The meat processing industry has experienced a significant transformation in the last two decades, with innovation driving change in how meat processors and retailers operate. In the past, tracking meat inventory and cut and kill-floor schedules relied on outdated methods such as Chief tablets and Excel spreadsheets. Procurement managers often made decisions based on educated guesses rather than data when purchasing hogs and scheduling kill dates. This lack of reliable projection data created significant challenges for plant managers and sales teams struggling to keep up with fluctuations in livestock supply and retail market demand. We interviewed Dave Brown of Ever.Ag Data Labs to understand how data helps solve these challenges.
Data science is changing the landscape of the meat processing industry
Dave Brown, co-founder of Austin Data Labs (now Ever.Ag Data Labs), spent many years in pork processing plants, including his time at Farmland and Smithfield. Over the course of his career, he saw a growing opportunity for meat supply chains to use data science for more effective supply chain management. In the meat business, scheduling and product availability numbers are often tracked on spreadsheets, making it impossible to get real-time reports of available products with numerous SKUs and multiple freezer locations. Staying current on inventory or scheduling timely meat processing was challenging at best, and forecasting sales and procurement was essentially guesswork.
Dave recognized the need for better data analytics in production planning to efficiently fabricate carcasses into an optimum mix of cuts that would meet retail and wholesale demand while maximizing profits. In 2014 he teamed up with Sushil Verma and Simon Drake to build an AI-based data science platform that solved a host of common challenges: scAIcloud®.
Dave stated, “We build systems configured to a plant’s needs that tell meat processors what they should schedule in the plant, what the sales team has left to sell, and then forecast future sales to aid the procurement team. What we do is provide processors with tracking and forecasting software that provides solid numbers for managers to make better decisions.”
Optimizing the supply chain
Using data to resolve planning problems in the supply chain is rapidly becoming the gold standard, providing a better way to deliver improved operational performance. Optimizing the workflow at the plant level not only helps the processors, but also provides retail supermarkets with a competitive advantage – a framework for delivering freshness and quality at a competitive price. By analyzing data on product shelf life, sales patterns, and consumer demand, retailers can stock the right amount of product and reduce spoilage and waste.
Having access to raw material supply data is critical for processing plants. By applying data science, managers can analyze supply and demand drivers, while the system tells them what they have left to sell and provides an improved production schedule to fill those demands. This ensures an adequate supply, prevents shortages, and helps avoid excess unsold inventory.
Our software optimizes your entire supply chain. We also offer more granular solutions for scheduling your production plants, providing a supply plan, a demand plan, an inventory analyzer, and product availability. The ability to define retail product specifications and standards enables retail supermarkets to benefit from optimization across the supply chain as well.
Maximizing Profits
In the meat business, wasted product means wasted money. Pricing is a critical aspect of the business, and staying competitive while keeping some margin can be challenging. Leveraging data science allows meat producers to analyze consumer demand, competitor prices, and market trends to optimize pricing strategies.
Having timely and accurate data prepares demand planning and sales team to be proactive in meeting the needs of their customers and adjusting to supply chain variabilities. “Product availability and demand planning are critical components of managing volatility in the market, whether it be price dips or demand changes. Processors can more easily navigate the fluctuations in supply and demand with a robust data set and up-to-date inventory numbers,” said Dave.
Who benefits most from the tech integration in the meat business?
Forecasting supply is a challenging and critical part of the business. Processors often begin to see the economic benefit of integrating data science into their plant management and forecasting immediately. Insightful data gives processors options on how to deconstruct carcasses and determine which cuts are needed to meet retail demand while tracking the inventory and sales they still need to sell.
Dave says, “The packer benefits first, by optimizing their supply chain and procurement, but as they make more margin, the money trickles down to producers at the farm and ranch level because when packers make significant margin, they increase kills, driving livestock demand and price up. Data science is making the whole industry more efficient, and this in turn affects the pricing and quality of products consumers buy in the supermarkets. It’s a win-win situation!”
Making decisions with better data presents immense opportunities to drive innovation in the animal protein sector. Industry experts like the people powering Ever.Ag Data Labs bring deep expertise in food processing and the agriculture industry, enabling clients to leverage data and AI to optimize supply chains. Collaborating with experienced partners allows companies to tap into the power of data science to drive transformative advances through AI-powered innovation.
Learn more about Ever.Ag Data Labs: Ever.Ag Unveils Ever.Ag Data Labs: A New Era of AI-Based (globenewswire.com)
