Wikibon’s recent Big Data analytics survey revealed several challenges practitioners face as they strive to gain actionable insights from their data. Many of these are technology related such as maintaining application performance and and integrating multiple data sources. But survey respondents also detailed some of the top non-technology related barriers to Big Data success. Among the top: selling the value of Big Data analytics to end-users.
This is a critical inhibitor and has a direct impact on Big Data ROI. For all the talk of the technologies involved in making Big Data analytics possible, all the technology in the world isn’t going to move the needle on sales, revenue, profit or any other metric if end-users don’t use the results of Big Data projects. This means business users leveraging data visualization tools to get a more accurate view of the business and insights about next-best-actions and then integrating these insights into their existing business processes and decision-making practices.
Put another way, people are often afraid of change. In business, this means people often prefer to continue making decisions the way they have for decades rather than disrupt their methods with a new way of operating. To overcome this barrier and spur adoption of data-driven decision making (powered by Big Data analytics that is often abstracted away from the end-user), Big Data practitioners must become data story tellers.
Consider the case of Seattle Children’s Hospital, which is actually three institutions in one. The clinical hospital specializes in medical treatment of children from birth through young adulthood. The research arm’s focus is pediatric medical research spread across specialties including cancer, genetics, and infectious disease. And Seattle Children’s foundatin’s mission is to raise funds to support both the clinical and research arms.
Eugene Kolker is Seattle Children’s Chief Data Officer. He and his team focus on data analysis services to both improve patient outcomes and increase operational efficiencies. For example, Kolker is leveraging Big Data analytics to find ways to improve complex disease management for chronic conditions such as diabetes. His team also analyzes the hospital’s use of various assets to find ways to improve resource allocation. The insights Kolker and his team generate are used by practitioners – both clinicians and management – throughout the hospital.
As complex as the Big Data analysis is, Kolker highlights another challenge: selling the value of data analysis to end-users. “You have to be a data storyteller. Otherwise you’re going to be somewhere and [end-users] will be in another place.” Kolker says getting end-users on board requires relating the impact of Big Data analytics to end-users in ways that illustrate its benefits in practical terms.
For example, if a Big Data practitioner can show a clinician (doctor, nurse practitioner, etc.) how the inclusion of new insights into his or her decision-making process will reduce patient readmissions by x%, the clinician is more likely to embrace new ways of operating that incorporate analytics.
Kolker said it is also important to include end-users in the development of Big Data analytics projects from the beginning. This way, end-users feel invested in projects and their outcomes. Otherwise, says Kolker, “you’re not going to make a big impact.”
Action Item: Big Data practitioners must be more than technologists. They must also be data storytellers. Practitioners must effectively communicate the practical benefits of Big Data analytics in order to spur adoption and make a meaningful impact.
