Mo’Better Risk — Tournaments and Games of Failure Part II

My last post discussed economic tournaments and games of failure in how they describe the success and failure of companies, with a comic example for IT start-up companies.  Glen Alleman at his Herding Cats blog has a more serious response in handily rebutting those who believe that #NoEstimates, Lean, Agile, and other cult-like fads can overcome the bottom line, that is, apply a method to reduce inherent risk and drive success.  As Glen writes:

“It’s about the money. It’s always about the money. Many want it to be about them or their colleagues, or the work environment, or the learning opportunities, or the self actualization.” — Glen Alleman, Herding Cats

Perfectly good products and companies fail all the time.  Oftentimes the best products fail to win the market, or do so only fleetingly.  Just think of the roles of the dead (or walking dead) over the years:  Novell, WordPerfect, Visicalc, Harvard Graphics; the list can go on and on.  Thus, one point that I would deviate from Glen is that it is not always EBITDA.  If that were true then both Facebook and Amazon would not be around today.  We see tremendous payouts to companies with promising technologies acquired for outrageous sums of money, though they have yet to make a profit.  But for every one of these there are many others that see the light of day for a moment and then flicker out of existence

So what is going on and how does this inform our knowledge of project management?  For the measure of our success is time and money, in most cases.  Obviously not all cases.  I’ve given two cases of success that appeared to be failure in previous posts to this blog: the M1A1 Tank and the ACA.  The reason why these “failures” were misdiagnosed was that the agreed measure(s) of success were incorrect.  Knowing this difference, where, and how it applies is important.

So how do tournaments and games of failure play a role in project management?  I submit that the lesson learned from these observations is that we see certain types of behaviors that are encouraged that tend to “bake” certain risks into our projects.  In high tech we know that there will be a thousand failures for every success, but it is important to keep the players playing–at least it is in the interest of the acquiring organization to do so, and is in the public interest in many cases as well.  We also know that most IT projects by most measures–both contracted out and organic–tend to realize a high rate of failure.  But if you win an important contract or secure an important project, the rewards can be significant.

The behaviors that are reinforced in this scenario on the part of the competing organization is to underestimate the cost and time involved in the effort; that is, so-called “bid to win.”  On the acquiring organization’s part, contracting officers lately have been all too happy to award contracts they know to be too low (and normally out of the competitive range) even though they realize it to be significantly below the independent estimate.  Thus “buying in” provides a significant risk that is hard to overcome.

Other behaviors that we see given the project ecosystem are the bias toward optimism and requirements instability.

In the first case, bias toward optimism, we often hear project and program managers dismiss bad news because it is “looking in the rear view mirror.”  We are “exploring,” we are told, and so the end state will not be dictated by history.  We often hear a version of this meme in cases where those in power wish to avoid accountability.  “Mistakes were made” and “we are focused on the future” are attempts to change the subject and avoid the reckoning that will come.  In most cases, however, particularly in project management, the motivations are not dishonest but, instead, sociological and psychological.  People who tend to build things–engineers in general, software coders, designers, etc.–tend to be an optimistic lot.  In very few cases will you find one of them who will refuse to take on a challenge.  How many cases have we presented a challenge to someone with these traits and heard the refrain:  “I can do that.”?  This form of self-delusion can be both an asset and a risk.  Who but an optimist would take on any technically challenging project?  But this is also the trait that will keep people working to the bitter end in a failure that places the entire enterprise at risk.

I have already spent some bits in previous posts regarding the instability of requirements, but this is part and parcel of the traits that we see within this framework.  Our end users determine that given how things are going we really need additional functionality, features, or improvements prior to the product roll out.  Our technical personnel will determine that for “just a bit more effort” they can achieve a higher level of performance or add capabilities at marginal or tradeoff cost.  In many cases, given the realization that the acquisition was a buy-in, project and program managers allow great latitude in accepting as a change an item that was assumed to be in the original scope.

There is a point where one or more of these factors is “baked in” into the course that the project will take.  We can delude ourselves into believing that we can change the course of the trajectory of the system through the application of methods: Agile, Lean, Six Sigma, PMBOK, etc. but, in the end, if we exhaust our resources without a road map on how to do this we will fail.  Our systems must be powerful and discrete enough to note the trend that is “baked in” due to factors in the structure and architecture of the effort being undertaken.  This is the core risk that must be managed in any undertaking.  A good example that applies to a complex topic like Global Warming was recently illustrated by Neil deGrasse Tyson in the series Cosmos:

In this example Dr. Tyson is climate and the dog is the weather.  But in our own analogy Dr. Tyson can be the trajectory of the system with the dog representing the “noise” of periodic indicators and activity around the effort.  We often spend a lot of time and effort (which I would argue is largely unproductive) on influencing these transient conditions in simpler systems rather than on the core inertia of the system itself.  That is where the risk lies. Thus, not all indicators are the same.  Some are measuring transient anomalies that have nothing to do with changing the core direction of the system, others are more valuable.  These latter indicators are the ones that we need to cultivate and develop, and they reside in an initial measurement of the inherent risk of the system largely based on its architecture that is antecedent to the start of the work.

This is not to say that we can do nothing about the trajectory.  A simpler system can be influenced more easily.  We cannot recover the effort already expended–which is why even historical indicators are important.  It is because they inform our future expectations and, if we pay attention to them, they keep us grounded in reality.  Even in the case of Global Warming we can change, though gradually, what will be a disastrous result if we allow things to continue on their present course.  In a deterministic universe we can influence the outcomes based on the contingent probabilities presented to us over time.  Thus, we will know if we have handled the core risk of the system by focusing on these better indicators as the effort progresses.  This will affect its trajectory.

Of course, a more direct way of modifying these risks is to make systemic adjustments.  Do we really need a tournament-based system as it exists and is the waste inherent in accepting so much failure really necessary?  What would that alternative look like?