with problems, making judgmental decisions on the basis of collected facts. Problem definers were not predominant at lower levels of the organization. One-third of the problem definers held upper level management positions while another one-fourth were responsible for specialized activities within their organizations, overseeing special projects and individuals much like upper level managers. Sixty-eight of the problem definers had non-business educations with none having more than a bachelors degree. As knowledge and judgment on which to base evaluation expands, managers may become less adept at defining problems and more adept at selecting and implementing alternatives. Several tentative hypotheses can be tested in future research including: 1) determining whether problem definers are scarce in organizations, 2) determining whether problem definers are more prevalent in some types of organizations than others, 3) verifying unique cognitive and personal need characteristics, 4) determining whether non-managers rather than managers have problem defining skills.
- problem definers
- sequential problem solving process
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- Problem solving
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Phillips Danielson, Waltraud. Managerial Problem Definition: A Descriptive Study of Problem Definers , dissertation , August 1985; Denton, Texas . ( https://digital.library.unt.edu/ark:/67531/metadc331384/ : accessed August 17, 2024 ), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu ; .
- Encyclopedia of Management
- Problem Solving
PROBLEM SOLVING
![what are the nature of managerial problem solving Problem Solving 315](https://www.referenceforbusiness.com/photos/problem-solving-315.jpg)
A managerial problem can be described as the gap between a given current state of affairs and a future desired state. Problem solving may then be thought of as the process of analyzing the situation and developing a solution to bridge the gap. While it is widely recognized that different diagnostic techniques are appropriate in different situations, problem solving as a formal analytical framework applies to all but the simplest managerial problems. The framework is analogous to the scientific method used in chemistry, astronomy, and the other physical sciences. In both cases, the purpose underlying the analytic process is to minimize the influence of the investigator's personal biases, maximize the likelihood of an accurate result, and facilitate communication among affected parties.
Problem solving was popularized by W. Edwards Deming and the expansion of the total quality management movement in the 1980s. While Deming described what he called the Shewhart cycle, the technique is more commonly known as the Deming Wheel or simply as the PDCA cycle. Regardless of the name, a problem solver is urged to follow a step-by-step approach to problem solving-plan, do, check, act (hence the PDCA acronym).
In the planning stage, a manager develops a working hypothesis about why a given problem exists and then develops a proposed solution to the problem. The second step is to implement, or do, the proposed remedy. Next, the manager studies or checks the result of the action taken. The focus of this review is to determine whether the proposed solution achieved the desired result-was the problem solved? The fourth step then depends upon the interpretation of the check on results. If the problem was solved, the manager acts to institutionalize the proposed solution. This might mean establishing controls or changing policy manuals to ensure that the new way of doing business continues. However, if the check indicates that the problem was not solved or was only partially corrected, the manager acts by initiating a new cycle. Indeed, the technique is represented as a cycle based on the belief that many problems are never fully solved. For example, suppose that the problem in a given manufacturing facility is determined to be that labor productivity is too low. A change in processing methods may be found to successfully increase labor productivity. However, this does not preclude additional increases in labor productivity. Therefore, the PDCA cycle suggests that managers should pursue a course of continuous improvement activity.
The problem-solving framework can be used in a wide variety of business situations, including both large-scale management-change initiatives and routine improvement or corrective activity. Indeed, management consultants may be thought of as professional problem solvers. By relying on the proven problem-solving framework, external consultants are often able to overcome their lack of specific industry experience or knowledge of an organization's internal dynamics to provide meaningful analysis and suggestions for improvement. To more fully explore the issues presented by problem solving, the four-step PDCA cycle is expanded to a nine-step framework in the next section.
Perhaps the only generalizable caveat regarding problem solving is to guard against overuse of the framework. For example, Florida Power & Light became well known for their problem-solving ability in the late 1980s. One of their most successful initiatives was to institute an aggressive tree-trimming program to anticipate and prevent power failure due to downed limbs falling on electrical lines during storms. They were so successful that they integrated the problem-solving framework into their day-to-day managerial decision making and organizational culture. While this resulted in well reasoned decisions, it also meant that implementing even simple changes like moving a filing cabinet closer to the people using it required an overly bureaucratic approval process. This phenomenon is commonly referred to as paralysis of analysis. Therefore, managers should remain aware of the costs in both time and resources associated with the problem-solving framework. Accordingly, the nine-step framework described below is offered as a suggested guide to problem solving. Managers should feel free to simplify the framework as appropriate given their particular situation.
THE PROBLEM-SOLVING FRAMEWORK
Problem identification..
Although business problems in the form of a broken piece of machinery or an irate customer are readily apparent, many problems present themselves in a more subtle fashion. For example, if a firm's overall sales are increasing, but its percentage of market share is declining, there is no attention-grabbing incident to indicate that a problem exists. However, the problem-solving framework is still helpful in analyzing the current state of affairs and developing a management intervention to guide the firm toward the future desired state. Therefore, a solid approach to problem solving begins with a solid approach to problem identification. Whatever techniques are used, a firm's approach to problem identification should address three common identification shortfalls. First and most obviously, the firm wants to avoid being blindsided. Many problems develop over time; however, unless the firm is paying attention, warning signals may go unheeded until it is too late to effectively respond. A second common error of problem identification is not appropriating properly. This means that although a firm recognizes that an issue exists, they do not recognize the significance of the problem and fail to dedicate sufficient resources to its solution. It can be argued that not prioritizing properly has kept many traditional retail firms from responding effectively to emerging internet-based competitors. Finally, a third common error in problem identification is overreaction-the Chicken Little syndrome. Just as every falling acorn does not indicate that the sky is falling, neither does every customer complaint indicates that a crisis exists. Therefore, a firm's problem identification methods should strive to present an accurate assessment of the problems and opportunities facing the firm.
While no specific problem-identification technique will be appropriate for every situation, there are several techniques that are widely applicable. Two of the most useful techniques are statistical process control (SPC) and benchmarking. SPC is commonly used in the repetitive manufacturing industries, but can also prove useful in any stable production or service-delivery setting. A well formulated SPC program serves to inform managers when their operational processes are performing as expected and when something unexpected is introducing variation in process outputs. A simplified version of SPC is to examine performance outliers-those instances when performance was unusually poor or unusually good. It is believed that determining what went wrong, or conversely what went right, may inspire process or product modifications. Competitive benchmarking allows managers to keep tabs on their competition and thereby gauge their customers' evolving expectations. For instance, benchmarking might involve reverse engineering-disassembling a competitor's product-to study its design features and estimate the competitor's manufacturing costs. Texas Nameplate Company, Inc., a 1998 Malcolm Baldrige National Quality Award winner, uses competitive benchmarking by periodically ordering products from their competitors to compare their delivery-time performance.
Additional listening and problem identification techniques include the time-tested management-by-walking-around, revamped with a Japanese influence as going to gemba. The technique suggests that managers go to where the action is-to the production floor, point of delivery, or even to the customer's facilities to directly observe how things are done and how the product is used. Other methods include active solicitation of customer complaints and feedback. Bennigan's Restaurants offer a five-dollar credit toward future purchases to randomly selected customers who respond to telephone surveys on their satisfaction with their most recent restaurant visit. Granite Rock Company, a 1992 Baldrige Award winner, goes even farther by allowing customers to choose not to pay for any item that fails to meet their expectations. All that Granite Rock asks in return is an explanation of why the product was unsatisfactory.
PROBLEM VERIFICATION.
The amount of resources that should be dedicated to verification will vary greatly depending upon how the problem itself is manifested. If the problem is straightforward and well-defined, only a cursory level of verification may be appropriate. However, many business problems are complex and ill defined. These situations may be similar to the case of a physician who is confronted with a patient that has self-diagnosed his medical condition. While considering the patient's claim, the doctor will conduct her own analysis to verify the diagnosis. Similarly, the need for verification is especially important when a manager is asked to step in and solve a problem that has been identified by someone else. The introduction of the manager's fresh perspective and the possibility of a hidden agenda on the part of the individual who initially identified the issue under consideration suggests that a "trust, but verify" approach may be prudent. Otherwise, the manager may eventually discover she has expended a great deal of time and effort pursuing a solution to the wrong problem.
In the case of particularly ambiguous problems, McKinsey & Company, a management-consulting group, uses a technique they call Forces at Work. In this analysis, McKinsey's consultants review the external pressures on the client firm arising from suppliers, customers, competitors, regulators, technology shifts, and substitute products. They then attempt to document the direction and magnitude of any changes in the various pressures on the firm. In addition, they review any internal changes, such as shifts in labor relations or changes in production technology. Finally, they look at how the various factors are impacting the way the firm designs, manufactures, distributes, sells, and services its products. Essentially, McKinsey attempts to create comprehensive before-and-after snapshots of their client's business environment. Focusing on the differences between the two, they hope to identify and clarify the nature of the challenges facing the firm.
PROBLEM DEFINITION.
The next step in problem solving is to formally define the problem to be addressed. This is a negotiation between the individuals tasked with solving the problem and the individuals who over-see their work. Essentially, the parties need to come to an agreement on what a solution to the problem will look like. Are the overseers anticipating an implementation plan, a fully operational production line, a recommendation for capital investment, or a new product design? What metrics are considered important-cycle time, material costs, market share, scrap rates, or warranty costs? Complex problems may be broken down into mutually exclusive and collectively exhaustive components, allowing each piece to be addressed separately. The negotiation should recognize that the scope of the problem that is defined will drive the resource requirements of the problem solvers. The more focused the problem definition, the fewer resources necessary to generate a solution. Finally, the time frame for problem analysis should also be established. Many business problems require an expedited or emergency response. This may mean that the problem solvers need to generate a temporary or interim solution to the problem before they can fully explore the underlying causes of the problem. Ensuring that the overseers recognize the limitations inherent in an interim solution serves to preserve the credibility of the problem solvers.
ROOT-CAUSE ANALYSIS.
Now that the problem has been formally defined, the next step is for the problem solvers to attempt to identify the causes of the problem. The ultimate goal is to uncover the root cause or causes of the problem. The root cause is defined as that condition or event that, if corrected or eliminated, would prevent the problem from occurring. However, the problem solver should focus on potential root causes they are within the realm of potential control. For example, finding that a particular weight of motor oil is insufficient to protect an engine from overheating readily leads to an actionable plan for improvement. Finding that the root cause of a problem is gravity does not.
A common technique for generating potential root causes is the cause-and-effect diagram (also known as the fishbone or Ishikawa diagram). Using the diagram as a brainstorming tool, problem solvers traditionally review how the characteristics or operation of raw materials, labor inputs, equipment, physical environment, and management policies might cause the identified problem. Each branch of the diagram then becomes a statement of a causal hypothesis. For example, one branch of the diagram might suggest that low salaries are leading to high employee turnover, which in turn results in inexperienced operators running the machinery, which leads to a high scrap rate and ultimately higher material costs. This analysis suggests that to address the problem of high material costs, the firm may have to address the root cause of insufficient salaries.
Collection and examination of data may also lead the problem solver toward causal hypotheses. Check sheets, scatter plots, Pareto diagrams, data stratification, and a number of other graphical and statistical tools can aid problem solvers as they look for relationships between the problems identified and various input variables. Patterns in the data, changes in a variable over time, or comparisons to similar systems may all be useful in developing working theories about why something is happening. The problem solver should also consider the possibility of multiple causes or interaction effects. Perhaps the problem manifests only when a specific event occurs and certain conditions are met-the temperature is above 85 degrees or the ambient humidity is abnormally low.
Once the problem solver has identified the likely root causes of the problem, an examination of the available evidence should be used to confirm or disconfirm which potential causes actually are present and impacting the performance under consideration. This might entail developing an experiment where the candidate cause is controlled to determine whether its manipulation influences the presence of the problem. At this stage of the analysis, the problem solver should remain open to disconfirming evidence. Many elegant theories fail to achieve the necessary confirmation when put to the test. At this stage of the analysis it is also common for the problem solver to discover simple, easily implemented actions that will solve all or part of the problem. If this occurs, then clearly the problem solver should grasp the opportunity to "pick the low hanging fruit." Even if only a small component of the problem is solved, these interim wins serve to build momentum and add credibility to the problem-solving process.
ALTERNATIVE GENERATION.
Once the root causes of the problem have been identified, the problem solver can concentrate on developing approaches to prevent, eliminate, or control them. This is a creative process. The problem solver should feel free to challenge assumptions about how business was conducted in the past. At times, an effective approach is to generalize the relationship between the cause and the problem. Then the problem solver can look for similar relationships between other cause and effects that might provide insight on how to address the issues at hand. In general, it is useful to attempt to generate multiple candidate solutions. By keeping the creative process going, even after a viable solution is proposed, the problem solver retains the possibility of identifying a more effective or less expensive solution to the problem.
EVALUATION OF ALTERNATIVES.
Assuming that the problem was well defined, evaluation of the effectiveness of alternative solutions should be relatively straightforward. The issue is simply to what extent each alternative alleviates the problem. Using the metrics previously identified as important for judging success, the various alternatives can generally be directly compared. However, in addition to simply measuring the end result, the problem solvers may also want to consider the resources necessary to implement each solution. Organizations are made up of real people, with real strengths and weaknesses. A given solution may require competencies or access to finite resources that simply do not exist in the organization. In addition, there may be political considerations within the organization that influence the desirability of one alternative over another. Therefore, the problem solver may want to consider both the tangible and intangible benefits and costs of each alternative.
IMPLEMENTATION.
A very common problem-solving failure is for firms to stop once the plan of action is developed. Regardless of how good the plan is, it is useless unless it is implemented. Therefore, once a specific course of action has been approved, it should continue to receive the necessary attention and support to achieve success. The work should be broken down into tasks that can be assigned and managed. Specific mile-stones with target dates for completion should be established. Traditional project management techniques, such as the critical path method (CPM) or the program evaluation and review technique (PERT) are very useful to oversee implementation efforts.
POST-IMPLEMENTATION REVIEW.
Another common failure is for firms to simply move on after a solution has been implemented. At a minimum, a post-implementation evaluation of whether or not the problem has been solved should be conducted. If appropriate and using the metrics that were established earlier, this process should again be relatively straightforward-were the expected results achieved? The review can also determine whether additional improvement activities are justified. As the PDCA cycle suggests, some problems are never solved, they are only diminished. If the issue at hand is of that nature, then initiating a new cycle of problem-solving activity may be appropriate.
A secondary consideration for the post-implementation review is a debriefing of the problem solvers themselves. By its very nature, problem solving often presents managers with novel situations. As a consequence, the problem-solving environment is generally rich in learning opportunities. To the extent that such learning can be captured and shared throughout the organization, the management capital of the firm can be enhanced. In addition, a debriefing may also provide valuable insights into the firm's problem-solving process itself. Given the firm's unique competitive environment, knowing what worked and what did not may help focus future problem-solving initiatives.
INSTITUTIONALIZATION AND CONTROL.
The final step in problem solving is to institutionalize the results of the initiative. It is natural for any system to degrade over time. Therefore, any changes made as a result of the problem-solving effort should be locked in before they are lost. This might entail amending policy manuals, establishing new control metrics, or even rewriting job descriptions. In addition, the firm should also consider whether the problem addressed in the initiative at hand is an isolated incident or whether the solution can be leveraged throughout the organization. Frequently, similar problems are present in other departments or other geographic locations. If this is the case, institutionalization might involve transferring the newly developed practices to these new settings.
SEE ALSO: Project Management
Daniel R. Heiser
Revised by Badie N. Farah
FURTHER READING:
Deming, W. Edwards. Out of the Crisis. Cambridge: Massachusetts Institute of Technology, Center for Advanced Engineering Study, 1992.
Ketola, Jeanne and Kathy Roberts. Correct! Prevent! Improve!: Driving Improvement Through Problem Solving and Corrective and Preventive Action. Milwaukee: ASQ Quality Press, 2003.
National Institute of Standards and Technology. "Award Recipients." Malcolm Baldrige National Quality Award Program, 1999. Available from http://www.quality.nist.gov.
Rasiel, Ethan M. The McKinsey Mind: Using the Techniques of the World's Top Strategic Consultants to Help You and Your Business. New York: McGraw-Hill, 2001.
——. The McKinsey Way—Understanding and Implementing the Problem-Solving Tools and Management Techniques of the World's Top Strategic Consulting Firm. New York: McGraw-Hill, 1999.
Smith, Gerald F. Quality Problem Solving. Milwaukee: ASQ Quality Press, 1998.
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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.
![what are the nature of managerial problem solving Want better strategies? Become a bulletproof problem solver](https://www.mckinsey.com/~/media/mckinsey/business%20functions/strategy%20and%20corporate%20finance/our%20insights/want%20better%20strategies%20become%20a%20bulletproof%20problem%20solver/want-better-strategies_1536x1536.jpg?cq=50&mh=145&car=16:9&cpy=Center)
Want better strategies? Become a bulletproof problem solver
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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- 15 August 2024
How I’m looking to medicine’s past to heal hurt and support peace in the Middle East
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Navid Madani is the founding director of the Science Health Education (SHE) Center at the Dana-Farber Cancer Institute of Harvard Medical School in Boston, Massachusetts.
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This month, I am in Amman, Jordan, teaching on the annual Palestine Social Medicine Course. This course, now in its second year, aims to educate educators, public-health workers, physicians and medical students about the limitations of the biological model of medicine in settings of fragmentation, violence and dispossession. It examines the effects of conflicts and violence on public health and human rights, emphasizing the need for resilience and commitment to these values in the face of adversity.
The course is organized by the Palestine Program for Health and Human Rights, a partnership between the François-Xavier Bagnoud Center for Health and Human Rights at Harvard University in Boston, Massachusetts, and the Institute of Community and Public Health at Birzeit University in the West Bank. Last year, it was taught in Birzeit. It was moved to Amman this year because of escalating violence and restrictions imposed by the Israeli military and settlers in the West Bank.
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I’m a Palestinian scientist building a more inclusive future
Since violence escalated on 7 October 2023, many scientific and medical gatherings in the Middle East have been postponed or cancelled. Travel to the region is difficult, because many airlines have stopped flying there. Yet the organizers felt strongly that it was important to keep the course running, because the exchanges it enables are crucial. They provide students with access to cutting-edge knowledge and methods that help to prepare them to contribute to science and medicine — to the benefit of society.
The war in Gaza is harming thousands of people now, but will have ripple effects on all nations for decades, if not centuries, to come. Violence and war anywhere harm us all — not just in terms of people killed and places destroyed, but in the loss of capacity for exploring solutions to problems that plague humanity. People who are having to fight or run for their lives, or who spend their time finding shelter or trying to advocate for fundamental human rights and dignity, do not have time for wider problem-solving.
Scientists, physicians and health-care providers usually address the ills of the patient or population in front of us. Social medicine is occupied with a larger challenge: healing the hurts of a region or population with a long history of pain. This means identifying the social determinants of health that affect the population — including, for example, sexism, racism, economic inequality and historical, multigenerational traumas — and seeking to heal the people living under their shadow.
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The Taliban ‘took my life’ — scientists who fled takeover speak out
Recent history could easily make us throw up our hands in despair. In the Middle East, especially, peace seems so far away. Progress on so many fronts — social, scientific, diplomatic — seems to be retreating while exposure to horrifying trauma increases daily.
Yet the region has a rich history of medical and scientific advancements. Crucial contributions came from ancient civilizations such as the Persian Empire, Mesopotamia and Egypt, culminating in the Islamic Golden Age from the eighth to the thirteenth century. Philosopher-scientists such as Abū Bakr al-Rāzī (often known in the West as Razi or Rhazes), al-Zahrawi (Abulcasis) and Ibn Sina (Avicenna) shaped science and medicine in the Islamic world and Europe in ways that lasted for centuries.
Years of experience in the Middle East and North Africa have shown me that scientific training and other events held in the region, rather than in Europe or the United States, can provide a valuable historical perspective and cultural context while fostering global collaboration.
For example, hosting a scientific symposium in Tehran, despite geopolitical pressures against it — as I did in 2012 — exposed participants to contemporary Iranian advances in medical research, such as work in stem-cell research and medical nanotechnology, which have since gained international recognition.
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Tracking women’s mental health amid trauma in Yemen
By connecting international scholars with local practitioners, the Palestine Social Medicine Course highlights the specific health challenges faced by Palestinians, while creating a platform for cross-cultural dialogue and knowledge exchange.
Immersing ourselves in the settings where historical advances in science and medicine were made provides deeper insights into how societal values and needs have shaped scientific discoveries and medical practices. Studying pioneers such as Ibn Sina and al-Rāzī can inspire current and future practitioners to innovate and push the boundaries of their fields. And fostering global collaborations and building connections with scholars and institutions in the Middle East enriches the collective understanding and application of medical and scientific knowledge.
We scientists and medical professionals need to do what we can to change the sad trajectory of violence. Those of us who want peace, understanding and progress towards humanity’s well-being must dig in and push for that vision.
During what is sometimes called the Dark Ages in Europe, scientific and medical innovations from the Middle East and North Africa shone a guiding light to bring humanity a reasoned approach to health and problem-solving. Perhaps looking through the lens of history can inspire us to find new solutions to address contemporary challenges, in this region and worldwide.
Nature 632 , 709 (2024)
doi: https://doi.org/10.1038/d41586-024-02674-1
The views expressed are the author’s own and do not necessarily represent those of her institution.
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Abstract. Solving Managerial Problems Systematically describes the Seven Steps of the Managerial Problem-Solving Method. With this It helps trouble-shooters arrive at solutions by ticking the boxes on a methodological checklist, and teaches them to differentiate between knowledge and action problems. The Language of Variables ensures that ...
The emphasis on and intensity of managerial activities varies considerably by the department the manager is assigned to. At a personal level, knowing that the mix of conceptual, human, and technical skills changes over time and that different functional areas require different levels of specific management activities can serve at least two ...
This research examines problem definition as the first step in a sequential problem solving process. Seventy-seven managers in four diverse organizations were studied to determine common characteristics of problem definers. Among the variables considered as differentiating problem definers from non-problem definers were cognitive style, personal need characteristics, preference for ideation ...
A problem-solving decision-making style allows for management to create solutions to issues that exist within the workplace. This is a common style of decision-making, since a key role of management involves resolving workplace issues to improve workflow and create a positive environment for team members. You might make problem-solving ...
A managerial problem can be described as the gap between a given current state of affairs and a future desired state. Problem solving may then be thought of as the process of analyzing the situation and developing a solution to bridge the gap. While it is widely recognized that different diagnostic techniques are appropriate in different ...
Problem solving is identifying and solving problems by applying critical thinking, creativity, communication, and analytical skills. It's an essential skill for managers because it helps them make informed decisions that can impact their team's productivity and the company's bottom line. In this blog post, we'll cover the five essential ...
Nature of Managerial Economics. To know more about managerial economics, we must know about its various characteristics. Let us read about the nature of this concept in the following points: Art and Science: Managerial economics requires a lot of logical thinking and creative skills for decision making or problem-solving. It is also considered ...
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].
In this traumatized region, exploring a rich history of scientific and medical problem-solving provides the context to imagine a better future.