Project Management Saving The World
| GTIM Nation knows of my disdain for the old saw that the point of “all” management is to “maximize shareholder wealth.” Even though this assertion is easily overturned, it’s still commonly taught in business schools around the world. I firmly believe that this tenet of commonly-embraced management science is not only wrong, but its acceptance has led to a whole host of bad business decisions, and that its continued assumed preeminence represents a menace to the advancement of management science and, by extension, the success of all mankind. Okay, that’s a bit much to digest all at once, so let’s break it down into management-sized pieces, kind of like a Work Breakdown Structure. One of the biggest economic issues in the United States right now has to do with the development of data centers. These data centers have generated a great deal of controversy, mostly centering around their need for electricity and water, as well as their projected impact to the economies of the areas where they are located. Those in favor of these centers often point to the anticipated benefits of employment and generated tax revenue for whatever government is in place for that locale. From my perusal of the news/opinion pieces on their development, those opposed appear to have the much louder voices, and those voices are proving to be persuasive indeed. But consider: what’s the point of these data centers? It’s mostly to enhance current internet capabilities, but also to help advance the field of Artificial Intelligence, or AI. Okay, so what happens if AI becomes more advanced? Naturally, doomsday scenarios abound, much as they did when computers first became commonplace in the nominal execution of management duties. Last I checked, the world has not come under the control of a supercomputer threatening to attack multiple metropolitan areas with nuclear weapons, as in The Forbin Project. My best guess as to the impact of AI on management in general and Project Management in particular is that its use will reduce the number of dumb decisions made in business settings. As Milton Freeman famously said, “So that the record of history is absolutely crystal clear that there is no alternative way, so far discovered, of improving the lot of the ordinary people that can hold a candle to the productive activities that are unleashed by a free-enterprise system.”[i] Consider the folly of all of the businesses, large and small, that pursued unproductive to straight-up silly goals, and the economic resources that they ultimately wasted. Now consider what would happen if such business decisions were to be culled from the arena of workable ideas before they even sought funding, even by as much as 5%. If the businesses in the United States alone did this, the increase in GDP would be $1.514 Trillion (USD). Just for the record, besides the US, there are only 10 countries world-wide with a GDP above that increase. Of course, advances in AI are absolutely not confined to the US, and an improvement in better decision-making of only 5% might prove conservative. In short, advances in AI can have a profound positive effect on people’s lives across the globe. What’s standing in its way? The aforementioned opposition to data centers, for one. I do not have access to the board rooms and inner dealings of the executives who are seeking to construct these data centers, but it’s easy for me to speculate that at least some of them are being advised by their Note that I am absolutely not talking about stakeholders here. PMI defines stakeholders as “an individual, group, or organization that may affect, be affected by, or perceive itself to be affected by a decision, activity, or outcome of a project, program, or portfolio.” I’m talking about customers, both current and potential. Customers are different. Those pursuing data centers need to interact with them in such a way that they not only cease opposing these Projects, but will actually help make it happen. How to do that? Show them the product or service being provided, how it will make their (business) lives better, and by how much. This PM-orientation has the chance to utterly re-do the conversation with respect to the data centers, and, by extension, an improvement of the management sciences at a scale previously held to be unattainable. But that’s not going to happen under the “maximize shareholder wealth” paradigm. No, if the business world is to be saved, it simply has to be by Project Management. [i] Retrieved from https://www.azquotes.com/author/5181-Milton_Friedman/tag/capitalism on 26 August 26, 2026, 20:16 MDT. |
Posted on: August 31, 2026 10:34 PM
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Consultant, Or Auditor?
The answer to the question in the title might not be as clear-cut as some in GTIM Nation believe, and to demonstrate this let’s break out the Game Theorists’ favorite tool, the Payoff Grid. Consider that both consultants and auditors seek to review the target organization’s business practices as they manifest in its reviewable outputs, hoping to glean insights into its management techniques and how those techniques are eventually implemented and executed. This being the case, the two axes for the Payoff Grid readily present themselves: (1) Is the organization doing something correctly or incorrectly, right or wrong (as determined by either the named audit standard, or the Consultant’s personal opinion), and (2) Is the person making this determination correct, or incorrect? Here’s the Grid:
As is the case in most of these Payoff Grids, Scenarios B1 and A2 show the ideal, sought-after outcome. The Consultant/Auditor makes the right call, and revisions to the organization, its business model, and practices can be based on reliable information. But it’s in the abnormal Scenarios where the trouble lurks, so let’s get right into them. While both Auditors and Consultants are vulnerable to the abnormal Scenarios, the Auditors are more likely to err in A1, while the Consultants are more likely to err in Scenario B2. Here’s why. An Auditor will usually be hired by an agency outside the target organization, for the purpose of finding fault or errors in the way the target is executing scope, recording transactions, performing proper safety functions, etc., etc. To this end the Auditor would never want to find themselves making a determination that falls within Scenario B2, which would represent a failure on their part to correctly identify a real problem. A B2 error could end the Auditor’s career if that uncaught error ended up causing catastrophic results later. On the other hand, an A1 error has very little downside, at least to the Auditor. The target organization would simply have to spend more time and energy developing either an evidence package that explains why the determination is mistaken, or, in a surprisingly high number of cases, admit to the “error” and provide an evidence package on why it won’t happen again. Same Payoff Grid, but very different payoff scenario for the Consultant. Consultants are almost always hired by the host organization, meaning that somebody within said organization has recognized a vulnerability or shortfall in performance, thinks that they know the approximate area of causality, but lacks either the technical expertise or organizational clout to specifically identify and rectify it. Consultants in areas where the targeted practice or underlying management science is clearly and thoroughly captured in some sort of codex, and where the collection of the evidence package is well-proscribed (like in accounting) have a fairly straight-forward path. Not so outside those confines, as in Project Management, which brings us to our very first barrier to consultant accuracy: what’s the audit standard, or baseline against which the host organization is being evaluated? Typically, this would be the Consultant’s education and experience, augmented by some published standard, such as the PMBOK Guide®. But those three bases vary wildly – the PMBOK® alone has gone through eight revisions. All things fail by irrelevant comparisons goes the saying, and there’s going to be considerable pressure for the Consultant’s findings to be consistent with the things their sponsor suspected in the first place. Then we have the problem of mono-dimensionality. Recall the old saw “affordability, availability, quality: pick any two.” Does the host organization have a business model oriented towards availability and affordability? Then the recommendation that additional resources be used in pursuing a higher level of PM quality would probably not be indicated, but a consultant using just the PMBOK Guide® as the standard might recommend exactly that. Also consider the makeup of the host organization. Is it dominated by the Maccoby architype Jungle Fighters and Company Men, with Craftsmen and Gamesmen in short supply? Then the recommendation of more scrupulous adherence to the aforementioned PMBOK Guide® couldn’t happen, even if it was the right call. And these are just two out of a myriad of factors that should come into play when formulating a workable correction to an existing management strategy, let alone the discovery of the optimal one. What we have here is a situation where two different but related roles of organizational outsiders, tasked to evaluate that organization’s business model or management practices and generate findings/recommendations for the errors they perceive, are working under pressures that push them towards a specific type of bias. Let me be clear: I’m not asserting that most (or even a plurality of) auditors or consultants will succumb to these influences, and allow their findings to stray from an even-handed approach. What I am saying is that, if the results of this outsider’s analysis are influenced by who is paying for them, even in the slightest degree, then we’re no longer in the realm of the management sciences. So, sure, go ahead and hire consultants and work with auditors. Just understand why and in what direction they are may err. |
Posted on: August 21, 2026 03:23 PM
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“And then a miracle occurs…”
| A famous cartoon by Sydney Harris has two men standing in front of a chalkboard with equations on it. In the middle of the equations are the words “And then a miracle occurs,” with one of the men telling the other (in the caption) “I think you should be more explicit here in step two.” Of course, being the geek that I am, I thought this hilarious. It also came to mind repeatedly during a real-life experience, which I will share. At a conference on the topic of machine learning and predictive analytics I attended, there were some paper presentations worth the price of admission, but others seemed oriented towards a specific product. Intrigued, I visited the exhibitors’ hall, and interacted with many of the vendors who had set up booths. Without exception, they boasted of their abilities to pull data from multiple sources and multiple formats, and also showed a variety of histograms, pie charts, area diagrams, etc., etc., as their available outputs (unfortunately, none of them demonstrated the capacity to deliver information via Chernoff Faces, but that’s another day’s blog). I approached several of them, and politely engaged them thus. “It’s my opinion that all Management Information Systems have the same basic architecture, in three sequential steps. Step One: data is collected based on a certain discipline, or binning structure. Step Two: this data is processed via some sort of methodology into information. Step Three: this information is delivered to decision-makers in such a way that they can use it to make, well, decisions. You have demonstrated your product’s ability to collect data from different sources, and your booth is festooned with samples of its output. Here’s my question: what methodology do you use to convert the data into usable information?” I was somewhat disappointed to receive the same basic answer (or a derivative) from every single vendor: It’s whatever the customer wants to use. One vendor in particular started a discussion so overwrought with jargon that I had to interrupt, and ask point-blank “Your marketing material claims the ability to produce ‘predictive analytics.’ Suppose I came to you representing a mid-sized company, and I was ready to purchase this product. Exactly what would you be delivering?” The answer, padded as it was with the aforementioned excessive jargon, basically came down to “it depends.” At least they didn’t go straight to “And then a miracle occurs.” I thought then, and believe now, that this was something of a disingenuous answer, in that on the one hand, these vendors were selling a capability in the vein of predictive analytics, and on the other were simply deferring to “customer preferences” when it came to how such an output was to be achieved. I could have told them then and there, the customer wants you to deliver an information stream that could be legitimately considered to be in the realm of predictive analytics, with the data they currently have available. If these potential customers knew how to do that at the present time, they really wouldn’t have a need for your product, now would they? But besides the pursuit of a “predictive analytics” package that could deliver the relevant, accurate, and timely information stream needed to obviate most (or even all) of the decisions for whatever level of management at which it’s aimed, we have the layered dynamic of macro-organizational decision oversight versus the latitude of movement that managers would require in order to bring their projects in on-time, on-budget. Put another way, does the owning organization reward managers who make all of their decisions consistent with policy, procedure, and even the unstated aspects of organizational culture, with mixed ultimate results; or, does it value those managers who bring their projects in on-time, on-budget, but bend an occasional unstated/undocumented rule from time to time? I would maintain that this is not a trivial dichotomy. For another mental exercise, imagine that one of these vendors did have the methodology to convert available data into a reliably predictive analytical information stream, and were simply reluctant to disclose it to some wise-guy inquisitive booth-visitor. And suppose that, once this system came on-line to its buyer’s home organization, that it informed said manager that the best course of action was contrary to previously-communicated organizational goals or agendas. What happens then? It's long been my considered opinion that organizational culture is downstream from individual Project Teams’ success. Are you looking for a significant organizational culture change? Don’t waste your time kvetching to the staff about how they should behave better. Instead, get the Projects in the portfolio to come in on-time, on-budget a majority of the time, using a specific set of PM strategies. That’s when the real culture-change miracle occurs. |
Posted on: August 10, 2026 11:07 PM
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Back To The PM Future (A Parody)
| I was taking a long walk with my wife (who, incidentally, also holds an MBA) at 2:45 P.M. on June 21, 2026, when a DeLorean with some strange gizmo on its trunk seem to come out of nowhere (why so specific as to the time and date of this walk? I’ll explain shortly.) A tall, wild-haired fellow wearing a lab coat exited the car after a hasty parking job, and approached me. “You’re Michael Hatfield, the blogger, right?” “You have the advantage of me, sir.” “I’m one of your readers – you can call me Doc. I recently became a PMP®, and I’ve been trying to track you down in order to answer one question.” “For so much effort over one question, I hope I can answer it.” “I’ve been reading your blog on ProjectManagement.com for some time now, and I’ve noticed you often point to the difference in type, not degree, between Asset Management and Project Management.” “Yeah, that’s one of my favorite soap boxes.” “From the time period I come from … uhh, I mean, the place that I come from, the Asset Managers’ narrative has completely dominated the management sciences, especially the whole business about how the point of all management is to ‘maximize shareholder wealth.’ Here’s my question: If you had access to a time machine, and could go back in time to substitute the PM’s approach to management for the Asset Managers’ version, when and where would that be?” “Oh, that’s easy” I replied. “Go back to the 1913 Income Tax Act in the United States. It passed immediately after the 16th Amendment. If I could go back in time to the one moment in history that locked the Asset Managers’ narrative into the dominant role in the management sciences, it would be then.” “How would you change it, if you could?” “Rather than use a general ledger for computing individuals’ or corporate tax load, I would use an Earned Value Management System, and pull a percentage from failed Projects. That way, original estimates would have to become more accurate, and tax penalties would go against mis-managed Projects in such a way as to discourage poor performance, along with its attendant wasted resources. Assets sitting around aren’t good for anything, much less the basis for assessing taxes. It should be based on how those assets perform, or fail to perform.” “Can I give you a ride in my DeLorean?” “Can my wife come too?” “There’s really not enough room…” ** * * |
Posted on: July 31, 2026 12:11 AM
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When All You Have Is A PM Hammer…
| A few blogs back I kvetched extensively about Information Technology (IT) project sponsors being unable or unwilling to specify their expected output, describing it as a derivative of “bring me a rock” syndrome[i] . But, to be intellectually honest, its supply-side counterpart is just as irksome and dangerous to IT project success, and that counterpart is this: the idea that the Project Controllers or IT PM’s favorite tool is the solution to producing the executive’s sought-after management information stream, when it certainly is not. It’s not only counterproductive to attaining the desired Project outcome, it actually turns its advocates into compromised hacks, who only need a small amount of organizational power to become completely insufferable. Before I examine this phenomenon at length, let’s take a second to zoom out of the Project portfolio-level information streams, and ask the basic question: what information do successful PMs crave? And why? GTIM Nation is familiar with my take on the Pareto Principle when it comes to management information, that the 80th percentile best managers who have access to 20% of the information needed to obviate a given decision will be consistently out-performed by the 20th percentile worst managers who have access to 80% of the information so needed. This being the case, even middling management talent will look like superstars if they are on the receiving end of timely, accurate, and relevant PM information on a sufficient scale. Enter the PM software providers. The ones who can provide this level of PM information, particularly from a unique perspective, will have very little problem monetizing such technology in the PM universe. (In a little bit of AI-related irony, if such a stack of algorithms is ever developed, the clear implication is that AI will come for our PM jobs sooner rather than later. Don’t worry – it will never happen. Probably.) Hence the rush to market one’s cost and schedule performance measurement system(s) as being whole portfolio controlling-worthy, if not the entire enterprise. This error is the mirror image of the one I’ve been accusing our friends, the accountants, of making for almost my entire writing career. No organization can be optimally (or even workably) managed from the information derived exclusively from the general ledger. Oh, sure, the “maximize shareholder wealth” adherents may disagree, but outside of them, and the academics who teach such dribble, the previous sentence’s assertion is undeniably true. So, what are we to make of the PM specialist who insists that a Critical Path or Earned Value Management-based system, even one claiming “enterprise” status, can answer the questions surrounding the pressing issues bandied about in the board room? Should we not view them with the same skepticism as the general ledger aficionados? And here an additional irony becomes apparent. The Project Controls Specialist who has become an expert on Platform X, and is convinced that this particular software generates the highly sought-after information stream that will turn those middling PMs into superstars, will push Platform X, usually to the exclusion of any and all other systems. In doing so, they present as a quasi-expert in the utility of Project Management writ large, as if to reject Platform X is to reject all of the PM codex. Again, no one Management Information System (MIS) can hope to provide a majority – or even a plurality – of the information needed to obviate the decisions required to bring even the most anodyne projects in on-time, on-budget. In essence, the one pushing the one-platform solution ends up not only discrediting themselves (and their favorite MIS) when the final product is glaringly short of expectations, they make the whole of PM look unsatisfactory as a management science endeavor by this extended act of reductionism. In case I haven’t been clear in the previous paragraphs, let me say this: there is no single MIS that can collect the data, process it into information, and deliver that information in a format that the decision-makers can use to arrive at all optimal (or even workable) PM decisions on a consistent basis, claims of being able to manage the “enterprise” notwithstanding. To disagree with the previous sentence is to engage in the previously-mentioned reductionism on a grand, PM-oriented scale. Further, it undersells the utility of PM techniques, approaches, and strategies in such a way as to imply that we PM-types can, indeed, be replaced by Artificial Intelligence bots. And I will never accede to that, because it’s simply not so. So, put down the hammer. [i] Hatfield, Michael, George Jetson, Bring Me A Rock, https://www.projectmanagement.com/blog-post/80094/george-jetson--bring-me-a-rock-.. |
Posted on: July 21, 2026 11:15 PM
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