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|In: Metrics|Last Updated:

I’ve been reading up on technical debt. I’d thought the name was self-explanatory. Nope. Much to my surprise, I found the term’s formal definition excludes quite a lot of debts of a technical nature.

According to most authors, “technical debt” is really application development debt.

Just as paleontologists changed Brontosaurus’s name to Apatosaurus in 1903 when they discovered Othniel Charles Marsh had given the genus that name back in 1877, so I have to respect the going definition of technical debt: a concept in software development that reflects the implied cost of additional rework caused by choosing an easy solution now instead of using a better approach that would take longer.

Yes, “technical debt” excludes a lot of what IT typically owes the future, illustrating an important principle of organizational dynamics: Someone Else’s Problems rarely matter.

And so, from now on, here in KJR-land we’ll refer to Chronodebt, defined as the accumulated cost of remediating all IT assets that aren’t what engineering standards say they should be.

Chronodebt is what your IT organization owes the god of time.

Chronodebt includes technical debt. It also includes the costs of: Converting an application whose supplier is out of business to something supported by a financially solvent vendor; upgrading server operating systems from out-of-support versions to something more current; and replacing hardware that’s out of warranty and aging beyond its projected lifespan.

Chronodebt also encompasses a frequent outcome of mergers and acquisitions: Acquiring a business and failing to integrate it into the enterprise.

A nicety here: Not all acquisitions should be integrated. It’s perfectly valid to run an enterprise as a holding company whose separate lines of business are left alone to win in their marketplaces.

If those running the business want a holding company then taking on an acquisition does add the acquired company’s Chronodebt to the total, but doesn’t add the cost of deferred integration.

If, on the other hand, the M&A plan does include some level of business integration or standardization, then failing to consolidate applications does add to the Chronodebt load.

Then there are boundary issues — issues like poorly engineered integration. Sure, we can blame an applications team for deploying a custom-programmed interface to keep two systems synchronized.

Is this really technical debt? Yes it is, if the IT architecture includes an enterprise service bus (ESB) or functionally similar integration platform and the applications team either ignores it or disguises a custom-programmed interface by hiding it inside the ESB.

But calling a custom point-to-point interface technical debt when it’s the best engineering possible given the IT organization’s existing set of approved standards just doesn’t seem accurate. After all, there’s no remediation path to improve the interface and won’t be, unless and until IT adds an integration platform to the mix.

In most situations, then, a classic integration tangle isn’t technical debt no matter how big a mess it is in the aggregate. It is, on the other hand, part of IT’s total Chronodebt because a time will come when untangling it becomes a priority, and when that time comes the time, expense, and complexity of the effort will be, shall we say, non-trivial.

All of which leads to a question: Should your average CIO calculate the company’s total Chronodebt?

The answer: Sorta.

The first question is jurisdiction. If the company has an enterprise architecture or enterprise technical architecture management function, then this is the group responsible for calculating Chronodebt, wherever and whoever it reports to in the enterprise.

The second question is whether to treat Chronodebt as a financial measure or as a non-financial metric. For most businesses, most of the time, keeping track of Chronodebt’s components, and grading each one with some sort of size and complexity indicator that associates with the cost of fixing it should be sufficient, and avoids errors of false precision.

On top of which there’s little point to developing a financial Chronodebt estimate.

One reason: Chronodebt measures remediation costs, not the business impact of the problems. Financial debt measurement works this way too: It notes the cost of repaying a loan, not what the loan shark’s leg breaker will do to you if you don’t.

The other reason is built into the Generally Accepted Accounting Principles (GAAP) — the official standard of accounting professionalism. As mentioned last week, unlike financial debt, Chronodebt and other forms of borrowing from the future don’t and probably can’t appear as a liabilities on the balance sheet.

In the KJR Manifesto, Metrics Fallacy #3 states that anything you don’t measure you don’t get.

Chronodebt’s absence from the balance sheet explains why IT has so much trouble getting funding to repay it.

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|In: Cognitive Enterprise|Last Updated:

Pop quiz!

Question #1: In the past 20 years, the proportion of the world population living in extreme poverty has (A) almost doubled; (B) Remained more or less the same; (C) almost halved.

Question #2: Worldwide, 30-year-old men have spent 10 years in school. How many years have women of the same age spent in school? (A) 9 years; (B) 6 years; (C) 3 years.

The correct answers are C and A. If you got them wrong, you have a lot of company. Across a wide variety of groups worldwide, faced with these and many more questions with factual answers, people do far worse than they would by choosing responses at random.

Which brings us to the next addition to your KJR bookshelf: Factfulness: Ten Reasons We’re Wrong About the World — and Why Things are Better Than You Think (Hans Rosling with Ola Rosling and Anna Rosling Rönnlund, Flatiron Books 2018). Unlike books that rely on cognitive science to explain why we’re all so illogical so often, Rosling focuses on the how of it. Factfulness is about the mistakes we make when data are available to guide us but, for one reason or another, we don’t consult it to form our opinions. Viewed through this lens, it appears we’re all prone to these ten bad mental habits:

  1. Gaps: We expect to find chasms separating one group from another. Most of the time the data show a continuum. Our category boundaries are arbitrary.
  2. Negativity: We expect news, and especially trends, to be bad.
  3. Extrapolation: We expect trend lines to be straight. Most real-world trends are S-shaped, asymptotic, or exponential.
  4. Fear: What we’re afraid of and what the most important risks actually are often don’t line up.
  5. Size: We often fall for numbers that seem alarmingly big or small, but for which we’re given no scale. Especially, we fall for quantities that are better expressed as ratios.
  6. Generalization: We often use categories to inappropriately lump unlike things together and fail to lump like things together. Likewise we use them to imagine an anecdote or individual is representative of a category we more or less arbitrarily assign them to when it’s just as reasonable to consider them to be members of an entirely different group.
  7. Destiny: It’s easy to think people are in the circumstances they’re in because it’s inevitable. In KJR-land we’ve called this the Assumption of the Present.
  8. Single Perspective: Beware the hammer and nail error, although right-thinking KJR members know the correct formulation is “If all you have are thumbs, every hammer looks like a problem.” Roslund’s advice: Make sure you have a toolbox, not just one tool.
  9. Blame: For most people, most of the time, assigning it is our favorite form of root-cause analysis.
  10. Urgency: The sales rep’s favorite. In most situations we have time to think, if we’d only have the presence of mind to use it. While analysis paralysis can certainly be deadly, mistaking reasonable due diligence for analysis paralysis is at least as problematic.

The book certainly isn’t perfect. There were times that, adopting my Mr. Yeahbut persona, I wanted to strangle the author, or at least have the opportunity for a heated argument. Example:

Question #3: In 1996, tigers, giant pandas, and black rhinos were all listed as endangered. How many of these three species are more critically endangered today? (A) Two of them; (B) One of them; (C) None of them.

The answer is C — none are more critically endangered, which might lead an unwary reader to conclude we’re making progress on mass species extinction. It made me wonder why Roslund chose these three species and not, say, Hawksbill sea turtles, Sumatran orangutans, and African elephants, all of which are more endangered than they were twenty years ago.

Yeahbut, this seems like a deliberate generalization error to me, especially as, in contrast to the book’s many data-supported trends, it provides no species loss trend analysis.

But enough griping. Factfulness is worth reading just because it’s interesting, and surprisingly engaging given how hard it is to write about statistical trends without a soporific result.

It’s also illustrates well why big data, analytics, and business intelligence matter, providing cautionary tales of the mistakes we make when we don’t rely on data to inform our opinions.

I’ll finish with a Factfulness suggestion that would substantially improve our world, if only everyone would adopt it: In the absence of data it’s downright relaxing to not form, let alone express, strongly held opinions.

Not having to listen to them? Even more relaxing.

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