Philadelphia, PA — Qlik®, a global leader in data integration, data quality, analytics, and artificial intelligence (AI), has helped SLA Software Logistik Artland achieve a breakthrough in forecasting accuracy for a customer, which is a major German meat producer. By leveraging Qlik’s predictive AI capabilities, SLA reduced the daily deviation between predicted and actual customer demand from an industry average of 30–35% to just 1%. This improvement significantly cut food waste, lowered costs associated with storage and downgrades, and delivered key environmental and animal welfare benefits.
Historically, production planners at the facility faced the daunting challenge of deciding daily output volumes hours before actual customer orders arrived. With traditional forecasting methods yielding accuracy rates of just 65-75%, the company regularly confronted substantial economic and operational losses, especially in organic meat production, where excess product typically must be downgraded to conventional meat at significantly reduced margins.
To address this critical issue, SLA turned to Qlik Predict, a predictive analytics solution powered by artificial intelligence and machine learning. The company trained Qlik Predict with comprehensive historical sales data combined with additional factors such as weather conditions, holidays, store sizes, and geographic delivery points. Testing this predictive model against actual historical data, SLA quickly improved forecast accuracy from 75% in worst-case scenarios to consistently over 90%, and ultimately achieving daily deviations of approximately 1%.
“In an industry where we're producing around 500 tons of meat daily, every percentage point improvement directly translates into thousands of euros in cost savings,” said Alexander Engel, Head of Business Intelligence at SLA. “By reducing forecasting deviations to just 1%, we're not only protecting organic meat from costly downgrades, but also significantly cutting waste, improving our margins, and achieving crucial sustainability outcomes.”
The Qlik-powered predictive solution was fully deployed and operational within just two weeks. With this capability, SLA was able to match production to demand for its customer, reducing both the need for excess cold storage and labor-intensive processes associated with inventory management.
“Real-world AI success means swiftly and clearly delivering measurable business outcomes,” said Brendan Grady, Executive Vice President and General Manager of Qlik’s Analytics Business Unit. “SLA’s impressive results demonstrate Qlik Predict’s ability to rapidly operationalize AI for immediate financial and environmental benefits. This case is a clear example of how predictive analytics can fundamentally change the economics of industries as critical and complex as food production.”
Following this success, SLA is planning to extend predictive analytics to other areas of the food production value chain, including logistics, product picking, and transportation route optimization, leveraging integrations with Qlik Answers and Amazon Bedrock. Engel from SLA added, "Our goal is to consistently bring industry-leading digital innovations to the fundamental operations of the food industry. Qlik Predict is proving ideal for scenarios requiring accurate forecasts to drive real-time, effective decision-making."
About SLA Software Logistik Artland
SLA develops and implements end-to-end digital solutions tailored to the food industry. Its portfolio includes AI, ERP, and shop-floor systems that help producers optimize planning, production, logistics, and sustainability efforts.
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