2020 has been a year like no other for food-related industries, fueled by shifts in demand and supply and dramatic (and likely) permanent changes in consumer behavior.
What can we learn from this upheaval, and what steps can we take to fortify the food supply chain in the face of these and future challenges?
Prior to the Coronavirus disease (COVID-19) pandemic, food-based consumer spending was in somewhat of a comfort zone with 4% year-over-year growth (2017-2018) on average spread between both retail food and foodservice outlets, which include restaurants, hotels, schools, hospitals and prisons. Share-of-wallet was also spilt within each group with both assuming 50%. Once the pandemic hit and restrictions were imposed, the scales were tipped as consumers initially began “pantry loading” for certain consumables and then later for longer-term foodstuffs. Restaurants, hotels and even schools quickly closed and demand in those channels plummeted.
The bullwhip effect from the channel demand shift quickly exposed the fragility of inventory management, supply replenishment and disrupted upstream channels. Food packaging and processing became unbalanced with downstream demand, and distribution channels became unhinged, causing food to be trapped upstream with really nowhere to go. The result was massive amounts of waste in an already high waste industry.
Leveraging supply chain networks to take the sting out of the bullwhip effect
Wikipedia defines the bullwhip effect as “increasing swings in inventory in response to shifts in consumer demand, as one moves further up the supply chain.” Like the movement at the end of a whip, bullwhip effect is triggered by small changes at the demand end of the chain that are increasingly amplified upstream in the supply network. The more remote a supply chain node is from the originating demand signal, the greater the distortion in response. The bullwhip effect is present in the supply chain at the best of times, but the pandemic exaggerated the phenomenon with its larger than normal swings in demand. We could say, the “flick of the wrist” of normal bullwhip became a wildly waving arm.
To see the significant role that bullwhip effect plays in the supply chain, consider a common example. The typical food retail supply network carries 65 days of inventory, which exists to buffer the inefficiency and fragility present in supply replenishment, along with poor demand accuracy, which compounds the problem. This results in only 96% in-store/in-stock availability on average and only 80% availability for promoted items. The net is that for most retailers the pandemic flushed their excess 40 days of stock in 10 days due to pantry loading. These extra 40 days were there to protect them from deficiencies in their software, analytics and processes, and without them, they were fully exposed.
Fortunately, the bullwhip effect can be contained by reducing information time lags and sources of variability in the supply chain, including both demand and supply variability. Modern technology, in the form of real-time supply networks, provide a single version of the truth that is shared with all participants as changes occur, so all parties know actual demand and supply across the network at all times. This eliminates the need to estimate demand and orders and removes much of the root cause of the bullwhip effect. After-all, if actual demand and supply are known, there’s less need to inflate inventory to cushion against uncertainty.
When running on a real-time network platform, instead of 65 days of inventory, the food supply network can carry only 25 with 99% in-store/in-stock for both promoted and non-promoted items. A network that runs with 25 days of inventory as opposed to 65 is by default both agile and responsive. Thus, it’s able to withstand most shocks and improve business continuity regardless of conditions, as demand shifts are transmitted in real time across the network to all relevant trading partners.
But, channel demand was not the only one impacted, as the bullwhip effect quickly disrupted upstream channels as well. Food packaging and processing became unbalanced with downstream demand and distribution channels unhinged, causing food to be trapped upstream with really nowhere to go.
The packaging dilemma and permanent changes
Despite COVID-19’s impact to the food supply industry as a whole, the same amount of food was still being consumed. The difference was, and continues to be, is that it is moving through different channels and in different forms with more consumer-sized “each’s” or individual items, rather than the bulk packaging a foodservice organization would typically receive.
Achieving this switch would take a significant investment for bulk producers and packagers to switch to providing each’s. It becomes a question of risk in terms of whether the shift is mostly a medium-term event (with a smaller payback for the investment) or whether this is a more permanent shift (with a decent business opportunity upside). Considerations would include the flexibility to handle multiple order cancellations, which would require upstream inventory to move through alternate channels, packaging options and potentially include capabilities like micro-fulfillment centers and last mile delivery to ensure full consumption.
Forecasting demand scenarios in the coming months requires all parties to recognize that a certain percentage of the recent shifts in product movement to the end consumer via these new channels are here to stay. This presents significant risk for food producers, packagers, and distributors, along with the food retailers and food service operators themselves. Artificial intelligence and machine learning will be key in understanding demand patterns in the “next normal” and drive increased demand forecast accuracy.
With a supply network platform, demand shifts are immediately evident. The uncertainties can be managed, both for the company and its upstream distributors, suppliers, producers and farmers, simply by adjusting network settings and by leveraging the predictive and prescriptive analytics. They can react in real time to dampen bullwhip, reduce overreaction and adjust their planning across all time horizons based on insights regarding the “next normal” post-pandemic. They can model various scenarios for future consumer spending and rely on advanced predictive and prescriptive analytics to help with decision making in these areas.
In a McKinsey survey of the food and consumer goods industries, 100% of respondents had experienced production and distribution problems. More than nine in 10 (91%) had problems with suppliers and a whopping 85% struggled with inefficient digital technologies in their supply chains.
Part II of this series will discuss additional challenges meat and produce manufacturers face and examine how a real-time business network helps them improve operational readiness and overall resilience.