More data points will be created in 2025 than all the years of data put together before it. The amount of data we create, store and use, is growing exponentially year by year. In previous articles I have written about the new spiderweb of a shopper path to purchase and the increasing fragmentation of trade activities that is driving up Trade Spend, despite depth of promotion declining. All of this is driving up the volume of data created in the FMCG space and the understanding of this is key to profitable market share growth.
A great example of this is image recognition. Over the past years of my career I have been lucky enough to work with TRAX- market leaders in Image Recognition technology in the FMCG space. They helped me track everything from Distribution to Share of Shelf and Display. A global program operated in over 30 countries, tracking over 75,000 stores. Now if do some maths: each store had roughly 10 photos taken in it, with approximately 5 KPI’s and +20 SKU’s meaning we had over 1000 data points measured per store per visit (often with multiple visits per month). A minimum of 75M data points per month, each of which can tell a story of profit, loss, revenue gain or decline. Thats crazy what do you do with 75M data points? How do you even make head or tail of that amount of data and turn it into something meaningful. I have long tasked TRAX with taking more responsibility for the data that they provide to FMCG/ retail organisations- to turn it into valuable insight, but the truth is, it is their customers that should be truly accountable. Image recognition can tell you that you only executed 50% of your planned displays, an informed, engaged and accountable organisation can ensure that the spend that went behind paying for them is recouped.
My point is this, when there is so much data it can be hard to see the wood from the trees. Where to start first with Image Recognition data- is it closing Must Stock List (MSL) Gaps or that less than perfect secondary display execution. So what is the solution because this data problem is going to continue to grow.
1. Companies must start to ORGANISE their data. It’s is painful and expensive but to be able to take advantage of the new age of AI your data needs to be in the right place. Set up master data platforms- customer and product, maintain them and invest behind data at the start to make your life more simple in the future.
2. FMCG organisations must start to STANDARDISE some elements of their categorisation- this will allow for data organisation. The Grocery channel can by name be anything from Grocery Retail, Supermarket, Hypermarkets, Consumer Grocery or Food & Beverage. It cannot be all; it needs to be one and markets will need to accept that.
3. How you VISUALISE your data is key. Through visualisation you can deliver simplicity, engagement, cultural buy in, insight and action all at the same time. Knowing how to represent your data in an easy, clean and consistent way, arranged around your business priorities is what sets apart great digital platforms from good ones.
You can only really deliver on Point 3 if you deliver on Points 1 & 2, but it is absolutely critical that in modern commercial organisations you either have dedicated resource that understands both data and commercial or partners that can help you deliver against these new requirements. Choosing what KPI’s you run your business on is a science, visualising those KPI’s is an artform and can only be done by people who know what is at stake- a data scientist without context and knowledge of the topic is like an artist without any idea of what to paint.
Visualisation can help drive engagement behind your KPI’s and engagement is key to action:
- If the data is easy to read, more people will read it more often and take action.
- If the data is well presented people will understand it more easily, spend more time looking into it, identify more insight, opportunity and take action.
- If the data is clean and transparent, everyone in the organisation will access it, live it and breathe it and your KPI’s will be adopted as culture
- If the data is easy to read, the chances are your boss will read it and you wont need to spend 48hrs making a presentation on a topic they should already know about.
In this new world of over loaded data, increasing fragmentation of activity and diversifying channels of engagement, being able to master this artform is critical. Less is more when it comes to data, and how we visualise our data helps understand more whilst using less.
.png)
Subscribe to our newsletter.
