Accept Software Resource Library

Analytics, Innovation and Thinking

Our team here regularly reads the ribbonfarm blog by Venkat and one of his latest posts created quite a stir interesting enough to bring the conversation here.

It’s a long read, but I encourage you take a look before reading on.

If you dig into the comments you’ll find that Venkat had a set of experiences in his professional life that made him frustrated with people becoming overly-analytical. He feels surrounded by people using statistics to “avoid thinking” and ultimately deflect blame for failures to the analytical model.

When Venkat says some bring the data driven model to a “holy activity”, that’s no joke and for many his comments are like an assault on their religion. Data is a tool so powerful, it’s no wonder it’s prompted a level of near-religious following. I’ll count myself amongst followers in that church.

Getting back to the root point of the post, here’s my comments on the issues raised and I’d like to hear what our readers think as well.

Religion
First off - we all acknowledge that analytics are a good thing. This discussion is NOT about whether analytics are good or bad, but whether people are using them well and balancing them with other forms of thinking.

Speed
A key point that Venkat did not raise with excessive analytics is that organizations tend to become crippled by inaction as they embark on an endless quest for ever better, more confident data. What organizations need to focus on is getting “good enough” data to make actionable decisions FAST.

We had what we call an “innovation jam” here at Accept, which was a 3-4 day sprint. We went through 79 feature ideas submitted by customers through our own ideation platform, narrowed that down to 27, then 9, then 5 and created 5 new features in less than a week.

Spending three months to go through the same cycle wouldn’t dramatically reduce the risk of failure, it would only mean we took too long to fail. Too long to learn our lessons and too long to get the product to market. Excessive hesitation caused by an obsession with finding perfect data are focused on avoiding risk, avoiding failure, when they often just need to fail faster so they can get it right.

Accountability
I think if analytics are a scapegoat – if people are not held responsible for the decisions they make, because blame can be deflected to an error in number crunching – that’s an organizational and cultural problem.

Everyone needs to be accountable for results, not mistakes. Additionally, accountability needs to be so clear and pre-ordained, there is no escaping it. If you match that organizational culture with an acceptance of failure where employees are comfortable admitting failure and finding solutions, then you have an atmosphere for innovation.

This excessive level of analytics is prompted mostly from a fear of failure. Get over it, fail faster, and you’ll succeed more.

Thinking
Venkat’s blog post is named after something he describes as a meditative state of deeply considering a specific use case. I think the fact that people don’t do this is reflective of the nature of modern product management. The pace of release deadlines is so grueling, that taking some time to stop and think isn’t budgeted into our daily schedule.

Without injecting strategic thinking into innovation, we end up developing fast, but bringing the wrong products to market. Venkat’s post has some interesting guidance on how to do that thinking, but however you do it, just stop, think, and make the right decisions, fast.

Analytics are a powerful weapon, but just as they can foster intellectual decisions, influence product development in the right direction or validate thinking, they can also create slow, lumbering lethargy.