Data Management and Analytics in the New Normal

What to do when you can no longer “trust your gut”? 

The digital analytics race has caused Consumer Goods Brands to focus on their ability to access data for better decision-making around commercial strategy and the wider Revenue Management approach. 

Key trends observed across retail and consumer landscape 

Assortment Rationalization -> retailers have revised their category management approach to simplify assortments, become more agile and provide more affordable products 

Channel Shift -> exponential growth of the online channel, the DTC development and people switching to more affordable store formats have significantly affected the customer/route to market mix and consequently affected profitability for CG companies 

Trading Down -> consumers are more and more willing to shift to more affordable brands and options when it comes to essential categories 

The above trends accelerated the digital transformation process for Consumer Goods Brands seeking to gain competitive advantage by making information more accessible and build robust analytics at scale for their commercial teams. 

5 lessons on data management and analytics to drive commercial insights in the new normal   

  1. Clearly map stock through the value chain ->the ongoing changes in route to market and channels mix within customers are adding additional layers of complexities when analysing promotional efficiency. Reaching consensus across supply chain, sales and marketing can become prohibitive unless volumes are clearly mapped across sell in, secondary sales and sell out. The wrong source of analysis can give a totally skewed picture of result when looking at the same metric (e.g. Net Incremental Volumes and Uplift). It is important to create awareness across the organisation of what these different metrics mean, but also establish strong central analytical capabilities to unlock insights.  
  1. Descriptive Analytics first -> Implementing predictive and prescriptive analytics is paramount for CG companies however, data models basic KPIs must be robust to bridge the adoption gap and build confidence in the organization. Adoption of descriptive analytics across Promotions, Pricing, Terms and Assortment should be the first step in the change management process.
  2. Rethink sales predictors -> sales models previously adopted are most likely going to be obsolete and different combinations of data sets are going to be required to drive better demand predictions. New data points across online and offline previously neglected should be considered on top of historical sales (e.g. consumer sentiment, consumer price index, etc.)
  3. Forget about your “Yearly Budget” -> previous years plans, and yearly budget can no longer be used as a benchmark to adjust commercial plans and tweak promotions to deliver against Joint Business Plan objectives. CGs capabilities to “archive” data and leverage “snapshots” of their commercial plans at a given point in time (e.g. on a weekly basis) has proven like a much better approach to support promotional reviews and drive meaningful conversations internally and with retailers 

  1. Agility and Speed to value win– >  CG companies should focus on the quick wins and deploy at pace new digital initiatives to build confidence within the organization rather than the other way around. Retailers planning cycles are shortening and consumer behaviours are changing more rapidly and both promotional plan and analytical tools require more frequent adjustments to fit business needs. The ability of organizations to implement and progressively improve through “Try and Error” can drive competitive advantage. 

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