McKinsey: Solving the digital and analytics scale-up challenge in consumer goods
“In the early days of digital and analytics transformations, companies prioritized individual use cases, largely in the commercial functions, based on feasibility and impact. To support the highest-priority use cases, companies then established a set of broad-based enablers—for instance, a data lake, a technology stack, and a technical organization that housed all newer talent profiles, such as data scientists. In theory, these enablers would meet the needs of the entire enterprise. In practice, however, generic enablers rarely meet specific business requirements. Successfully scaling up digital and analytics efforts thus requires a different approach: one that prioritizes fully enabled domain transformations rather than unrelated use cases.”