Self-Service Data Analytics and Governance for Managers

CHAPTER 4Self-Service Data Analytics Project Governance

We have already explained that the hyper-organic growth pattern of self-service data analytics is unlike any other centralized digital transformation change pattern. Once innovators and first-movers adopt tooling, and the success is observed by influencers across the organization, if properly nurtured an eruption of excitement will build around the new capabilities. New users will begin to adopt at feverish pace. As data analytics tooling permeates organizations in every function and at an exponentially increasing rate, it is critical that organizations have strong foundations of governance to keep the ship steadily on course, from early on in their digital journey.

Despite the fact that effective governance may be staged around core technology and may operate effectively for core systems-based transformation, in a decentralized user-driven automation environment, the legacy governance structure may be side-stepped. Without the benefit of governance to control and temper the flood of new processing automation, managers can find themselves unaware of the extent to which new procedures have been forged. They may not have clear visibility to the newly created dependencies, which can prevent them from adequately assessing risk, and they may find themselves lacking when asked to demonstrate adequate program control to senior management, auditors, and even regulators. The new decentralized capabilities placed into the hands ...