The Desire Paths in Your Data

On the days that I drive to work I have around a one mile walk from my car park to my office. There's one particular spot where I can take a shortcut by going off the paved path and cutting across some open ground. It saves me a minute or so on the way to work. Despite the fact that there is a perfectly good sidewalk built by the local council it's obvious that a lot of people must do the same as me, and opt for the faster route as well, because there's now a clearly worn path across the open ground, established by people choosing this path every day. Urban planners call these desire paths - the paths that people choose to take between two points regardless of other options that may be available to them.

If you look hard enough you'll find desire paths through your data as well. Your business intelligence solution offers many conventional paths (like the sidewalks built by my local council). These are the pre-built reports and other instruments that you present to your users. But I bet many of your users have built desire paths - the tips and tricks they use to get and analyse the information they need to do their everyday jobs. Or perhaps the extra things they have to do, those downloads and manipulations in Excel or the sneaky Access database sitting on a spare PC under someone's desk,  because your BI solution doesn't let them do their jobs or perform the analysis they need in its entirety. Now you could argue that desire paths in a BI solution actually represent a form of self-service BI. However, unless you've engineered things this way then you're probably only kidding yourself. Yes, desire paths are examples of your users finding ways to help themselves, but chances are that it's due to shortcomings, not features, within your BI solution.

Desire paths have a dark side in the natural world - they often result in trampled vegetation, can contribute to erosion and (not being as safe as constructed sidewalks) can also lead to injury for those using them. Similarly, in the IT world they are actually likely to cause harm to the reputation of your BI solution or of your BI team. Just like people in the natural world wandering a direct route desire path, shaking their head(s) and wondering why their local planning authority spent all that money building a meandering sidewalk twice as long as it needed to be, your users may well wonder where all of that IT spend on BI went, especially when they "can do the same thing (but better) in Excel". Perhaps worse still desire paths can cause actual harm to your organisation, be it financial or other type of loss, due to decisions based upon flawed analysis or data as desire paths can lack the checks and balances that come from underlying planning.

Our challenge as practitioners, managers and custodians of our organisations' BI assets is to find these desire paths (and in so doing also to find which of our pre-built paths are no longer as relevant as they could be). Can we build established footpaths where the users' desire paths have been worn in over months and years of usage? It works in the natural world and it can work in the technology world as well. There are stories of park planners in some countries visiting areas after fresh snowfall to get a sense of where those using the area are choosing to walk. I've heard of at least one university which built no structured sidewalks on a new campus until such time as the students established desire paths between buildings, simply choosing to pave these paths one year on.

In today's reality of shrinking budgets we all get busy just keeping our BI environments running and meeting the needs for new reports and analytics, let alone spending time worrying about how we'll deal with the next big (data) thing looming on the horizon. But I'd advocate there may be good value to be had in taking the opportunity to look for and act on desire paths when we can. The trick will be finding, or engineering, those occasions, like those times of fresh snowfall, when the circumstances are right to see the desire paths and incorporate key ones amongst them into your BI solution.

Happy (re)building!