Analytics

For decades now, companies big and small have embraced Agile software development methods. The rationale here is straightforward: Why take one or two years to fully deploy a system, app, or website when so many things can and do go wrong? Why try to cook one big batch and boil the ocean? Why not cook many smaller batches? Double that when the world changes faster than ever. Brass tacks: It's no coincidence that methods such as Scrum have exploded with no end in sight. Yet, when developing and using analytics, many organizations paradoxically continue to think in terms of traditional, phase-gate IT projects. That is, they optimistically plan for six-month or year-long projects to launch dashboards, key performance indicators (KPIs), data-visualization tools, predictive models, and their ilk. Antiquated techniques abound. In so doing, these organizations bet--often incorrectly--that they will diligently gather every requirement and data source. In their conceit, they assume perfect conception, planning, and execution. Even if they pull off these enormous feats, it's usually a fool's errand for one simple fact the world is moving faster than ever. This is insanity. In Analytics: The A