Like an individual artist or craftsperson, the analytical artisan created analytics for him or herself, perhaps facilitated by a support person. At most a more senior decision-maker might see the results of the analysis—after all, this was the “decision support” period.
For much of their fifty-year lifespan, analytics were “artisanal”—hand-crafted, slow, and expensive to create. The goal was typically to create a report or dashboard using descriptive statistics, although there were occasionally some predictive regression models too. But there was another attribute of artisanal analytics that I have seldom mentioned until now: they were individually-oriented.