If you haven’t already, go see The Martian.

Back in 1998 I wrote, I love the movie Apollo 13. It’s a modern rarity. Engineers and scientists — smart people dedicated to their jobs — are the heroes, and they become heroes by doing their jobs intelligently and with dedication.

The situation has improved since then, mostly courtesy of Marvel’s movie division: Lots of Marvel’s heroes are genius scientists and inventors.

But they’re geniuses in a different way. Tony Stark has lots of cool toys to play with, and gestures in three dimensions to make holographic thingies move around in the air while speaking technogibberish to whoever is in range. He has more in common with a sorcerer’s apprentice than with any actual scientist or inventor.

Not so the NASA engineers depicted with a great deal of accuracy in Apollo 13 (according to Jim Lovell and Gene Kranz, who I once had the privilege of hearing speak on the subject). They don’t invent entire new branches of physics and then turn them into working technology just in time to save the day. They solve problems using tested engineering principles, figuring things out and sweating the details along the way.

The Martian is like that too. No, it isn’t “based on a true story,” (yet?) as Apollo 13 was and Imitation Game pretended to be. But with The Martian every frame is infused with verisimilitude. The tech looks real, and the dialog describing the tech is sound engineering.

Which has what to do with running a business, leading an IT organization, or any of KJR’s other usual themes?

Just this: Scientists and engineers are the ones who create wealth. The rest of us just play games with it.

Too extreme?

Maybe. Reliable numbers are hard to come by (they require economists, who in turn require models). So take what follows with a grain or two of salt.

I started with “The Economic Impacts of the U.S. Space Program,” (Jerome Schnee, Business Administration Department, Rutgers University). Adding a bit of spreadsheet work, it appears that had the Mercury/Gemini/Apollo program never taken place, today, right now, the U.S. economy would be about 8 percent smaller.

As the Internet was designed and built by scientists and engineers (please, no Al Gore jokes), it’s in bounds for this discussion too. A 2011 McKinsey study found that without it the economy would be 10 percent smaller, and growing more slowly: As of 2011 more than a fifth of all economic growth was due to it.

Extrapolating from macroeconomics to microeconomics is even more problematic than macroeconomics itself. In this case, though, it seems reasonable to figure that the economic impact of the technologies developed for the space program, and of the Internet and World Wide Web, were largely expressed through their business use. If this chain of logic holds up, it means your average business would have something like 20% less revenue and profit today if it weren’t for the space program and Internet.

And that’s just the space program and Internet, far from the only endeavors into which scientists and engineers pour their efforts.

Putting these technologies to use in the businesses that have benefited from them took the efforts of scientists and engineers … in the case of the Internet, programmers, systems administrators and other technical professionals.

Eliminate every Internet-related programming job (in this day and age that’s all of them) from every business at the same moment, and their top and bottom lines would shrink by 10 percent.

And that understates their importance to your company: Eliminate their jobs in just one company and its top and bottom lines would shrink to negative numbers, because without use of the Internet they’d be unable to compete at all.

Which leads to a question: Does your company treat its technical professionals like people who contribute 10 percent to the top and bottom line?

Do you?

From its early days to the present, everything about information technology has been hard to measure. Even such seemingly basic concepts as productivity and value have been damnably hard to get a handle on, which has led many misguided organizations to focus their attention on the only aspect of information technology that’s easy to measure.

Its cost.

Here’s an adjective/noun/object combination I never expected to type: I just read an excellent analysis by McKinsey.

Usually, when I read something by McKinsey my reaction is how useful it would have been five years ago. Not this time.

The article in question is: “Raising your Digital Quotient,” by Tanguy Catlin, Jay Scanlan, and Paul Willmott.

While you should read the original, as a public service here are some key takeaways:

  • Not every company can transform global marketplaces: Thank you! It’s easy to spot a business that’s succeeded in spectacular fashion, generalize from its success, and then recommend everyone else do the same thing. Temptation and good logic, though, rarely coexist.

The magic buzz-phrase I most often read about “digital” (and when did “digital” become a noun?) is that it “enables new business models.” Strikingly absent from most of these sources are examples of truly new business models. Even the oft-mentioned Uber is little more than a broker … a business model best described as ancient.

McKinsey’s advice for most companies is to figure out how digital stuff make them better at the business models they currently rely on.

  • Customers: McKinsey points out, and KJR completely endorses the notion that one of the most important aspects of digital disruption is how digital stuff affects or transforms how customers research and decide on products and services. Digital strategy should be built around determining how a company can best integrate itself into this new pattern.

Simple example: The big deal about Uber is supposed to be how easily you can book a ride by clicking on a mobile app. In the Minneapolis/St. Paul metro area I easily book taxis with an app called iHail … and I get a ride from a fully insured driver who has a chauffeur’s license. Had the U.S. taxi industry figured this out instead of relying on lawsuits and lobbying, I wonder if Uber would have made the inroads it did.

  • Culture overcomes: Without taking anything away from the importance of the digital technologies themselves, a “strong and adaptive culture” can overcome a lot of lacks.

The more I consult, the more convinced I am that no matter what the business change, culture is the lead story, not one factor among many in reducing an organization’s resistance to change.

  • Integrating the unintegratable: Not really unintegratable, but almost always unintegrated, are data about customers from internal systems and data about customers from the social web. Put them together — demographic and purchase history from your internal systems, combined with search patterns, consumption data, and psychographic tells from customers’ on-line behavior — and you can predict what customers are likely to want to buy far better than with either in isolation.
  • Process automation: McKinsey is more diplomatic about this than what follows:

Once upon a time, before the reign of “internal customers” put a halt to IT’s habit of provided technology leadership, conversations about the role of computers was how to automate business processes.

Whether or not there’s truly a causal relationship between the two events, at roughly the same time internal customers became IT’s reason for being, process optimization disciplines like Lean and Six Sigma supplanted the assumption of full automation.

It’s time for the past to become the future. For true processes (regular readers will recall KJR’s ongoing crusade to distinguish between processes and practices), everyone involved should assume full automation is possible, and design the process accordingly. As part of the design, kick out exceptions for human intervention when needed.

But assume you can fully automate at least the 20 percent of the cases that account for 80 percent of the work. This will inevitably reduce cycle times by orders of magnitude, reduce error rates to trivial fractions of their former selves, and cut incremental costs to the bone.

What McKinsey also doesn’t say: Do not, under any circumstances, let savings fall to the bottom line. Either use them to reinvest in your business, or to reduce product pricing. Like that annoying song about poker, it isn’t time to count your money yet — you’re still playing the game.

  • Agility applies to more than just Agile: Apply incremental “test-and-learn” (to use McKinsey’s phrase) everywhere. Or if you, like me, prefer OODA theory, increase the speed and reduce the scope of your loops. There comes a point when evidence trumps analysis. So emulate direct marketers — stop theorizing and test, test, test. It’s cheaper, and it works better besides.

There’s much more to the McKinsey paper than this. Take the time to read the whole thing.

Even though it lacks the inordinately valuable commentary I’ve added in the above summary.