Now is the time to get good at math, you crazy college kids.

I was browsing an Accenture report concerning the state of the analytics market, the field where advanced math is applied to business problems. Accenture predicts a dearth of data wizards in the coming decade, which means rapid salary inflations for anyone with education or experience in statistics and research methodologies, and who can apply that knowledge to huge data repositories. Digitally divining new profitability will be in demand for all but the most mundane of industries, which makes a great fit for gigantic multi-national firms with ample budgets.

Small players will benefit too, but differently.

Like life, markets find a way. In the analytics market we see several common business models. Some vendors provide customized services to help enterprises gather, process and profit from data. Others provide both packaged and client-specific modeling. A few of the brave offer SaaS platforms that deliver third party data and can be blended with your own using either or both pre-packaged analytic modules and home-grown code. One firm with who I am overly acquainted has done all three, albeit for a narrow market segment.

Accenture may be right about a growing sparseness of data scientists, but this will only hinder analytics vendors and large enterprises. Down the food chain there already exist app stores for analytics, allowing our poorer business cousins to get into the game and begin refining their knowledge, markets, segments and profitability. Wikipedia and predecessor Nupedia have shown it is not always better to buy academic-level insight to create a product, but to allow the open market provide a million solutions and let the same market select what works. Graduates with backgrounds in one or another industry and enough mathematical moxie to accurately analyze data will create analytics apps that give small and mid-sized businesses a big data boost.

The market is succeeding in serving the primary segments of analytics consumers, namely the segment vector based on company size. It is also satisfying a secondary segment vector, industry verticals. The next step is hybriding all that plus a third vector – internal operations department – into data marts to complete the picture.

Accenture may be correct in counting the number of advanced analytics experts produced by universities against the demand curve, but they didn’t articulate how people without PhDs, but with sufficient knowledge will become the data analysts for the lower tiers. Together this creates the marketing insight for this week, namely that segmentation is still the key to success in all markets, and finding your segment(s) and addressing the needs in those segments in a way that is meaningful, usable, affordable and profitable is required. Shortages of talent in one segment do not create problems in another because the needs therein are different as are the solutions.