Why raw data alone is insufficient for making decisions

The WSj recently published an article regarding the prospects of asking/demanding that political candidates or prospective CEOs release DNA sequence information.

For us, even though data-driven analysis is the first phase in our business leadership process (Data-Driven Analytics (DDA), Informed Decision-Making (IDM), and Intentions-Based Guidance (IBG)), it is important to understand that data alone is meaningless. While the connections between sales data and pricing strategies or marketing campaigns is at least intuitively in the ballpark for most managers, the connections between DNA sequences, genetic predispositions, health risks, and actual health problems are far more attenuated. Geneticists and doctors (since the intersection is the important issue) know that only certain DNA sequences lead to definite health problems, and that only some health problems are tied primarily to purely genetic factors. For example, Huntington’s Chorea, a genetic disorder, is caused precisely by a specific gene and regularly occurs when the mutation is present. Alternatively, even if I don’t have a genetic predisposition to lung cancer, if I smoke a pack a day, I’m very likely to end up in trouble.

From a business perspective, it is clear to all (well, most, since we’ve found some of the exceptions) that if your sales price doesn’t cover your costs, you’re either in for a serious economic catastrophe or an antitrust investigation. But that single accounting snapshot is not a good description of how business happens. Businesses are continually making sale after sale, at varying prices, to different customers of different products and services. Tracking the change, rate of change, and source of change across those variables can point you in the right direction. Financial snapshots are like DNA; it’s possible for them to point to problems all by themselves, but most of the time, you have to analyze the system dynamically because it’s a dynamic system. In science, it’s called experimentation; in medicine, it’s called treatment; in business, it’s called management.