Using 14th Century Thinking in Making Important Business Decisions
Microsoft, Google (Alphabet), and Amazon offer examples of a new social paradigm. Peter Drucker alluded to it in The Post-Capitalist Economy. Kevin Kelly defined it as New Rules for the New Economy. Later he updated his depiction of it as What Technology Wants, and (more recently) as The Inevitable. When you watch the daily news, you wonder if anybody got the message. But the global economy doesn’t care; it is what it is. The question is no longer whether to innovate, but how?
Back in the early years of the new millennium, I helped local companies put their network infrastructures together and then manage them. Things have changed. There’s no point in doing that anymore; it’s cheaper and more effective to manage your network infrastructure in “the cloud.” Whether you use AWS, Azure, Google’s Cloud Platform, or another cloud service is secondary. How you manage the migration, whether you maintain a hybrid, or develop your own distributed infrastructure is a business decision of great consequence; and big consultants (like KPMG) charge big bucks to help you figure it out.
But it really isn’t that hard or expensive to set up a test sight. The question, which cloud provider to use reminds me of 1982 when people argued whether Apple or the PC were better. None of them used 10% of what their machines were capable of anyway. Back then Unix dominated in business. When a copy of MSDOS showed up at the computer store where I worked, our technical guy looked at it, threw it over his shoulder and said, “That’ll never amount to anything.” Meantime, I’ve watched Lotus 123, dBase IV, WordPerfect, and Novell get run over by Microsoft, which is now the most valuable company on the globe.
The real question comes down to how you account for time and track your decisions. What quantitative decision model anticipated Covid-19 and its economic effect? People like Nassim Taleb and Danny Kahneman have been telling us this for a long time. Drucker was on it way before that (as usual).
Back in the Pleistocene Era, when I started my career, we ardently studied time and motion on assembly lines. Later there was a cartoon in the New Yorker showing two executives walking by the open door of another executive’s office. The door read, “Ajax Soap,” and the guy in the office had his feet up on his desk, which had a sign on it that read, “Think.” The two executives walking by with concerned faces asked each other, “How do we know Smedley’s thinking soap?”
In his High Output Management, Andy Grove defined management control as “performance.” Later his protégé, John Doerr, who’d invested early, took the concept of objectives and key results to Google.
The thing is, top executives at Microsoft, Alphabet, and Amazon have some answers, but you’re not going to find them spilling the beans from their boardrooms onto YouTube videos for their competitors to watch. You must figure out what works on your own.
One thing we know for sure: your odds are higher if you collaborate with a qualified team. We also learned just recently that we don’t have to go into the office to do that. Whether you use Teams or Zoom may be secondary.
The thing about Microsoft’s value-added proposition is that all their software works together. Now they’ve added Business Central, which is based upon the most popular accounting software I was selling way back in the day (when Unix systems on Altos platforms dominated in small local businesses); that is, Great Plains.
In hindsight, it is now clear that this integrity in office productivity software is exactly how Microsoft rolled over Lotus, Ashton Tate, and Novell. That’s a key result. Whether it’s causal is moot; despite all the arguments, enough people have bought into Microsoft’s value-added proposition to make them #1 in market cap.
I’ve never played the game of my gun (or network platform) is bigger than yours. It doesn’t work. It’s irrelevant. The core question is, what kind of model works best in making the decision? What’s different today about applying “operations research” to knowledge work is that you need the answer to ask the right question. In other words, how much time should you invest in such a study?
It comes down to Peter Drucker again, and he takes it back to the 14th Century, Dominican Monk, Meister Eckhart: do your best and then measure the results. Great, who really does that? First you must have a system, then you have a theory—some quantitatively viable model—that poses a convincing set of correlative values that affect your periodic results. Finally, you must have a reliable way of tracking the important factors and correcting course regularly.
Back to the question: how much time (money) should you invest in improving the system you already have? It comes down to informed intuition, gut-level feeling, and courage. Computer systems (even with AI) don’t have those (yet); only human beings do.