I just learned the term ‘yak shaving’. It’s not really clear to me if it’s usually a positive or negative thing, but today I want to talk about a good kind.
The definition of yak shaving from Urban Dictionary is:
“Any seemingly pointless activity which is actually necessary to solve a problem which solves a problem which, several levels of recursion later, solves the real problem you’re working on.”
Apparently it probably originated from Ren and Stimpy.
I’m not sure what they were planning to do with the yak afterwards.
BI dashboard builders almost always seem to offer a speedometer or gauge as a favourite way of visualising your most important data. Like this:
Pretty enough to look at, I suppose. But an absolutely shocking example of data visualisation, which will absolutely not help people to run their businesses and will make using the dashboard a source of stress rather than a helpful and calm tool of control.
I’ve been talking to lots of people about the nascent Magic Dashboard product, and am starting to think that it’s amazing how many businesses there are which have no particular metrics tracking (or, only in the owner’s back-of-envelope tracking). A major reason why big chains succeed is that they can afford to pay for central resources to do all sorts of things, one of those being tracking their metrics and turning that into business insight and advice, which they can then apply at scale. The Magic Dashboard dream is to make business tracking easy enough that you don’t need highly trained and highly paid analysts to tell you what’s going on; as a competent and busy business owner it could be at your fingertips right away, without you needing to worry about the stats.
Anyway, loosely inspired by the excellent Tim Harford’s piece on coffee shop economics (you should go read it here if you haven’t already, and buy his book, it is brilliant), here as a thought experiment are three ways that my favourite local coffee shop could use a magic dashboard:
Here is a very striking example of how adding some simple analysis to a raw metric can be incredibly important.
When businesses talk about their ‘analytics’, most of the time what they’re actually talking about is plain graphs of business metrics. Maybe if you’re lucky they will also include some information on averages or on last year’s comparable values.
Business leaders get used to eyeballing these graphs and drawing their own conclusions about what’s going on. As I discussed in my last post, most of the time they want to know (a) does any point stick out and (b) what’s the overall trend. The problem is that humans are far better at spotting some types of pattern than others. Good basic data visualisation helps enormously, but still not everything you need to know is immediately visible. Take a look at the chart below – this shows online sales by day for a real business.