Ready to Order Smarter? — How Predictive Analytics Delivers Inventory Intelligence
In today’s restaurants, it’s common practice to have two people count inventory. But what if you could have a set of analytical “eyes” on your inventory at all times — not only tracking your depletions, but also automatically ordering based on forecasted demand? Now that’s smarter inventory management!
How fast can your managers accurately perform the following inventory calculation?
Forecasted Need + Safety Stock – Current On-Hand Inventory – Inventory on Order
An hour? Two hours? Four hours? A day?
What if your restaurants could calculate this equation instantly? How much time could you save on food waste and labor? How much would productivity increase? How much happier would your managers be?
These are important questions at a time when food waste costs, staffing expenses, and manager turnover are on the rise. It’s also why a growing number of restaurants are deploying predictive analytics to achieve smarter inventory ordering. Predictive analytics computes inventory calculations for restaurants so that managers don’t have to engage in time-consuming and frustrating manual or outdated inventory management.
Predictive Analytics = Multiple Benefits
Predictive analytics is the science of analyzing current and historical facts to calculate forecasts about future or otherwise unknown events. Other industries have deployed it for years to gain the benefits of faster and better insight into critical day-to-day operations, so they can improve productivity, performance, and cost management.
Now, restaurants can take advantage of this science to improve their daily decision-making. Predictive analytics forecasts combine multiple algorithms, event drivers, operational data, and the application of “best fit” forecasts for each store, so each restaurant can make their inventory ordering smarter.
Ordering based on predictive analytics focuses managers on the most critical areas of inventory management, enabling them to improve operations in several strategic ways including:
- Order accurately without dealing with multiple spreadsheets and reports
- Be prepared for expected and unexpected events
- Prevent mistakes before they happen
- Control food and waste costs
- Forecast prep and thaw to ensure the freshest products are used at the right times
- Avoid out of stocks by anticipating shortages or higher sales and taking proactive action
- Pinpoint variances and analyze causes, such as portioning errors or food theft
Two Important Elements of Predictive Analytics
Historically, managers tend to order based on gut instinct. But because they are often worried they’ll under-order, they tend to over order. This naturally leads to waste — both food and profits. Intelligent demand forecasting not only helps them make more accurate ordering decisions but also gives them the rationale to support the forecasts.
1. Forecasting Demand
Simply stated, the better the forecast, the smarter your ordering will be. That’s why forecasting needs to be based on your restaurants’ actual operational data and historical performance, as well as real-world events, including anomalies, like bad weather or traffic jams. Over time, forecasting accuracy improves, in other words — it gets smarter and smarter.
2. Forecasting Rationale
Providing a smart ordering forecast is one thing. Getting your managers to trust is another. Giving them a rationale presented in an easy-to-read summary can build their confidence in the reports. This helps prevent managers from making assumptions, thereby, lowering waste or under ordering mistakes. Also, over time, they will better understand how smarter daily decisions impact both the top- and bottom-line, leading to a greater feeling of success and job satisfaction.
Three Key Options for Suggested Ordering
Predictive analytics presents managers with three options for calculating “suggested ordering”: forecasting, pars, and usage per thousand (UPT).
- Forecasting. Forecasting is the only method that allows restaurants to define a safety stock, which is used to increase the forecasted suggested quantity if the forecast itself ends up being too low. Think of it as a smart backup. It generates an order based on this calculation: Suggested Order = Forecasted Need + Safety Stock – Current On-Hand
- Pars. This calculates the minimum amount of an item a restaurant must have on hand to support daily operations. It generates an order based on this calculation: Suggested Order = Par – Current On-Hand
- UPT. Not every item will be calculated within a recipe, like ketchup, napkins, or soda syrup. This is where a UPT measurement brings a level of sophistication to inventory ordering. It generates an order based on this calculation: Suggested Order = Forecasted sales ($) ÷ by 1000 x configured UPT on the Item
In today’s restaurants, it’s common practice to have two people count inventory. After all, two pairs of eyes are better than one, right? But what if you could have a set of analytical “eyes” on your inventory at all times — not only tracking your depletions but also automatically ordering based on forecasted demand? Now that’s smarter inventory management!