More than 20 years ago I worked with algorithmic and heuristic-based supply chain management solutions. These were aimed at harmonising and optimising the disparate data signals that at that time emanated from siloed systems which, in the main, were either ‘challenging’ to integrate and in some instances, probably all-but impossible to do so.
Enterprise Resource Planning (ERP) systems were the vogue, created to provide a more streamlined view of a business’ transactional operations and this certainly assisted when it came time to source the data needed to calculate sales history, which would in turn be the foundation for the generation of future demand forecasts and distribution supply models. Some ERP systems had rudimentary functionality, but the majority performed better when mated to best-of-breed decision support systems engineered from the ground up to cater for the task in hand.
2017. And many of those challenges seemingly remain. And yet…
Over the years, I’ve been intrinsically involved in internal and partner-based collaboration processes and supporting tools, such as Vendor Managed Inventory (VMI), CPFR (Collaborative Planning, Forecasting & Replenishment), S&OP (Sales & Operations Planning) and ECR (Efficient Consumer Response), all of which have been targeted at further optimising operational practices. Many of the pitfalls relating to siloed data repositories and disjointed atomistic reporting capability have continually hampered efforts to fully exploit these process concepts. However, through advanced analytics, contemporary data tools and an ever-evolving understanding of how best to leverage the latent information contained within the vast array of data generated every single second, perhaps we’re at last approaching a time when the retail supply chain can truly evolve.
All those years ago, the best – the only – hope of understanding future sales demand lay in sales history. Look at volumes, frequency and patterns of sale to peer into the supply chain crystal ball in the hope of planning for something similar in the days, weeks and months ahead. Overlay actual sales with some marketing intelligence, an appreciation of promotional planning, stock levels, even causal indicators such as weather patterns and the forecast could be improved.
Yet, as the saying goes, the one thing you can always guarantee will be inaccurate is the forecast. An anonymous quote sums it up perfectly: "Forecasting is the art of saying what will happen, and then explaining why it didn't…” Life’s like that – inherently unpredictable, when with demand management a business craves stability and predictability.
In 2017, retailers now have to contend with omnichannel customer demand whilst all the time maintaining customer expectations and experience from an increasingly tech-savvy, fickle generation of shoppers – and generating growth and profits for shareholders at the same time. Another TLA (Three-Letter Acronym) has gone mainstream, becoming omnipresent and something additional with which retailers now have to contend: the so-called Internet of Things (IoT). IoT devices are everywhere – and their proliferation will only continue in an exponential way.
Fridges and freezers are online. Warehouse doors monitor shipments automatically in real time. Production machinery is monitoring itself and tracking its own maintenance scheduling and unplanned failures. In-store, we see customer tracking, smart shelf-edge and even shelf item monitoring, allowing integrated replenishment from stock room to gondola, RFID-enabled item tracking and customer store journey-capturing camera technology. Add in the mobile devices increasingly being used by the connected retail associate to assist in real time customer service and sales and it’s easy to understand that the volumes of data being generated far outstrip most businesses’ ability to make use of it. 20 years ago we used to call it ‘drinking from the fire-hose’ – sure, you’ll get a drink but you’ll get blasted in the face whilst trying to do so and the vast, vast amount of water will get wasted as it passes you by. Sound familiar? It should do – it’s more relevant than ever.
IoT devices have the capability to record and report on processes and components. With a coherent strategy on developing a contemporary data-lake (data itself, the people who use it and the principles by which it is governed), we’re entering the era when it will be possible to divine multiple demand signals and to make analytical sense of what they imply in real time.
The years of developing underlying processes to better share the critical triggers of demand among all the partners in an often lengthy supply chain are starting to bear fruit as we see technology deliver not just data, but true information.
It’s unlikely to be a panacea, but the supply chain is being drawn along by the pace of data change. Being able to first recognise and thereafter react to the opportunities this presents is the most contemporary use-case of retail digitisation we see today.
