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SECTOR REPORTS

SOFTWARE & TECHNOLOGY

BY MONTE ZWEBEN

OPERATIONAL AI HELPS FOODSERVICE COMPANIES OPTIMIZE THEIR SUPPLY CHAINS Use machine learning to sense, plan and act on the microevents that determine supply and demand across the entire food supply chain.

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rtificial intelligence is ushering in a new way of looking at supply chain optimization. It is allowing supply chain managers to compress the sense-plan-act cycle to almost real-time intervals. Companies that plan supply and demand on a monthly or weekly basis can now read signals from their supply chain in seconds, plan based on the realities of the moment and take immediate action based on the new plan. Planning teams have always reacted to actual data, so one might ask what is different now? The main difference is that companies can now get so granular that they can sense, plan and act to micro-events. A micro-event is a factor that can impact a plan, is very detailed, and is potentially intermittent, meaning it does not occur with regular frequency. Probably the most intuitive example of a micro-event is weather. Weather has a profound impact on supply chain operations, but it is intermittent and totally unpredictable. Thus, how can we use weather to help optimize supply chains? Let’s take demand planning, for example. Most demand planning is performed using historical statistical algorithms that average or smooth demand data. Some use moving averages that take a window of previous periods and average them to find the next period’s prediction for demand. For instance, if a product had a demand of 10, 12 and 14 units in the last three months, we could

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average these to predict demand of 36/3 or 13 units for the next month. Other approaches use exponential smoothing to try to capture trends in demand signals. These ubiquitous approaches use actual data from previous periods to predict future demand. But for the food supply chain, the growing trend for fresh, local food to make its way to grocery stores, restaurants, fast casuals and even quick service restaurant (QSR) chains has made monthly, and even weekly, planning almost obsolete. Now, companies across the food industry are tapping into machine learning and artificial intelligence to make better decisions faster when it comes to supply and demand.

Using Machine Learning to Manage Micro-Events New machine learning approaches to forecasting augment this historical approach by adding a real-time predictive component. Machine learning models are often used to classify data into categories. For example, suppose we built a model that learned whether demand is affected by weather. If we had an accurate model, we could apply it in real time, and use the micro-event to adjust our forecast. The model would take weather variables and statistically correlate them with demand signals. We could then increment or decrement the forecast based on the model’s prediction. Then, the model would test

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real-time conditions and predict the degree to which the weather would impact the forecast. There are many mathematical approaches to machine learning, but what is common is that the model could dynamically predict an adjustment to demand based on the weather. This model is trained from past experience. What are other micro-events that can be very powerful influencers of supply and demand? They tend to be localized—and perhaps short-lived—but often wreak havoc in a supply chain. For example: • Local sporting events and concerts. In one geography, a local QSR noticed large spikes after Friday night high school football games • Power outages. One short power outage can cause conditions rendering certain products highly in demand, or cause spoilage that strips supply • Social media. One celebrity mention can have a significant impact on demand • Commerce activity. The popularity of certain products can impact other products, even across vendor and category • Fires and natural disasters. An event can take out full sources of supply, while also dramatically changing demand • Recalls. Product quality announcements can affect both demand and supply • Strikes. In some geographies, strikes can have a profound

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3/1/19 11:39 AM

Profile for Supply+Demand Chain/Food Logistics

Food Logistics March 2019  

Food Logistics is the only publication exclusively dedicated to covering the movement of product through the global food and beverage supply...

Food Logistics March 2019  

Food Logistics is the only publication exclusively dedicated to covering the movement of product through the global food and beverage supply...