For the past 4 weeks I have been commuting by bicycle and it has been one of the best things I have ever done. Not only have I saved a bunch of money by not driving a car, I have felt great. The big surprise, however, has been the transformation it has brought to my life.  Normally, commuting by car takes an hour in normal traffic and parking. Biking takes an extra hour per day, when you factor in both ways. But for that extra hour I am getting 3 hours of exercise. I was already a regular 2 hour per day rider, so by killing two birds with one stone I am saving an hour, and getting another hour of exercise. I am also aware of the stress that driving through traffic induces. I don’t know exactly why, but driving during rush hour makes us miserable, and judging by the way we treat each other on the roads, I’d say this is widespread.

Something about the silence on the bike, left to my own thoughts, reflections and efforts is peaceful and productive. I’ve solved difficult problems and planned busy days while pedaling. My mood and energy are off the charts. I have felt so great that I don’t think I can give it up. I often wonder why I don’t see more people commuting by bike, and I have come to the conclusion that this is one of those things where perception and reality are just not aligned. Isn’t it puzzling that a person would drive a car to work for an hour, drive to the gym after work, ride a stationary bike for an hour in a spin class, and then get home just in time to have dinner and put the kids to bed? Somehow that scenario is perceived to be more time efficient – a bad assumption. It is neither time, stress or financially efficient when compared to riding a bike. We’ve just come to assume that this is how it should be done. Worse than that, there are far too many people who have accepted the level of health and well-being that driving takes from them every day.

What does this have to do with business analytics? The other day I tentatively confessed to a manager that the amount of data and formatting required for a specific report was creating complexity that made it difficult to complete. This led to a conversation where I came to realize that Finance, for example, typically asks IT for much more than it needs because they routinely respond to ad hoc requests from management and do not always know what data they might need to see on a report. Thus, reports are not designed to answer a specific question, but a handful of them – just in case. These complicated reports expose challenges to data integration, and make it difficult for report designers to understand the purpose of the report. This results in slow report development, poor performance and frustration on both sides. Finance is frustrated because it takes so long to produce reports, they perform poorly, they encounter errors too frequently and it is difficult to make changes. IT is frustrated because the reports are far too complicated, they perform poorly, and they are hard to support and maintain. Everybody is frustrated over the same things.

Is there an answer? Maybe. If IT focused on delivering an ad hoc data environment, instead of reports, and trained Finance to use it, things might be better. If we stopped making reports loaded with data for finance to export to Excel and produce pivot tables, and instead delivered an environment where a wide range of questions can be answered, paired with simple and appealing visualizations to enhance understanding, we might sidestep a lot of headaches. No more 3 hour run times, 15 minute downloads, or formatting miracles to produce complicated reports that are hard to create and hard to understand. Instead, a quick and flexible environment that can respond to a variety of questions with ease and simplicity. What will it take? A different approach.

A few decades ago American companies changed the way they managed inventory and production in favor of a variety of methods collectively called Just in Time. The basic premise was to align materials, plans and labor with demand. One of the key ideas born out of this transition was to be able to quickly produce what was needed, when it was needed. Today, Finance wants a suite of reports that include everything – just in case. In order to implement Just in Time with analytics, we need to create reliable and flexible databases that are easy to understand and pair them with tools that Finance and the rest of the business can use to get the answers they need, when they need them. This will require different, but not more, effort on the part of finance and IT. Instead of designing reports, IT will design databases and user interfaces. Instead of searching through reports for data, Finance will search the database. I think that when we achieve this, we will realize that it’s not only less effort, but it is more effective and more valuable. We will save time, produce better information and avoid many of the challenges that are tripping us up today. Now, back to pedaling!

QuantifiedMechanix