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The First Steps to BI Adoption
Kjersten Moody, Chief Data and Analytics Officer, State Farm
For many organizations, the investments in BI have centered on data lakes, visualization tools, and data governance strategies and techniques. These investments are maturing and producing incremental value for organizations. Indeed, a well-populated and functioning data lake is rapidly approaching the point where having one is no longer a point of competitive advantage. Rather, its existence avoid measurable competitive disadvantage. We have excellent examples and familiar leadership patterns to establish data governance, KPI standardization, and report consolidation. In other words, a roadmap for a mature and well-run BI capability can be fairly easily established, if it hasn’t already been achieved.
As thought leaders, the next frontier of significant new business value is emerging in the extension of BI with predictive modeling.
BI is quickly becoming table stakes. The competitive future will belong in part to those who deploy and mature dynamic and predictive reporting at scale
The first step is to honestly assess the maturity of your BI organization and your underlying readiness to build and link models to your reports at scale. What is in your data catalog and what is its availability? What is your report format and delivery platform? What are the surrounding business performance management or report review processes? Look at your technology and operating model standards and evaluate how well they are embedded across the organization. In an ideal state, your data is readily available, reports distributed to a single, flexible app, and business leaders have a regular cadence for reviewing information and planning next steps.
The second step is to open the door to your data science team and define how the teams work together. At a minimum, these discussions should include topics such as success criteria for the partnership, access to data, co-location, and prioritization of work (or backlog alignment).
Finally, jointly approach with your data science partners a business area to pilot the shift with you. Begin the conversation with the business area by asking what key business challenges, questions, or difficult scenarios they are facing. If they could look into a crystal ball, what questions would they want answers to? As with any transformative work, using BI capabilities to their fullest takes a collaborative approach in which business, technology, and data teams take collective responsibility for tackling the challenges and opportunities.
BI is quickly becoming table stakes. The competitive future will belong in part to those who deploy and mature dynamic and predictive reporting at scale. When that happens, organizations will have the trusted insights to shape the future and explore the art of the possible.
Now it’s time to take the first steps…and enjoy the journey!