Baselines are wonderful. According to the dictionary, they are: a minimum, or starting point, used for comparisons. Why is this wonderful? It’s because a starting point does not have to have any external comparison, no judgement.
This is hugely important if you want to successfully start something that will be sustainable. You have a starting point and you can measure against it …later. It is easy to become defeated when you think about starting something new or even a reboot of something you’ve been doing for a while.
A starting point is not overwhelming. But if you think about starting something new with the mindset of immediately comparing it to one thing or many things, it is overwhelming, defeating.
All of this I’ve said in a statistical (analytics) scenario. But it happens in everyday life, too. For example, I am pretty awful at keeping my car clean. I don’t eat a lot of fast food, so it is not filled with trash and greasy wrappers. But I do park in a parking garage, and honestly don’t drive that much, so it can get very dusty. Rather than doing anything about it, I just thought how great it would be to have a clean car. But in my mind, it turned into a big project – getting it spotlessly detailed, or even a bigger deal, me doing it myself…and then the upkeep. All of a sudden a dusty car didn’t seem so bad.
But back to analytics. Statistically or analytically speaking, a baseline is important to start or reboot your data driven approach. Many people think analytics and they immediately jump to a benchmark mentality. How do I stack up to my competition? That is dangerous.
Eventually you’ll want to strive to meet or exceed your competitors performance. But you need a while to ‘level the playing field,’ to get comfortable with, and understand YOUR data. Once you are comfortable, then it will be fair to compare.
But first, think ‘starting point.’ And, hey look. It may not be the cleanest car in the parking garage. But it’s a start.