People made decisions for many millennia without the benefit of IT, and it’s not self-evident that we make our really big decisions in the computer age consistently better than before. Smaller decisions in relatively information-rich situations are another matter. But IT, properly used, has been and will continue to be important to decision makers in critical ways.
IT is really good at collecting, storing, retrieving, and analyzing facts and making them instantly available everywhere. The more heavily a good decision requires and relies on facts and rigorous analysis versus the other ingredients noted above, the more helpful IT can be.
By shortening the time between decisions and when their results can be seen so the decision maker can analyze and act on them, decisions can become much smaller in scope, limiting their risk. Many more such decisions will be needed, but the sheer volume of data collected can help decision makers improve their rules and guidelines (see sidebar).
IT can help identify in a timely way when decisions are needed. For example, it can supply early problem detection and trends via dashboards, executive support systems, and business intelligence.
It should be obvious, but it always seems to bear repeating that information upon which decisions are made must be accurate! There’s no room for fudges, and a culture that tolerates them (or even encourages them with a nudge and a wink) must change. Turbulence can destroy an enterprise that doesn’t have a handle on what’s really going on. Good decisions will result solely from luck.
Zara: Succeeding in Fast Fashion with Data-Driven Decision-Making
Zara is a ubiquitous European chain of clothing shops catering to young women who want to be fashionable but have a limited clothing budget. This is not an easy clientele. Their tastes can be fickle, and some seemingly inspired ideas just don’t catch on.
Most retailers in this space can’t afford to have garments made in high-wage Europe, so they rely on China and other low-wage countries for their production. Although this lowers unit costs, the lengthy supply chain stretches the turnaround times for changing the styles, cuts, colors, and sizes of the products, as well as the markets to which they’re sent. Thus, the stakes of these product decisions are high, and the error rate in making them is reflected in the prevalence of clearance sales, with as much as 70%-80% off. What never makes it to the financial statement is the opportunity loss when an item is an unanticipated hot seller, but the company can’t get it to the shops before customers move on.
Zara had a different idea. It made its products in Spain, its home country, in small workshops close to its distribution facility. How could Zara afford this? The company used IT to reduce the scope, and thus the risk, of its product decisions. By capturing extensive product data at the point of sale, transmitting it in near real time to headquarters, and analyzing it quickly and thoroughly, the retailer could rapidly change work orders and production runs to increase the supply of what sold well and decrease or eliminate production of what didn’t. Zara could also quickly reallocate products from one market to another (e.g., if Dutch women liked something German women didn’t). The result was a near absence of clearance sales. Everybody won: customers got what they wanted, Spaniards got jobs, and Zara made money.
[For more from the author on decision-making, see: “Navigating Business Through Turbulent Waters.”]