Empiricists love data. Lots of data.
Warren Kinston and Jimmy Algie posited that there are seven, and only seven, unique mindsets or approaches humans use when making decisions about action. This is conscious decision, not simply unconscious reaction based on stimula-response. I’ve got the full article available, although the quality is wanting. (See )
Warren Kinston and Jimmy Algie weren’t a couple of bumblers: Algie had been looking at this since the 1970s and Kinston had, too, from a different angle. Their work together extended Algie’s original work of four approaches and was based on extensive experience consulting with managers and professionals in commerce and medicine, and through many open workshops where the decision methods were taught and tested.
Each approach has specific mindset and values that make it uniquely appropriate for certain types of problems. Adherents to a particular type (and we are all) believe that their favored approach works in all situations. But it doesn’t.
Decision making approaches can also be seen as “languages of achievement” because it is through them that we act. We make decisions about action.
Many of our disagreements in meetings and even families can be seen as disagreements about how to decide, rather than the action itself.
Also, I will just note here something Warren has pointed out several times: your decision making language seems to be doing the work. If I know your dominant decision approach, I can predict with uncanny accuracy how you will approach the problem and what decisions you will make. It is almost as if we are simply channels for the approach. Knowing more about them can make this not true, so this is worth looking at.
Here’s the first decision making approach.
The Empiricist Decision Making Approach
The empiricist approach believes in certainty, in undeniable facts. It believes that data collection and information are vitally important to make any decision. The organizational cultural stage based in the Empiricist approach is Information Culture. This approach is low on both task and person orientations.
In Kinston’s spiral of Strengthening the Management Culture, the growth phase where Empiricist dominates the corporate culture is a late stage and a major milestone. This may explain why so many people have poor feelings about Empiricists: they do their best cultural work when there has already been a great deal of groundwork laid by other decision making approaches. This “information culture” needs to be the cure for unproven nature of the assertions made in the Rationalist phase. Of course, the Empiricist approach is the best approach for certain problems (described below) at any phase of growth.
Empiricist Action Process
Empiricists work by reducing a problem to a manageable size. They then use the data that is available (or collect some more where needed) to define the problem. That information should then point out exactly what the right solution is. They’ll usually want to pilot the solution, and then bring it to scale.
The Empiricist pilot run is a real pilot test: one where if successful you take it to scale. I’ve used the term “pilot” here at times to mean “let’s create a small test to learn what might work and what probably doesn’t”. These are quite different, although both involve small runs. For Empiricists, the pilot is simply a very small scale of the larger solution.
Empiricists believe that what is necessary to solve a problem is a clear understanding of the facts. They pooh-pooh shared values or people’s aspirations, believing that if you just would take a look at the facts as they are, you would come to agreement. With them.
For the most part, Empiricists denigrate theories of any sort, insisting that seeing the facts as they are is all you need.
Disciplines that use the scientific methods rooted in positivist assumptions are dominated by Empiricists because this decision-making approach fits. Software and Information Technology / informatics often dominated by empiricists, and indeed much of that work is well accomplished using the Empiricist decision approach. In these disciplines, the Empiricist mindset can run rampant and show its shadow side. (See Table 1 for examples of how Empiricist values can degenerate.)
Empiricists have clear ideas of “good” vs “evil”, in that clear-headed technical people are “good” and muddy-thinking, touchy-feely magicians like politicians and managers being “evil”. They are quite incapable of seeing the “facts” about opinions or politics. These are things that keep people from following the obvious course of action, made plain by the facts as they are.
In this, they also are an antidote for lots of muddy thinking about the current state of reality. This mindset works very well at solving problems with existing states. In software development, this is the difference between creating something brand new and simply integrating or upgrading a known solution. These two are often confused both by the client and the vendor but should have two entirely different approaches and quite probably different staff.
Because they rely so heavily on data about the current state and the recent past, the Empiricist approach works poorly with ill-defined problems that require a brand new approach.
Empiricists also tend to hate change. The mindset requires a stable present so that trends can be seen from the past. Discontinuous change, such as the introduction of web services in the mid-1990s, overwhelms this approach until enough data can be collected and a trend observed.
Empiricist Decision-making vs. Empirical Inquiry
It’s important to note that this has been about an approach to decision making and not the process of inquiry. These are related but not the same thing.
All referenced documents are available via email upon a request in the comments.
- Kinston, Warren. 1994. Strengthening the Management Culture. SIGMA Centre, London.
- Kinston, W. and Algie, J, 1989, “Seven Distinctive Paths of Decision and Action“, Systems Research, 6:117-132.
- Kinston, Warren. 1991. “Decision Systems, Inquiring Systems and a New Framework for Action”. (Submitted to Journal of Applied Systems Analysis but not published.) SIGMA Centre, London.