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Crisp is a forecasting platform specifically developed for the food supply chain, with a mission to reduce food waste by delivering accurate, precise demand forecasts, thereby setting the stage for optimal production, inventory, and service levels.
The numbers on food waste are staggering:
- One-third of food produced for human consumption is lost or wasted; 1.6 billion tons a year worth $1.2 trillion.
- $400 billion of food loss occurs before food is delivered to stores.
- 31% of food loss occurs at the consumer and retail level…an average of 219 lbs. per person.
Crisp focuses on reducing food waste through forecasting technology
Food industry participants are taking steps to reduce these statistics, including using apps to sell close-dated products, adopting standard “Best if Used By” labeling, and collaborating to facilitate donations of excess food. While these initiatives are commendable, the most effective way to reduce food waste is to not create excess food in the first place. More closely aligning demand and supply eliminates both excess inventory and retail out-of-stocks. The result: less waste, fresher product, happier customers, and increased profit. In short, source reduction begins with accurate, timely demand forecasts.
For produce and other perishable foods, accurate forecasting is especially challenging due to accelerating consumer demand, exploding innovation, sourcing and processing lead times, and short shelf life. This is particularly true for organic produce: consumption growth is outpacing supply, expanding supply is time and acreage bound, and getting product from farm to market is often more complex than for conventional products.
Are Traasdahl, CEO and Founder, Crisp
Enter Crisp, a Software-as-a-Service (SaaS) forecasting platform developed specifically to address the unique challenges and complexities of the food supply chain, with an emphasis on perishable foods. “With Crisp, it’s easy and fast to make the leap from complex, error-prone spreadsheets to high-speed, automated forecasting that incorporates all available demand signals and uses the latest forecasting models and machine learning algorithms,” said Are Traasdahl, Crisp CEO and Founder. “The Crisp cloud-based platform plugs seamlessly into existing ERP and IT systems; it can be set up and generating forecasts in under an hour. The interface is intuitive and user-friendly. Set-up is easy, output is fast, impact is high, and value is immediate.”
The paradox of food waste, hunger, and environmental impact came to life for Are Traasdahl, a successful technology entrepreneur, during a recent family adventure that spanned 30 countries. He saw vast amounts of crops left rotting in the field and food that spoiled or was thrown out before it reached the market. He also saw people unsure of where they would get their next meal. He returned to the US with an emotional connection to food disparity and inspired to find a solution.
Dag Liodden, Founder & CTO, Crisp
Traasdahl and his technology partner, Dag Liodden, researched the size and scope of food waste and met with hundreds of industry experts, probing to find its root cause. Their conclusion: food waste is grounded in lagging, inaccurate, incomplete data moving slowly across the complex food ecosystem. As everyone along the supply chain self-optimizes based on their own siloed data, errors compound, creating ripples across the entire supply chain known as the bull-whip effect. Their solution: leverage real-time, accurate, reliable, comprehensive data and state-of-the-art computing power to forecast consumer demand accurately, easily, quickly, and cost-effectively…creating a single version of forecast truth to drive upstream supply chain planning and operations.
Crisp has found that food waste is grounded in lagging, inaccurate, incomplete data throughout the chain
In their prior companies, Traasdahl and Liodden successfully connected trillions of signals from disparate sources and used computing power to make the data actionable. Believing this approach could be applied to the food supply chain, they created Crisp, a cloud-based demand forecasting platform that ingests hundreds of factors and trillions of data points, and leverages machine learning and artificial intelligence to produce highly accurate, granular-level, demand forecasts within minutes.
Because food waste is greatest among perishable foods, Crisp was tested and refined with those categories first, working with 30 clients across produce, fresh-prepared foods, meat, seafood, and retail. “We learned a tremendous amount working with our Alpha partners and meeting with hundreds of food suppliers and retailers. Their feedback significantly informed our approach,” said Traasdahl. “One thing we heard repeatedly is that, traditionally, most technology platforms, regardless of purpose, have been designed for CPG and are not comprehensive or flexible enough to accommodate the complexities of perishables. We took a perishables-first approach in creating Crisp; because of that, our platform flexes, accommodates, and accurately forecasts demand for all food categories, both perishable and packaged.”
Are Traasdahl and Dag Liodden have spent time with industry experts to research food waste
“The most accurate demand forecasts start with consumer takeaway at point of sale, even in supply-constrained categories or situations,” Traasdahl continued. “Perishable food producers often claim forecasting isn’t essential because they don’t grow/raise/catch enough product to supply all presumed marketplace demand. Therefore, they allocate available volume to their customers. But the reality is, forecasting true consumer demand in this situation is just as critical, if not more so! Understanding potential consumer sell-through by customer allows suppliers to strategically allocate available short-term supply while judiciously planning additional capacity for longer-term growth. Communication is essential; sharing information about demand, capacity and inventory alleviates customer anxiety while strengthening the partnership. Crisp provides the platform and venue for this type of collaboration.”
