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How data is gaining value

Historically, much of the value that vendors associated with software was in the algorithms and the code. Well, that and the lock-in created by the dominant market share of proprietary software products and their proprietary formats. Sure, many companies build proprietary technologies on top of open source code. This sort of arrangement is especially prevalent in the public cloud world. Because cloud providers don’t distribute their products in the traditional sense, licenses impose fewer restrictions on how they can use open source software as part of their technology.

However, some public cloud providers also contribute to open source projects. The contributions by Google to Kubernetes and TensorFlow are cases in point. Open source projects with strong communities have demonstrated an effectiveness as a development model that’s impossible to ignore.

TensorFlow is a particularly interesting case in the context of IoT and machine learning. Google describes it as “an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them.” Open sourced by the Google Brain team, it reached version 1.0 earlier this year.

Why interesting?

Why companies choose to open source

Consider that you might reasonably think that a lot of Google’s (and, more broadly, Alphabet’s) IP is wrapped up in algorithms, software and general know-how around artificial intelligence. Or, really, ways to extract insights, deliver results or take actions based on data — whether that means displaying a personalized ad or enabling a car to drive autonomously. TensorFlow would seem to be squarely in the domain of these “crown jewels.” And yet here it is open sourced.

In part, this reflects a wider pattern around open source generally. You may write (and tightly control) a lot of internal code relevant to your business. But you can also benefit from opening up related software to a wider pool of developers and users. It’s not either/or.

Thus, you have financial institutions cooperating on blockchain, messaging and other technologies while also holding back plenty of proprietary trading algorithms. TensorFlow likewise represents a small slice of Google’s machine learning research.

It’s also about the data

However, there’s something else going on too. With the almost countless petabytes of data that will be generated by IoT systems and connected devices more broadly, value is shifting from code to data. Of course, it’s far from trivial to figure out how to do useful things with data you collect. But to the degree than an organization controls and owns data, they may choose to focus on effectively monetizing that data while maximizing the community and development velocity of the software.

We see this happening elsewhere as well. Baidu has open sourced autonomous driving technology. The storyline is that this is a way to level the playing field against other vendors taking a more traditional proprietary approach. But it also appears as if the company views the data it is collecting as a competitive differentiator that it doesn’t plan to release.

The new data-driven services

We see the value of data in many of the new services organizations are starting to deliver. For example, as noted in an MIT Sloan Management Review article, “GE wants to go beyond helping its customers manage the performance of individual GE machines to managing the data on all of the machines in a customer’s entire operation.” Other services can include optimizing preventative maintenance schedules on jet turbines and other industrial machinery.

Huge data lakes that aren’t curated or properly analyzed aren’t a benefit, of course. In fact, data that’s not used intelligently can have a negative ROI because of its collection, storage and management costs. But when data can be effectively used to guide actions and gain useful insights, it’s an increasingly large part of a technology company’s value. (And almost every organization is a technology company today.)

All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.