A Lesson from the 1800s: Good Data In, Good Results Out
Charles Babbage wouldn’t know a Software-as-a-Service Cloud model from Service-Oriented Architecture. But the 19th Century mathematician, philosopher, inventor and mechanical engineer credited with designing the world’s first mechanical computer, understood, even back in 1864, that good decisions never come from bad data.
It’s a lesson that today’s supply chain management pros, from purchasing managers to loading dock foreman, are learning applies to them every bit as much as it applies to accountants and IT geeks.
In his book Passages from the Life of a Philosopher, published 149 years ago, Babbage wrote that he had been asked several times after creating what he called his “analytical machine” whether “if you put into the machine wrong figures, will the right answers come out?"
The great polymath, described by his biographers as being as snooty and as elitist an intellectual as he was a cantankerous and a quarrelsome jerk who did not suffer gladly the plebes with whom he had to share life, didn’t so much answer such questions as he insulted those who asked them.
“I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question,” Babbage wrote condescendingly.
Babbage, Distilled: Garbage In. Garbage Out
Ninety-nine years later, the writer of a syndicated newspaper article about the first efforts to computerize the Internal Revenue Service distilled Babbage’s message into a more memorable phrase: “Garbage in. Garbage out.” And George Fuechsel, a technical instructor working for IBM in those days, immediately latched on to that phrase and began drilling it into legions of bright young technologists who passed through the highly-regarded training programs at what was then the world’s leading technology company
It has achieved cliché status in the American lexicon over the last 50 years. And like all clichés, it has achieved that status because it encompasses an important and universal, or near-universal, truth that’s especially applicable in the world of information technology. And as the power of technology continues to flow down through businesses and the organizational ranks the way lava flows down the sides of a volcano, more and more workers whose jobs used to involve pencils, clipboards and lots of “rules of thumb” and “guesstimating” are coming to understand the need for entering, maintaining and tracking accurate data.
Nowhere is that now more obvious than in the world of supply chain management. In today’s hyper-competitive, cost-conscious business environment the costs of buying and storing unneeded inventory, of financing its purchase, of building facilities to store, of deploying fleets of vehicles to move it, and hiring large numbers of people to manage and move are so high that companies increasingly need to track items in inventory down to the smallest detail in order to remain competitive. And given the potentially catastrophic top – and bottom – line impact of not having enough items in inventory, or of not knowing where they are, exactly, in the supply chain, companies no longer can afford to risk their future on someone’s rule-of-thumb methodology for counting, tracking and ordering.
Solutions Deliver Visibility
That’s why companies are equipping warehouse, loading dock and even transportation workers with advanced held-held devices and/or smartphones loaded up with easy-to-use inventory management application. And it’s why even those businesses that have long bought into the use of computerized inventory management techniques now are upping their game by transition to advanced solutions, whether they are cloud-based systems that minimize up-front investment, or systems run through on-site servers.
Such systems go far beyond merely counting the number of units shipped or received. They make companies more cost competitive by making it possible to track demand trends, demand for product variations, and even variable costs in real time. When the many different sets of data tracked by such systems are entered accurately and instantly, supply chain managers can determine the exact best time to order more parts and raw materials, when to turn on and speed up (or slow down and turn off) the assembly lines.
There’s only one problem with “Garbage In. Garbage Out.” It is both an accurate and memorable aphorism, but it suffers from its negative tilt. So I prefer a positively re-stated version: Good data in. Good results out.