Analytics -Making the Transition From “I Feel” to “I Know”

A young, bright, energetic MBA graduate from a top college joined the “Most Innovative Company Pvt Ltd”. He was full of ideas and keen to change the world with his overflowing cup of knowledge. Within one month of joining his company, he presented an interesting idea to his manager. His manager asked him to learn more details about the company, the business context and prepare a proposal. However, by next week, manager was running after quarterly targets and he asked the new joinee to focus on the targets, rather than the new idea he was pondering over.

Three months in the company, manager asked the trainee to focus on another idea, manager’s pet idea, which he has been pushing for a few years and was not able to move forward for lack of time. The trainee was assigned the task of preparing a presentation, putting the stuff together and do the background work. He got to spend a lot of time of his manager and three months down the line, the proposal was ready.

Since Business Head was visiting for annual review, his manager presented the idea to the Business Head. Business Head liked the presentation but did not feel that idea was significant. He asked the manager (and in turn, the trainee) to work on another project which was Business Head’s pet project. Another six months down the line and much effort spent, even that idea was rejected because CEO did not feel that the idea will succeed.

Does the story sound familiar? A lot of ideas get rejected because the idea champions fail to convince the decision maker. If a decision maker FEELS that idea will not work, that is the final outcome. If you look at the whole story, it was all about different people making decisions on what they FELT will work or not. In the end, idea champions failed to present data and customer insight to support their idea. Projects were conceived because managers FELT that they will work, they did not KNOW that they will work.

That’s where analytics is important, in removing the guesswork from decision making. It is important to use customer insights from data and if data is missing, collect it before making the pitch. Make the decision maker believe that you KNOW that the project will work.