Management Tools

Introduction

This book is designed for everybody who wants to learn how to manage or to improve existing management skills. A manager is a person who decides what to do and, in part, how to do it. The underlying aim is normally to be as efficient as possible. In the language of most businesses, that means to be as profitable as possible. One may ask how efficiency is defined or what profitability exactly means and how it is measured. Applying a suitable definition and measurement procedure is one skill a manager needs (although this book does not cover it), but there are many more skills required. Examples are how to determine whether a business is developing in the right direction or who should do what. This book aims to teach these kinds of skills. They are taught here in the forms of methods and tools.

Management, in the sense addressed in this book, has been around ever since big companies came into existence. About 100 years ago, Frederick W. Taylor presented his principles of scientific management. His were among the first major theoretical thoughts about management. Many more thinkers have followed him right up to the present. Today, most managers have formal educations in business and management. The MBA is probably the best-known such degree. Most MBA degrees are offered by business schools. I intentionally use the word “school” here rather than “university” because, while I personally associate universities with teaching science, I do not regard management as science. Please note that this does not mean that a manager does not need to be smart. On the contrary, good management requires high intelligence in the same way as does science. But that does not imply that management is a science. The task of a scientist might be, for example, to understand how the universe formed. The corresponding task of a manager is to make the production of a universe most efficient. In this example, the task of the manager is far more difficult than is that of the scientist. But it is absolutely not science. Of course, humankind is not yet producing universes. The things humankind does produce are pretty simple by comparison, and the science underlying that production was typically well understood long ago. Otherwise, production would not be possible. Consider a vacuum cleaner as an example. The science behind it is trivial, and its basic engineering is only a bit more complicated. But to reduce the cost to produce a vacuum cleaner, now that is a challenge. Perhaps this is why academics in management especially feel compelled to emphasize over and over their scientific approach. Besides feeding their own vanity, this results in a business education that is overly theoretical. Although business schools are a step in the right direction, they still are often too academic in their approach. One way to overcome this problem is to learn by doing, and in general that is not a bad method. Experience is so important in management that most people who become CEOs are over the age of 50. By contrast, scientists becoming professors are often under the age of 40. While Nobel Prizes are awarded mostly to people in their retirement years, these are usually for discoveries made between the ages of 25 and 45. Obviously, to be a top performer in management requires more years than to achieve the same in science. In my opinion, there are three reasons for this (the first of which is clear from the remarks above):

n    Most relevant education takes place on the job.

n    Management is more difficult than science.

n    To be a leader as well as a manager requires a certain age.

As I have mentioned, learning by doing is good in any discipline. It entails some waste, however, if the wheel must be invented over and over again. To minimize this loss is one of the goals of this book. My second claim would probably be welcomed by business academics but dismissed by scientists. I have worked extensively in both of these worlds, and I can confirm it without reservation. Management is a far younger discipline than is science, and its basic rules are still undiscovered. The content of this book represents one small step toward identifying those rules.[1] Please note that while management is more difficult than science, this does not imply that managers are smarter than scientists. Another point as to why management is more difficult than science is closely related to the third point above. Management has to do with people, and people are far more complicated than are, for example, elementary particles. Although management is distinct from leading, the two skill sets are often intertwined. (For a thorough definition of management and leadership, please see 7.4.4.) Leading involves people and the relations and emotions between them. To understand such things is rarely possible before the age of 40.

What to expect

As stated several times already, this book explains the skills necessary to manage a business. The general goal of every business is to be profitable. The only variation is whether to be profitable in the short run or long term. (In principle this applies even for charities and nonprofit organizations.) A manager has only two ways to improve profitability. One is to lower costs and the other is to increase revenue. All other concerns such as high quality products, motivated employees, or investing in high technology are useful only if they are helpful in lowering cost or increasing revenue. From this, one might conclude that a manager has to know just two things (you guessed it): How to lower cost and to increase revenue. One could argue, therefore, that this book should have had two chapters only. One should be called “How to lower cost” and the other “How to increase revenue.” Books are available that deal with one or both topics. Typically, they are in the form of “100 ideas for…” They might be quite useful, and especially if a manager has to solve a specific problem in the short run. In my opinion, though, they are not suitable for long-term considerations and a thorough understanding. Therefore, I have taken a different approach here. I am explaining typical things a manager has to do in order to achieve his or her major goal. Please note that none of these should be done for their own sake. The reason for applying the methods and tools presented here is always to increase revenue or to lower cost, at least in the long run.

The arguably most essential task a manager has is to organize. In short, organizing means to decide “who should do what” and “who is reporting to whom.” Chapter “5 Organization” of this book deals with this problem. One may consider the organization of an entire company or just the organization of next week’s work. The logic behind it is always the same. Please understand that to change an organization never reduces costs directly. The change may lead to increased revenue because one can serve the market better, or cost savings created by other means may require a new organization. To organize is an almost daily job of a manager, and especially if it is defined as broadly as it is here. Therefore, chapter 5 – or more precisely 5.2.2 – is undoubtedly the most important one in this book. Nevertheless, just reading these 12 pages is most likely of very limited help. Almost everything written here prior to 5.2.2 is essential for understanding that section (and many other methods and tools presented here).

Chapter 2 is about business process modeling. In simple terms, it is a standard way to describe what is done in a business. Obviously, one must first write down what is done before one can think of organizing it. Besides its being indispensable for organization, process modeling is mandatory for controlling (4), balanced scorecard approaches (3), reengineering (5.5), activity based costing (6.3) and many more activities. I am aware of no manager who does not need to know about it, and a big chunk of all consultants’ revenues comes from modeling processes. Please note that it is by no means limited to IT problems, such as introducing a new ERP system. I deliberately stress here its importance outside the IT world. (For IT applications, some useful literature can be found. Otherwise, there is none other available.)

The third chapter deals with the buzzword “balanced scorecard” (BSC). In simple terms, this is about finding the right quantities to indicate how the business is getting along. There are thousands of publications on this topic. Here, I will focus on the basic ingredients, and I will stress typical problems and mistakes. One of the key findings is that balanced scorecard is the one and only method for determining performance indicators. Therefore, it is clear that the idea of BSC is much older than the publications of Robert S. Kaplan and David Norton on the subject. While they are not the inventors of BSC, Kaplan and Norton are the people who made BSC happen – and that is arguably a much bigger achievement. A second finding that is not so common but is nevertheless important of chapter 3 is that BSC is closely related to organization. To find proper performance measures may require a change of the organization.

In chapter 4 (controlling), I show how to use the performance indicators defined via BSC. As is the case with BSC, there are many books and publications on controlling. I will emphasize the basic steps and the typical but fundamental mistakes that occur. Again, it will become clear that controlling is very closely related to organization. In order to make a proper controlling possible one has to choose a certain organization. (Indeed, chapter 5 will make clear that enabling a proper controlling is the construction rule for a new organization.) A second rarely considered finding of chapter 4 is the fact that, for reasons that are fundamental, controlling is not always possible. The consequences of this should be clear. First, attempting to control under such circumstances is a complete waste. Second, management is scarcely possible in such a situation.

Chapter 5 deals with organization, as mentioned above. Some additional, related topics are discussed there. In 5.3 , I will explain how many people should be working in a single organizational unit. A fairly new approach of using a so-called feedback circle is discussed in 5.3.3. The number of people one person leads is commonly referred to as a span of control. In 5.4 , I will show that there is an optimal span of control (typically 8 to 10). Values below and above this optimum will lead to higher costs. In 5.5 , I will demonstrate that reengineering is a very proper tool and not just a fashionable buzzword from the 1990s. Process organization is sometimes considered a new organizational form. In 5.6, I will make clear that it is the (one and only reasonable) way to find an optimal organization. “Self-organization” is considered a situation where an organization changes (for the better) without any interference by the management. In addition to discussing its usefulness and difficulties, I will clearly affirm in 5.7 that it has nothing to do with such almost spooky things as violating one of the most fundamental laws of physics (increase of entropy).

In chapter 6 , I will shed light on some quantitative methods and tools that are often used. One quite general conclusion will be that, in calculating, one must always take into account a margin of error (6.1.2). By doing so, one will see that quite a few cost calculations are a complete waste of time because their margin of error is too high. There even are situations where it is quite impossible to decide whether a particular product leads to a profit or loss. So-called semi-quantitative methods are used to evaluate, for example, a strategy by assigning scores to certain features. In 6.2, I will show the typical mistakes that are made, and especially if the total score is built by multiplying the individual scores. 6.4 explains a neat tool to determine the (market-driven) target cost of a product and its components. 6.5 will lead to the frontier of research in management. Here, the chaos theory is applied to show that very small causes can result in enormous effects. Consequently, one can show that, for example, supply chain networks are sometimes fundamentally not manageable. The same can be true for complex projects. Therefore, a fundamental change in management approach is necessary.

In chapter 7 , additional tools and methods to manage an operation are scrutinized. The central task of planning is reviewed in 7.1. By applying a simple model, it is possible to calculate the margin of error of a plan or forecast. Long-term planning can easily lead to a margin of error of, say, 100%. That points to severe consequences for the usefulness of business plans. In the next tool discussed (benchmarking), one compares two businesses. The goal of 7.2 is to point out mistakes that are avoidable. In the third subchapter learning curves are discussed. Everything that is done repeatedly will lead to learning, and normally to higher efficiency. The exact form of such learning curves is derived in 7.3. The result is indispensable for any kind of controlling where learning is involved. This book ends with some hints on soft skills (7.4). This important topic can easily fill an entire book. The aim here is to encourage the reader to think about it thoroughly.

Table of content

Preface

Table of Contents

Figures

1      Introduction

2      Business process modeling

2.1       Choose a structure

2.2       Select a language

2.2.1        SADT

2.2.2        ARIS

2.3       Use of brown papers

3      Balanced scorecard

3.1       The general problem

3.2       An example of BSC

4      Controlling process

4.1       The four basic steps

4.2       Frequency of controlling

4.3       Problems and shortcomings

4.4       Examples

Case: Aluminum tube welding

Case: Management consulting

Case: R&D Controlling

5      Organization

5.1       Define roles and responsibilities

5.2       Defining an organization

5.2.1        Basic organizational forms

5.2.2        To engineer an organization

Case: University controlling

Case: Purchasing

5.2.3        Personal conflicts

5.3       How to staff an organization

5.3.1        The bottom up approach

5.3.2        The benchmark approach

5.3.3        The feedback circuit approach

5.4       Find an optimal span of control

5.4.1        Definitions and formulas

5.4.2        Getting the optimum

5.5       Using reengineering

5.5.1        Hammer’s approach

Case: Bills payable department

5.5.2        A non-business example

5.5.3        Applying reengineering

5.6       Buzzword process organization

5.7       Myths of self-organization

6      Quantitative tools

6.1       Dealing with numbers and errors

6.1.1        How to define measures

Case: Person’s weight

Case: Number of vendors

6.1.2        Taking into account the margin of error

Case: Calculation of automotive parts

6.2       Applying semi-quantitative methods

6.3       Preparing activity-based costing

6.3.1        Theory of ABC

6.3.2        A simplified version

Case: ABC at aluminum tube welding

6.3.3        Reasons not to choose ABC

6.4       Using target costing

6.4.1        The basic idea

6.4.2        An example

6.5       Commenting on chaos

6.5.1        Chaos in science

6.5.2        Chaos in the business world

Example: Warehouse locations

6.5.3        Dealing with chaos

Example: Chaotic project

6.5.4        Conserved quantities

7      Operations management

7.1       Plan and forecast the business

Example: Reasonable planning period

Example: Quality of planning

7.2       Using benchmarks

7.2.1        Definition of benchmarking

7.2.2        Mistakes to avoid

7.3       Learning curves

7.3.1        Theory of learning curves

7.3.2        Controlling with learning curves

7.4       Soft skills

7.4.1        Defining goals

7.4.2        How to give and receive feedback

7.4.3        Managing meetings

7.4.4        Leading and managing

8      Appendices

8.1   &nb