Recent research shows that approximately 90% of organisations rely on data to drive predictive decision-making, yet these same organisations overwhelmingly agree that a backlog of data debt negatively affects their ability to deliver new advanced analytics capabilities.
Delivering predictive analytics and AI capabilities requires a strategic plan. Yet, while 95% of businesses have a data strategy in place, the same research finds that only 29% of these businesses have a strategy that is clear, understood, and actionable.A fundamental issue is that, too often, the data strategy is a cookie-cutter exercise focused on the latest buzzwords.
At a tactical level, managers need to maintain or enhance existing IT systems, deal with new compliance and regulatory requirements, and create IT capabilities to keep the business running. As one gathers more information, clear relationships and dependencies between goals will typically emerge, as will a clearer picture of the required data sets and data capabilities. For example, marketing’s objective to enhance customer care may be both driven and enabled by IT’s goal to deliver a true 360-degree customer view. However, the need to protect customer data privacy andThere is an underlying dependency on customer data to deliver each of these goals.