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Greg here—Bob has emerged from his igloo in Minnesota with this column.  Enjoy!

Something to look forward to …

Members of the KJR community know that businesses can optimize their operational processes in no more than three at a time out of these six possible dimensions: Fixed cost, incremental cost, cycle time, throughput, quality, and excellence. For definitions, look here: Do six dimensions make a business multiverse? – IS Survivor Publishing .

If you’ve ever been involved in a process optimization effort you’ll know that relatively few process consultants even recognize the six dimensions’ importance. You’ll also know that simplification is the process optimizer’s go-to solution to all process improvement challenges.

What simplification means in practice is that business management wants fewer defects and lower incremental costs, and wants them enough to give up on excellence – the ability to customize, tailor, and adapt – to get them.

As a practical matter this quality vs excellence and cost trade-off explains why, when men buy pants, they can get them with even-numbered inseams only. It’s personal – I need pants with a 31” inseam, but the best fitting pants I can buy come in at either 30 or 32 inches.

A pants manufacturing and inventory stocking process that delivers only even-numbered inseams, it appears, must be simpler than one that delivers inseams to the nearest inch.

Why does simplification work?

It works because we human beings are limited critters. Show a business manager a swim lane diagram with seven or fewer boxes and branches and they will understand how the process is supposed to work at a glance.

Show the same business manager a swim lane diagram with twenty boxes and they’ll have to study it to make sense of what’s supposed to happen.

So in our current state of process engineering sophistication, if we want excellence – the ability to create highly customized and tailored process outputs – we have to be willing to pay for it with higher fixed costs (say, buying more precise pant pattern cutting machines), reduced quality (31” inseams that actually vary from 29.5” to 31.5”) or increased waste leading to higher incremental costs by increasing inspections and discarding pants with inseams more than a half inch different from 31”.

Imagine some bright staffer suggests a way to get the excellence you want to bring to the pants marketplace, but their solution entails a radically more complex process – one with 23 swim lane boxes and branches.

I’m so sorry.

Except that when you look at the situation more closely you’ll recognize a hidden assumption – that the seven-box process limitation is intrinsic.

But there’s no reason to make that assumption. Enter a speculative possibility: Use artificial intelligence to overcome the seven-box limit.

There is, after all, no reason to expect a competent process-design AI to succumb to it. Quite the opposite: we can predict with some confidence that an AI process designer, equipped with genetic design algorithms, could cope with far more process complexity – more boxes and branches, that is – than we lowly humans could manage if left to our own limitations.

Bob’s last word: Ten increasingly short (“decreasingly short”?) years ago I predicted a shift in business emphasis, from quality as primary driver to excellence (“More storm warnings,” 3/4/2014). I’ve seen nothing that suggests the process optimization industry has kept up. Lean, six sigma, and lean-six-sigma still monomaniacally focus on quality improvement. Theory of constraints still says quality improvement is nice, but increased throughput is the name of the winning game.

And business process re-engineering’s devotees still don’t seem to have figured out that BPR as usually practiced is just waterfall software development without the software, but with the same structural flaws.

Interestingly, a bit of googling (and CoPiloting) reveals that there has been work done to apply genetic algorithms to complex process optimization challenges (for example, “An improved genetic algorithm for multidimensional optimization of precedence-constrained production planning and scheduling | Journal of Industrial Engineering International (springer.com) , Son Duy Dao, Kazem Abhary & Romeo Marian, 2017).

And this was published before the recent wave of AI-everywhere enthusiasm. Which leads me to suggest a name for this new partnership of artificial intelligence and genetic algorithms: AIGA (pronounced “EYE gah”).

Whether the current crop of process optimization consultancies will adopt AIGA or not is anyone’s guess.

My guess? Nope.

# # #

If you’re following AI trends and want something that isn’t just the same old same old, you’ll want to read Bob’s last two CIO Survival Guide entries: SharePoint Premium highlights the hard road CIOs face with generative AI | CIO and The last thing most CIOs need is an AI plan | CIO .

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“Do you know how much Curt Cousins makes?!?!?!”

Expressing outrage over professional athlete compensation is a popular pastime. And yes, on the face of it the hundreds of millions they’re paid is absurd, unlike the completely reasonable tens of billions paid to team owners in exchange for broadcast rights to the games their teams play.

Personally, I don’t see the problem. Athletes are paid for their work. Team owners? Not so much.

The question team owners must answer when negotiating athlete salaries is much the same as the question management must answer when setting compensation, whether it’s for current staff or new hires: What would constitute a fair number?

I’m happy to help. Here’s a framework you can use, both to arrive at the right number and to communicate the logic of it. It has four components: (1) raises; (2) the annual bonus; (3) spot bonuses; and (4) promotions. One at a time:

Raises: A raise, in theory, adjusts the employee’s base compensation – their salary or hourly rate – to what a competitor would offer to hire them away, based, for the most part on the position in question. It’s where the law of supply and demand holds sway. The perfect raise makes each employee’s pay high enough that they have no incentive to leave and the company has no incentive to replace them.

The company’s payroll analysts should be able to provide a reasonable estimate for each job title, although it’s worth noting that they’re likely under some pressure to underestimate what the market would really have to offer.

Raises have nothing to do with an employee’s performance – an essential and often botched aspect of how compensation should work. That’s because a raise is an annuity – it pays employees in future years for their performance this year.

The annual bonus: Unlike raises, employee performance this year has everything to do with their annual bonus. There’s no algorithm for calculating it. Think of the annual bonus as the company’s way of saying thank you to the employee for going above and beyond what their base compensation would lead their manager to expect.

Among the reasons for using the annual bonus to recognize exceptional performance is that in round numbers it can be three times what the company could offer were it to recognize it in the form of a raise. That’s because the bonus is a one-time event where a raise is, as mentioned, paid year after year after year.

Spot bonuses: Where the annual bonus recognizes a year’s worth of strong performance, a spot bonus is a handy way for a manager to thank an employee for something exceptional they just did. It should be in proportion to the business value of what they did, and it should be big enough that the employee sees it as a big number.

Promotions: A raise increases an employee’s base compensation in line with how the labor marketplace has changed for the job they’re paid for. A promotion changes the job they’re paid for, which means their base compensation should change along with it.

It’s worth noting that promotions come in two forms. One recognizes an increase in skills that makes an employee more effective in the job they hold. You might, for example, promote a developer to senior developer – same responsibilities but better at them.

The other changes the job the employee does, for example, from developer to project manager.

This framework has the advantage of clarity, but it will require strong and consistent communication, because how it addresses skills and performance can be unsettling. Especially, decoupling raises from performance just isn’t how most employees think about what they should expect.

Bob’s last word: You might have noticed that nothing in this framework is expressed in terms of rewards and incentives. That’s deliberate. As Alfie Kohn pointed out in his classic “Punished by rewards,” (1993), managers who rely on compensation for motivation are trying to bribe them to perform. And, it sets up a reverse expectation: If the employee doesn’t get the raise they want the manager shouldn’t expect them to perform at their best.

Smart managers don’t think about compensation in terms of incentives and rewards. They think of it as the company’s loudest and most sincere voice when it comes to expressing its appreciation for a job well done.

Bob’s sales pitch: No, I haven’t changed my mind. I’m still planning to retire the end of the year. I’m still interested in your ideas for what KJR might discuss between now and then. Let me know, either through my Contact form, or in the Comments.

On CIO.com’s CIO Survival Guide: “6 ways CIOs sabotage their IT consultant’s success.” The point? It’s up to IT’s leaders to make it possible for the consultants they engage to succeed. If they weren’t serious about the project, why did they sign the contract?

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