Game Theory in Management

According to The Daily Beast, there are a whole lot of things that are more likely to happen to you than winning the lottery, specifically, the American lottery MegaMillions (Note to my readers: I’m not shilling for MegaMillions, I’m just using them to point out the folly of Gaussian Curve aficionados). How these odds are calculated is not provided, but the following are supposedly more likely than winning a jackpot:

• Death by vending machine
• Airline-related terrorist attack
• Having identical quadruplets
• Becoming President of the United States
• Dying in an asteroid apocalypse[i]

…among others. Keeping with my deep-seated skepticism about anything statisticians assert, I did a little digging on my own. Consider:

• Since MegaMillions began in 2002, there have been an average of 14.7 jackpot winners per year.
• Death by vending machine: 2 -3 per year[ii]. This appears to be less likely.
• Airline-related terrorist attack: none in the United States since 11 September 2001. Ditto.
• Having identical quadruplets: I couldn’t find definitive numbers for the United States, but experts estimate there are currently 50 sets worldwide[iii]. In order for this to be more likely than winning the lottery, the sample set would have to be only 3.57 years long, and that’s worldwide. I’m calling this less likely, as well.
• Becoming President of the United States: 1 every 4 years, at most. I mean, seriously, how does anybody conclude that something that happens .25 times per year is more likely than something that happens more than 14 times per year?
• Dying in an asteroid apocalypse: zero incidents in recorded history. Compared to 219 MegaMillions winners total, I’m thinking that the whole asteroid apocalypse thing is just a bit less likely than winning the lottery.

Again, I have no idea how these odds were computed, but verifiable performance reveals that these computations were, well, wrong. I mean, seriously – death due to asteroid apocalypse is more likely than something that’s happened 219 times since 2002? Do these people even read what they’re asserting?

I think the reason that The Daily Beast’s published assertions were wrong has to do with the nature of calculating possible future outcomes. A “fair” coin – one that’s perfectly balanced, I guess – when flipped, will come up heads half the time, and tails the other half. Even here, though, causes me to wonder: how hard could it be for a patient person to learn to flip a coin in such a way as to lead to a result where the flipped coin would land the same side up as when it was positioned for flipping? I imagine it wouldn’t be easy, but it probably isn’t impossible. And, if this, the ultimate in binary-outcome randomness, can be influenced, what scenario can’t?

Meanwhile, Back In The Project Management World…

As I’ve maintained for years now, the future cannot be quantified, therefore the optimal project management strategy for any given situation cannot be calculated. The projected outcome from individual decisions may (or, realistically, may not) be estimable, but that’s not the same thing as calculating an optimal strategy. Even within the confines of game theory, the strategies that lead to maximizing a given participant’s payoff rarely translate to supposedly analogous real-life situations. But that doesn’t stop risk management experts from claiming that they can do so, no siree. If you think about it, though, there’s really nothing to stop them. When they are transparently wrong, they can always point to the occurrence that upended their “analysis” as being from the realm of the “unknown unknowns.” Convenient, huh?

Now, I am aware that no risk management specialist worth the title claims to be able to predict the future with usable certainty. They will maintain that they are simply identifying risks that may negatively impact their organizations – until they aren’t, and insist that “opportunity management,” or “upside risk,” is part and parcel of risk management, even though those aspects of the word “risk” appear nowhere in any reputable dictionary.

So, to the two or three remaining risk management specialists who read this blog, I have some advice for you. When generating an estimate of the things that are, say, more likely to happen to a person than winning the lottery, you might want to start with one critical data point: how many people tend to win the lottery? And, if it averages out to 14.7 people per year, seek out statistics on things that happen more often than that. Does this sound like common sense? Well, it is. Does it also sound simple? It most certainly is not, for it represents a paradigm shift in the way risk management is conducted. The implication is that the future, to the extent that it can be grasped in any meaningful way, is best projected based on past performance. Project-ruining occurrences tend to happen to project teams that historically perform poorly, no matter the identified and “quantified” cause. No amount of hyper-ventilating analysis based on Gaussian curves can change that.

Now, if you’ll excuse me, I think I'll go buy a lottery ticket.

[i] Retrieved from https://www.thedailybeast.com/15-things-more-likely-to-happen-than-winning-mega-millions, 11 November 2017, 13:46 MST.

[ii] Retrieved from https://www.quora.com/Fact-Vending-machines-kill-4-times-as-many-people-as-sharks-per-year-How-can-that-be on 13 November 2017, 18:45 MST.

[iii] Retrieved from https://www.livescience.com/52613-identical-triplets-quadruplets-science.html on 13 November 2017, 18:46 MST.

From an article entitled “Less Work For Mother,”:

In the early 1960s, when synthetic no-iron fabrics were introduced, the size of the household laundry load increased again; shirts and skirts, sheets and blouses that had once been sent out to the dry cleaner or the corner laundry were now being tossed into the household wash basket. By the 1980s the aver- age American housewife, armed now with an automatic washing machine and an automatic dryer, was processing roughly ten times (by weight) the amount of laundry that her mother had been accustomed to. Drudgery had disappeared, but the laundry hadn’t. The average time spent on this chore in 1925 had been 5.8 hours per week; in 1964 it was 6.2.[i]

Meanwhile, back in the PM world of the 1980s…

I’m old enough to remember a time when, for contractors working for the United States Department of Defense, our cost and schedule performance reports would be typed (on an IBM Selectric®, no less) onto a printed form from the Government Printing Office. Of course, all of the calculations for the time-phased budget (Budgeted Cost of Work Scheduled, or BCWS), the Earned Value (Budgeted Cost of Work Performed, or BCWP), and actual costs (Actual Costs of Work Performed, or ACWP), as well as the associated indices and percentages, were done by hand, calculator (no, not the kind you had to hand-crank – don’t be ridiculous) or, on occasion, on one of the new-fangled spreadsheet programs (Lotus 1-2-3® was the favorite, although Quattro® was coming on strong. Microsoft Excel® wouldn’t become the go-to application for another decade[ii].). It was, obviously, somewhat time-consuming, but we consistently delivered our reports on-time, and somehow managed to bring in our projects (mostly) on-time, on-budget.

Fast forward to the 21^st Century, and the very idea of using a typewriter is absurd, much less for generating formal project performance reports. Both desktop computers and Project Management software applications have advanced significantly, so we’re all processing more and better PM information, right? Well, much like the change in clothes-washing technology meant more clothing was being cleaned, the new hardware and software capabilities are processing much more data.

But is it better information?

Meanwhile, back in the PM world of 2017…

Certain guidance and procedure-generating organizations that I won’t name keep sending out missives on the subject of what constitutes more advanced PM information, much of it silliness. A few examples include:

• In the Critical Path Schedule, one of them actually proposes a limit (a very low limit, at that) for the number of activities that can be logically linked via a start-to-start relationship. What if the nature of the project work is such that that’s the most appropriate way of logically linking those activities? Tough.
• A similar limit is mandated suggested for finish-to-finish relationships.
• There’s also a lot of churn on the amount of float in the schedule network, again regardless of the match of the specific project’s work with the logical links among its activities.

Each of these is asserted due to a supposed vulnerability of project schedules that have multiple start-to-start, finish-to-finish, or high-float elements to hiding or camouflaging negative variances. I have never – and I do mean never – seen any hard data supporting this assertion. It seems to always based on hypothetical scenarios.

Then there’s the ultimate data collecting and crunching waste, that of comparing the project’s time-phased budget to its actual costs. There was a time when anybody asserting that this is an appropriate (much less necessary) PM analysis technique would have been immediately recognized as a hack. But now, some guidance-generating organizations are actually calling for it to be performed, and even amped up: this analysis must now be executed at a level of granularity all the way down to the line-item level in the original basis of estimate as it compares to the line-item level in the general ledger. The reason why this analysis is provably useless at higher levels, but suddenly takes on the patina of legitimacy when it’s performed at a sufficiently detailed level, is not provided.

Now back to the 1980s…

It’s analogous to our 1930s American housewife, having access to 1980s clothes-washing technology, electing to run the exact same clothes through the washer to the dryer, and then simply loaded them back into the washer, without expanding the amount of laundry actually being cleaned. In order for the act of cleaning clothes to have any value whatsoever, the clothes in question must actually need cleaning. Similarly, in order for all of this advanced data processing capability to have any significance whatsoever, the resulting analysis must be relevant. Using advanced data processing capacity to deliver irrelevant data isn’t advancing Project Management science. It is, in fact, wasting time and energy when so many of the existing techniques, which have been shown to work (like the calculated Estimate at Completion), are being elbowed aside.

Rather than embrace these “advanced” techniques, we would be better served making more use of the IBM Selectric®.

[i] Retrieved from http://www.americanheritage.com/content/less-work-mother, November 3, 2017, 20:36 MDT.

[ii] Microsoft Excel. (2017, November 1). In Wikipedia, The Free Encyclopedia. Retrieved 02:43, November 4, 2017, from https://en.wikipedia.org/w/index.php?title=Microsoft_Excel&oldid=808192493.

As we wrap up October and its theme of Portfolio Management, I’d like to take some time to examine what it is that sets Portfolio Managers apart from other types of managers, and some of the ensuing implications. In last week’s blog I discussed how Portfolio Managers can be expected to be the targets of Asset, Project, and Strategic Managers, all of whom will want to sell their ideas of discipline pre-eminence: the Asset Managers will try to push the notion that all management is purposed towards maximizing shareholder wealth, the PMs will want an emphasis on meeting project performance goals with respect to scope, cost, and schedule, while the Strategic Managers will seek to maximize the organization’s market share. Going back further in time, this blog often takes aim at what I consider to be invalid management practices, notions, and information systems, and the business-decision follies that can (and do) result from their presence within the organization. Now, I want to combine these two notions into a hopefully useful insight that will add clarity to the Portfolio Managers job, if not make it out-and-out easier.

Virtually all Portfolio Managers will be confronted with managers seeking to further their particular discipline’s organizational interest, usually at the expense of others (old conservative axiom: there are no solutions, only trade-offs). When these managers do so with clearly invalid techniques or strategies (and, yes, I’m looking at you risk managers), it’s relatively easy to identify and frustrate these actions. But what happens when the techniques being pushed have been proven to be useful or effective, but they’re being pushed into areas where they lose this effectiveness?

The Significance of St. Crispin’s Day

This past Wednesday was the 602^nd anniversary of the Battle of Agincourt, where Henry V of England and his army of approximately 7000 were intercepted by a French army of over 30,000 in a field bounded on both sides by thick woods. Dating from even before the Battle of Cannae in 216 BC, numerically superior armies had great success by encircling their opponents, and attacking from all sides, particularly if the attacking forces had superior mobility (e.g., cavalry units available). But this technique was unavailable to the French, since the field of battle was relatively narrow and, as previously mentioned, bounded by forest. Even without the envelopment tactic available to them, the French were confident of victory, since not only did they outnumber the English, but their armor was superior as well. Unfortunately for the French, the field of battle had been recently ploughed, and it rained heavily the night before. By the time the vanguards of the two armies were within weapons range of each other, the French knights, wearing around 60 lbs. of armor, were exhausted and sinking into the mud, making them easy targets for the lightly (if at all) armored English longbow archers. The ensuing fighting resulted in an astonishingly lopsided victory for the English.

As the martial equivalent of Portfolio Managers, the French leadership (Charles d’Albret) was, no doubt, thoroughly familiar with the traditional tactics of advancing his goals, in this case envelopment, or simply overwhelming the opponent with superior arms and armor. But 602 years ago those two techniques, as successful as they were in many other occasions, were not only ineffective, but disastrous for the superior French forces. The conditions on the day of battle had changed so significantly that the familiar strategies would have had to have been abandoned if there was to be any hope of victory, either by retreating to a place large enough for envelopment, or arranging to fight on more solid ground, or both.

Meanwhile, back at the Portfolio Management Program Office

Managerial advisors and their Management Information Systems (MISs) are thoroughly familiar with the traditional techniques and strategies that will allow the organization to advance on its overarching goals. The challenge for the Portfolio Manager is to quickly and accurately identify those situations where the traditional techniques do not work, and those advising their use must be ignored. In short, rule number one for the Portfolio Manager is to question every tactic, technique, or strategy that they’ve been taught will work in most (or all) managerial situations, and be prepared to abandon such approaches when the situation merits it. And rule number two: even rule number one should be questioned, from time to time.

This is why those executives who seek to fulfill the role of Portfolio Manager, but can’t be convinced to alter their technical approach to management problems, will almost always represent one of the greatest threats to the overall success of the organization. If they can’t recognize their own moribund, staid, and pathology-ridden techniques and eliminate them, how can they be expected to do the same with the other types of management?

According to FOOD52, the Japanese cuisine item sushi made its American debut in Los Angeles, California, in the late 1960s[i]. By the 1990s its popularity had exploded to the point that it was not at all unusual for people in the Midwest to go out for sushi, and restaurants that served it were positively ubiquitous in the major cities. Another venue for serving sushi was gas stations, which might strike my overseas readers as strange, since sushi is made up of, basically, fresh, uncooked fish, seaweed, and rice, with a variety of additional ingredients typically available. Uncooked fish doesn’t stay fresh (or even edible) for long, not to mention seaweed. And gas stations aren’t known for their ability to produce, maintain, or sell items that have particularly short shelf-lives, historically opting for foodstuffs that could probably survive a nuclear attack. I don’t mean to disparage entire retail chains selling a particular item – but I would never eat sushi sold at such a venue.

Meanwhile, back in the Project Portfolio Management World…

Referring back to my personal adaptation of the Pareto Principle, that the 80^th percentile best managers with access to 20% of the information needed to obviate a given decision will be out-performed by the 20^th percentile worst managers with 80% of the information so needed, it goes without saying that successful Portfolio Managers either have to be extremely advanced (or consistently lucky), or simply appropriately informed of the issues surrounding and impacted by the decisions they make. Okay, but with various managers, analysts, and information specialists all vying for the Portfolio Manager’s attention in order to hawk their own preferred information streams (which demand a very specific type of expertise, held only by those pushing them, don’t you know), how is our nominal Portfolio Manager to differentiate between the valid ones, and those that are useless, or even detract from the targeted 80%? I mean, Chief Financial Officers have been known to insist that everything that the Portfolio Manager needs to know can be derived from the general ledger – surely our PortMan should listen to him!

Yeah, and if you believe that, then you may also be consoled by the fact that gas station sushi in Ohio looks a lot like authentic Japanese restaurant sushi from Honolulu.

Those proffered information streams come at you fast

The thing about the types of information that the PortMan needs to make better decisions that her competitors is that, like sushi, it has a very short shelf-life. How to arrive at the best strategy to leverage assets, project performance, and market share to attain the organization’s overarching goals is an elusive solution, which lives in a dynamic, fast-moving environment. As I asserted in last week’s blog, there are precious few usable formulaic approaches, and even among those none are effective across a wide range of industries or situations. But, if I can’t tell my readers what’s the consistently-right answer, I can jolly well warn them of the wrong ones.

One sure tell that the person pushing a certain type of analysis doesn’t have a valid basis is if they ask the question “Why wouldn’t you want to have this information?” Management Information Systems (MISs), like anything else of value, take time to set up, feed, and maintain. If a given MIS’s output does not provide timely, accurate, and relevant information, then all the energy that went into setting it up, collecting its data set, and maintaining it is wasted. Not only that, but the valid system that should have been set up in its stead doesn’t go on-line, and that 80% goal slips further and further away. So, when any of the MIS-pushers invoke this line of persuasion, as if management information just kind of exists out there, and it’s free for the taking, then something is definitely wrong with their grasp of efficacy.

Another sure-fire indicator of an invalid MIS has to do with its structure. All valid MISs have this (very general) structure in common: (1) data is gathered, based on some discipline (2) the data is processed into information, based on some methodology (like Earned Value or Critical Path) (3) the information is delivered to the decision-makers in a format they can readily understand. Conversely, invalid MISs are often structured like a poll. A central data repository is surrounded by input/output nodes, and the “information” is pulled from it as needed. The two problems with polls are that (1) someone always has better or more accurate data, and (2) the “data” they contain are usually hearsay or subjective perceptions, which are inherently unreliable from the get-go. Polls’ data goes bad faster than unrefrigerated, uncooked fish.

We know where we’ve been, can we know where we’re going?

One final sure-fire indicator that a proffered MIS is less usable than small units of seaweed-wrapped bait has to do with whether it’s a feedback or feed-forward system. Feedback systems are based on events that have already occurred, so that their data is verifiably accurate. Feed-forward systems, by contrast, are based on projections of what experts (both real and fake) believe will happen in the future, meaning that the data in these systems is highly subjective, and, therefore, highly unreliable. Unfortunately, this is the very type of system that modern-day risk managers use, as both decision-tree analysis and Monte Carlo simulations involve collecting experts’ opinions of how the future might unfold differently from the projects’ baselines, guess estimating the odds of the alternate outcome, and cost or schedule impact.

And larding over these guesses estimates with statistical jargon does not remedy this foundational error.

Ignoring any of these warning signs is analogous to purchasing fine Japanese cuisine from an establishment with a primary purpose of pumping petrol out of underground tanks for use in automobiles. It’s possible that both the information and sushi are ingestible, but you’d be better off with one of those hot dogs that’s been turning around and around on the steel-cylinder heating unit since the last Bush administration.

[i] Retrieved from https://food52.com/blog/9183-the-history-of-sushi-in-the-u-s on October 21, 2017, 13:27 MDT.

Before I get to my promised (from last week’s blog) workable definition of Portfolio Management, I want to pass along a little story from my younger days. There was a car I would occasionally see in traffic that looked like a 1978 Lincoln Continental Mk. V (a luxury coupe), but with a really weird twist: its suspension was significantly raised with oversized wheels and extended suspension so that the bottom of the chassis was at least four feet off of the surface, by my estimation. It also had a custom paint job, with the words (I swear I am not making this up) “High Class” written in script on its running boards.

Being something of a car aficionado myself, I must say this is a remarkable fail. Unless the Mark V’s original drivetrain was replaced, it likely had an engine that cranked out an anemic 225 horsepower into a three-speed automatic transmission, comically inadequate for the job of off-road racing, rock-climbing, or any of the other uses that raised sports vehicles typically perform. On the other hand, if this autofrankenstein’s owner had in mind that he was enhancing a luxury coupe’s function, I have to believe he was gravely mistaken. Just getting into the thing must have required a small stepladder – hardly the automotive accessory bound to impress the girl you’ve asked to the prom (a quick insight into car guys’ thinking: the acid test for any luxury car is whether or not you would want to show up to your prom date’s daddy’s house in it).

Meanwhile, Back In The Project Management World…

In my previous writings where I point out that Asset Management, Project Management, and Strategic Management are three very different disciplines, with different goals, methods, and associated management information systems supporting them, I have referred to the macroeconomic examples of hostile takeovers, vampire advertising campaigns, etc.to support my assertion. But there is another genre where these differences manifest themselves – tool usage.

Even a cursory review of management information tool misusage confirms my thesis. When Asset Managers (read: accountants) seek to generate, say, the Estimate at Completion costs for a given project, they invariably use either spend variances or a regression analysis of actual costs, both of which return inaccurate projections. No matter: the accountants will insist that this ridiculous methodology is reliable, when the valid source of this information is an Earned Value Management System. Attempting to use the general ledger tool to produce a PM product is the management science equivalent of absurdly raising the suspension of an American luxury coupe, and thinking that some improvement had been achieved.

And it’s not just general ledger overreach

On the other hand we have attempts to use PM tools for resource management, as in those cases where Work Packages are developed for organizational breakdown structure elements. Work Packages, of course, capture pieces of scope, which are then costed and scheduled. The generic test for whether or not an element of work should be captured in a Work Package is the question: what percent complete are you? If the WP manager is in charge of a piece of scope, this is an answerable question. Alternately, if the manager is responsible for a function, or a resource, this is an unanswerable question. And, if this is an unanswerable question, then the work being managed (almost always) should not be managed as a project, and any cost or schedule performance data produced is bound to be error-filled.

Need more evidence? Ask your accountant to pull information from the general ledger about how your organization is performing against other companies’ project teams. Surely this is essential Strategic Management information – and yet, the self-appointed keepers of all relevant management data simply cannot deliver in this arena.

What tool misuse can tell us

All of which leads us to a workable definition of Portfolio Management. Begin with the premise that Asset Management, Project Management, and Strategic Management are fundamentally different. What’s called for in intelligent Portfolio Management is a balance among the three types, an acknowledgement that an inherent conflict of epistemological interests is in play. Imagine yourself as a “portfolio manager” in whatever organization, occupying whatever role-title that entails. Unless your Chief Information Officer oversees a hot mess of information streams that conflict, overlap, or serve no purpose, there’s a decent chance that your primary petitioners will want you to decide in favor of one of three goals:

• Maximize shareholder wealth (Asset Managers)
• Improve project performance (Project Managers)
• Increase market share (Strategic Managers)

… which almost always conflict with each other. That’s why no single software platform can provide THE information stream for the portfolio manager – they’re inherently rooted in one of these widely disparate types, and typically project that particular type’s techniques into arenas where they quickly lose efficacy. Portfolio Management cannot be reduced to a formulaic analysis, no matter how complex those algorithms may be.

With all that having been written, here’s the promised workable definition of portfolio management:

Portfolio Management is the pursuit of balancing the organization’s initiatives among Asset, Project, and Strategic goals in order to attain the organization’s overarching, or consolidated objectives.

Yes, I know I’m probably the only person who thinks this way, but all of the other definitions I’ve seen always seemed to be lacking precision, as if airy or inchoate but sophisticated-sounding management science-babble could serve as a structure for advancing portfolio management maturity. You may as well raise the suspension of an iconic luxury car, and call it “High Class.”

Oh, wait, that’s been done already.