Restaurant sales reached $70.6 billion in June 2021 following the distribution of millions of coronavirus vaccine doses, a whopping $40 billion increase from the same month in 2020. Now, as the delta variant sweeps the U.S., it is critical for restaurant suppliers to remain swift in their responses to fluctuations in demand.
Food service suppliers face constant obstacles in maintaining inventory, even under normal circumstances. But the pandemic-driven swings in demand—as well as supply chain disruptions like inflated prices and supply shortages—have made it even more difficult to operate.
To thrive in today’s unpredictable economy, suppliers need a dynamic forecasting strategy that helps them proactively manage fluctuations in restaurant industry demand. Leveraging data-driven technology such as predictive analytics is the key to more precise forecasting going forward.
The challenges of maintaining adequate inventory
Even before the COVID-19 pandemic, inventory overstock and understock contributed to millions of lost dollars every year. Pandemic-related spikes in demand, business closures, and an increasingly competitive landscape further exacerbated the problem.
When the first wave of the pandemic hit the U.S., for example, the surge in demand for certain retail soared while food service demand plummeted. As restaurants began to reopen at full capacity, suppliers juggled higher food costs, supply shortages, and other pandemic-induced disruptions. A study from March 2021 found that 44% of small businesses experienced shortages in their supply chains.
With these challenges in mind, foodservice suppliers should rethink their strategies. Nearly half of supply chain leaders increased spending on innovative technologies during the pandemic because many of the traditional processes and systems are no longer enough.
Traditional procurement strategies built only on human intelligence are time consuming and resource intensive, and they do not provide your business with the agility to thrive in today’s supply chain landscape. To remain competitive and to stay ahead of rapidly shifting demands, you need predictive analytics that leverage real-time data and past usage trends to enhance your forecasting.
How predictive analytics can improve purchase decisions
Predictive analytics use statistical algorithms, machine learning, and artificial intelligence (AI), as well as internal and external data sources to forecast future trends more accurately. When coupled with an enterprise resource planning (ERP) system, predictive analytics can help you make smarter purchase decisions and improve your response time to shifts in demand and consumption patterns. Research from 2019 shows that nearly half of companies that use big data analytics in their daily operations react faster and more effectively to supply chain issues.
In practice, predictive analytics unlock two critical abilities that help your business keep pace with a challenging supply chain:
- Advanced purchasing
Predictive analytics enable you to match external data, such as weather patterns and agricultural impact, with internal data such as sales history, to detect trends and make predictions. This type of forecasting lets you see which food items are in demand, as well as what times they are in the lowest or highest demand. Using this information, you can better predict trends such as farmers’ or suppliers’ lead times and make advanced purchase decisions.
If you typically procure a particular product in seven to 14 days, but a supplier is not able to deliver it for another month, you can purchase a two-month supply of that product in advance, for example. Ensuring timely order procurement and distribution can help preserve customer loyalty and avoid chargebacks such as late fines, which major buyers like Walmart and Sysco are pinning on suppliers.
- Shifts in demand
Takeout and delivery became essential for restaurants’ survival during the pandemic, and businesses had to quickly ramp up their carryout capabilities. Even restaurants that did not offer delivery and carryout prior to the pandemic had to pivot and acquire food service packaging — and they had to do it fast.
During the pandemic, foodservice packaging like takeout containers, napkins, and disposable silverware quickly became scarce, which made it difficult for suppliers to meet order deadlines. This scenario underscored the need to react quickly to changes in demand. With predictive analytics, you can more accurately predict future trends, improving your response time and allowing you to procure the right supplies at the right time.
Data-driven purchase decisions are critical
The past year and a half has been a rollercoaster of fluctuating demand and disruptions, highlighting the importance of dynamic supply chain operations and speeding up the adoption of innovative technologies like predictive analytics. Integrating predictive analytics into your day-to-day operations eliminates some of the guesswork from traditional forecasting, enabling you to make timelier, data-driven decisions that will help your business thrive.
Joe Scioscia is the VP of Sales at VAI with a demonstrated history of working in the computer software industry. Joe is a strong sales professional skilled in channel building, enterprise software (ERP), sales force automation (CRM), warehouse management, e-commerce and cloud computing.
