Koch Ag & Energy Solutions (KAES) Transforms their Operations with Rapid Deployment and Data-Driven Insights
Cognite enabled KAES to rapidly unify and contextualize data with Cognite Data Fusion, driving predictive operations, faster deployments, and improved efficiency.
Onboarded 6 sites in under 6 months, and a 7th in two months
Enabled agile, data-driven workflows by unifying trillions of rows of time-series data
Onboarded 60% of users in one month with intuitive software design
KAES Goes from Data Silos to Scalable Success in Months
KAES partnered with Cognite to unify siloed data, enabling rapid deployment across six sites in under six months. By integrating Cognite’s tools, they improved maintenance workflows, scaled predictive capabilities, and empowered users, driving operational efficiency and agility.
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In their own words
The only way we can build the fleet of the future is by harnessing data…that’s why we partnered with Cognite.
Josh Dotson
Industry 4.0 Leader, KOCH – AG & Energy Solutions
A few key factors for us to consider when looking for a partner were speed, automated contextualization, and the ability to keep up with rapidly changing technology. We decided to partner with a company where this was their comparative advantage - that's why we partnered with Cognite.
Josh Dotson
Industry 4.0 Leader, KOCH – AG & Energy Solutions
It’s been 6 months of partnering with Cognite [...], we have been able to fully stand up the foundation, contextualize over 500,000 engineering documents, P&IDs, PFDs, plot plans, over 250,000 hours of our time series data, and over 7 years of work order history.
Josh Dotson
Industry 4.0 Leader, KOCH – AG & Energy Solutions
The Total Economic Impact of Cognite Data Fusion®
Customer interviews and financial analysis reveal an ROI of 400% and total benefits of $21.56M over three years for the Cognite Data Fusion® platform.
Summary of benefits
(three-year risk-adjusted)
Improved SME efficiency
$1.5M
Revenue gains arising from shorter shutdown period
$4.8M
Real-time data efficiencies
$2.3M
Optimized planned maintenance programme
$4.3M
Energy efficiency savings
$5.1M
Optimization of heavy machinery and industrial work-flow
$9M