How bad was grocery service in 2020?
To say that the pandemic has made 2020 a very difficult year would be an understatement. Due to service disruptions – not being able to buy toilet paper, for example – the supply chain has been more under discussion than ever. It was also a very, very difficult year for supply chain professionals working in the grocery supply chain.
But how bad was it? And how can consumer goods companies learn from their performance in this pandemic to prepare for the future? A study from E2open – the 2021 benchmark forecast and inventory study: Supply chain performance during the Covid-19 pandemic – provides the answers.
I look forward to this study every year. Comparative analysis of the forecasting process is difficult. E2open has found an innovative way to do it. The company provides demand and inventory planning solutions based on public cloud architecture. They provide these solutions to some of the world’s largest consumer goods and food and beverage companies. Thanks to this architecture, E2open can access, aggregate and anonymize the data of its customer base. They can then use the data to provide an apple-to-apple benchmark on a variety of innovative supply chain metrics applicable to the grocery store supply chain.
The forecast accuracy was terrible
The study shows that providing good service to grocery chains has never been so difficult. In the first few months of the pandemic, demand planning error jumped to 59%, up 14% from the pre-pandemic error rate of 45%. “Traditional forecasting,” the study noted, “is based on the presumption that history will repeat itself. Even in the best of circumstances, this method has limitations. During the pandemic, it failed completely. trying to predict demand in March 2020 as the world fell into lockdown and everything turned upside down, what happened in March 2019 had little to no relevance. The pandemic created seismic changes in the world. consumer behavior. “
The panic buying exacerbated the problem. As the shelves emptied at the start of the pandemic, consumers were less picky about their preferences. They looked for any product in a category that they could get their hands on. This meant that slow moving items in one product category were picked up and the forecast for those items was significantly too low.
“While supply chains are flexible in nature and designed to accommodate deviations from plan,” the study points out, “cases of ‘extreme error’ – where forecasts exceed or fall by two. times or more to sales – are the most costly and disruptive to business These extreme error events “are the supply chain equivalent of flushing a freeway or closing a bridge.” These are events that are extremely costly to manage or represent huge potential revenue losses.During the pandemic, extreme error events reached 38%. Before the pandemic, that number was 27%.
Regardless of the type of demand planning solution used, forecast accuracy decreased. But if there was a silver lining, it was that companies were using scheduling systems that combined demand sensing – the use of multiple real-time signals (like sales to a particular store or shipments from customers). warehouses from a retailer to their stores) – and machine learning, had far fewer errors. Demand sensing solutions as defined in this report produce daily forecasts that reflect current market realities, so it shouldn’t be surprising that these forecasting solutions work best when uncertainty increases.
Service drops to historic lows
At the start of the pandemic – the months after March, when nations closed their borders – service fell to 83%. This is a historic low. For multinational consumer goods and food and beverage companies, service is typically 99%. Service is calculated as the difference between orders and shipments divided by shipments. In other words, if manufacturers cannot deliver everything that retailers order, then there is a service failure.
By June, service levels had rebounded to 86%. For the remainder of 2020, service levels remained at 86%. Although this was an improvement, it was still much worse than the base service levels of 99%. Unsurprisingly, safety stock – the inventory buffers used to protect against variability in demand and supply disruptions – increased 4% to deal with volatility caused by the pandemic.
Despite service disruptions, revenues increased
For the most part, the companies participating in this study manufacture products that end up in grocery stores. Because many consumers started working from home and drastically cut restaurant meals and travel, the demand for groceries skyrocketed. The result was the strongest sales growth in the ten-year history of this study. However, there were unrealized revenue opportunities for manufacturers. Sales could have been even higher if the service had been better. The math is simple, a 13% reduction in service over the course of a year translates into a 13% decrease in sales.
The multinationals participating in this study also took steps to maximize their revenues in a very difficult operating environment. The service for the fast players – the products that are their main money generators – would have been even worse if it had not been for a change in strategy. There has been a shift from “growth through innovation” to “growth through efficiency”. Historically, fast-moving consumer goods manufacturers drive demand through a constant stream of launches, with around one-third of items replaced each year. 2020 was different. It was a time of need and the demand for essential goods was high. The challenge for businesses was less to create new demand than to fill orders for existing demand. In response, manufacturers have adopted strategies to maximize production efficiency, halving the rate of introduction to focus on existing products that consumers trust. In addition, the focus has shifted to higher volume items to reduce change and maximize production. The rapid change in strategy to focus on efficiency and secure supply during this time of need reflects a strong corporate commitment to social responsibility. “
Supply chain management doesn’t get any easier. Leaders will have to deal with supply chain disruptions caused by new virus variants, global warming, growing geopolitical pressures, rising populism, cyber attacks, terrorism or other as yet unknown crises.
Understanding what happened during the pandemic helps leaders prepare for other large-scale disruptions in the future. Metrics, such as predictability, extreme underselling error, extreme overselling error, or forecasting value-added, help a company understand how its supply chain is performing during the biggest disruption in the business. modern history. Understanding these inventory and forecasting metrics, and what drives them, can help businesses better serve their customers while reducing costs or revenues.