Exposing the Myths – why FMCG Data is much simpler than you think

Each time I read an article about data, I am reminded of ‘Good to Great’ (by Jim Collins). The book exposes the many myths often credited with creating large-scale corporate change. For me two of these myths in particular always underpin the dialogue about data. The first is The Myth of Fear-Driven Change — the idea that a fear of being left behind, the fear of seeing others win or the fear of failure would propel a business to change. Or The Myth of Technology-Driven Change — the idea that technology itself will deliver the big breakthrough the business is looking for. All the buzz about big data, prescriptive analytics, math men and modelling uses these myths to sell complex data solutions.

The good news is that data in FMCG is much simpler than this. If you are looking to use data to step-change your business, you need a back-to-basics approach. For FMCG Sales and Marketing Analytics, there is a wealth of data available that can yield rich insight. There are three key sources of FMCG data: internal sales, field sales and retailer data. The data should be used to explore market size and trends, channel/retailer performance and brand dynamics (yours and competitors’). The insights generated from analysing the data will support two key activities: business planning and customer engagement. To get value from data and support these key activities, the business must be doing analysis as well as reporting. Reporting is the process of organising and summarising data in an easily-read format to communicate important information. Analysis is an interactive process of the analyst transforming the information in these reports into insight.

Now you know the scope of the task, how do you set your business up to succeed? According to Collins (‘Good to Great’) it starts by getting the right people for the job. He uses the analogy of getting the right people on the bus, advocating that this should happen before setting a new direction. The right people consistently put ‘a shoulder to the wheel’, contributing a series of small steps which will gain momentum over time. This ‘Flywheel Effect’, according to Collins, is how businesses progress (move from good to great).

So how do you identify the right people to design and analyse reports in FMCG? At the risk of stating the obvious, they should like working with data and have a combination of both technical and commercial skills, with the emphasis on the latter. Surprisingly, many of those working with data in FMCG can be described as ‘accidental analysts’, having inherited the data brief by moving from another position in the business.  Another shortcoming of the FMCG model has been to isolate the data brief in one function (usually category management). This does not recognise the importance of having data skills available across multiple functions e.g. national accounts, field sales and marketing as well as category. It is limiting model and one which sells some of the data-rich areas in the business short.

To summarise, if you want to move your data journey forward, ignore the data myths that are fear-based and push technology solutions as the answer. Remember that FMCG data is simple and make sure you take the following steps:

  1. Decide how you want data to support better business planning and customer engagement.
  2. Ensure data skills are available across multiple functions.
  3. Confirm that the business is doing analysis as well as reporting.