Don't let the absence of facts slow you down

We've all read articles bemoaning how calculators and their digital cousins have destroyed our children's motivation to memorize the multiplication tables, crippling their mental math skills for life.

Recent experience prompts me to put another such burning proposition on the table: Google may have ruined our ability to estimate.

Last year I spent a great deal of time working with a corporation that was tackling a critically important issue: whether it would have access to the talent it needs over the next several decades.

This is a complicated and interesting question. To answer it properly, you'd like to understand how many children will be born in various parts of the world, whether those children will obtain educational degrees relevant to your industry, if they'll choose to work in your industry or to take those skills elsewhere, the number of other employers who will be competing for those same skills, and a myriad of other basically unknowable facts.

While I was working with one team to develop a set of options to develop more talent should the fundamental answer turn out to be "no," another team set out to create a model of the company's projected talent supply and demand. The internal team scoured every available source of input at their disposal and returned with a sobering conclusion: there were no facts to be found.

A decision was then made to hire one of the premier global research firms to assemble the required information. After some time and even more money, the firm's considered answer came back: there were no facts to be found.

A young, extremely bright modeling expert jumped in to sort things out, confident that his online search skills would ferret out the data needed. His eventual conclusion? There were no facts to be found.

Even though I was primarily focused on other aspects of the project, this chain of events had, by now, fully captured my attention, in part because it brought back such vivid memories of my earliest work experience.

My first job out of graduate school was as a consultant at Arthur D. Little. Most of the work we did then, in the 1970's, was, in essence, providing information for use in business forecasts. I remember projecting the demand for chemicals to be used in swimming pools and rubber for roofing, of paper for hot drink cups and soda ash (whatever that is!) in water softeners. My husband was amazed that major corporations paid excellent money for someone who, prior to getting the assignment, knew nothing about chemicals or roofing to forecast future demand for their important products.

What I and my colleagues were doing, of course, was creating algorithms based on the few facts that were available, logic, and some market research upon which to base reasonable proxies linking the facts together. An algorithm regarding the demand for swimming pool chemicals, for example, might be based the number of houses in a region (findable fact), times the percentage of those houses with pools (estimated based on findable facts regarding the region's socio-economic breakdown and the correlation between household incomes and swimming pools), times the percentage of those pools that would be sanitized by the chemical in question (based on market research interviews with local pool supply shops regarding customer preferences in their region). Sometimes we'd come at the answer from several different directions, creating multiple algorithms, to double-check that they'd all arrive at a similar, or what I liked to call "it's bigger than a bread box," answer.

My surprise in the talent supply and demand work was that none of the folks involved —neither the global research firm nor any of the very bright colleagues — were developing algorithms or searching for proxies. They were all only looking for facts.

Chances are there are no facts on the future talent supply for your industry — just as there are no facts on a wide range of the complicated problems our businesses wrestle with each day. But this should never stop us from developing reasonable and very credible numerical estimates to guide our evaluation and decision-making processes.

Not finding the answer on Google shouldn't slow us down.