From Available to Promise to Intelligent Order Promising – CPG

How to do it – people and process. The importance of sensing demand and customer segmentation, and the role of AI in enabling this.

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It is human nature to hold onto things that don’t work very well, rather than throwing them out and replacing them with something better. It’s easy with stuff – a broken phone is replaced with a new phone. But, when it comes to processes, or ways of working, it’s much harder. All professions are filled with outdated, inadequate or even downright dangerous processes, and because they all worked once, we all think that they still work, preferring to blame external factors rather than our own shortcomings.

Well now most consumer packaged goods companies (CPGs) are, at least, aware that these external factors have gone way beyond the ordinary and weigh so heavily on the company and its brands that new ways of doing things are now a matter of survival.

This much has been said before and will again, but the difference this time is that the single most reliable indicator of demand on which forecasts have been built since forever is no longer reliable. The history of consumer demand now looks like a lost golden age that is never to return. Demand patterns have gone haywire, particularly since Covid, and even once useful indicators given off by customer baskets cannot be trusted, particularly as they change so often.

Hopes for a return to the old sanity already looks as if they are going to be dashed on the rocks of blind optimism, especially once other trends are factored in, notably fragmenting diet types, new life and work models, health and safety concerns, and of course competition from younger disruptor brands and private label.

We know it is not a lack of data that holds us back. So, it must come down to the tools to exploit it to build plans and forecasts that can embed consumer and market insight into available-to-promise. We call it “Intelligent Order Promising” because implicit in our approach is the certainty that the plan will deliver because it can embrace all the variables and respond instantly to any changes in conditions.

Intelligent Order Promising (IOP) combines demand sensing that starts at retailers’ ship-to location and adds AI/ML that takes their attributes into account around service levels, profitability, volume growth, and size of OTIF fines to define order priority.

IOP immediately deals with a common problem that arises when the plan and real demand are out of sync. Allocation favours the largest customers who shout the loudest, regardless of the CPG’s own profitability targets. IOP enables CPGs to optimise distribution of both allocated and unallocated stock in fair proportion to each retailer, without damaging the CPG’s own commercial KPIs.

And because the processes are automated and deliver much higher accuracy, CPGs can save both time and money not having to fix the problems that arise from guesswork or politics. Further along the fulfilment cycle, because CPGs are using common data and decision making processes, sales and supply chain can intelligently manage demand and supply variability at the order execution level, where currently the problems often lands with the customer service organization and logistics.

Automation at this level also enables a more open relationship with retailer customers that gives them the confidence to explore more ambitious ideas for the future.

While adopting an automated solution does require a change of thinking, actually rolling it out is relatively simple because it integrates with existing core systems, mainly SAP, Oracle, Kinaxis and Blue Yonder, rather than replace them.

The first step is to assemble a team of stakeholders that can agree on expected outcomes and how to segment customers. Benchmarking against past performance is important so that results will be highly visible which is important in supporting a wider roll out after an initial pilot.

The go live should then effectively be a non-event so that the new system becomes business as usual, immediately.

Covid has been the catalyst for this approach, but it is already tried and tested. In the face of all the market dynamics discussed, it is clear to most CPGs that trying to “do better what no longer works” is simply not the answer because the sales and profitability attrition is now hurting badly and leaking across the brand, which will be hard to come back from.

In short, the ability to build more accurate plans that can be executed in times of uncertainty has become mission critical, particularly where unusual demand in the last year has caused some CPGs to miss their targets, leading to unhappy retail customers and consumers.