Three Organizational Best Practices for Becoming Data-Driven
If people in your enterprise don't buy into data-driven techniques, try these three organizational best practices to make individual change more successful.
- By Fern Halper
- February 16, 2018
My colleague Dave Stodder and I recently finished writing our Best Practices Report, What it Takes to Be Data-Driven: Technologies and Practices for Becoming a Smarter Organization. What struck me in analyzing the data for the report is that although organizations have embraced BI and analytics, they still have a journey in front of them to become data-driven. About a third of our respondents felt they were data-driven; another third felt just the opposite. The final third are sitting on the fence. The good news is that over 80 percent of respondents to our best practices survey felt they were moving in the right direction to become data-driven.
Defining Data-Driven Practices
What does that right direction entail? In the report, we describe the data-driven organization as one that makes informed, evidence-based decisions -- that is, an organization that can formulate and answer business questions easily using relevant data, reports, visualizations, and analytics and take action on the answers. Becoming data-driven is both an organizational ambition and an imperative; it involves culture as well as technology. It is about using data to take decisive action, in addition to building relationships and trust around the data, how people look at the data, and how they analyze it.
A data-driven organization has certain technological and organizational characteristics. The technology side includes integrated data management and support, good data quality, an integrated analytics tools strategy, and the ability to operationalize analytics and drive action from these analytics. On the organizational front, it includes strong leadership, transparency, governance, and an empowered team with a self-service culture. A third of the survey respondents had no data governance in place and over half were not satisfied with how they were moving forward in terms of self-service.
Your Data-Driven Enterprise Needs Everyone on Board
Problems on the people side of the equation are often harder to overcome than the technology obstacles. That's why getting the people aspects right is so important. If the people in the organization don't buy into becoming data-driven, then it likely won't happen. A few organizational best practices that help facilitate individual change include:
- Incentives. Only 7 percent of respondents use incentives such as bonuses or recognition for those who apply BI and analytics to decisions that deliver measurable output from efforts. Organizations need to focus more on incentivizing individuals to use analytics. This cuts across the organization, from a business manager using self-service analytics to a call-center agent who may use the results of an analysis to suggest a next-best offer to a customer. Incentive plans should be well-thought-out and attractive to specific roles.
- Empowerment. An organization must empower users to apply data and analytics to solving business problems. It is not enough to supply users with self-service tools so they can be independent of IT. Users also need the structure, governance, and facilitation of training and skills development that IT can provide. This helps to build confidence.
- Analytics literacy. Developing skills and analytics literacy is critical for success. This is the case for those performing analysis as well as those using the results of analysis as part of an operational business process. With literacy comes trust, which is also a key for success. How can organizations expect a business user to analyze data if she doesn't know how to use a tool or think critically about data? How can a call center agent use the analytics results if he hasn't bought into the idea or doesn't understand what the results mean? Knowledge helps people feel empowered.
Of course, as one of our survey respondents noted, "In order to break down barriers it is important to take time to step back from both the analysts and the data and get to know people on a personal level." Building relationships and trust is often the key to cultural change.
For more on building a data-driven organization, please read our latest best practices report, which can be found at https://tdwi.org/research/2017/12/bi-all-ppm-all-best-practices-report-what-it-takes-to-be-data-driven.aspx.
Fern Halper, Ph.D., is well known in the analytics community, having published hundreds of articles, research reports, speeches, webinars, and more on data mining and information technology over the past 20 years. Halper is also co-author of several “Dummies” books on cloud computing, hybrid cloud, and big data. She is the director of TDWI Research for advanced analytics, focusing on predictive analytics, social media analysis, text analytics, cloud computing, and “big data” analytics approaches. She has been a partner at industry analyst firm Hurwitz & Associates and a lead analyst for Bell Labs. Her Ph.D. is from Texas A&M University. You can reach her at firstname.lastname@example.org, on Twitter @fhalper, and on LinkedIn at linkedin.com/in/fbhalper.