Since the dawn of the information age (a.k.a.: the early 1990’s), data management professionals have waged an eternal battle to justify the required investment in people, processes, and technology to deliver high-quality, trusted, and secure data to their organizations. Time and again, spanning these decades, our data champions struggle to build business cases to illustrate how bad data impacts productivity, profitability, growth, customer loyalty, and employee morale, and can introduce all kinds of risk to the business and IT. It was tough going early on – data warehousing was a playground, not an enterprise competency, and certainly not a business imperative. Times change. Data warehousing (DW) and business intelligence (BI) reporting which leverage foundational data integration (DI) and data quality (DQ) capabilities are table stakes to run a competitive business. Data management leaders don’t have to work quite as hard to justify investment in these initiatives as they once did.
But the information age continues to move forward. Front- and back-office applications running on relational databases still exist aplenty, but now must integrate with SaaS applications running on public or private clouds. Operational BI reporting on costly data warehouse platforms remains, but now these workloads are balanced alongside lower-cost, elastic Cloud and Hadoop computing environments. The data management challenge today is exponentially more complicated. There is less business confidence in the trust and security of this heterogeneous spaghetti map of information than ever before, requiring justification to invest in even more data management competencies, such as master data management (MDM), metadata management, and data security, to name just a few. Data governance as an organizational discipline is needed now more than ever, and isn’t it time that business leaders stop expecting IT to carry this weight alone?
It’s 2016 and there are likely only a small handful of (soon to be unemployed?) CEOs that completely dismiss the value of effectively managing the critical data that runs their business. So in this day and age, while business cases are of course necessary, the thesis of everyone must evolve from “Should we do this?” to “Where do we start?”
Here are a few tips to help get you going:
- Get your arms around what kind of data governance organization you’ll need to accomplish your goals. Not every data governance program should look the same; it needs to reflect the culture and priorities of the business it represents – and adapt over time. For some useful resources to build this plan, check out the eBook, “Just Enough Data Governance” and the best practice community www.GovernYourData.com.
- Make sure your business case states clear business goals, performance metrics, and benchmarks that will not only solicit initial sponsorship but also ensure ongoing support and momentum to continue your data management journey. For some detailed tips and examples of industry-specific business drivers, check out “How to Get C-Level Buy-in For Your Trusted Data Initiative.”