As a management consultant (who has worked both externally and internally to organizations), I have been enabling organizations to make better decisions throughout my career. I’ve helped organizations with specific decisions (i.e. building a business case for a new product) and I’ve also helped organizations design decision making processes (i.e. strategy formulation processes / performance reviews).
I am well versed in what be considered good practice for decision-making in the management consulting industry or business schools (a simple example of what is accepted as a good practice is the guide for building business cases by HBR).
In recent years, there has been a lot of interest in the limitations of “consultant-type” decision-making models. I’ll briefly discuss some of the resulting trends that have been most popular here, namely; the limitations of traditional approaches in dealing with uncertainty as well as the limited way in which they consider decision-maker bias.
In recent years there has been increased interest in agile methods and associated ones (for example the Lean Startup) that help reduce uncertainty by making incremental decisions at short intervals (usually related to product development). The idea is that by quickly prototyping you get quicker feedback from stakeholders (i.e. users) and thus reducing the risk associated with large investments and at the same time accelerating the feedback and learning cycle.
The surge in popularity around behavioral economics (Thaler has recently won the Nobel Price for Economics) has helped create more awareness about bias in decision-making and how decision-making actually happens (this article/tool co-authored with the behavioral economics hero Daniel Kahneman published in HBR should give you an overview of some of the ideas).
The idea is that we don’t make decisions in the way economists expects us to (which underlies much of the guidance for building a business case) and that we predictably make biased decisions (for example, most people are willing to overpay for a certain outcome rather than take a risk on the outcome – even if that decision is probabilistically inferior)*.
So there is obviously a realization that additional nuance is needed in terms of how we make decisions**. The above are in some ways attempts to reconcile how decision making happens in the real world with our frameworks. Nonetheless, most of us know that decisions are affected by other factors (especially in organizational settings):
- Who is involved in a certain decision?
- The timing of bringing up a problem / solution
- The processes / style of decision making within an organization
In that sense, I find the scope of the discussions around uncertainty and bias to be too narrow. Behavioral economics is focused on decisions at the individual-level whereas Lean / Agile methods focus on decision-making in the project context, and although they bring us closer to real-world decision making, they still fall short in my opinion.
I’ve recently been reading the book A Primer On Decision Making by James G. March*** and in the book he talks about decision-making in ways that are more consistent with what happens in the real world. He also discusses a multitude of factors that come into play when making decisions. The below extract from the preface of the book provides insight into the spirit of its writing:
The essays in the book are concerned with how decisions actually happen rather than how they ought to happen….Understanding any specific decision in a specific situation requires a great deal of concrete contextual knowledge – details about the historical, social, political, and economics worlds surrounding the decision and about the individuals, organizations, and institutions involved. There are no stories of the rich drama of decision, no elaborations of history….
Since the book provides insight into how decision-making takes place in the real work (with all of the associated complexity), it does not lend itself well a normative framework that can be easily implemented. Although March discusses, how decision-making can be “engineered” towards the end of his book, the ideas are mostly suited (I believe) for reflection and use in a coaching context.
In this series, I’ve decided to write a series of short stories based on some of the concepts that March presents in his book. I am hoping these could be used in a coaching context; that they would help leaders reflect on decision making and how they and their organizations make decisions and hopefully this can build a foundation for better decision making****.
In the next post two posts we will be introducing the the organization that is the setting of the story as well as James who is our main character. We will be describing decision-making within the context of the organization through James’ eyes (James and the organization are fictional). We will be going through through the following short-stories:
- Building a business case is simple, right?
- What does a leader mean when he says that we are data driven?
- Why is there always a conflict with sales?
- Sausages and decision making!
- Have we learnt anything?
**In Toronto there is a consulting company that specializes in helping organizations better understand how consumers and themselves make decisions, using concepts from the field of behavioral economics (check-out BEworks).
*** Footnote: My MPA studies have introduced me to the works Herbert Simon and James March (thank you professor Erhard Friedberg).
****I fully realize that as I am writing this series of posts, I am fully in control of the characters and description of events, and therefore they must at least to some extent reflect my experiences, perceptions, and beliefs and all the biases that accompany them.