Data analytics - the final mile problem

HBR published an interesting article for what is essentially the “final mile problem” for data analytics. The article is here https://bit.ly/2TEc8HA but it got me to thinking about solutions.

The premise is that companies spend all their time, energy and focus on getting, cleansing and storing data. They spend more time and money choosing an analytics tool and getting approval. They finally get a “yes” and celebrate. Then they sit back and wait for the million-dollar insights to come rolling in from their employees. Except they don’t. 

From my experience, people all respond differently to change…especially technical change. You need to approach them from a lot of different angles to see what sticks. Here are ten things I’ve learned from doing this before…

1.   Pick a user-friendly tool. Don’t stumble right out of the gate, choose an analytic tool that’s intuitive and that doesn’t intimidate.

2.   Who’s in charge? The business? IT? An analytic center of competence? Scott Baio? It matters less who you choose, but you’ve got to pick one. 

3.   Communicate the strategy. Most people aren’t lemmings. They need to know why they should do this and how it all hangs together. 

4.   Make it personal. You need to make a compelling case for analytics at the individual level. If it doesn’t make a person happier, richer or skinnier, it probably isn’t going to take. Data visualize the pounds away!

5.   Analytics translators! If you don’t know what they are, you should. Critical folks who bridge the gap between the business and IT. https://mck.co/2HRBnQ6

6.   Find your data influencers. You know who they are…the ones you always go to when you need an answer. You need to get these people to buy in and become your data ambassadors…your analytical trendsetters. Help your analytics go viral.

7.   Training, training, training. Group, individual, online, in person, videos, documentation…we all learn differently. It must be available and tailored to the specific person’s level and needs. The data needs of a Sr. Manager are much different from a business analyst. Coach accordingly. 

8.   Time to for people to learn it…at their speed, with their data. People are busy…often because they are ineffective at performing analytics…and so don’t have time to learn effective analytics. Hmmm…

9.   Support – build a community. Don’t let people suffer in silence. Learning a tool or building a model can be challenging, especially early on. Don’t let people become discouraged. Have your subject matter experts host office hours, have a SWAT team to quickly resolve problems, an analytic Batphone...anything to help people maintain their analytic learning momentum.

10.   Support from management – visibly use the data to make decisions, use the tool/dashboards in meetings, praise others who do likewise. 

It's a shame to do all the upfront work and drop the ball at the very end. It is also very difficult to regain momentum if you miss your first opportunity to do this. Make your final mile, your best mile.