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Posts Tagged ‘Nash equilibrium’

A prisoner’s dilemma when agreeing to a management schedule

May 14, 2019 No comments

Two software developers, both looking for promotion/pay-rise by gaining favorable management reviews, are regularly given projects to complete by a date specified by management; the project schedules are sometimes unachievable, with probability p.

Let’s assume that both developers are simultaneously given a project, and the corresponding schedule. If the specified schedule is unachievable, High quality work can only be performed by asking for more time, otherwise performing Low quality work is the only way of meeting the schedule.

If either developer faces an unachievable deadline, they have to immediately decide whether to produce High or Low quality work. A High quality decision requires that they ask management for more time, and incur a penalty they perceive to be C (saying they cannot meet the specified schedule makes them feel less worthy of a promotion/pay-rise); a Low quality decision is perceived to be likely to incur a penalty of Q_1 (because of its possible downstream impact on project completion), if one developer chooses Low, and Q_2, if both developers choose Low. It is assumed that: Q_1 < Q_2 < C.

This is a prisoner’s dilemma problem. The following mathematical results are taken from: “The Effects of Time Pressure on Quality in Software Development: An Agency Model”, by Robert D. Austin (cannot find a downloadable pdf).

There are two Nash equilibriums, for the decision made by the two developers: Low-Low and High-High (i.e., both perform Low quality work, or both perform High quality work). Low-High is not a stable equilibrium, in that on the next iteration the two developers may switch their decisions.

High-High is a pure strategy (i.e., always use it), when: 1-{Q_1}/C <= p

High-High is Pareto superior to Low-Low when: 1-{Q_2}/{C-Q_1+Q_2} < p < 1-{Q_1}/C

How might management use this analysis to increase the likelihood that a High-High quality decision is made?

Evidence shows that 50% of developer estimates, of task effort, underestimate the actual effort; there is sufficient uncertainty in software development that the likelihood of consistently produce accurate estimates is low (i.e., p is a very fuzzy quantity). Managers wanting to increase the likelihood of a High-High decision could be generous when setting deadlines (e.g., multiple developer estimates by 200%, when setting the deadline for delivery), but managers are often under pressure from customers, to specify aggressively short deadlines.

The penalty for a developer admitting that they cannot deliver by the specified schedule, C, could be set very low (e.g., by management not taking this factor into account when deciding developer promotion/pay-rise). But this might encourage developers to always give this response. If all developers mutually agreed to cooperate, to always give this response, none of them would lose relative to the others; but there is an incentive for the more capable developers to defect, and the less capable developers to want to use this strategy.

Regular code reviews are a possible technique for motivating High-High, by increasing the likelihood of any lone Low decision being detected. A Low-Low decision may go unreported by those involved.

To summarise: an interesting analysis that appears to have no practical use, because reasonable estimates of the values of the variables involved are unavailable.