Comment: Category management in an omnichannel world
Shoppers are undertaking ever more complex journeys when buying goods, which straddle numerous channels, while also becoming increasingly demanding in terms of how they expect to be serviced by retailers. This includes both a need for immediacy of delivery and the tailoring of offers to their specific preferences.
The result of this revolution in customer behaviour is that the old ways of category management are reaching their sell-by-date. They are being superseded by a new way of working. From traditional task-driven methods, based on past sales, the industry is gradually shifting towards a more customer-centric methodology that adapts to real-time demand and customer behaviours by utilising a myriad of data sources.
This represents a marked strategic change for the retail industry that has to date largely recognised category management as simply a spreadsheet juggling exercise that uses scant amounts of data beyond the basic information that flows from a Point-of-Sale system. As data becomes more widely accessible, and in turn an increasingly vital business tool for retailers.
The profusion of data sources and the growth omnichannel retail are combining to drive significant change. Consumers are saying to retailers: ‘meet my needs regardless of whether I am in-store, at home, or on the move using my mobile devices’.
Mobile is certainly playing an increasingly impactful role. It is likely that this year’s Black Friday sales will exceed those of Cyber Monday because many people will be in-store on their mobiles comparing prices.
This ‘always-on consumer’ is fuelling an immediacy that is forcing retailers to adapt to remain competitive. To meet the new customer needs requires radical action (all based on available data) to be taken in the supply chain.
Making sense of data
This boils down to three key points: an ability to anticipate demand; the alignment of assortments with local demographics and shopping patterns; and the translation of assortment decisions into executable space plans that optimise space allocation.
For these to be deliverable on the shop floor requires category management to involve the whole supply chain. This means there needs to be greater collaboration between suppliers and retailers. They both need to work together on a new breed of KPIs (Key Performance Indicators) as well as working together to better understand the segmentation of customer bases.
Fundamental to this is customer data – regardless of whether it is sourced from an in-house CRM system or loyalty programme, or bought in from a third-party like Dunnhumby – that all contributes to the ‘secret sauce’ of the retailer or brand owner. This appetite for accessing customer data and the visibility it gives on demand patterns is undoubtedly behind the recent deal by Unilever to buy Dollar Shave Club for $1bn.
But it is not just about access to data that is an imperative today. It is a blunt instrument unless rich insight can be derived from the raw data. Hence data science needs to be thrown into the mix. New capabilities like machine learning are developing at a rapid pace and will have a growing impact on category management as it will provide the indicators of what actions to take.
It will help create a better understanding of the market and enable a greater sensing of demand through more predictive capabilities. The fact is retailers need to leverage the available consumer insights to support increased localisation and personalisation as well as dynamic pricing and improved merchandising.
The major grocers have recognised the need to take onboard this thinking as they come under increased pressure from discount chains. They need to more efficiently manage their inventories across different store formats – through localising their assortments.
Such moves towards localising the offer is putting a strain on retailers and manufacturers who are finding the old way of using planograms is simply not sustainable. The need for constant generation of new planograms to support their increasing desire for localisation strategies is highlighting the fact that automation needs to be introduced into their systems. This will reduce labour-intensive human touch-points and lead to real-time capabilities within the category management function.
This is not some dream-like scenario that will only come to fruition many years into the future because, for instance, we are already seeing the early signs of assortment planning being re-invented.
Next-generation retail planning
The next generation of retail planning solutions will enable retailers to think like their customers shop –with data science scoring of individual items in the assortment by customer segment and cluster, using historical buying behaviours to forecast their predicted performance. This will enable planners to align product selection with customer preferences while maximising sales, margin and inventory productivity.
To help the industry progress along this journey towards creating the next generation of category management solutions, we are starting to see increased cross retailer collaboration, as they strive to create a framework of best practice.
Although such collaboration is an acknowledgment of the magnitude of the challenge ahead it also highlights that the category management industry is working hard to create future solutions that will deliver on the increasingly complex demands of both customers and retailers.