February 22, 2016
When 80% Data Quality is not going to cut it: Governance & Quality before Analytics
Gartner’s 4Q15 forecast shows that 2016 global spending for enterprise software will be $358.8 billion in U.S. dollars (1). BI and Analytics is the projected second highest Enterprise Application Software spend category in 2016 (1). We feel business, who live their operations day-in, die for actionable insights, insights which can increase traffic at stores or online and engage their interests for longer.
With increased cloud offerings, business users are short circuiting IT involvement in procuring software. “Many organizations’ budgets and decision rights have shifted significantly beyond direct IT control to business or to a strategic corporate budget or steering committee.” (3). In some cases different business units end up with different BI and Analytics software. Instant gratification to be able to do data discovery on the fly with the newer BI and analytics tools is leading executives to run their business with 80% governed/validated data. Interestingly enough, a Gartner study concluded that maturity in business with respect to BI is still low with only 5% have the ability to completely deploy advanced analytics (3).
Putting all this together,
- Operations are spending more money on tools
- to show quick results, while they have
- low maturity in using them, and they do
- not have capability to deploy advanced analytics
Result: Visually appealing insights based on poor data quality and governance, which differ among business analysts leading to distrust on the insights.
Gartner recommends that analytics governance is the one the important pillars for a successful business analytics strategy. “If your organization is focused on a broader enterprise information management (EIM) program in an effort to align, leverage and link people, process, data and technology across multiple information and analytic investments, this analytics strategy will not operate in isolation” (2). Businesses which consciously neglect governance can drag their companies into poor financial performance and potentially into legal ramifications. “Legal and economic consequences from failing to comply with regulatory requirements” (4).
As everyone catches on this trend of self-service and data discovery tools, differentiation will lie in the 20% of businesses who are investing in processes, governance and data quality.
Executives signing the checks on these BI spend, need to ask the following questions now!
- How reliable are these insights?
- What’s the quality of the data feeding these insights?
- Am I bringing in the right data sources?
- Am I making the right connections with the data sources?
- Why are insights across various business analysts different?
- Do I have a process to ensure data is being governed?
- Do I have a tool to set up data governance so that my insights are accurate?
- Is my process setup to handle bad data quality
- Do I have a system which manages by exception?
Riversand understands this. Our Multi-domain MDMCenter is built on providing downstream users with governed and good master data, on which they can base actionable insights. We offer Data Stewardship and Governance through our Data Quality Management module, which comes integrated with the basic product offering. Through our visual representations, user can view in process data quality compliance and act on exceptions.
Now you can focus on growing your business with customer acquisition and engagement and rely on us to deliver governed and good master data.
- Gartner: Forecast: Enterprise Software Markets, Worldwide, 2012-2019, 4Q15 Update, 17 December 2015
- Gartner: Use the Gartner Business Analytics Compass to Drive Strategy; 19 November 2015
- Gartner: Survey Analysis: ITScore Assessment Shows BI Maturity Remains Low With Organizations Ill Prepared For Challenges Ahead, 05 August 2015
- Gartner: Establish a Framework for Analytics Governance, October 30th 2014, Gartner Foundational, Feb 2016