Systems as Mental Interfaces

In today’s post we’ll be discussing Dr. Edward Martin Baker’s amazing little book, Scoring a Whole in One. Credit is due to Sean Murphy, of SKMurphy, Inc., who reached out and asked if I’d like to collaborate on something based on Baker’s book. I said yes, and we each did a post on it. Below is mine. And here is the link to Sean’s excellent post.

Baker was a protégé of W. Edwards Deming. Deming thought Baker’s ideas brought new thinking to the table and encouraged him to write his own book. He first wrote Scoring a Whole in One. He later wrote another book, The Symphony of Profound Knowledge, which we will look at in a future post.

Let’s get started!

Scoring a Whole in One is to the point, frank, and brilliant. The entire book is an argument against the futility of the normal business-school way of running things. It is about the necessity of taking a holistic, systemic view (hence the “whole” in the title).

Most organizations operate from the assumption that system performance is determined by the independent performance of component parts or business units or divisions. The reality of the matter is a different animal…requiring a different approach.

Baker illustrates with a story: An American auto manufacturer knew customers preferred a car made by a Japanese competitor. They didn’t understand why, so they thought they’d do some research. They bought one of the competitor’s cars, chose one of their own, and took them both apart. They had specialists analyze all the parts and the findings were sent to a manager who assembled a report. The conclusion was that the American car parts were of superior quality…and so they were just as puzzled as they were before.

What were they missing? As Baker puts it, the method they used for their research was the same approach they took to design their cars. Neither focused on the larger system. Imagine, Baker asks, if you took the best parts from the best cars on Earth and then put them together into a single car, would the result be the ultimate car? Far from it—it would not even run. Yet this is how most orgs think and operate.

The performance of any complex system is not the sum of the performance of each of its parts considered separately; rather, it must include the product of their interactions, which often have indirect effects larger than the initial changes made.

In other words, if a system only has three parts, A, B, and C, then its performance is not A + B + C. System performance includes relevant relationships between interacting parts. Let’s say for our example that parts A and B and parts A and C interact. As shown below, system performance here then would equal A + B + C + AB + AC (image from Baker’s book).

Ignoring interactions and indirect effects, organizations instead tend to focus on silo optimization. This fallacy is typically baked into incentives programs. In another of Baker’s examples, the management of the engine division of an auto manufacturer rejected a change that would reduce cost per vehicle by $80…because it would increase cost per engine by $30. Thus, a change that would save the company an average of $50 million a year was rejected because it made one division’s siloed metrics worse—but are they really to be faulted?

After all, they did what they were incentivized to do. Their bonuses probably weren’t tied to optimizing the system. As Goldratt famously states in The Haystack Syndrome, “Tell me how you measure me, and I will tell you how I will behave. If you measure me in an illogical way…do not complain about illogical behavior.”

As Baker puts it, “When the management system relies on bribes and punishments, it encourages individuals, or teams, to behave in competitive, self-optimizing, self-protective ways,” a point he powerfully makes with a series of interaction matrices (image adapted from Baker’s book).

In the example above, Purchasing, Engineering, and Assembly all make respective improvements, resulting…not in improvements overall…but in things getting worse. This will seem counterintuitive as long as one fails to think in terms of interactions. Just as two medicines that could help you might together make you sicker, so too could departments improving themselves in isolation make overall system performance worse.

In fact, in order to optimize the larger system, some departments or orgs or teams may need to become worse on their metrics, as illustrated in the image below (adapted from Baker’s book).  

If systems aren’t optimized by having everyone improve their own metrics, then this should impact how performance reviews are done. (Recall the Goldratt quote above.) If you tell people that internal competition and infighting is a problem but are still clinging to the annual performance reviews and reward mechanisms that incentivize such behavior, then your say-do ratio is off. As Baker further argues, you’re fooling yourself by even believing you can accurately parse who caused what anyway.

This point brings us to the title of the book, a play on words referencing a golf analogy. To quote Baker, “The various components of the body cannot be individually credited for their contribution to a good golf swing.” An organization is no different, he argues. If a system is performing well, then it is illogical to try to identify the separate contributions of participants. The credit should be shared equally. This is also one of the lessons of Deming’s famous “red bead experiment.” If you’re unfamiliar, then check out this post by Daniel Good.

As Good puts it, if someone’s performance = their own contribution + the effect of the system on that contribution, then even if you theoretically could assign a value to someone’s (apparent) performance, the resulting equation is still not solvable! You’ll instead “narratize” the gaps here, ultimately basing pay on what you find to be believable stories.

Attempting to base rewards on performance likely makes little sense anyway. (Note this does not imply that everyone should be paid the same. Rewards should primarily be based on doing the right things, not on outcomes. Pay should also be based on level of expertise, seniority, skills acquired, and level of responsibility.)

It is vital to map your systems. The “system,” as you think of it, is a mental model—it is itself a form of map; and, as the General Semantics folks stress, “The map is not the territory.” Baker agrees with this: Whatever we think our system is, this is always just “the way we think about the territory, about ‘what’s out there,’ although ‘what’s out there,’ and what’s in our mind cannot be easily separated, if at all.”

For you, the system as you conceive of it is essentially your “mental interface” determining any interactions or interventions it will occur to you to undertake. If you aren’t mapping and improving your model of the systems at play, then your interface for making changes is left unstated, half-baked, and likely highly inaccurate and discrepant.

To improve your interventions, you must improve your mental interface.

This image has an empty alt attribute; its file name is jester-3.png

3 thoughts on “Systems as Mental Interfaces

  1. Another great post/summary of a complex but important perspective on group endeavors. The complexity in its system inherently means consequences to changes are hard to predict. In organizational optimization (if based on the above that is even possible) are there any recommended methods for experimentation to understand those potential interactions and consequences? How do you “Fix” an undesired outcome that is a result of the system but changing any one aspect of the system would create a new “broken” state? Also do you have any references for “Pay should also be based on level of expertise, seniority, skills acquired, and level of responsibility.” I am fascinated by compensation schemes.


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