The Science of Kanban – Economics

This is the fourth part of a write-up of a talk I gave at a number of conferences last year. The previous post was about the science of process

Having a good understanding of how creative people can have an efficient process still isn’t enough however. As Russell Ackoff is often quoted as saying, “It’s better to do the right thing wrong, than the wrong thing right”. An understanding of economics is needed to avoid “doing the wrong thing right”, by focussing on the “right thing”, whether that involves financial return, risk management or information discovery, all of which are of value. One financial model that I picked up from Chris Matts is that features should increase future revenue, protect existing revenue, reduce existing costs, or avoid future costs.

Life Cycle Profits

A basic understanding of investment over time helps explain why smaller batches and smaller increments are preferable from an economic perspective. In Software by Numbers, Denne and Cleland-Huang show the investment, payback and profit periods. A smaller cash injection, over a shorter investment period, can enable a product to become self-funding and break-even sooner, such that the profit can be invested back into the product for continued development.

Cost of Delay

The Cost of Delay concept, as popularised by David Anderson, further informs scheduling decisions based on cost over time. The four most common archetypes used (but limited to) are:

• Expedite – the cost of delay is high and immediate. These items are genuinely urgent and should be prioritised above everything else.
• Standard – the cost of delay rises linearly. Examples are items with an opportunity cost, where the later the delivery, the more opportunity for gain is lost.
• Fixed Date – the cost of delay rises sharply at a specific date. Examples are regulatory dates at which fines may be imposed, or seasonal dates such as Christmas or trade-shows.
• Intangible – the cost of delay is likely to happen in future, but the exact nature is unpredictable. Examples are technical debt or infrastructure work

Information Theory

Value does not have to be purely financial. In particular there is often value in information generated, as suggested by information theory.

Information Theory says that for experiments with pass/fail results, a 50% failure rate is optimal. Always failing suggests that nothing is known, and subsequently nothing is being learned. Always succeeding suggests that everything is already known, and thus nothing is being learned.

The Lean Startup approach is essentially based on information theory, with the goal being to loop through the Build, Measure and Learn cycle as quickly as possible.

This can be thought of as buying information, and asymmetric payoff curves help explain the benefits of this approach. Given some notional performance target, an asymmetric payoff curve is one where being below target results in a loss, being above target results in a gain, and hitting the target results in breaking even. Buying information enables the shape of the curve to be changed such that losses below target are minimised, and gains above target are maximised.

Scheduling

Having a good understanding of the economics enables better decision making when designing and scheduling the work. Usually selection of what work should be pulled next relates to cost and value. Higher value for lower cost generally trumps lower value for highest cost.

An example is risk reduction. There is value in risk reduction, where the higher the risk, the greater the value there is in reducing it, and there is also a cost associated with reducing the risk. Having an understanding of the relative values and costs of risk reduction activities informs the sequencing of high value, low cost items earlier and low value, high cost items later.

Similarly Set Based Concurrent Engineering can be informed by economics. SBCE involves working on multiple parallel initiatives in order to reduce risk. Multiple initiatives should only be run while the total cost of the initiatives is less than the value of the risk reduction. Each additional initiative adds less value exponentially, while the total cost rises linearly. Multiple experiments are like buying insurance; when the cost of the insurance is greater than the economic benefit, it’s not worth paying for.

In the final part, I’ll draw together some conclusions.