Agriculture company, mid-sized, USA
Inconsistent yield forecasting caused supply chain disruptions, delayed shipments, and unmet demand. Lack of real-time data worsened the issue, leaving customers uninformed, damaging trust, and reducing repeat business.
The company’s approach to forecasting was largely manual, relying heavily on the acumen of their harvest planners. This method didn't embrace the wide array of data potentially at their fingertips.
Manual yield forecasting and underutilized data resulted in accuracy below 88%. Challenges included outdated tech, difficult to scale, and too many siloed systems, slowing development work.
Limited business and IT resources led to skill deficits and a lack of specialized knowledge, hindering accurate yield forecasting and optimal productivity.
"Instead of building our own digital ecosystem—which would have taken 12-18 months—we were able to start within 8 weeks, thanks to Calibo's platform. For one application, we improved yield forecasting by 7%, resulting in millions of USD in savings within the first three quarters after implementation."
Chief Information Officer
Cutomer
Solution
The solution, crafted by Calibo using their Data Fabric Studio, leveraged advanced data science and forecasting methodologies to significantly enhance prediction capabilities, ensuring high accuracy and reliability.
Post-implementation benefits and outcomes
The customer saved several months of development time using Calibo, reducing the build time of a best-of-breed tech stack from 12-18 months to just 8 weeks, enabling faster realization of data and digital initiatives.
88-95%
Yield forecasting improved by 7%, from 88% to 95%.
$M
The increased accuracy also saved 900+ tons of tomatoes from potential wastage per quarter.
50%
Business-impacting applications can now be built within half of the time with Calibo, as opposed to previously.
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