Back when we had no choice, bespoke software or big data science projects would be planned for years before releasing a version 1.0. Data would be painstakingly cleansed, systems would go through long quality cycles, and budgets would inevitably be extended. Even if all went well, the best that could be hoped for was everything going to plan.

Unfortunately, the plan would be obsolete by the launch date.

Creating static systems or data science deliverables are only as good as the insights were at the beginning. No business stays that still these days. Thankfully, that’s where a measurable strategy, software that learns, and fast delivery cycles can save the day.