Industry TalkRegular Industry Development Updates, Opinions and Talking Points relating to Manufacturing, the Supply Chain and Logistics.
How retailers can future-proof their forecasting models post-pandemic
While we’re all waiting for the world to return to a sense of ‘normality’, many retailers are wondering what that normal will look like. How can the retail industry prepare for what is to come when the past year has been so full of uncertainty?
According to Accenture, 94% of Fortune 1000 companies have experienced critical supply chain disruptions in the wake of COVID-19. There are therefore many lessons in supply chain management that can be learned from how the pandemic has been handled.
Top of mind for all businesses must be how to make themselves more agile, by better understanding and responding to changing consumer behaviours and the economic climate. Data, and what we do with it, will play a crucial role in enabling this agility and will help retailers to respond faster to sudden changes in demand – regardless of the cause.
Data based forecasting
Traditional retail forecasting has been based on the analysis of past sales to predict future growth – but this is no longer enough. The global pandemic highlighted the inadequacy of this approach, as supermarkets in particular were faced with enormous challenges. Nobody could have foreseen a scenario in which loo roll and flour would suddenly become the main focus of consumer desire, but the right technology might have helped to mitigate the high supply chain costs that many retailers faced to refill the shelves .
To avoid being taken entirely by surprise in the future, retailers need to analyse customer behaviour across each individual channel. During the pandemic, for example many more customers moved to online shopping; behaviour that had a direct impact on in-store sales. Category managers equipped with the right technology can analyse the performance of their assortments both online and in store in order to make the right decisions for their customers, even when shopping habits are changing rapidly.
This is where AI comes in. Sifting through mountains of data from different channels requires software that can learn to recognise patterns, identify anomalies and, most importantly, recommend actions. A run on flour, for example, could indicate that yeast will soon follow; while a surge in canned vegetables may affect the demand for fresh ones.
Human analysts would take days or even weeks to understand the changing patterns of shopping behaviour that are taking place worldwide in a crisis. Software powered by AI can do so in a matter of minutes.
Focus on inventory visibility
Full inventory visibility had been a key focus for many retailers looking to improve their supply chains pre-Covid – and has come into sharper focus over the past year. During the pandemic, many shortages were due to the inability of retailers to view their inventory in real-time and to respond quickly. Waiting a few days for a stock report is too late when world events are changing customer behaviour by the hour.
To be ready to handle future disruptions, retailers must be able to see and understand their inventory as a whole. This means not only taking into account every distribution channel, but also having visibility over suppliers’ stock availability. Only then can they be confident that they have the flexibility to keep the right balance of stock in the warehouse and the right products in the stores.
A holistic view of the supply chain
Ultimately, retailers need to have a holistic view of their supply chain, bringing together sales information, marketing insights, inventory details and supplier data. There’s no longer any question that customers are now omni-channel shoppers, and retailers must be ready to respond to their needs. No element of the retail operation can now exist in a silo; category management and merchandising cannot be separated from the supply chain, just as online and offline channels must be viewed as a whole.
The data is there – and now the technology exists to manage it. Advances in AI mean retailers now have access to prescriptive analytics, whereby machine learning can help them decide the best course of action to take based on historical and real-time data. Data can not only present a full picture of what’s happening now, but will help retailers to decide what to do next.
By leveraging a platform that supports advanced analytics, AI and machine learning, retailers can build a strong and resilient supply chain. There’s no longer any need to be spending time chasing after data and reports – with the right technology in place, retailers will be able to react swiftly to any event, no matter how disruptive.