Data Analytics Makes the Transition From Novelty to Commodity

What happens when the use of analytics in business stops being new and different?

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Competing With Data & Analytics

How does data inform business processes, offerings, and engagement with customers? This research looks at trends in the use of analytics, the evolution of analytics strategy, optimal team composition, and new opportunities for data-driven innovation.
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Right now, many organizations find analytics vexing. They observe other organizations extracting value from data in ways they can’t, and wonder what the secret might be. But this vexation won’t last.

Value-adding analytical capabilities are increasingly attainable. For example, even the most basic websites can effortlessly incorporate Google web analytics. More complex applications can build on remarkably stable and sophisticated components such as infrastructure (Amazon S3, Google Cloud), platforms (OpenStack, Hadoop), structured databases (MySql, SQLite), and unstructured storage (Couchbase, MongoDB).

Before long, organizations will have unprecedented access to the components necessary to build advanced analytical processes. As costs for these components drop, consumption of analytics will increase along two dimensions — that is, more organizations will incorporate analytics, and each individual organization will incorporate analytics into more processes. The proliferation of analytics is already shaping many business environments as initial competitive advantages erode (see the recent MIT SMR/SAS report, The Analytics Mandate.)

To paraphrase Syndrome, the villain in The Incredibles movie, if everyone is special, then no one is.

As analytics become readily available to all organizations, they will take on the characteristics of a commodity. Every successful technology eventually makes the transition from being an emerging technology to a commodity technology. Examples like railways (late 19th century), electricity (early 20th century), and information technology (late 20th century) follow this now-classic pattern.

As more companies adopt and adapt to advanced analytics, what will the impending commoditization of analytics mean for your organization? The following four changes are on the horizon.

1. Increase in Project ROI

Reduction in costs associated with analytical components increase project ROI. For organizations embracing analytical approaches for the first time, cost reductions diminish barriers to entry and make initial projects easier to justify. For organizations with prior experience with analytical technologies, previously untenable projects will become practical, and organizational appetite for projects with analytical components will grow.

A lower revenue threshold for positive ROI will support incremental approaches. When an organization is building on prior experience with analytical technologies, one-time costs are usually accounted for in earlier efforts, so organizations will be able to justify projects that extend prior work and progressively improve processes.

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Topics

Competing With Data & Analytics

How does data inform business processes, offerings, and engagement with customers? This research looks at trends in the use of analytics, the evolution of analytics strategy, optimal team composition, and new opportunities for data-driven innovation.
More in this series

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