More than 30 senior executives from leading organizations around the Washington DC and Baltimore region attended our first networking and learning event, Distilled Data, in June at Sagamore Spirits Distillery.
While everyone enjoyed delicious refreshments provided by the Copper Kitchen, we heard presentations by Brooke Jones, founding partner at WebbMason Analytics; Robert Emerson, vice president of strategic data management from BlueCross North Carolina; and Greg Cashman, a sales engineer at Dataiku.
The presentations stimulated lively discussions and attendees opened up about their successes as well as the challenges they face as they manage the shift to data-centric business practices.
“We had a great discussion, not around specific technologies, but about strategy and the difficulties of implementing the cultural changes needed to embrace fact-based leadership,” said Todd Jones, managing partner at WebbMason Analytics. “From putting the right team together to proving value, everyone was incredibly frank about the obstacles and what they are doing to overcome them.”
Top three barriers to analytics adoption
What skills do you need on the data and analytics team?
“It’s clear from the group’s conversations that determining which skills are needed, nice to have, or not required, is still open to debate,” said Todd.
Everyone present agreed that subject matter experts, who know the business, data and processes, are vital to success. However, there were considerable differences in opinion about whether you need a business or data analyst or both.
At WebbMason Analytics, we see these as two very distinct roles. While both work with numbers, a business analyst is focused on the data from the perspective of its implications to the business, whereas a data analyst sifts through information and provides expertise for the enterprise’s core systems.
How can you show the ROI for analytics solutions?
The group wanted to know if analytics platforms are a replacement for existing legacy systems, such as the data warehouse, and what the ROI of such a replacement would be.
The short answer is that an analytics platform complements legacy systems in the short- and mid-term. Long-term solutions may see the analytics platform replace the data warehouse. Justifying the ROI is a mid- and long-term goal. To realize the return in a measurable way, ROI needs to be evaluated from multiple points of view before implementing the solution, including full or partial system replacement and supporting new products requiring new types of data not possible with a legacy system.
We are so adamant that ROI should be established for each investment that we’ve developed a three-part framework that we use to calculate and validate the impact of advanced analytics solutions on both cost and revenue.
How to get support for data analytics projects?
Getting buy-in for holistic analytic investments can be difficult because they impact so many parts of the organization.
Instead of getting into the technical details of a solution and its implementation, analytics leaders need to tell stories that show stakeholders the benefits of data and analytics.
Whether they are big or small, incorporating business wins into the narrative helps drive home the message that analytics offers a new fact-based approach to solving business problems.
While these are the big three takeaways from this event, executives and their organizations face a multitude of cultural, personnel and process challenges that extend far beyond choosing the right technology and data sets.
Working with a partner such as WebbMason Analytics can not only help you avoid the pitfalls but also help you accelerate your transition to a data-centric enterprise.