Why engineering data preparation is the hidden ROI driver

Engineering data preparation is the systematic process of cleansing, structuring, enriching, and tagging raw test and sensor data so engineers can find, trust, and use it quickly for analytics and AI. Done well, it turns chaotic files and logs into a reusable asset that cuts time-to-insight from days to seconds and unlocks predictive models.

Part 3 — The AI Bottleneck Nobody Is Talking About

Walking the floor at CES this year felt like stepping into a future that suddenly arrived all at once. Everywhere you turned, there were robots, intelligent machines, autonomous systems, and increasingly lifelike interfaces. But unlike past years, many of these technologies no longer felt like fragile demos or research experiments.

Over the next few weeks, I’ll be sharing a short series of observations from CES 2026 across three themes:

Engineering teams possess an underutilized goldmine in today’s fast-paced industrial landscape: their data. From sensor readings and vibration logs to video, sound, and test metadata, engineering data holds critical insights that can accelerate innovation, reduce costs, and safeguard operations against failure. Yet, a significant portion of engineering time is wasted merely searching for, organizing and wrangling data to make it usable.

Barry Hutt co-founder Viviota

Harvard Business Review[i] reported that cross-industry studies show, on average, less than half of an organization's structured data is actively used in making decisions—and less than 1% of its unstructured data is analyzed or even used at all. 

"What we've got here is a failure to communicate." In the 1967 Paul Newman movie classic Cool Hand Luke, that memorable line is uttered by the character "Captain" (head of the chain gang) to justify beating Cool Hand Luke, played by Newman. Captain of Road Prison 36 has just told Luke that he is wearing chains for his good—to which the prisoner cleverly responds, "Wish you'd stop bein' so good to me, Cap'n."