On Attempting To Kill Darth Vader With A Blaster

 

What’s a “blaster?” We don’t know exactly, because a working model hasn’t been invented yet in this galaxy; however, we have many, many examples of how they work in the setting for the Star Wars movies, that galaxy far, far away, and have seen it in action. They come in various sizes, from a pistol-sized personal weapon all the way up to massive ship-mounted cannons. No matter the size, when fired they shoot out a bright segment of a beam of light, of various colors, accompanied by a distinctive high-pitched sound. The Jedi eschew them as being “uncivilized,” and “random.” Nevertheless, they appear to be the go-to weapon of virtually every non-Jedi or Sith combatant in the Star Wars series of films. A well-placed shot will kill on impact (e.g., Greedo in the original release), while a glancing shot will create a painful wound (Leia, in Return of the Jedi). The personal blasters used by storm troopers can take down armored vehicles (the Jawas’ sand crawler in the original), and transmit a considerable amount of heat (in The Empire Strikes Back, the walls in Cloud City that were hit near Luke were not only cratered, but at least one of them was maintaining a small flame).

In four of the first six Star Wars films, Darth Vader (the evil version of Anakin Skywalker) spends considerable time as an apex villain, naturally attracting his share of blaster fire. Not only is Vader capable of deflecting individual blasts using his light saber, he can completely absorb a personal blaster shot, from extremely close range, in the palm of his hand (The Empire Strikes Back). So, what does end up killing Darth Vader? It would appear to be a combination of exhaustion from participating in a light saber duel with his son, Luke Skywalker, followed closely by an intense dose of Sith “lightning,” intended to kill Luke but intercepted by Vader as the Emperor is being tossed down a massive power generating shaft.

Meanwhile, Back In The Project Management Galaxy World…

While my poison-pixel criticisms of common risk management analysis techniques have been bright, powerful, and leave flaming craters behind, they have not brought down the massive risk management empire, estimated at $11 Billion (USD) in 2016.[i] Since I view risk management as being the apex villain of the Project Management Galaxy World, it’s incumbent on me to stay true to my Jedi early PMP® training, and thwart their attempts at taking over the management universe. Think I’m exaggerating their intentions? The last time I challenged a well-known risk management expert to define the purview of RM, he responded “any event or condition that can have an impact on a project, positive or negative.” He was somewhat taken aback when I pointed out that that definition not only covered every other aspect of management, but of living life in general. So, yeah, I''m okay with the belief that they’re out to take over the management world.

But pointing out the logical flaws in their techniques appears to have done little more than earn me a spot on their “Most Despised Business Writers” list. Clearly, I need a more effective strategy if I’m going to convince a plurality of my readers that these guys are, well, wrong. And to find that strategy I only needed to look at their genre, where a better approach readily presented itself. You see, risk management falls within the genre of Predictive Analytics, along with regression analysis, descriptive systems, and … Game Theory!

As confirmed members of GTIM Nation know, one of the favorite tools of Game Theorists is the payoff grid. Personally, I can’t seem to string together more than five or six blogs in a row without using one. Let’s do one on risk management, shall we? Consider:

Let’s dismiss Scenario C right off the bat. If the risk analysts failed to predict an event that didn’t happen anyway, then the control set is literally infinite (though I can’t help to wonder what number would be assigned to the “wasn’t predicted, didn’t happen” scenario that involves a Sith Lord arriving on the project’s job site and destroying everything with a lightsaber).

Scenario B appears to contradict my thesis, no? The risk analyst predicted that something “positive or negative” would happen to the project, and that thing occurred! Let’s set this scenario aside for just a few more sentences.

I’ve been proposing an experiment to reveal the number of times Scenario A has happened. That experiment would be to have the risk managers and Earned Value analysts compile a list of projects/tasks at the reporting level of the Work Breakdown Structure that are going to overrun, and eliminate the agreed-upon tasks. The remainder would represent a workable test of risk management efficacy – and I’m confident I know who would win.

Scenario D happens all the time, but somehow doesn’t erode the confidence placed in risk management techniques. Why is that? It’s due to the same reason that Scenario B, when it actually occurs, fails to serve as supporting evidence.

Read any project’s risk management plan, or analysis. Whichever technique is employed (categorization, decision tree, Monte Carlo, whatever), the results are the same: There is an X% chance that scenario N will occur, having a cost impact of Y dollars and Z units of time. They’re not even really predicting anything! Such an analysis has all the relevance of being reminded that, prior to flipping a fair coin, the odds of it landing heads-up are 50-50. When Scenario A unfolds, the risk managers can point to not having actually predicted that that something would happen, just that there was a possibility that it would happen. And, when Scenario D unfolds, they can always point to that wandering invisible unicorn of doom, the “unknown unknown” events (actually, the whole definition of “known unknowns” and “unknown unknowns” struck me as highly circular at best, and flat-out tautology at worst).

So, what has our payoff grid revealed? That risk management can’t produce anything that’s actually evaluate-able. When they’re “right,” they’re brilliantly insightful, don’t you know, but when they’re wrong, well, they didn’t actually predict a specific scenario would unfold now, did they?

Using one Predictive Analytic technique to showcase the intellectual vapidity of another might seem to be a bit unfair. After all, those endowed with The Force have a limited ability to perform a mystical version of Predictive Analytics. But, that being the case, maybe the Sith risk analysts should have seen it coming…

[i] Retrieved from https://www.globenewswire.com/news-release/2017/03/15/937815/0/en/Assessing-the-17-1-Billion-Technologies-for-Assessing-Risk-Management-Markets-Global-Report-2017.html on 6 July 2019, 14:01 MDT.