With consumer channels multiplying at an astonishing rate and consumer demand for lower prices and increasingly innovative products showing no signs of stopping, pressure on supply chains to deliver on availability, price and speed is mounting.
For years the holy grail of the supply chain has been 100% forecast accuracy and in the quest to achieve this we have seen a huge amount of investment in an array of systems and planning tools. Yet there has been no improvement to the accuracy of weekly forecasting for the past five years.
This suggests new approaches are needed to truly effect change. I’ve recently been inspired to re-think this problem by considering the fast-paced world of the Grand Prix through our alliance with McLaren.
Success in this sport is driven (excuse the pun!) not just by the skill of the driver and the speed of the car, but also by teams using the perfect harmony of simulation and predictive analytics. Using myriad data points, engineers simulate the entire racing environment months in advance. On race day itself, the engineers follow the race in real time and, using simulations fed with historical and live data, are able to advise where to make changes.
Imagine if it were possible to manage a supply chain in the same way? Simulations could be run months in advance, taking into account multiple variables impacting consumer demand and spend. Both sides of supply and demand could then collaborate to design, build, adjust, and implement the ideal plan.
Predictive analytics could be used to respond to changes in customer behaviour in real time. This could range from a seasonal event, a promotion, the launch of a new product, a change in disposable income, the weather, or even just business as usual. Conditions could be monitored on a constant basis with prepared responses and decisions executed in real time.
In my view, trying to force up forecast accuracy isn’t the answer to the supply chain issues. Winning the supply chain race could be better achieved by using a combination of simulation and predictive analytics to effectively see round corners and deal with what might be coming down the track.
Liz Claydon is KPMG’s UK head of consumer markets