Uncovering hidden optimization potential (Pt 1)

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Large, highly successful companies often find it difficult to take their game to the next level. The increasing complexity that accompanies success can seem like a formidable barrier to continued growth and success.

But isn’t.

The real barrier is simply the limitations of the human brain. While the average person finds it difficult to remember more than seven digits, the average planner regularly makes decisions that involve millions of options and a bewildering array of business rules and constraints. It goes without saying that if planning is a struggle, re-planning to recover from day-of-operations disruptions is a nightmare.

How, then, do businesses cope with the obvious mismatch between limited human brain power and apparently limitless complexity?

The coping mechanisms of complex businesses are so common that it’s worth reminding ourselves that they are far from ideal: They only exist because human beings just aren’t very good at processing large quantities of data.

Here are a couple of coping mechanisms that you may recognize.

  • Reducing complexity by oversimplification

This is planning by ‘rule of thumb’. Instead of considering all the factors that determine whether one course of action is better than another, planners focus on optimizing a particular KPI. For example, planners may focus on minimizing the number of empty miles, even though this KPI is only one of many that determine the cost of a trip.

  • Ignoring complexity by controlling what you can

A policy of ‘divide and rule’ provides an illusion of control by dividing a planning challenge into manageable parts. For example, instead of optimizing the entire sequence of a multi-stage production process, planners may focus on optimizing individual stages while ignoring how each decision affects the process as a whole. Similarly, a service organization consisting of several departments may optimize the utilization rate of employees in each department while ignoring opportunities to save costs by deploying employees across the organization.

The culprits in both these cases are proxy KPIs that stand in place of the real KPIs the business needs to optimize. In the logistics example, the real KPI was the total cost of trips – and not the number of empty miles. In the case of the multi-stage production process, the real goal was to improve the productivity of the entire process rather than the output of individual stages.

Controlling what you can control, and planning by rules of thumb put complexity in the driving seat. Your business is organized around complexity, and the KPIs you steer by are chosen because there is simply no way to steer by the real indicators of operational excellence.

Are there other signs that a breakthrough is possible? Check out Part 2 in Arjen’s series on uncovering hidden optimization potential