Consumer buying behaviors have shifted drastically in recent years, and with soaring inflation and new price hikes, it’s likely that purchase priorities are going to shift again in the next six to 12 months, says Karen Clarke, SVP & managing director of AMER, Anaplan, a supplier of integrated business planning tools.

“I know it can be tempting for businesses to order an excess of product to meet unexpected spikes in consumer demand—it’s something we’ve seen happen within the beauty industry as apps like TikTok drive product virality,” says Clarke. “However, given the realities of a potential recessionary period, coupled with global supply chain congestion and rapid trend cycles, it’s more likely that demand will normalize before you can actually produce and ship new products to your manufacturers. To avoid over-ordering or missing out on these peak sales moments, today’s food processors need a faster, smarter indicator to gauge inventory needs and react to shifts in demand beyond traditional forecasting.”

Thankfully there are new methods and systems that can help food processors predict inventory needs and react more quickly when those needs shift, adds Clarke. Demand-sensing, for instance, allows businesses to analyze real-time data—things like product mentions or weather trends—and then evaluate their influence on demand. “Say you process vanilla beans into vanilla extract; you can use demand sensing to scrape TikTok for baking trends, determine whether a spike is coming, then coordinate additional vanilla bean inventory or adjust pricing for your vanilla extract to help capitalize on peak sales opportunities.,” Clarke explains.

To help cope with day-to-day changes, IFS recently added a function to its cloud-based ERP that lets processors get end-to-end visibility of the day’s planning process, making it possible to adjust the plan as required. IFS named it “intraday planning”, and according to Maggie Slowik, IFS global industry director of manufacturing, the concept behind it is useful for food and beverage manufacturers who are operating in a fast-paced environment, such as fresh food, where products have a relatively short shelf-life.

When a planner starts their working day, several questions are likely to be top of mind, says Slowik. “Questions such as, how can I best respond to any short turnaround orders that come in today? How do I adjust supply to meet demand? And finally, What impact will my actions have further down the line? Not only does intraday planning help answer these critical questions, but it also pre-empts them.”

To begin, you can configure manufactured parts so planning engines like MRP (materials requirements planning) and DOP (dynamic order processing) schedule manufacturing to finish on the same date as the order is required, says Slowik.

Another benefit is that short-term supply and demand can be balanced for ingredients, taking into consideration timings within the day, right down to the minute level, adds Slowik.

This method allows planners to see and review the plan for the whole day, allowing them to quickly react or adjust the plan when needed. For instance, if they see a negative balance on an order, they can manually or automatically adjust the “needed by” date/time and lot size of a shop order to match the demand, says Slowik.

This kind of agility and responsiveness supports decision-making during compressed timescales, helping manufacturers drive bottom line growth and increase customer service, while keeping production disruption to a minimum.

Another issue that can wreak havoc with scheduling at the last minute is changing weather. Some ERP vendors have found ways to help processors cope by factoring weather into demand planning. For example, IFS uses an AI-assisted weather forecast.

“The idea is to draw in external weather forecasts, apply algorithms to them, and essentially correlate these weather patterns with demand behaviors in the past to improve forecasting accuracy,” says Slowik. This type of planning is especially relevant to those food and beverage companies who make products where demand is weather-dependent. For instance, salad, ice-cream or beer manufacturers, where their goods will be more in-demand during warm periods. “But perhaps more importantly, companies can get a better prediction of what’s going to happen in the future—right down to the level of days—and plan accordingly,” says Slowik.

Other external feeds can also be entered into the demand planner, which could help processors respond to sudden consumer demand changes, such as news feeds and regulatory changes/developments, Slowik adds.

Applying Technology to Find Solutions

Tools that enable integrated business planning (IBP) are critical in this complex supply chain environment, especially since supply chain risk is tied directly to business risk, says Clarke. IBP helps organizations minimize those risks while maximizing profits. It’s a process that aligns revenue targets from demand and supply plans with costs, and then arms leaders with financial, workforce, material and capacity considerations to ensure operational and financial plans can be truly optimized for success. While point solutions can address specific parts of the business, tools that are actually integrated are critical to driving the level of visibility and real-time collaboration required for IBP.

What are some of the IBP tools that you’d expect to find in a system? Jim Byrnes, CEO of Blue Ridge, lists a few, which include demand forecasting, supply planning, inventory allocation, sales and operations planning, replenishment and pricing, supply chain and procurement, CRM and insurance-based solutions. Beyond the tools themselves, implementing the correct processes not only minimizes risk but also optimizes these solutions to deliver world-class customer experiences, says Byrnes.

When it comes to shifting customer needs, multi-echelon inventory optimization (MEIO) is a good solution, adds Byrnes. MEIO gives businesses the ability to optimize inventory placement throughout the supply chain to match projected demand and meet fluctuating customer demands.

“Another great tool for gaining a more agile and accurate view of your supply chain is digital twin technology,” says Clarke. “We’ve partnered with Google Cloud to bring supply chain digital twin capabilities to our customers. Essentially, businesses have a virtual copy of their physical supply chain and can combine data from a variety of sources to see how different scenarios will impact the flow of goods across their supply chain. Supply chain leaders can use this end-to-end visibility to make more informed, data-driven decisions.

For instance, a food processor could combine data from public sources (like weather data) with data from their suppliers (like the transportation status of certain goods) to understand the impact a cold storm might have on the delivery of a specific item in a specific region. Using that information, the food processor could make a real-time decision to pivot orders over to a supplier not impacted by the weather event, says Clarke.

AI to Make Informed Decisions

At the instrumentation company where I worked, the plant manager—based on his three decades of experience and orders at hand—planned what components needed to be made for stock. Is a singular “prophet” even viable today?

“The answer is two-fold,” says Byrnes. “Intelligent supply chain planning solutions leverage thousands of data points and use machine learning and complex mathematical equations to predict forward-looking consumer demand. However, the industry-specific ‘prophets’ you are referring to are still as crucial as they were twenty years ago. We believe that humans and technology working together provides the winning combination for businesses operating in the food sector.”

IFS’ Slowik adds, “The prophet example reiterates the point that we cannot take the human element out of the technology equation. However, the danger with such an expert is often the lack of knowledge transfer.

“A more scientific approach would be to: 1) find a way to democratize/transfer the knowledge across the organization, and 2) enhance the prophet’s decision-making capabilities with AI, especially in today’s digital economy where data is exploding, and neither humans nor systems can keep up any longer,” explains Slowik.

Clarke says this is where the power of scenario planning, or ‘what-if’ analysis comes into play. “Businesses need to be able to see the impact of potential disruptive factors on inventory and production plans—like an unplanned weather event or factory closure. Nuanced scenario modeling capabilities help provide that end-to-end visibility so that planners can be more strategic—and data-driven—as they make decisions about the allocation of resources, materials, and production capacity.”