The Optimal Implementation Strategy

From the Game Theory in Management Blog
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Modelling Business Decisions and their Consequences

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Among Game Theorists a favorite game for analyzing cooperation or defection among non-related biological units in a common environment is The Prisoner’s Dilemma. The basic version of the game goes like this: you are a prisoner, and your jailer comes to you and says that he will cut your sentence if you rat out your cellmate. The dilemma comes about when you realize that your cellmate will receive the exact same offer. There are four possible outcomes:

  • You both inform on the other, and each receive three years sentence.
  • Neither of you informs on the other, and you each get one year.
  • You rat out your cellmate, but he does not inform on you: you walk free, while he gets 5 years.
  • Your cellmate rats you out, but you don’t inform on him – he walks free, while you get five years (this is known as the “Suckers’ Payoff”).

In the 1980s, Robert Axelrod sponsored a tournament of computer programs playing multiple iterations of the Prisoner’s Dilemma against each other. Both conventional wisdom and the Nash Equilibrium had informed that the optimal strategy would be to always defect, since the player would never want to be on the receiving end of the Suckers’ Payoff, and always defecting was the only way to guarantee that. However, in the event, the winning program, named “Tit for Tat,” did not enact that strategy. Instead, it initially did not inform. Thereafter, it did whatever the opposing program did on the previous iteration. After the competition, some analysts looked in to why Tit for Tat’s strategy was successful. To that end, they developed some variants to compete against the original. One defected on the first iteration, and then did the Tit-for-Tat strategy; another cooperated the first five iterations, and then performed the Tit-for-Tat strategy, among others. All of the variants failed. The analysts concluded that Tit for Tat succeeded due to three factors:

  • It was originally nice. It cooperated.
  • It retaliated immediately for defection.
  • It forgave immediately and completely for cooperation.

I Would Normally Write “Meanwhile, Back In The Project Management World…” At This Point, But I’ve Been Talking PM This Whole Time…

For some time I had been struggling mightily with which broad-based PM implementation strategy could be considered optimal as I was doing research for my first book, Things Your PMO Is Doing Wrong (PMI® Publishing, 2008) when it hit me: make the implementation strategy incorporate Tit-for-Tat’s three factors! Consider:

  • When rolling out the new PM initiative, program, structure, whatever, make it “nice,” as in falling-off-a-log simple for the target organization to plug-and-play. From last week’s blog, the resistance tactic of claiming difficulty in advancing the PM capability is effectively blocked.
  • “Retaliate” is a bit strong. However, if you are counting on participation from some elements of the organization, and that participation isn’t forthcoming, you can’t let that slide. You MUST respond, and effectively. Again from last week’s blog, this factor will negate the “Slow Roll” or “Silent Veto” counter-strategies.
  • If you are receiving cooperation, but the data is of poor quality, then the participants are golden. Data quality can be improved, but deliberate non-participation cannot.

I would like to call GTIM Nation’s attention to the first factor of the Optimal Strategy, that of making the advancement in capability extremely easy to implement, since it does contradict much of what passes for insight on what needs to be included in a PM advancement effort. Conventional wisdom holds that, in order to implement a valid, or quality, or advanced, or authentic (choose your superlative) Project Management Information System, the person directing the effort must include such things as a robust risk management system, or a quality program, or a communications management plan, or a comprehensive set of procedures, or training, or, or, or.  The list is as long as the number of self-styled experts who have latched on to some aspect of PM that lies outside the mainstream ideas of Scope, Cost, and Schedule, muddying the waters of a clearly articulatable approach to a common management problem.

And here’s the infuriating part: once all of the ancillary “experts” have larded up the implementation strategy so that it’s anything but simple to roll out, they will turn around and claim that any system that actually is easy to install simply must be invalid. To be fair, it’s basic human nature to reflexively reject the notion that complex problems could have a simple solution. But the cynic in me can’t help but believe that another factor is that, should the experts’ pet analysis technique become ensconced in the PM codex as being a key or critical component of a truly valid PMIS, then those experts’ area of expertise will see an increase in demand, making them and their like-minded comrades more valuable to organizations struggling with the best way of advancing PM.

I have incorporated these three factors in the implementation strategy for small organizations, all the way up to very large portfolios, and it has always delivered an effective PMIS in an unexpectedly brief amount of time, all while demonstrably advancing PM maturity. GTIM Nation knows that I’m no ringer for the Game Theory crowd – I have often called out deficiencies in their approach, usually for failure to take into account sufficient parameters to provide a strongly analogous “game.”

But not this time. This time, Game Theory has painted a great big epistemological arrow for we PM-types to see what the optimal general implementation strategy ought to include. The fact that it happens to exclude risk managers is just icing on the cake.

Posted on: July 22, 2019 09:35 PM | Permalink

Comments (4)

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Thanks for this article. I love it when the simple approach is best.

Perfect. Thank you for sharing your insights

Nice post Michael.

Sort of be nice (treat people well), but don't be a chump?
Fail fast, fail early ... and then (potentially) recover fast and well?

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