What this global independent safety science company wanted was a new decision-making engine to fuel their sales strategy. Over many years of success and expansion, the company’s information systems had literally grown apart, creating holes in their understanding of customer behavior and financial performance. To deliver a consistent customer experience and recognize trends and opportunities, they needed to make information easy to access and analyze across business units and disparate systems. They selected Oracle technology to unify their data. Early in the migration process they encountered a barrier to obtaining the efficiencies and agility needed from the new technology: the inability to ensure data quality. At that point, this enterprise turned to Point B to help put their data house in order.
Accountability is key
Point B worked with a core team of executive sponsors, mid-level domain owners and stakeholders throughout the enterprise to establish an accountability matrix to make it clear how decisions are made and who is responsible. This step resulted in two critical success drivers: responsible people feel empowered to make decisions and everyone else understanding how to participate in the decision-making process.
With an organizational model and process identified for overall governance, we focused on decision points for reviewing and approving process changes from all perspectives. This included technology, information needs and workflow. Applying our deep change management experience, we created four simple guidelines for ensuring governance solutions are accountable to their intended goals:
Activities must be accelerators for achieving business goals rather than blockers.
For data to be valuable it should be managed and shared.
Align activities to address risks and opportunities.
Prioritize action over academics.
This approach supports efficiency and employee efforts to make the best possible decisions in all circumstances.
Pilot jump-starts acceptance
Because data governance requires change throughout the enterprise, we created a launch strategy that starts with a series of targeted pilot projects. The goal of each pilot is to test the governance system—and win new champions, building momentum for the general rollout.
By the conclusion of this eight-month project, we established an enduring framework for policy-setting, decision-making and management of business processes, data and enterprise technology. The data governance process is gaining traction throughout the organization as an effective business tool, making data policy standardization a much easier internal sell. Confidence in their decisions is increased because they can trust the underlying data quality.