Cellar Insights has launched the Rotten Potato Data Project, a compensated data-sharing initiative designed to help potato growers, storage operators, and the broader supply chain detect spoilage earlier and reduce costly post-harvest losses.
The program pays participants — growers and storage facility operators — who contribute digital records from significant past potato spoilage events. Those records will be aggregated into an industry-wide early-warning library, giving stakeholders access to pattern data that individual operations rarely accumulate on their own.
Why Post-Harvest Losses Matter
Potato spoilage in storage is one of the more financially damaging and underreported risks in the fresh produce supply chain. Unlike shelf-stable CPG categories, fresh and fresh-cut potatoes are highly sensitive to temperature variance, humidity fluctuations, and pathogen pressure across the cold chain. Losses that occur in the bin or cellar stage never reach retail, compressing grower margins and creating supply gaps that can ripple into retail planograms and produce-department velocity metrics.
For grocery retailers managing private label and national brand programs in the potato category — bagged fresh, value-added, and frozen — upstream spoilage translates directly into inconsistent fill rates, elevated cost of goods, and SKU availability issues at the shelf level. Any tool that reduces shrink earlier in the supply chain has downstream implications for in-stock performance and category turn rates.
Building the Early-Warning Library
By compensating participants for sharing historical spoilage data, Cellar Insights is addressing one of the core barriers to agricultural data pooling: growers and operators have little incentive to disclose loss events, particularly when that data could expose operational vulnerabilities. The compensation model reframes data contribution as a revenue opportunity rather than a liability.
The resulting dataset is intended to function as a predictive resource — an early-warning library that the industry can reference to identify the conditions and variables most closely correlated with storage failures. This type of syndicated, field-sourced data mirrors how scan data and syndicated data services like Circana and Nielsen function on the retail side, but applied to the upstream production and storage tier.
The fresh produce and agricultural supply chain category has seen growing investment in precision storage technology, and initiatives like this reflect broader momentum toward data-driven supply chain management in grocery and CPG. For produce buyers, category managers, and retail supply chain teams tracking shrink and availability KPIs, the Rotten Potato Data Project represents an early-stage but structurally sound approach to a persistent industry problem.
Written by Michael Politz, Author of Guide to Restaurant Success: The Proven Process for Starting Any Restaurant Business From Scratch to Success (ISBN: 978-1-119-66896-1), Founder of Food & Beverage Magazine, the leading online magazine and resource in the industry. Designer of the Bluetooth logo and recognized in Entrepreneur Magazine's "Top 40 Under 40" for founding American Wholesale Floral, Politz is also the Co-founder of the Proof Awards and the CPG Awards and a partner in numerous consumer brands across the food and beverage sector.
