Growth Dynamics in New Markets: Improving Decision Making through Model-Based Management

By Martin F. G. Schaffernicht and Stefan N. Groesser

An innovative simulation-based approach for strategic decision making when launching new products

Growth Dynamics in New Markets contains a dynamic case study and simulations that reveal what it takes to successfully introduce a product into a new market. Written by experts in the field, the text and companion website include a compelling simulation game and a variety of simulation models. Using the simulation game and computer models, readers are challenged to design and put in place a strategy about product introduction and competitive behavior. The simulation models build on each other to help to arrive at a comprehensive understanding of product uptake as well as market development and competitive dynamics. The authors present different approaches for enhancing the models and offer guidance for applying them to real-world problems.

This groundbreaking text clearly shows how to develop maps of dynamic systems, formulate candidate policies and evaluate them based on the simulations. It also reveals how to use computer simulations to understand what decisions could and should be made, when to make them and how intensive they should be. The authors present an interactive approach that:

• Contains an innovative combination of a case study, simulation game and simulation models for developing the skills to introduce a product to the marketplace
• Offers targeted questions that help to enhance the understanding of the material presented
• Presents detailed answers and solutions to a number or real-world business challenges
• Features video tutorials that explain how the simulation experiments are implemented and interpreted
• Aids in the development an action-oriented, pragmatic understanding of the underlying forces in business

Designed for students of business administration, management, industrial engineering, informatics, engineering, and public policy, Growth Dynamics in New Markets offers an innovative approach that combines the practice of dynamic reasoning and the use of simulation to design and test possible policies. 

• Language: English
• Publisher: Wiley
• Release date: Apr 17, 2018
• ISBN: 9781119127413

Book preview

PREFACE

Invitation to explore

We are inviting you on a journey to explore the different elements of introducing a product into a new market. You will assume the role of a manager responsible for successful product introduction while a competitor strives to do the same. Your potential customers are free to choose either of the products. How should you make your decisions given that you have a direct competitor acting simultaneously? Which strategies can improve your decision making in such a dynamic situation?

Remember, not only managers have goals, make plans, decide, and execute. This is what individuals do irrespective of their profession. What follows are a few general remarks to set the stage.

Making plans requires the ability to know where you currently are, where you want to go, and how to get from here to there. Maps or diagrams are helpful tools. There are many well‐known examples of maps. For instance, explorers developed maps to navigate through a geographical area or topological space.

The map in Figure 0.1 dates back to the year 1630. It was created to help navigators cross the Atlantic Ocean (‘Mar del Norte’) to the Pacific Ocean via the Strait of Magellan. At this time, ships sailed from Europe to the New World, and since navigators always looked in the upward direction, it was useful for them to draw a map and position East at the top.

Image described by caption.

Figure 0.1 A navigation map of the Strait of Magellan (Princeton University Library, 2016)

‘To navigate’ stems from the two Latin words ‘nāvis’ (ship) and ‘āgis’ (drive); it literally means to steer or drive a ship. However, that what we want to steer is not always a ship, and not all the maps are geographical ones. Architects and planners design maps of buildings or bridges. Systems engineers map information systems with databases and computer programs. Both architectural and information systems maps are construction plans for artificial, man‐made objects. Organizational consultants map, revise, and design business processes and organizational structures, thereby planning how different organizational members interact to carry out their work. In these cases, the maps represent structures, i.e. elements that are essentially static.

However, business managers are often confronted with situations, with or without a map, that defy their ability to anticipate what will happen. Imagine you are a corporate strategist. You must develop a plan for long‐term success and, thereby, need to anticipate the potential actions of your suppliers, competitors, and customers who have also developed their own plans based on their own goals and expectations about your actions. Such structurally interdependent situations are ‘dynamic systems’. A dynamic system consists of several interrelated components with different actors. The components and actors react to one another and have different reasons for influencing and altering the system.

One example of a dynamic system is the strategic planning of football (soccer) matches. The map in Figure 0.2 illustrates the movements a soccer team can perform when the opposing team’s defence players attack a player. The teams have opposing goals and the actions of one team decrease the level of goal achievement of the other team. Further, each team plans and decides its moves considering the respective previous and expected moves of the opposing team. Therefore, the soccer‐planning map not only illustrates structural elements but also considers past or expected moves.

Schematic map for switching sides and keeping control of the ball in football depicting dashed arrows marking the path in the field.

Figure 0.2 A map for switching sides and keeping control of the ball in soccer

Managers are faced with even more dynamic situations: the ‘game’ they are in is not as well defined as football. Competitors, customers, and other actors are free to decide on their course of action. Let us assume there is a company: NewTel. It is about to introduce mobile phones – a durable consumer good typically used for 9–18 months – to a new market in the presence of one rival of approximately the same size. You are a top manager at NewTel and face the challenge of taking the necessary decisions to lead the product introduction to a success. Uncovering and developing a new market in parallel to your rival is the dynamic challenge at hand: both you and your competitor will strive to capture customers from the same population as quickly as possible. The customers, of course, are influenced by the actions of both companies in the market. The interdependency between you and your competitor in this limited market leads to a highly complex situation, where your decisions may easily generate undesired effects and dynamics.

Which factors should you include in your management map to successfully ‘navigate’ NewTel? How do you determine these factors? How will this map help you to make successful decisions? Since many of those factors will be changing, and at different speeds, you will need to know why and how quickly they are changing and how you can influence them through the decisions you take. What you need are tools for mapping and planning in dynamic systems. You need an approach to determine the relevant factors in messy situations, map their dynamic relationships and show immediate, as well as delayed, effects to determine their impact over time on the relevant outcome of interest. The simulation model‐based management approach will support you in this regard.

What will you learn?

You will learn how to develop maps of dynamic systems, how to formulate candidate decision policies, and how to evaluate them based on simulations. Moreover, you will learn to elaborate and use your own computer simulations to find out what decisions you could and should make (content of the decision), when you should make them (timing of the decision), and how intensive they should be (intensity of the decision). When reaching the end of the book, you will have an intuitive understanding and skills to master dynamic business challenges such as:

Self‐limiting growth: dynamics fuelled by word‐of‐mouth diffusion is self‐reinforcing and displays exponential growth until the shrinking population of potential customers limits growth. Overall customer growth follows an S‐shaped behaviour.

Obsolescence speeds re‐purchases: the product’s life cycle duration determines the relationship between current customers and new sales to potential customers.

Sell earlier, not more: advertising can increase purchases now by anticipating future purchases. It is recognized that a decrease in purchases will follow.

Sources of revenue: revenues depend on new purchases from customers who pay the sales price and current customers who pay the subscription rate. With a limited population, higher revenues from sales cannot be sustained without losing revenues from subscriptions, and vice versa. Your business model must state how you balance these two revenue streams.

Customer net value: advertising can require more financial resources than the value of the additional sales.

Double‐action of prices: an increase in prices leads to higher revenues from sales and revenues from subscription, but it also reduces the new sales and, therefore, the number of current customers paying the subscription, which in turn decreases revenues.

Relative attractivity: in rivalry situations, customers make decisions about purchasing and switching according to the price and the amount of advertising the company displays in comparison to its competitors.

Options for rivalry: companies can compete for potential customers or each other’s current customers. The levers used for each type of rivalry are different.

Competition versus cooperation: competing by lowering prices can lead to acquiring more new customers, but it also decreases the revenue per sale and monthly subscription, thereby reducing the market value. Moreover, it is likely to trigger a price war.

Each chapter guides you through applicable content and questions enabling you to develop these insights yourself. You will first arrive at answers and then elaborate on them while going deeper and deeper into the subject. Methodological concepts such as variables, causal links, and feedback loops will become your normal language, and you will develop and experiment with simulation models. These simulation models will allow you to qualify your answers and to pose new questions. In summary, the book prepares you to approach dynamic management problems in a systematic and consistent way. Moreover, you can use simulation models to reflect upon the dynamics of business and make better grounded decisions. At the end of this journey, you will be able to develop dynamic maps and use simulation models to reflect upon the dynamics of business for designing successful business policies. Such models serve the purpose of designing decision policies. When management relies on such policies, we refer to it as model‐based management (Schwaninger, 2010). This book is designed to help build several skills that belong or relate to the system dynamics competency framework (Schaffernicht and Groesser, 2016).

What are the components of the book?

The book consists of three components.

The printed text. This is the thread in your learning journey. It successively introduces you to management challenges at the company NewTel. In addition, it introduces concepts and examples of possible dynamics, poses relevant questions, guides you through model conceptualization, allows you to develop hypotheses, to test your findings through simulations, and to interpret the simulation results for decision making.

Simulation models. Each chapter is augmented by one or more simulation models. They are available from the companion website. In this cascade of simulation models, each new model builds on the previous ones. The models help you to explore the dynamics resulting from your decision. Each simulation model is explained in a video tutorial.

Business simulator ‘SellPhone’. SellPhone allows you to gain first‐hand experience in your role as a manager of NewTel. You can get a feeling for how complex your task is. After you have mastered the content chapters in the printed text, SellPhone allows to you to double‐check your learning to see how successful you have been at leading your business.

What is the structure of the book?

The book has nine chapters. Chapter 1 introduces you to the telecommunication case. It provides relevant contextual information and identifies the goals and decision variables you have at your disposal to achieve the goals at NewTel. SellPhone is used to provide first‐hand experience in managing NewTel. You will address the following questions: What are the relevant factors in this case? How do the factors interact with the decisions made during the simulation? The following chapters will also address these questions. In Chapter 2, you will explore the dynamics of diffusion by word‐of‐mouth. We will introduce the mapping method. Three simulation models enrich the text of this chapter. Chapter 3 adds a limited product life cycle duration to the basic situation and explores its implications for the diffusion dynamics. Chapter 4 considers the effects of advertising spend on the acquisition of customers. You will discover the fundamental effect of advertising and discover what effect advertising has on purchases and the accumulation of customers. Chapter 5 introduces financial resources to the situation through a limited life cycle duration and advertising spending. You will explore the implications of purchasing price and subscription rate for revenues, and how the changes in the life cycle duration and in advertising spend impact profits. All aspects discussed so far are integrated into one systemic simulation model about NewTel. Chapter 6 helps you to systematically optimize your decisions for NewTel. It concludes the analysis of your company, since now you have the know‐how to ideally introduce your product into the new market. However, what about your direct competitor? Your strategy needs to consider your rival in your environment. How can you optimize NewTel’s success under these circumstances? Chapter 7 introduces your rival company RivTel. You will become familiar with two types of rivalry. The first deals with competing for potential customers and the second deals with competing for each other’s current customers. The simulation models help you to clarify the interdependencies and guide you to design superior policies. To follow, you are again invited to SellPhone to demonstrate what you have learned about managing a business in highly complex environments. Chapter 8 discusses the simplifying assumptions made in the case models. Possible modifications of the assumptions are discussed and a set of scenarios provided. Chapter 9 reviews the methodology used in the book and generalizes the case of NewTel to other management challenges.

Within the book, a number of icons are used.

In many places in the book, systems insights (SI) and management insights (MI) about the dynamics and structure of the business case can be gained. These SI and MI are relevant because they can be transferred to similar cases you encounter in your work. We also identify a series of principles (P) of dynamic systems that are not bound to the business case but which are fundamental concepts and relationships valid and applicable in any dynamic situation. Whenever appropriate, we have inserted Guidelines (G) as practical recommendations to help you develop good practices as a business modeller.

Who is the book for and how to use it?

Individual learners.

If you are an undergraduate student (sophomore, senior; major as well as non‐major) or a graduate student (master, executive MBA, Ph.D.) in business administration, strategic management, management science, business engineering, industrial engineering, marketing, decision making, economics, public policy, or public management, you will benefit from this book.

The book can also serve as a self‐directed learning journey supported by e‐learning components: an online simulator, video tutorials and worksheets for the DIYs. It is self‐contained and does not require other technical training or theoretical knowledge. Therefore, you can familiarize yourself with the approach, develop intuitive insights concerning the principles of diffusion for durable products, and you will enable yourself to work with specialized consultants.

The book invites you to be active. While you progress through each chapter, we strongly recommend that you replicate the simulation models and experiments and continue to perform your own experiments. As a guideline, you will find video tutorials for each experiment on the companion website. We encourage you to develop the book’s models on your own. Moreover, at the end of each of each chapter, you will find questions and further challenges for self‐study.

Lecturers.

If you are interested in lecturing in business administration, strategic management, management science, business engineering, industrial engineering, marketing, decision making, economics, public policy, or public management with a new and engaging approach, the book is beneficial to you. You can implement the material in undergraduate or graduate courses immediately. The book is purposefully short but is a comprehensive story on growth dynamics in business under rivalry conditions in new markets. Our approach offers a pragmatic and systematic method for studying management challenges and prepares your students for future courses in dynamic systems. Moreover, the book offers value by introducing a visual mapping approach that enables interdisciplinary thinking. The book has the potential to motivate students to follow‐up with more detailed studies on their own. The material accompanying the book requires no further preparation. It can be used directly off the shelf. We suggest using the book in one of the following ways:

For undergraduate students, it belongs to a business or strategy module and requires eight contact sessions (each 45 minutes). The lecturer guides students through each chapter. For Chapters 2–7 there are two possibilities. Firstly, you can have the students read each chapter, reproduce the small simulation models and perform the simulation experiments before the class session. Time in class is used for resolving questions and discussing challenging aspects. Or, secondly, you can introduce each chapter and reproduce the short simulation models; the students then experiment with the models in their self‐study time.

In a generalist MBA course, the book should be used in eight contact lessons. As in case‐based work, students read each chapter before the session and try to reproduce the simulation experiments with the pre‐developed models. The contact session is dedicated to resolving questions and reproducing a project‐like discussion where the lecturer guides the learners through the steps – from raising a question to a simulation model and towards simulation experiments. Students should be able to interpret the results in a plenary discussion.

In master’s courses with students who already have experience in system dynamics, the book can be studied in a reduced number of sessions. After the SellPhone game, students are challenged to develop their own model to design a strategy and decision policy. Each modelling attempt is debriefed in a plenary session in which the lecturer discusses the content of the respective chapter. After two iterations, there should be an additional session where discussion centres on the diverse simplifying assumptions and how to relax them.

If you are a lecturer, and you have questions, ask us: [e-mail] and [e-mail] (www.stefan‐groesser.com).

Before you start

We hope that you will gain as many dynamic insights while studying the book as we had while writing it. Moreover, we hope that the book helps you to train your disciplined, systemic, and dynamic thinking skills. Enjoy the time you spend developing hypotheses, formulating simulation models, and experimenting with them to solidify your understanding of management challenges and to develop your decision‐making capabilities in dynamic systems.

References

Princeton University Library. 2016. The Strait of Magellan: 250 Years of Maps (1520–1787). http://libweb5.princeton.edu/visual_materials/maps/websites/pacific/magellan‐strait/magellan‐strait‐maps.html (last accessed 23 October 2017).

Schwaninger, M. 2010. Model‐based management (MBM): a vital prerequisite for organizational viability. Kybernetes, 39(9/10), 1419–1428. https://doi.org/10.1108/03684921011081105.

Schaffernicht, M. and Groesser, S. 2016. A competence development framework for learning and teaching system dynamics. System Dynamics Review, 32(1), 52–81. doi: 10.1002/sdr.1550.

ACKNOWLEDGMENTS

This book would not have come into existence without the contribution of many people. Over the past years, several generations of MBA students at the Universidad de Talca, Chile, and those following the European Master in System Dynamics programme at various institutions have worked their way through previous versions of what is now in your hands. Conversations about management books using simulation modelling with Kim Warren and George Richardson reinforced the idea that such a book has an important role to play in management education. We would like to thank many people from Wiley for their vital support in developing this book. We wish to thank Graham Winch.

And most importantly, we thank our partners. Thank you, Paula, for your patience while I (Martin) was sitting in front of the screen and for your encouragement. And thank you, Saskia and Finn, that you have given me (Stefan) the time to work on this book.

ABOUT THE COMPANION WEBSITE

This book is accompanied by a companion website:

http://www.wiley.com/go/Schaffernicht/growth‐dynamics

The website includes:

simulation models;

an online simulator;

worksheet formats for working through the DIYs;

discussion of the DIYs, questions, and challenges.

Scan this QR code to visit the companion website

A QR code.

INTRODUCING A DURABLE PRODUCT IN A NEW MARKET

1.1 Introduction

This chapter introduces your challenge as a responsible manager at the telecommunication company NewTel. You have to introduce a durable product in the new market ‘Plutonia’. You will use the SellPhone‐Simulator (described later in the chapter) that provides you with first‐hand experience in dealing with your new situation. You are faced with difficult questions as the unfolding sequence of decisions that are required to manage your company unravels in a highly dynamic market with the major competitor RivTel. One hint: to manage is to convert information into decisions. In this sense, a manager is a decision maker; we will use both terms interchangeably. This book will help you to answer these questions systematically, so that you are better equipped to develop a successful strategy. After completion of the first chapter, you will have covered the following learning outcomes:

You will have become acquainted with your decision task and the SellPhone‐Simulator.

You will know the concepts ‘policy’ and ‘variable’, which are fundamental concepts that will accompany you throughout the book.

Your first attempt at growing NewTel in Plutonia will have yielded expected, and also unexpected, outcomes that require consistent explanations.

You will have practiced the use of ‘behaviour‐over‐time graphs’ displaying the behaviours and trends of variables over time, to identify important aspects of how these variables develop.

You will have generated questions about the factors that drive customer growth, and you will need the answers to manage NewTel’s market introduction successfully.

1.2 Your briefing for the business challenge in Plutonia

It is late afternoon on a Wednesday in July. You are sitting on a plane from Boston to Frankfurt on your way to the NewTel headquarters. You have been with the company for eight months. NewTel is a major telecommunication company that is about to introduce mobile telecommunication in Plutonia, a country where this type of service does not exist yet. Your task is to manage the company’s strategy for introducing your product and service into the country. The objective by which your superior will assess you is the Accumulated profits at the end of the first year of introduction. The market potential is estimated to be one million persons. As a first initiative, your predecessor in Plutonia distributed 5000 mobile phones to individuals for free, but then suddenly left NewTel. The free phones came with a subscription contract for nine months, which was not free: the subscription fee was initially set at $20. Also, an initial sales price for the mobile phone of $50 has been suggested to you. This is all the information you have now. No other plans exist to advance the business. Therefore, you have been appointed to take over immediately.

The market analysis available to you shows that you will have one major competitor – RivTel. The competitor is also preparing to sell mobile phone products and service bundles in Plutonia. Your market analysis team has provided you with further information informing you that the final customer can only differentiate the product and service bundles by the sales price of the product, the amount of the monthly subscription rate and the life cycle duration of the bundle. Hence, other factors such as quality, designs, or services are not differentiating factors for the final customers in Plutonia. However, you can also influence Potential customers by means of your monthly advertising spending.

Moreover, since Plutonia (Figure 1.1) is grateful that you are attempting to enter and, thus, develop its market, the government is willing to provide an infrastructure (e.g. telecommunication network) and other means needed (e.g. technical standards and legal regulations), so that you can concentrate on introducing the telecommunication service.

Image described by caption.

Figure 1.1 Map of Plutonia

While looking out of the window as the flight enters the European area over Great Britain, you reflect on your situation: Once you have introduced the product‐service bundle, how much profit would be a good result at the end of the year? What initiative should you launch to achieve good results? When should you launch it and how intensely? How will your decisions be influenced knowing that RivTel is on Plutonia’s doorstep?

Many questions are waiting to be answered. To reiterate, NewTel currently has 5000 customers in Plutonia. Your research shows that one million individuals could be interested in subscribing to a mobile telecommunication bundle. Your revenue will come from two sources. Firstly, from the sales price that new customers must pay for the initial purchase of the mobile phone and, secondly, from the monthly subscription rate they have to pay for the duration of the contract. The current legal situation in Plutonia, which you cannot alter, is that both the duration of the contract and the life cycle duration of the phone need to be identical. This current length is nine months; it can become shorter or longer if you decide to change it. NewTel does not produce the phones but purchases them from a long‐term business partner: Samuria Technologies from Neptunia sells them to you at a fixed price of $40, which will remain the same for the next few years because NewTel recently successfully renegotiated a supplier contract with Samuria. Moreover, NewTel incurs operating costs for using the telecommunication network and government services of Plutonia, i.e. costs for routing the calls and for using the required technical equipment. These costs amount to an average of $10 per month for each customer. NewTel can influence the operating costs by process improvement spending to fund cost reduction projects.

RivTel, your rival, has the same objective of maximizing Accumulated profits at the end of the first year. Your opponent manager at RivTel – whom you do not know yet – must make the same type of decisions. The decisions each of you make concentrate on the following variables: the mobile phone sales price, the monthly subscription rate, the life cycle duration of the mobile phone bundle, the monthly advertising spending, and the monthly process improvement spending.

An intersecting spanner and hammer icon. Toolbox 1.1:

Variables, units of measure, and behaviour modes

Companies or markets are dynamic: their components and elements change over time. A variable represents relevant components and elements and is something that may change its value over time.

Relevance: why do we need variables?

Variables are relevant for the process of structuring and understanding challenging situations. In such situations, we need to think about what the situation consists of and what the options are. When reflecting on a situation, we describe the thoughts in words. Some factors are relevant because of their behaviour and their presumed influence on one another. For example, in the case of a bakery business, if one wants to understand how revenue is generated over a period, for instance one month, important variables might include the number of customers purchasing during that month, the prices of the products purchased, and the number of products purchased by each customer. One must decide which factor is relevant enough to be considered as a variable.

It is also essential that each variable in a model has a corresponding entity in reality. If a variable is only there to avoid formulation problems or erroneous model behaviours, but the modeller cannot tell which real entity is represented by the variable, then the model loses contact with the real situation it is supposed to portray. Ensuring that each variable is linked to a real entity is part of the permanent validation effort.

Endogeneity: input, output or computed?

We need variables to decompose a problem and represent its relevant aspects. If a variable is relevant depends on the model purpose and problem to be solved. This indicates that a model boundary must be defined that delimits relevant, i.e. to be considered, from non‐relevant content, i.e. to be left out of a model. However, in the real situation such boundaries do not exist. Therefore, the variables inside the model boundary, for which equations will be developed, are not independent from the outside world. For this reason, we use input variables that contain estimated or approximated data instead of equations. These input variables will influence inner or endogenous variables in the model. The word ‘endogenous’ contains two ancient roots; ‘endo’ means ‘inside’, and is the opposite of ‘exo’ (‘outside’), and ‘genous’ means ‘generated’. Endogenous variables are computed by the equations inside the model’s boundary. Input variables are exogenous and nothing in the model influences them. Output variables, even though they are computed in the model, are also exogenous because they do not influence anything inside the model.

Definition: what is a variable?

When defining a variable, its attributes must be specified: name, unit of measure, and range of values.

Name: The name of a variable is substantive and should reveal the variable’s meaning. For example, product price is a transparent and valid name for a variable, as involved parties can easily understand what element of the system under study is meant.

Units of measure: Each variable needs a ‘unit of measure’ or ‘unit’. Being clear about units helps to ensure that the variables and the relationships between them are meaningful. Unit consistency, sometimes called dimensional consistency, means that the equations describing the relationships between the variables do not attempt to compare apples with oranges. Unit consistency also helps to ensure a conceptually sound model formulation, which is an important part of model validation.

For instance, the variable temperature can be measured in degrees Celsius, Kelvin, or Fahrenheit. Another example, currency reserves of the American Central Bank are measured in US Dollars ($). A bakery’s customers are measured in numbers of individuals and the price of bread might be expressed in Euro/kg. In cases, such as customers or workers, sometimes we make a difference between plural and singular: the baker may have 150 customers (individuals), monitors weekly sales ($/week) and wants to know the weekly sales per customer ($/week/individual). Different modelling software packages, which we start using shortly, have different ways to deal with the difference between singular and plural in units. To avoid unnecessary complications, we use only singular in the following equations, but follow the rules of grammar in the written text. The units are indicated in square brackets.

Value range: Often, only a limited range of values makes sense for the variable in the context under study. For instance, the numbers of customers can only be positive. By specifying the minimum and maximum value of a variable, it becomes easier to recognize flaws in one’s reasoning by realizing that an unreasonable value has been generated.

Behaviour: variables vary over time – but how?

It is important, but not sufficient, to know the current value of a variable at a given point in time. For a dynamic analysis, it is essential to know how the variable is changing over time. Considering the past, the rate of change of a variable and the fact that its rate or the direction of change are changing themselves is decisive to figure out how it might behave in the future, given that other elements in the system remain unchanged. Taking these dynamic features into account allows one to make hypotheses about causes for development over time and how one could possibly influence it to our favour.

For example, for the central bank to decide on its monetary policy, it needs to know if the inflation rate is stable or not. Moreover, the bank needs to know if the behaviour of the inflation rate has responded as expected after taking monetary action. And virtually any company will not only need to know how many customers it has at the end of the current month – but it also needs to know if the customer stock is growing or shrinking and if this is occurring with an increasing or decreasing slope.

There are many different such behaviours and they are categorized in behaviour modes (Table 1.1); they can be organized in three ‘atomic’ behaviour modes and several composed behaviour modes (Ford, 1999). The former behaviour patterns are called atomic behaviour modes because they cannot be decomposed in simpler elements of behaviour. More complex behaviour modes, such as oscillation or S‐shaped growth, can be decomposed into phases of atomic behaviour modes.

Table 1.1 Atomic behaviour modes

To gain an overview of the development of variables over time, graphs that show the behaviour of the variables are best to use. Such graphs are behaviour‐over‐time graphs (or BOTG in short). The horizontal axis represents time and the vertical axis displays the variable’s values in the respective unit of measure; for instance Accumulated profits measured in $. In the book, we use the word ‘graph’ as a synonym for BOTG. Figure 1.2 illustrates graphs for the most common behaviour modes.

Graphs illustrating atomic (top) and composed (bottom) behavior modes. Top graphs depict linear, exponential, and goal-seeking curves, while bottom depict S-shaped, oscillation, overshoot and collapse curves.

Figure 1.2 Graphs of the three atomic and three composed behaviour modes

The first three examples in Figure 1.2 show atomic behaviour modes that cannot be decomposed further. When the amount of change per time period is constant, the behaviour is linear. A special case of this behaviour mode is ‘steady state’: this is when a variable has stabilized at one value and neither increases nor decreases. Another term used for steady state is equilibrium. Exponential behaviour is accelerating growth or decline. Goal‐seeking behaviour is a slowing growth or decline, steadily approaching a long‐term value. The second three behaviour modes are more complex but can be decomposed in phases that correspond to atomic modes. S‐shaped growth is then a sequence of exponential growth followed by goal‐seeking growth. Oscillation is a longer sequence of exponential and goal‐seeking phases. Overshoot and collapse can be decomposed into exponential growth, then goal‐seeking growth, and eventually exponential decline.

In this book, variables appear in italics. This helps you to remember that regardless of the form in which a variable appears – in text, diagram, or equation – it is always the same variable. In the equations, the unit of measure of the variable will appear in brackets. For example, Current customers [individual]. The behaviour of the variables, i.e. the type of changes that occur in a variable, will be described in underlined words. This notation helps to get acquainted with the fact that structure (i.e, variables and causal links) is not the same as the behaviour of this structure.

Behaviour: reference mode versus simulated behaviour

We can partially test a model and its quality if we compare the simulated behaviour of variables to empirical data available of their behaviour over time. The term ‘reference mode’ refers to the empirical data. The data available may not always be statistically robust or detailed. However, if this is the case, one can attempt to obtain estimates from experts and then convert them into approximate behaviour patterns to estimate inflection points, extreme values, and value ranges. This reference mode often builds the starting point of an analysis. Most often, the behaviour of the reference mode is not fully understandable and requires further analysis.

Variables are important. Every time you reason about NewTel or something else, you use variables – explicitly or implicitly. Table 1.2 summarizes the variables you can change, i.e. the decision variables, their current values, and units of measure as well as the minimum and maximum values of the variables.

Table 1.2 Your decision variables

You must make your decisions once per month. You can set the sales price between $0 and $70. We use the $ symbol to represent US Dollars. There is only one mobile phone model available. Moreover,