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Data Analytics

It’s About the Economics of Machine Data, Stupid

October 25, 2018

If I never hear the phrase “Data is the new oil” again I will die a happy man. Don’t get me wrong – I wholeheartedly believe in the value of data and its power to transform businesses – but the frequency with which I hear this phrase reminds me we are still in the adolescent fascination phase of how we look at the power of data.

If I never hear the phrase “Data is the new oil” again I will die a happy man.

Initial “big data” projects are like a teenager dreaming about what they want to be before they enter the school of hard knocks. “Data lakes” become “data swamps” as the actual costs, resources, and people required to extract value reveal themselves. Becoming data-driven really does require fundamental change.

So how do we move from a limited use of data to fully operationalize its value across the business? It starts with three things:

  • Scope – be specific about what kind of data we are talking about.
  • Mindset – expand how we look at machine data. Yes, machine data is part of a company’s technology stack, but it is also an economic resource with quantifiable value and associated value extraction costs.
  • Technology – current approaches simply make the total cost of extracting value way too expensive.


We tend to talk about “data” as some amorphous thing, when the truth is there are many types of data. It’s easy to talk about how other companies use data: the 360 customer view; how Amazon knows what you want to purchase – and what you do – with every click. But what are you trying to accomplish? You need to identify the specific types of data needed to help you meet your goals.

At Devo we are focused on machine data – the rich real-time data readily available from every part of your digitized business. This is the fastest-growing type of data in companies today, which not only offers tremendous potential, but also faces some of the biggest challenges related to scale, speed of analysis, and making it easy for a broader audience within a company to use it.


Machine data is one of the most strategic assets a company has at its fingertips, yet it still tends to be viewed as a low-level technology resource.

Companies will not realize the real power of machine data until they see it as the economic resource, with a definable value, that it is. I talk to CIOs, CTOs, and Business Line Managers who see the line item on their budgets for machine data analytics double and triple while their value yield has plateaued.They are demanding that their architects, security and operations teams increase the value extraction-to-dollar ratio while also dramatically expanding the business surface they are mining data value from.


Yes, a shift in mindset is critical, however technology change is also required. While companies are benefiting from the value of machine data, they lack a viable business path to keep up with its rapid growth, and are frustrated by the time it takes to turn machine data into action. This is the problem Devo was founded to solve, and it’s how we help companies around the world every day.

The road to operationalizing the massive amounts of machine data available to nearly every business requires real change. It’s a journey with a clear roadmap and demonstrable benefit along the way.

Our latest white paper, Operational Data: A Roadmap to Value Creation, outlines this roadmap, with concrete tools and guidance. We also explore real-life examples of how companies have successfully unlocked and grown the value of their machine data from Automation → Information → Transformation.

Where are you on your journey?



More Data. More Clarity. More Confidence.