The Total Economic Impact™ Of UMH

Cost Savings And Business Benefits Enabled By UMH

Forrester Consulting interviewed UMH customers across automotive, food & beverage, and industrial manufacturing. They built a three-year financial model from real deployment data, not projections.

The results cover energy costs, manual labor, and unplanned downtime, risk-adjusted and presented in present value.

What's inside the study

The complete three-year financial model: benefits, costs, NPV, and ROI

Energy cost savings from real-time visibility into consumption across sites

Labor savings from eliminating manual inspections and meter reading rounds

Operational efficiency gains from faster downtime detection and root-cause analysis

Full methodology: risk-adjusted calculations, 10% discount rate, three-year horizon

Download the full Total Economic Impact™ study of UMH

About the Study

Executive Summary

Manufacturers are under increasing pressure to improve operational efficiency, reduce energy and labor costs, and modernize aging shop‑floor systems while preparing for stricter regulatory requirements and for the age of AI. Many organizations struggle to scale digital manufacturing efforts due to fragmented data, legacy systems, and lack of a unified operational data foundation.

UMH provides a AI data platform that enables manufacturing organizations to centralize IT and OT data in order to improve operational transparency, and support continuous improvement initiatives across sites. By establishing a unified data layer between shop floor systems and higher level applications, UMH helps organizations reduce costs, improve efficiency, and prepare for advanced analytics and AI.

UMH commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying UMH. The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of UMH on their organizations.

This study is commissioned by UMH and delivered by Forrester Consulting. It is not meant to be used as a competitive analysis.

Inside the financial model.

Forrester's TEI methodology quantifies four components for every investment. Here's what they examined for UMH.

Energy Costs

Real-time consumption visibility surfaced standby loads, pressure inefficiencies, and equipment running outside production hours. Sites reduced energy waste without capital expenditure.

Labor Costs

Manual machine inspections and meter reading rounds consumed recurring hours across every site. UMH automated data collection, eliminating the need for physical rounds entirely.

Operational Efficiency

Production teams gained visibility into machine states and downtime events in real time. Morning shift meetings changed when teams could see exactly what happened overnight, and why.

Future Option Value

Interviewees described UMH as the data foundation they needed before AI and predictive maintenance could realistically move forward. Use cases that were previously blocked are now feasible.

"We produce almost 20 million fasteners per day. That generates enormous amounts of data. Machine data, energy data, production orders. But it was all in separate systems. We had the data. We just couldn't use it."

Head of Processes, Digitalisation and Applications

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"With UMH, we gained real-time insight into our production for the first time. The platform’s flexibility allowed us to connect all our machines and drastically reduce manual data work. This has been a game-changer for our efficiency."

Head of Manufacturing IT

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"We finally found a product that is stable and flexible enough to connect all of our assets and sensors. Within weeks we achieved process transparency we never had before."

Managing Director

"I think that the future of industrial infrastructure must be modular and open source, as this is the only way to make data easily available and components interchangeable."

Director Smart Manufacturing

"We didn't buy a single-purpose product. We bought something we can use across all our use cases."

Head of IT

"Choosing an IoT system can be daunting due to high costs and integration complexities. UMH stood out by seamlessly combining microservices for effortless setup and customization. Its open-source approach offered the flexibility to fully tailor our IoT system, bridging IT and OT efficiently."

Production Development Manager

"AI is a topic where almost daily I get asked by top management: what are we doing with AI in production? And I always have to explain that you need to have data to start. Therefore, my standard answer is: what we are doing with AI is providing a common data platform with UMH so that we'll be able to use it"

Head of Processes, Digitalisation and Applications

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