FMCG businesses are awash with data, some of which involves parting with hard earned cash in order to buy from third parties. This makes sense if you are equipped to analyse that data, but it does take time, skilled resource and therefore, more money!
If you've had the chance to read some of our content before, you will notice we almost always either implicitly or explicitly refer to humanising data. This term, for me, sums up ‘the SKUtrak difference’ against other sources of retail data. The term, is not just some buzz-word or strap-line, it’s what we believe in and, when I say we believe in it, I mean we really believe - sometimes to a fault. In the early days of SKUtrak, we spent many hours deliberating whether we should actually allow our users to download ‘data’ from the platform or if we should stick strictly to our beliefs and only offer visual representations of Flow-of-Goods data. We conceded that this might be taking our beliefs too far - SKUtrak doesn’t do everything (yet!) that our users would need from retailer data so we shouldn’t restrict the ability to take the data elsewhere and make use of it. Of course we’d hope our users attempt their own ‘data humanisation’ but at the very least, they are able to feed the curated SKUtrak data into their own systems, spreadsheets or data viz tools.
“In order to be irreplaceable one must always be different.”
Coco Chanel
Good question, glad you asked! We have some clever people here at Atheon HQ and they will be able to dazzle and delight you with the science behind how the human brain has evolved to be able to interpret specific visual cues. My colleague Simon Runc regularly presents internally to the entire company on the science behind data viz and it is truly fascinating. The premise of data visualisation is that the human brain can only hold about 5 numbers in memory at any one time, meaning you will start to struggle spotting patterns in daily sales data for just one week if you are just looking at a spreadsheet. What the brain can do instinctively is differentiate between colours, hue, position, shape etc. It’s this core concept which forms the basis of what we do with retail Flow-of-Goods data - instead of a spreadsheet consisting of 15 columns and 100 rows, we visually represent that data in perhaps 3 charts on a dashboard. We then make these interactive so the user can hover and click and more information is revealed. In short, we surface the things in the data that we believe our users need to know, whilst still giving them a way to Explore the data where they need to.
As well as making data accessible to the masses, humanising is about making the data actionable and relevant. We believe that there is a place for looking at data weekly, fortnightly or monthly in arrears BUT SKUtrak encourages you to look at the data daily. If you don’t have time to look at it daily, don’t worry - SKUtrak updates every day so you can always see what happened yesterday. So if you have a promotion that started 3 days ago, you won’t have to wait until your periodic data is delivered, you can log in and see how well the promotion is going up to yesterday. It’s an adjustment in ways of working (for some more than others), but it could transform the way your business operates and can demonstrate to the retailer that you are proactive, informed and a supplier to be trusted.
Here’s a spreadsheet which shows just 8 days of volume sales and average selling price, for 4 SKUs:
Now here’s some fairly straightforward questions I’d want to ask of that data:
And now for the answers...
Easy, it’s the one at the top with the longest bar:
Easy, I can see from the above chart that I sold >17.6k units of Sadies Hot Chilli Tortilla, but if I want the exact number I just hover over the bar:
Easy, I look for the tallest bar:
Hmm, did you mean average selling price cumulatively for the 4 SKUs:
...or did you mean by SKU:
I think by now you are probably getting the idea, and hopefully I successfully ‘humanised’ SKUtrak’s ‘difference’. To give a little more context, the charts I’ve shared above all form part of just one dashboard, from one retailer, and from only one of the products available within SKUtrak:
Do you really love the spreadsheets themselves or is it the value you can demonstrate to your business by successfully wrangling an unholy mess of retailer data into something the business can understand? I get that Excel wizardry is a skill in itself (it paid my mortgage for a number of years), but where your skill really lies is knowing your business and being a domain expert. Less time gathering and manipulating data into spreadsheets means more time sweating the data, identifying issues and fixing them!
We can’t win everyone over, so please accept this as a gift from me to your spreadsheets:
=MID("theskutrakdifference",2,1)& CHAR(CODE("theskutrakdifference")+1)&CHAR(CODE(MID("theskutrakdifference",18,1))-1)&MID("theskutrakdifference",9,1)&MID("theskutrakdifference",(LEN("theskutrakdifference"))-2,1)&MID("theskutrakdifference",12,1)&MID("theskutrakdifference",4,1)&MID("theskutrakdifference",3,1)&" "&MID("theskutrakdifference",11,1)&MID("theskutrakdifference",9,1)&CHAR(CODE("theskutrakdifference"))&MID("theskutrakdifference",9,1)
If you don’t understand what the hell this jumble is, then get in touch - you’re our kind of people.
Ed started his career as a data analyst at a market research company working with FMCG suppliers to grocery retail, followed by several years heading up a team of data and consumer behaviour analysts. He joined Atheon Analytics in 2009 where he built the development team before moving into his current role as Product Manager.
Atheon helps FMCGs and Retailers to make better use of their ‘Flow-of-Goods’ data through their SKUtrak service.
