(Ook beschikbaar in het Nederlands.)
Behavioral sciences are hotly debated. Some even speak of a crisis.1Rens Bod (2010) Vergeten wetenschappen een geschiedenis van de humaniora2Klaus Oberauer and Stephan Lewandowsky (2019) Addressing the theory crisis in psychology Psychonomic Bulletin & Review21Elliot T Berkman en Sylas M Wilson (2020) So Useful as a Good Theory? The Practicality Crisis in (Social) Psychological Theory in Perspectives on Psychological Science This crisis arises from a) the lack of predictive value of behavioral theories, b) the very limited repeatability of studies in the Behavior knowledge domain and c) the extremely weak relationship between the statistical results and the conclusions drawn.
Change management is also part of this crisis. Decades of research by brilliant researchers have not led to universally applicable concepts and theories. Despite the large number of popular books, the results remain below par. The number of failed change projects is, and remains, still very high. The percentage of failed projects is around 65 percent, but the exact percentage does not matter.3Jarrel, T. (2017 September) Success factors for implementing change at scale. McKinsey & Co Presentation, Behavioral Science & Policy Association, New York, NY.4Meaney, M., & Pung, C. (2008 August) McKinsey global results: Creating organizational transformations. The McKinsey Quarterly: 1–7The core is that change hardly benefits from a structured approach in the form of a step-by-step plan.
This raises the question of whether the current set-up and approach can lead to a good theory of change. In this article we explain that the foundations for valid theories are missing and we propose a solution to test change theories for validity.
Statistically, there is a correlation between the number of ice creams we eat and the number of drownings. The more ice cream we eat, the more people drown. However, ice and drowning have no causal relationship. Both depend on the air temperature. When it's hot, we eat more ice cream and swim more often. Because we swim more, more people drown. However, eating ice cream has nothing to do with the drownings.
Can we substantiate that change management is a pseudoscience? Answering this question begins with establishing what a pseudoscience is. That is difficult. We cannot define precisely what a pseudoscience is.5https://nl.wikipedia.org/wiki/Pseudowetenschap Characteristics of a pseudoscience include making vague claims that are not supported by precise measurement, applicable are not described, that causal relationships are absent, that descriptions are deliberately vague and that evidence relies heavily on anecdotes. Examples of pseudoscience include the books "In Search of Excellence" by Peters & Waterman and "Good to Great" by Collins.6Robert H. Waterman (Jr.) en Tom Peters (1982) In Search of Excellence7James C. Collins (2001) Good to Great Why Some Companies Make the Leap...and Other's Don't Don't The claims in both books can be seen as a horoscope: what we see is often what we want to see. We tend to interpret evidence in ways that confirm our existing beliefs and ignore evidence to the contrary. Both books do not present a theory in advance that they test against the measurements, mix connections with causation and make statements that do not hold water when tested.9Michael A. Hitt & R. Duane Ireland (1987) Peters and Waterman Rvisited: The unended Quest for Excellence.
The evidence in these kinds of books rattles on all sides. Yet managers in all kinds of organizations fall for its lures. Under the influence of renowned publishers and advice from other managers, professional communities sometimes share downright folkloric beliefs. Because of this, they confuse familiarity with credibility. Furthermore, they only focus on success stories of other companies without really understanding the reality.
Popular models describing the steps to change the organization include Lewin's Three-Phase Process, Beer's Six-Step Change Management Model, Appreciative Inquiry, Judson's Five Steps, Kanter, Stein, and Jick's Ten Commandments, Kotter's Eight-Step Model, and Hiatt's ADKAR Model.
Stouten, Rousseau and De Cremer have summarized the main principles of these models of change and compared them with findings from scientific research, presented below in italics:8Stouten, J., Rousseau, D., & De Cremer, D. (2018). Successful Organizational Change. Academy of Management Annals, 12-2..
Scientifically, the popular management theories are not well founded. This is not a special observation. For example, Ten Have, Huijsmans and Otto convincingly demonstrate that change management has a credibility problem.10Ten Have, S., ten Have, W., Huijsmans, A. B., & Otto, M. (2016) Reconsidering change management: Applying evidence-based insights in change management practice. Routledge.
Entirely in the spirit of positive management, we prefer to reformulate the shortcomings of change management as challenges. Alvesson and Sveningsson describe five challenges to take change management to the next level.11Alvesson, M., & Sveningsson, S. (2015). Changing organizational culture: Cultural change work in progress. Routledge.
The first challenge is to describe the situation, the context, in which the change takes place. Broad social changes have a major impact on organizations and the views of employees, for example the environmental issue. Due to the lack of a situation description, many models lack connection with practice.
The second challenge is to interpret the large number of phenomena that influence and change at the same time. Objectives (CO2 neutral), technology (5G), systems (Cloud) and networks (Brexit) change simultaneously. How can cause and effect be discovered in this?
The third challenge is precisely naming the actors. Are we describing the government, the umbrella concern, the local branch, the department or the individuals? Or are we mixing the influence of all involved? Who then does what?
The fourth challenge is the realization that the need for change is broader than just making a profit. Not only organizations know the need for change, people do too. We almost always disregard the thinking patterns of individuals when changing organizations.
The fifth challenge is to better illuminate the aspect of time. We often only look at the beginning and end, not at the intermediate stages. Moreover, what was valid yesterday may no longer be valid today.
These challenges and problems make it clear once again why the scientific status of change management is under discussion.
The question of whether change management is pseudoscience is not under discussion in the scientific world. Students at any good university are told that most management theories are folklore; good to take note of, but not to apply.
What is missing in the training is the next step: a theoretical framework to set up well-founded models. What requirements must a model meet and how can these requirements be tested? How can sense be distinguished from nonsense? The lack of this framework makes it clear that taking the next step in making change management scientific is very difficult.
Building this framework is the real challenge in making change management scientific. We address this challenge below by describing the requirements a change management theory must meet in order to pass as scientific. With these requirements in hand, we can then test theories and models for validity.
The word goal has a bad name in the scientific world because of the metaphysical meaning it often takes on. In this article, however, we are talking about a concrete goal in this life, not after this life.
We anchor the requirements that a theory or model must meet to the goal of change management: observing and influencing a situation in order to achieve a set goal.
We make no demands on the goal. We only formulate the requirements that observations and influences must meet.
Observing does not change the reality outside the observer; an action does change reality. This difference leads to separate requirements for observing and influencing.
We experience reality by observing. In addition to concrete objects, such as stones, plants and animals (material), we also perceive ideas or concepts (immaterial). We often consider the combination of the material and the immaterial as a unity. A suitable word for 'that which we perceive' is therefore a unit of consideration.
The concept of abstraction has many meanings. In the art world, for example, it is about a form of expression that distances itself from visible reality. Linguists speak of a concept that is separate from everyday reality. In this article we understand an abstraction as a simplification of reality.
We simplify the complex reality by only paying attention to incentives that are important for decision making. We call this simplification abstraction and the result of a simplification we call an abstraction.
A unit of consideration is always an abstraction. An abstraction describes only those properties of an object that are characteristic of achieving a goal. Making abstractions therefore starts with the question: what is the goal, what do we want to achieve? The goal is of decisive importance in thinking about abstractions. For example, let's consider grass; simple enough and abundant in the Netherlands. Grass... What's difficult about grass? Grass in a pasture is fodder for free-roaming cows. Grass in a garden is a lawn. Grass next to a swimming pool is a playground. Grass in the national park in Athens is off limits. Grass in the nursery is called a plag and is available per roll. Grass in the football stadium is a turf and is wear-resistant. Grass on a golf course is a green. Grass along the side is bank or verge grass. Grass between the tiles is weed. Grass… Every time we look at the purpose of the grass and give it a name. Without knowing the purpose, it is not possible to understand the grass terms. Yet it is and remains grass. So simple and yet so difficult at the same time.
The function, the role or the significance that the unit of consideration has for the achievement of an observer's goal determines which properties are characteristic. The difficulty is not hidden in the grass, but in the simplification made. The abstraction requires knowledge and insight into the goal and the way in which we can achieve the goal. Only then can the abstraction be understood and it is clear why the associated characteristics have been chosen. No matter how simple the abstraction, the complexity lies hidden in the goal. If we do not see the goal, then the abstraction is complex.
Once the goal has been determined, we will get to work to achieve this goal. By paying attention only to information that is decisive for making decisions or, in other words, by applying abstractions, we can process information effectively and efficiently. If we pay attention to unimportant things, we waste energy. The faster we recognize the essence, the faster and better we can decide. Moreover, by distinguishing and remembering only the essentials, we relieve the memory.
Different ways of looking at reality can all be valid at the same time. Every observer can name an abstraction from his own goal. All abstractions mentioned in the example grass can be good from the point of view of the observer. Only by setting general valid requirements for abstractions can we test whether an abstraction is right or wrong. These requirements are important because incorrect abstractions lead to incorrect decisions and thus to inefficient (inefficient) routes to the goal.
The details can be read in chapter 3 Observing of the book «The Alforto framework».
We vereenvoudigen de complexe werkelijkheid door alleen aandacht te besteden aan prikkels die van belang zijn voor het nemen van beslissingen. Dit vereenvoudigen noemen we abstraheren en het resultaat van een vereenvoudiging noemen we een abstractie.
Observation lays the foundation for the development of activities. We are going to change reality to achieve the set goal. This is much more difficult than observing because we have to coordinate multiple decisions to achieve the goal. The actions must support and complement each other if we want to reach the end point. Combining a series of related decisions to perform actions is called control.
Humans utilize three control mechanisms. The first control mechanism is the step-by-step plan. The step-by-step plan is predetermined. The executor must perform all actions in sequence after which the result appears. The executor does not need to know why the steps have to be performed. We bake a cake and add an egg. Without an egg, the baked cake will not be airy. This knowledge is not important for the operator, but it is important that the egg must be added. We often call a step-by-step plan a procedure.
Responding to events is the second control mechanism. This is a large part of police work. An agent responds to a call, rushes to the scene of the disaster and offers assistance. Responding places higher demands on the agent than simply carrying out a step-by-step plan. The time is different every time, the places differ from time to time and the order of action must be adapted to the situation. This flexibility places higher demands on a person than simply carrying out a step-by-step plan.
The third route-finding control mechanism is even more difficult. We know where we want to go, but we don't know how to get there. The number of possible paths to the goal is very large in advance. Having already gained experience, we know that some roads are easier to walk than others. We then choose the best. If the road to the goal is new, then all we have to do is guess and miss. Over time, we gain enough experience to make the right decisions. The route-finding control mechanism places extremely high demands on the person.
The details can be read in chapter 4 Influencing of the book «The Alforto framework».
Influencing builds on observing. Perception allows us to increase the chance of success by choosing in advance which actions we want to take. Without observation, the unfolding of actions is mere coincidence. With observation, the actions can be made goal-oriented.
Observing and influencing each have different principles. The essence of perception is to simplify the real. We do this by setting up a hierarchy of abstractions. We divide similar observations into groups and name them. In other words, we classify. Child classifications include more attributes of parent. For example, the vehicle class is above the car. A car has an engine, wheels, et cetera.
When influencing, effectiveness and efficiency come first. Guaranteed to reach the goal with least effort is paramount, because it prevents wasting of valuable energy and time. Simplicity is a nice bonus, but it is subordinate to achieving the desired result. Searching for the best route to the goal is at the top of our wish list.
| Attribute | Classification Observe |
Route Influence |
|---|---|---|
| Final state | None | Mandatory |
| Acting person | Not required | Mandatory |
| Knowledge domain | All | All |
| Ordering principle | Hierarchy | Sequential |
| Validity Requirement | Falsification Requirement, Laws of Observing | Realization Desired State, Laws of Influence |
| Time and place required | Nee | Ja |
| Alternatieven | No | Yes |
| Optimization principle | Simpler | More efficient |
| Depending on | Formal abstractions | Classifications |
In table 1: Difference between classifications and routes. the most important differences between observing and influencing have been listed.
It is mandatory to name the final state when influencing. Without knowing the destination it is not possible to test the validity of the route. Observation has no end goal. It is merely a description of a situation from a chosen point of view at a particular time.
An acting person is obliged in case of influence. Someone takes an action. An observation is passive and has no acting person.
The attribute «knowledge domain» refers to the classification of knowledge based on uncertainty. Reactions of matter (physics) are easy to predict. Human behavior is much more difficult to predict because it can be changed at any time. Realizing the route to a goal is behavior and, unlike reactions of matter, is not 100% predictable.
The ordering principle in observing is the hierarchy of abstractions. The main principle in influencing is the sequentiality of actions. One comes after the other. It is not possible the other way around.
The validity requirements in perception are Karl Popper's falsification requirement and the Laws of Observation. (See chapter 3.3). In the case of influence, the ultimate test is to determine whether the goal has been set. The description must also comply with the Laws of Influence (See chapter 4.4).
Time and place are not mandatory for an observation. The designation house is a correct representation of an observation. Adding the place and time of the sighting adds information, but is not mandatory. In the case of an influence, time and place are decisive because the order depends on time and place. Both are therefore mandatory.
Observations preferably have no alternatives. An unequivocal observation is preferred. Paths to a goal can describe multiple alternatives. The choice of influence depends on the exact circumstances. The optimization principle in observation is simplicity, in influencing it is efficiency. Effectiveness is already implicitly mentioned under the validity requirement. "Depending on" describes that routes to a target depend on previous classifications made. Turning left at the mill assumes that the influencer knows the term mill. Routes always rely on classifications. Classifications build on formal abstractions that are always true, such as 1+1 = 2. Mixing classifications and routes in the same enumeration leads to a loss of simplicity and meaning. When describing a route, we name the connecting nodes and do not list classifications. If we pursue a goal, a route description with classifications as a step leads to a puzzle tour. How can a next step towards a goal be a classification? We go to the stand in Zandvoort and the next step is the classification of means of transport into motorized and non-motorized. And now? Which means of transport should we choose and why? Only consecutive steps belong in a route. A route requires an active choice with an activity, a classification does not require a choice. Conversely, a route does not belong in a classification.
The objection that we can classify routes does not get to the heart of the distinction between classifications and routes. Of course it is possible to classify alternative routes, but the main classification is then a classification. Characteristics of routes then form the classification criterion. The classification of a route is not itself a route. Conversely, classifications always underpin a route. The sentence “At the station, take the train to Zandvoort.” uses the classifications station, train and Zandvoort to indicate the route. In short, classifications and routes can support each other, but combining them at the same level is not possible.
Mixing classifications and routes occurs frequently in the Behavior knowledge domain. Policy documents in particular often fall into this trap. We summarize all kinds of trends and social developments. We then conclude that we need to change and that the positive and negative consequences deserve a lot of attention.12Bijvoorbeeld The Hague Centre for Strategic Studies (2017) Grote bewegingen, Grote impact However, there is no connection with any influence route. It remains unclear what considerations a decision-maker should make.
The distinction between a classification and a route has received little attention so far. As a result, we often confuse relationships in classification with routes in control despite the fundamental differences between them.
The distinction between observations and influencing leads to a three-stage structure of observing and influencing. The first step is to name objects with words. For example, we distinguish nails and hammers. In step two we use these names to describe the route to a goal. Drive the nails into the wood with a hammer and then glue … the top plate … to make a cabinet. In step three we compare this route with alternatives and classify the routes. We compare features of the routes such as cabinets with nails, with screws or with staples. It is important that in step three we describe the characteristics of routes and not isolated objects as in step 1.
With this we have three reference layers:
Each reference layer must meet the general requirements we set for classifications and routes. Observations (A and C) must obey the Laws of Abstractions and activities must obey the Laws of Influence (B). Classifications and routes can support each other, but a combination at the same level is not allowed.
When Dmitri Mendeleev invents the periodic table of the elements in his dreams, the end result is a classification (A), a classification of matter based on the number of protons and electrons. Making this classification is a human activity and is therefore a route (B). For correct influence we connect all nodes to each other. We can observe, compare and simplify the ways in which we do this (C).
The correctness of an abstraction can be tested with eight rules. The first and second rules are that the observer maintains a common intent and that the abstraction is constructed from this constant intent. The third rule states that only properties that influence the purpose belong in the abstraction. The fourth and fifth lines prohibit loops in the description. An abstraction should not describe itself and the observer should not be part of its features. Rules six, seven and eight stipulate that an abstraction can only be placed in a hierarchy if all the features of a parent abstraction influence the underlying abstractions and that decisive features are superordinate to juxtaposition. See chapter 3.3 of the book «The Alforto framework» for details.
The correctness of an influence can be tested with seven rules. It starts with the rule that the performer has an equal goal in mind. Furthermore, only steps that contribute to achieving the goal belong in the description. It is also forbidden for a description to describe itself. After this, naming the order of the steps is essential and the characteristics of the nodes must match. Finally, we describe all nodes as clearly as possible in form, time and place. See chapter 4.4 of the book «The Alforto framework» for details.
The Laws of Observation (WvW) are generally valid for all observations, including the perception of influence. We don't need additional rules to classify influence perception. The Laws of Observation apply unchanged to the classification of influence. It is difficult to categorize influence correctly, because mixing viewpoints makes classification much easier. And unfortunately also strips it of all meaning.
In Chapter 2 we made it clear that change management is not scientifically based and that it is therefore a pseudoscience. We call it a pseudoscience without specifying exactly the criteria that a scientific theory of behavior must meet. We don't get beyond a feeling. This is remarkable. If we want to arrive at an objective assessment of change management, naming these criteria is the first step.
In chapters 3 and 4 we derived the criteria for testing change management from the purpose of change management. The goal can only be achieved by observing and performing actions. Observing (classifying) and influencing (choosing a route) each use different principles. As a result, we set different requirements for both. Observations must obey the Laws of Observation. Influencing must comply with the Laws of Influencing. Mixing perception and influence is not allowed because a classification with a route is not the simplest description and a route with a classification cannot be converted into actions. When classifying routes, we should also use characteristics of the routes as a classification criterion. The subject of the classification is the route, not an arbitrary observation without influence on the choice of route.
With these criteria in hand, we can make a definition of a pseudoscience in the knowledge domain of Behavior. A pseudoscience mixes classifications and directions in an enumeration at the same level of observation (in the same layer). In addition, it identifies characteristics of influence that do not affect a route. Furthermore, a pseudoscience does not satisfy the Laws of Observation and Laws of Influence.
change management is only scientifically substantiated if:
The question of whether change management is a science can be traced back to the difference between routes and classifications. Change models should describe pathways and use classifications to name phenomena and summarize pathways. However, most theories merely classify, whether or not statistically substantiated, and that is not enough to claim scientific status. Classifications that are not based on routes, by definition, do not describe valid cause-effect relationships in the Behavior knowledge domain.
The title of this article is: Why is change management pseudoscience? The answer is that no theory of change meets the criteria we set to pass as scientific. A bold statement that can be defended until proven otherwise. Your task is to falsify this statement by finding a theory of change that does meet the above requirements. You can of course also test the validity of the criteria and make proposals to tighten them up.
The examples in this chapter do not test the criteria mentioned in chapter 4. That is nonsensical, because no change theory or model meets the basic premise: explicitly stating the practical goal of the change. Instead, we emphasize the guises pseudoscience hides in; preferably in intelligent-looking reflections that cannot be disproved one-two-three.
The 10-step model of Stouten, Rousseau and De Cremer is pseudoscience. In essence, it is a classification of subjects that are always valid. It applies to all projects and the importance of each step cannot be indicated. The subjects are so far removed from a practical solution that no decision can be derived from them. Moreover, the model does not provide any support for making practical choices. Comments on each step in the model are printed in italics below.
The main problem of the 10-step model is the lack of routes to a goal. It is a classification of influence in step C. However, it does not name characteristics or specific routes and is therefore not objectively verifiable. It is generally valid and therefore meaningless. It is a clear example of pseudoscience because:
In Chapter 3, we said that getting a student at any good university instilled in us that almost all management theories are folklore; good to take note of, but not to apply. That is not entirely true. Sometimes ideas slip through the cracks and we still teach folklore.
An example of this is the Amsterdam Information Management Model that is used to 'solve' the problem of finding a good alignment between business and ICT.
The Amsterdam Information Management Model (AIM) is a nine-plane model that combines two dimensions, each with three perspectives. See figure 1. In 1997, Abcouwer, Maes and Truijens introduced this framework in which management issues can be positioned around information management.14Toon Abcouwer, Herman Gels en Jan Truijens (1997) Informatiemanagement en InformatiebeleidThe framework was further elaborated in 1999 and 2003 by Maes. The nine-plane model is mainly used to study the relationship between the organization and its information provision. The model is actively taught at the University of Amsterdam.
The adaptive cycle is part of the training. (see image 2). The starting point is that an organization wants to be in balance. She does what she wants/needs and what she can. Disruptions create new challenges where traditional ways of acting no longer suffice; there is a crisis. The organization is looking for new solutions. She only chooses the best solution to implement. Called entrepreneurship in the scheme. According to the authors, each phase requires different management skills.
The adaptive cycle and the nine-plane model are examples of pseudoscience par excellence and can be compared with the replacement coefficient. It looks brilliant at first glance. After studying it gives the feeling of gaining insight into the operation of a company. It seems so good that we even teach it at the University of Amsterdam. However, the most important thing is missing: we can't do anything with it. It's no use. There is no decision to be taken from it. It is therefore a waste of time and energy.
In both models, a more extensive analysis reveals many fallacies. The main one is putting the goal out of brackets, not answering the why question. The models are therefore generally applicable in any situation. That is of course nonsensical. We choose a different goal in each situation and deduce other routes by answering the questions of who, when, where and how. The authors take it easy by ...(read this in the book). It is therefore not possible to specify a decision that arises from the model. This analysis is therefore completely up in the air; it is not connected with any influence of reality whatsoever.
The authors also leave the criteria for the classifications unmentioned. The dividing lines between the subjects are not clear, so that everyone can make their own classification. Have you ever seen a company where all activities are in balance? And what exactly is equilibrium? When is a crisis a crisis? A customer who does not pay? Yes, you can, if the amount is large, but not if it is a small amount. A product that is returned? Yes, if it is custom made, but not if it is a cheap off-the-shelf product. Because the two models are always valid, they are fine as a horoscope. “The coming week you will have to deal with successes and setbacks. Be prepared and find new solutions.”
At first glance, the nine-height and adaptive cycle models seem to make sense, but upon closer examination, they completely fail. We cannot derive any decision from it. It only complicates and offers no scientific insight. It is a mystery why the University of Amsterdam is teaching both models in 2019.
My apologies to the authors. It is a coincidence that it is precisely these models that come into the limelight. These are just examples of a fundamental problem in behavioral science: it is not possible to classify an influence (reference layer C) without naming the characteristics of the pathway (reference layer B).
Steven Covey describes effective leadership of change in three layers. The first layer consists of three qualities that ensure that a leader learns to be independent: 1) Be proactive, 2) Start with the end in mind and 3) Put things first. The second layer describes three properties that are about working together effectively: 4) Think in terms of win-win 5) First understand, then be understood 6) Synergy The third layer discusses people's ability to live to their full potential and to help others to do the same: 7) Keep the saw sharp - continuous improvement 8) Live from your strength and learn to inspire others.
Covey's ideas are inspiring and encourage people to think differently about their own role in groups. The train of thought opens a window to the role of people in achieving a goal. The central message is that not only the content is important, but also the functioning of the individuals and the groups. This approach is innovative, despite the lack of important components. What is missing is a firm anchoring of personal ambitions and group motives. Moreover, the elaboration of the guidelines gets stuck in simple mantras, which are very similar to Buddhist rules of life.
Due to the lack of solid anchoring, an important issue remains undiscussed: how can we use the eight characteristics if there is no substantive contribution? For example, I am not the best at anything and potentially have no more capacity than the average person. So fifty percent of people are better than me. I am leader of a group. What should I do now with Steven Covey's advice? I know that I want to go to the moon and be remembered for it, but I don't know how to get there. I have no substantive knowledge of the super complex matter, but I do have to make a decision. So I cannot first understand and then be understood. Besides, I don't know which things are important. I never complain, but don't see my goal getting closer through my own actions. The rocket to me is as big as it can be. And now? Can I be a leader? How should I act? Why was Wernher van Braun successful and I was not? No, I'm not complaining, I'm just exploring how I can improve. How can I realize my dream and be remembered at my funeral as the person I want to be but can't become because I don't excel at anything? Yes, I lobbied, but the group around me chose others to make my dreams come true. As soon as a positive solution direction is lacking, Steven Covey's ideas prove to be of no help in organizing my life and making good choices.
The second fundamental problem of the properties is that they provide no basis for any decision. They function well as a motivator and temporarily increase self-confidence, but they do not offer a helping hand to make decisions in practice. Ultimately, the value is therefore limited and even negative.
The world is more complex than Steven Covey would have you believe. Not everyone can be a celebrated leader; simply because the number of leadership positions is too small. Not everyone is the best. Not everyone has the following energy to fetch the sharp saw back and forth. Not everyone thinks the funeral is important. What was Wolfgang Amadeus Mozart's funeral? Yet many still enjoy his music every day.
Steven Covey's Seven or Eight Habits are prime examples of pseudoscience. It looks impressive, it inspires and gives a good feeling. It underlines that people are important. And that's where it ends. We cannot derive any decision from it. That's too bad. The basic idea is good, but the execution is too superficial. The book «The Framework» starts from the same basic idea, the goal, but works out the details in full.
A valid theory is a good tool for predicting, explaining and influencing human behavior. A valid theory names causal relations between action and result. One of the most valid and practical theories for improving performance is Goal-Setting Theory.18Miner, J. B. (2003). The rated importance, scientific validity, and practical usefulness of organizational behavior theories: A quantitative review. Academy of Management Learning & Education, 2, 250-268. 19Pinder, C. C. (1998). Work motivation: Theory, issues, and applications. Upper Saddle River, NJ: Prentice Hall. This isn't easy, because behavior pursues multiple goals at the same time. In The Framework we distinguish three substructures: the actual result, the personal satisfaction and the group interests. The challenge of change management is to combine the most efficient path to meaningful results with the personal ambitions of the employees and motives of the groups involved.
The task of the 'change manager' is to align substantive, personal and group interests:20The 'change manager' is in quotes because the term is empty. Everyone is a 'change manager'. The world is never stable.
Change management is a pseudoscience as soon as the causal link between the activities and the goal is missing. If the goal or the routes to the goal remain unnamed, then the insight is by definition nonsensical. The strength of the model increases if the ambitions of individuals and motives of groups are well described.
Scientifically sound change management does not describe horoscope-like, general truths that are vague enough to create an image of control, but clear decisions that lead to actual results. Moreover, these decisions are based on causal relationships.
Read more backgrounds in the book «The Alforto Framework».
See also:
Arjen Meijer
Mai 9 2021
Last change July 29 2023