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The formula is E= -SUM(p(i)*log2p(i)), where i indexes the events being tallied, and p(i) is the probability of each event i.

It’s how to calculate E, the amount of entropy … that is, information … in a system.

Unless, that is, you’re calculating the amount of information in a typical mission or vision statement. Then the formula is simpler: E=0, which is to say your average mission or vision statement is devoid of information.

You can search the entire universe of business (or, to simplify your efforts, search an entire Large Language Model of business) and find few parallels for the juxtaposition of earnestness exhibited during the creation of these documents with the cynicism they face once the drafting is done.

What’s particularly strange is how popular these documents are among business theorists given the near-total absence of research demonstrating their utility … especially as the same business theorists are the first to counsel executive management that they should stop engaging in “non-value-adding work” without appreciating the irony.

Information Technology organizations are, in my non-random-sampled experience, particularly prone to victimization by mission-statement advocates. But before we can understand the situation we’d better go back a couple of steps to define our terms:

Mission is what an organization exists to do. It’s akin to a charter, only shorter.

Mission statements are, typically, grammatically sound paragraphs, or in many cases run-on sentences that should be edited into sound paragraphs, that describe everything and anything an organization does, used to do, or might want to do in the future.

That’s what they are. What they ought to be are conversation starters about what the organization’s mission is – why it exists.

That’s why they’re information-free phrases – they provide no guidance as to what the organization should and should not be doing.

But what’s worse about most IT mission statements is how they’re created, and by whom.

The problem with how they’re created is a matter of their time budget: The management team tasked with creating one of these puppies spends, on average, 37.563 seconds on the substance of the statement, occupying the remainder of the one-hour mission-statement drafting meeting arguing about whether “happy” or “glad” is the more suitable word to include.

The problem with who creates the IT mission statement is that IT didn’t will itself into existence in the first place. At some moment in the by-now-distant past, the company’s ELT (executive leadership team) decided the company should have an IT department, either by that name or one of its historical synonyms.

That being the case, tasking IT management with creating an IT mission statement makes no sense. The ELT chartered the IT organization, so it should inform IT management why it exists, instead of asking IT management to guess at the answer.

Bob’s last word: IT vision statements aren’t subject to the same criticisms. As “vision” is a clear explanation of how tomorrow should be different from today, its formulation is a legitimate CIO responsibility, and in fact setting direction is the first of the eight tasks of IT leadership (or, for that matter, any area’s leadership).

And for that matter, while deciding what IT’s mission should be is an ELT responsibility, IT’s leaders are the experts in what it might be, so by all means the ELT should consult IT’s leaders when deciding IT’s mission.

But whether vision or mission, there’s no excuse for the statement that articulates them to be devoid of information. And as the ELT is involved, might I suggest involving the Chief Marketing Officer in how they’re phrased?

Bob’s sales pitch: I think you’ll enjoy what’s currently playing on CIO.com’s CIO Survival Guide: “5 IT management practices certain to kill IT productivity.”

I’m including it in the sales pitch section because it’s always helpful for my CIO.com’s editors to see that my articles there are generating lotsa clicks. Which is me hinting that you should encourage your friends to read it too.

And oh, by the way … what’s in it for you is that if you’re in IT management it’s worth paying attention to.

Sometimes, you read something that makes you want to take a long shower. The 48 Laws of Power, written by Robert Greene, and produced and “designed by” Joost Elffers (and what’s it say when a book’s producer/designer gets equal billing?) takes Machiavelli’s suggestions and the ethical dilemma he posed and eliminates the ethical dilemma.

Machiavelli expressed his dilemma in The Prince: “Any man who tries to be good all the time is bound to come to ruin among the great number who are not good. Hence a prince who wants to keep his authority must learn how not to be good, and use that knowledge, or refrain from using it, as necessity requires.”

Greene and Elffers say, “No one wants less power; everyone wants more.” “You will be able to make people bend to your will without their realizing what you have done. And if they do not realize what you have done, they will neither resent nor resist you.” “In fact, the better you are at dealing with power, the better friend, lover, husband, wife, and person you become.”

They figure everyone wants to increase their power, and always at someone else’s expense. This may be true in their world. In mine, most people want to optimize their power, not maximize it.

Powerlessness is a sorry state of affairs most of us try to avoid — true enough. Maximize your power, though, and you isolate and dehumanize yourself, substituting dry affairs for loving relationships, suspicion and manipulation for trusting friendships, and cold planning for the uninhibited enjoyment of life. Love and friendship require us to give others power over ourselves and vice versa.

On the other hand …

In your career you aren’t surrounded by friends. So while I don’t generally recommend “Keep[ing] others in suspended terror,” (Law 17), recognizing that your rivals do can prevent their achieving power over you. Nor should you “Use selective honesty … to disarm your victim,” (Law 12) for any number of reasons, not the least of which is an insufficient supply of naivete. If you’re naive enough to fall for it, though, your less scrupulous colleagues will manipulate you without much effort.

Some laws are just bad advice. Law 11, which advises you to “Learn to keep people dependent on you,” can change you from a peer to a subordinate in a hurry if you aren’t careful, and can prevent an employer from promoting you out of fear that what only you can do will no longer get done. If you’re irreplaceable, you’re unpromotable.

Other than its ethical repulsiveness, the biggest problem with this book is that some of its suggestions only work when everyone plays. “Get others to do the work for you, but always take the credit,” only works if people don’t confide in each other. Otherwise you can kiss Law #5, “So much depends on reputation — guard it with your life,” goodbye.

But … and it’s a big but … you can’t always avoid Machiavelli’s ethical dilemma, and even the most distasteful of these 48 “Laws” may be required to keep a bigger schmuck than you from taking over.

Sadly, you should own this book. Put it on your home (not office!) bookshelf, right next to Covey’s The Seven Habits of Highly Effective People and see if one of them bursts into flames.

Evolutionary theory has to account for all the bizarre complexity of the natural world: the tail feathers of peacocks; the mating rituals of praying mantises; the popularity of Beavis and Butthead. One interesting question: Why do prey animals herd?

Herds are easy targets for predators. So why do animals join them?

One ingenious theory has it that even though the herd as a whole makes an easy target, each individual member is less likely to get eaten – they can hide behind the herd. One critter – usually old or infirm – gets eaten and the rest escape. When you’re solitary, your risk goes up.

Predators hunt in packs for entirely different reasons. Human beings, as omnivores, appear to have the instincts of both predators and prey: We hunt in packs, herd when in danger.

Which explains the popularity of “research reports” showing how many of our peers are adopting some technology or other. These reports show us how big our herd is and where it seems to be going. Infused with this knowledge we can stay in the middle of our herd, safely out of trouble.

And so it was that I found myself reading an “executive report” last week with several dozen bar charts. A typical chart segmented respondents into five categories, and showed how many of the twenty or so “yes” responses fell into each one.

Academic journals impose a discipline – peer review – which usually catches egregious statistical nonsense. But while academic publication requires peer review, business publication requires only a printing press.

Which lead to this report’s distribution to a large number of CIOs. I wonder how many of them looked at the bar charts, murmured, “No error bars,” to themselves, and tossed this information-free report into the trash.

We read over and over again about information glut. I sometimes wonder if what we really have is nonsense glut, with no more actual new information each year than a century ago.

Bar charts without error bars – those pesky black lines that show how uncertain we are about each bar’s true value – are only one symptom of the larger epidemic. We’re inundated with nonsense because we not only tolerate it, we embrace it.

Don’t believe me? Here’s a question: faced with a report like this and a critique by one of your analysts pointing out its deficiencies, would you say, “Thanks for the analysis,” as you shred the offending pages, or would you say, “Well, any information is better than none at all.”

Thomas Jefferson once said, “Ignorance is preferable to error,” and as usual, Tom is worth listening to. Next time you’re faced with some analysis or other take the time to read it critically. Look for sample sizes so small that comparisons are meaningless, like the bar charts I’ve been complaining about.

Also look for leading questions, like, “Would you prefer a delicious, flame-broiled hamburger, or a greasy, nasty looking fried chunk of cow?” (If your source has an axe to grind and doesn’t tell you the exact question asked, you can be pretty sure of the phrasing.)

Look for graphs presenting “data” with no hint as to how items were scored. How many graphs have you seen that divide the known universe into quadrants? You know the ones: every company is given a dot, the dots are all over the landscape, the upper right quadrant is “good”, and you have no clue why each dot landed where it did because the two axes both represent matters of opinion (“vendor stability” or “industry presence”).

Readers David Cassell and Tony Olsen, both statisticians, recently acquainted me with two measures, Data Density, and the Data-Ink Ratio, from Edward Tufte’s wonderful book, The Visual Display of Quantitative Information:.

To calculate the Data Density divide the number of data points by the total graph area. You express the result in dpsi – data per square inch.

You calculate the Data-Ink Ratio by dividing the amount of ink used to display non-redundant data by the total ink used to print the graph. Use care when scraping the ink off the page – one sneeze and you’re out of luck.