Despite all the energy, hype, momentum, development, and investment towards it, adoption of analytics at the enterprise level is still low and 87% of the data science models never make it to production.
My name is Ahmer Inam, a data and analytics evangelist with former leadership roles at Nike Inc, PwC, Quaero, Sonic Automotive, Wells Fargo, and Cambia Health Solutions. I have been invited by IIA to share my perspectives on driving adoption of analytics at the enterprise level from my personal experiences. I will also be co-hosting a webinar on this topic with Bill Franks, CAO of IIA.
This is a hot button topic that is openly being discussed among analytics leaders who have been at it for a while. I had a recent dialog on this topic with Brian O’Neill and we both agreed that taking a human-centered design approach is likely a solution towards building data products that would see organizational adoption and drive value.
Brian wrote a blog for IIA recently <https://www.iianalytics.com/blog/2019/3/26/garbage-in-garbage-out-design-process-survey> and I agree with his observation that great products or services are not driven by just a requirements document and we have to involve users in the process. Brian and I will discuss this further in-depth in his upcoming podcast, Designing for Analytics.
The framework that I use to develop and deliver analytics products comes from being in the trenches and learning from past mistakes and failures and incremental successes. This framework includes the following steps:
Culturally Grounded Strategic Vision
Adoption Driven Team Structure
People + Data + Tech as Enablers
Multi-Level Business Partnerships
Focus on Winnable Problems
Drive and Measure Value
Impact Based Storytelling
Analytics in most organization is still a new function and the analytics leaders, to be successful, should focus on learning the embracing the cultural drivers of the firm. Every organization has a power-center in the C-suite which usually is driven by the leader who is responsible for the core function of the organization, e.g., a COO in a Supply Chain driven firm. In addition to that, there are cultural accelerators and detractors that analytics leaders would have to be aware of. “If we build it, they will come” approach just wouldn’t work. Analytics is a change agent and the analytics leaders should embrace their responsibility towards driving change management. The strategic vision for the analytics organization would then need to be honed in on that.
Beyond that, it gets a bit easier as we can then rely on our analytics experience and expertise to identify the winnable problems that would drive incremental value, setting up the team towards driving that, with continuous measurement and storytelling focusing on the impact. One formula of success for me has been the inclusion of end-users and domain experts as part of the scrum team itself. Designing products with the people, for the people, has proven to be of tremendous value in demystifying analytics and delivering on the promise of the art of the possible.