How Sales & Operations Planning Decisions Prevent Food Waste in the Supply Chain

Food waste along the wholesale and retail supply chain is often blamed on downstream operations failures. Its roots, however, oftentimes lie upstream. As we will explore in this post, food waste is typically a downstream consequence of inadequate upstream Sales & Operations Planning (S&OP) decision making.

The scale of this issue is massive, with 30-40% of the US food supply wasted each year. The U.S. government’s goal is to reduce food waste by 50% by 2030.

Balancing demand & supply with sales & operations planning (S&OP)

Sales and Operations Planning (S&OP) is a cross-functional process aligning demand forecasts with supply chain capacity, resources, and financial goals. S&OP connects sales, marketing, manufacturing, and finance to create a single consensus-driven plan for reducing costs by optimizing inventory levels and communications between stakeholders along the entire food chain. The primary function of S&OP is to compare anticipated demand against available supply to ensure food organizations meet customer needs without excess inventory.

Until the turn of the century, supply chain strategies did not adequately account for fluctuations in demand, often leading to excess inventory and higher waste. Today’s complex market requires a new strategy: a demand-driven supply network (DDSN).

A DDSN reverses the conventional “supply and demand” sequence by starting with the point of consumption (demand) and working backward to the point of production (supply). By analyzing factors including consumer behavior, pricing, and external considerations such as sporting events, weather patterns, and holidays, food businesses can better predict demand and adjust their supply chains accordingly.

How upstream S&OP decisions affect downstream food waste

Food waste is a significant downstream consequence of upstream Sales and Operations Planning (S&OP) decisions. "Upstream" refers to initial stages or “supply side” of the food chain. These stages include the sourcing of raw materials and manufacturing of finished goods. “Downstream“ refers to the post-production stages and “demand side” of the food chain at warehouses, distribution centers, and retail stores. These stages include transporting, storing, selling, ordering, and delivering products to end customers.

Upstream-related food waste is rooted in a supply-driven approach focusing on maximizing production volume rather than aligning output with actual market demand. Up to 40% of the food supply in the U.S. is never eaten, often due to overproduction and inefficient logistics planned early in the supply chain. While the physical waste occurs at the retail or consumer level (downstream), it is frequently caused by the following faulty upstream operations.

• Inadequate cold chain: Poorly optimized logistics upstream leads to spoilage of temperature-sensitive perishable foods.
• Forecasting errors: When uninformed about customer demand, producers overcompensate for potential shortages, resulting in unsold and wasted food.
• Lack of visibility and collaboration: An absence of supply chain visibility prevents timely adjustments to fluctuating market conditions.
• Rigid inventory management: Blindly adhering to high "minimum order quantity" (MOQ) contracts that favor oversupply lacks the flexibility needed to adjust to ever-changing market trends and customer demands.

The downstream consequences of faulty upstream S&OP decisions include the following:

• Significant waste: With excess inventory, high volumes of food expire before they can be sold or consumed. Almost 30 million tons of edible food are annually rejected at the packing or processing stage, creating massive upstream waste before it reaches the consumer.
• Reduced shelf life: Reduced shelf life limits retailers to a smaller window in which to sell food products, increasing the likelihood of expiration.
• Spoilage of perishables: When suppliers set high MOQs for retailers to reduce transportation costs and gain economies of scale, retailers must stock more products than they can sell, leading to case overloads, refrigeration asset performance decline, and spoilage at the retail level.
• Bullwhip effect: When retailers and suppliers fail to share real-time data regarding actual consumption rates, producers continue to manufacture at high rates even when demand drops, creating a "bullwhip effect" that results in unsold inventory.
• Financial loss: Misjudging demand or production capacity leads to substantial profit margins reductions for both producers and processors.

How S&OP helps mitigate doubt in a perishable supply chain

In a perishable supply chain such as fresh foods, doubts about safety and quality often stem from the high risk of product expiration and volatile demand. The following S&OP strategies mitigate this uncertainty.

Buffering overproduction

A data-driven "buffer" strategy transitions overproducing from reacting to uncertainty to proactively mitigating it. S&OP uses collaborative insights to create intentional, controlled buffers:

• Balancing service levels with spoilage risks: cross-functional teams (sales, marketing, operations, finance) simulate “what if” demand scenarios to determine optimal, safe, and cost-effective volumes of overproduction.
• Managing safety stock: inventory managers identify the appropriate level of buffer stock to hold for items with high variability, thus mitigating risk of stockouts during demand spikes.
• Optimizing inventory segmentation: products are segmented by demand volatility to enable higher overproduction only on high-margin products.

In sum, a buffering strategy within a perishable food supply chain minimizes spoilage and waste while ensuring that the excess is actually the right product at the right time.

Overstocking “just in case”

Combining strategic buffering with contingency planning transforms "just in case" overstocking from blind hoarding into a data-driven safeguard. The cross-functional S&OP team uses data analytics to select the best “just in time” strategies that predetermine the optimal level of excess to balance the high risk of spoilage against the cost of lost sales. These strategies include the following:

• Dynamic safety stock: set precise, dynamic safety stock levels for items with high-demand uncertainty.
• Shelf-life integration: incorporate expiration dates into inventory management to ensure that "just in case" stock is rotated properly.
• Strategic liquidation: use data-driven decisions to identify the best time to discount or bundle items before they spoil.

In sum, overstocking “just in case” within a perishable food supply chain is controlled, visible and proactive. Monitored through KPIs (e.g., inventory turns, spoilage rates) and based on calculated risk, this strategy enables higher service levels without exorbitant waste.

Shifting risk of stockouts directly into expiration and waste

Shifting risk from high-impact, customer-facing stockouts to the potential waste of lost inventory transforms the nature of the risk. The potential for financial loss moves from immediate lost revenue to future write-offs. Instead of risking a completely empty shelf, S&OP enables businesses to absorb demand spikes or supplier disruptions at the cost of increased waste. This strategy is generally deemed more acceptable than loss of customer loyalty.

• Balance strategy: decide to accept a higher risk of spoilage for specific high-margin perishable products to ensure they are available during a high-demand, high-profit period.
• Forecast accuracy: use data analytics to shift the risk toward products that might not meet their expiration dates if demand unexpectedly drops.
• End-to-end visibility: ensure all departments are working toward the same goal rather than in silos.

In sum, within a perishable food supply chain, the strategy of shifting the risk out of stockouts directly into expiration and waste protects business from the more damaging consequences of stockouts.

Optimizing S&OP to reduce food waste

Optimizing S&OP to reduce food waste relies on combining IoT data with prescriptive actions to identify gaps and misalignments in the supply chain that hinder operational efficiency, margin protection, and customer satisfaction. Key strategies to identify gaps include the following approaches.

Clustering demand streams

Clustering demand streams involves categorizing product demand across different channels. Because each stream represents an opportunity for accuracy or error, identifying demand patterns and interrelationships among them is crucial for detailed planning.

Predictive analytics clusters products along a continuum from slow-moving, low-predictability items (high risk) to fast-moving, high-predictability items (low risk). By clustering SKUs in this way, businesses reduce forecasting errors by optimizing inventories of substitute, complementary, and loss leader products.

Aligning S&OP with financial planning and demand manipulation

Financial metrics must also be integrated into S&OP to balance risk and profitability. Food organizations must:

• Prioritize high-margin items when taking inventory risks.
• Avoid risking low-margin items unless they are critical complements to higher-margin products.
• Introduce short-term strategic price strategies such as promotions to clear excess inventory and forward buying to offload stock.
  
  

Integrating demand forecasting and loss prevention 

Integration of demand forecasting and loss prevention plays a crucial role to ensure proper inventory levels and prevent unnecessary losses. Organizations can reduce unnecessary waste across the supply chain by leveraging insights and intelligence gathered from demand forecasting measures. This holistic approach proactively addresses potential risks by Identifying patterns and trends to Improve efficiency and profitability and foster a more secure and sustainable business environment.

Empowering cross-departmental collaboration

Effective S&OP hinges on cross-departmental collaboration. Sales, operations, and finance must work together to:

• Mitigate gaps caused by siloed operations.
• Align on demand forecasts.
• Identify key constraints and risks.
• Develop unified strategies to manage inventory and ensure profitability.
• Encourage a culture of data-sharing and joint decision-making.

SmartSense: Choosing the right technology

Reducing food waste requires improved, data-driven forecasting and increased, transparent communication between all levels of the food supply chain. But encouraging data sharing without empowering teams with the supply chain monitoring solutions will only go so far. Identifying and addressing gaps in S&OP requires a comprehensive, multi-dimensional, IoT-enabled approach.