SupplyChainTalk: How demand forecasting can help you beat waste 

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Views on news 

US president Donald Trump has threatened to impose a 100% tariff on the import of all goods from Canada to the US “immediately” if the country “makes a deal with China”. This comes shortly after an agreement was reached on a “strategic partnership” between Canada and China that saw the elimination of Canada’s 100% surtax on Chinese EV imports for the first 49,000 units.

 

Prior to Trump’s statement, the Canadian Vehicle Manufacturers’ Association, which represents Ford Motor Company, General Motors and Stellantis in Canada, issued a joint statement with the American Automotive Policy Council expressing concern over the removal of tariffs for Chinese EVs, saying it “has the potential to undermine Canada’s auto sector and presents risks to the future of the integrated North American auto supply chain.” All car manufacturers can do to fend off the negative impact of new tariffs is switching production around, as setting up new production lines takes strategic decisions and longer time.

 

Businesses must also make now contingency plans that weren’t needed before the tariff uncertainty. Although demand planning doesn’t take uncertainty completely out of the equation, it can help businesses navigate it much better. Retailers should also have conversations with their suppliers and manufacturers regarding how they are going to be impacted by new developments in international trade.  

 

How can demand forecasting help? 

Overstocking, a strategy for manufacturers to manage volatility, often results in overproduction, which is costly as it ties up production capacity and materials. Extra stock also takes up more warehouse space and uses up cashflow. Overstocking often happens because demand forecasting is too static and therefore doesn’t factor in seasonal changes or consumer sentiment. Buffering happens along the whole supply chain from manufacturers stocking more raw materials to retailers increasing their inventories.

 

As time passes, slow moving inventory (SMI) will become non-productive inventory and eventually ends up as waste. As demand forecasting is error-prone by definition, measuring its accuracy is key to making the most of it. Mistakes are bound to happen, but players in the supply chain ecosystem must make sure that a blame culture is avoided. The focus should always be on constant improvement and increasing accuracy.  To achieve that, a business must improve communication with its suppliers rather than basing forecasting exclusively on data in their ERP system. You need to understand your customers, too including their needs and how they use your products. It’s also key to be in line with your group purchasing organisation (GPO) and propose bulk buys to them based on demand increase you’re experiencing.  

 

Managing slow-moving inventory can involve donations to charities – particularly in the case of perishable products. Also, when you’re experiencing inaccuracies in forecasting, you must ask the question whether you overlooked or ignored data that could’ve made your planning more spot-on. It’s a good idea to have monthly reviews between procurement, finance and general management to assess where stocks are across core, satellite and contingency warehouses and how they should be moved to balance supply and demand. Demand planning can also leverage 12 or even 18 month weather reports that will forecast long-term trends, such as El Niño and La Niña.   

 

The panel’s advice 

• You should measure how successful your demand forecast has been on a continuous basis.  
• The fear of running out of stock and losing customers is much stronger than concerns about creating waste.  
• Build solid data models to get better demand forecasts.