Data and Analytics Strategy Predictions Through 2021

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Several colleagues and I just published our strategy predictions for data and analytics leaders: Predicts 2017: Licensing, Legal and Language Lessons for Data and Analytics Leaders. These are not predictions on technology, but rather on the drivers of behavior behind organizations monetizing, managing and measuring the increasing wealth of information assets available.

We believe that as information becomes an acknowledged (if not yet formally recognized) business asset, questions of its ownership, rights, monetization and valuation, along with how to communicate effectively about information, will become top of mind for data and analytics leaders.

Based on discussions we have had with thousands of clients over the past year, we’ve made a few key observations that portend some significant and interesting changes, including:

Most organizations are ineffective in communicating data and analytics related concepts across departments, resulting in suboptimal management and utilization of information.

Some major software vendors contractually prohibit users from accessing or extracting their own organization’s data using methods other than the vendor’s software itself.

Most business and analytics leaders do an insufficient job of legally protecting their organization’s proprietary algorithms.

Over 30% of organizations are directly monetizing information assets by bartering with them, trading them or licensing them outright.

Companies’ data and analytics capabilities are starting to become of material interest to institutional investors and equity analysts.

In this piece we discuss five key trends over the next five years:

Dolores Ianni and I discuss the challenge of vendors contractually preventing organizations from extracting their own data from the vendor’s applications. Who wouldn’t want to extract operational data into a data warehouse or data lake? We think this is deplorable behavior and predict a hasty end to it. However, as Dolores cautions for those already subject to such draconian contract terms: “If you think it’s your data and that you can freely move it — think again!” We offer particular market implications we foresee and recommendations for dealing with these situations.

Alex Linden, Marc Halpern and I examine the burgeoning marketplace for algorithms, and find that organizations are patenting algorithms today 30 times more than they were 15 years ago. We discuss the implications of this for businesses, and the emerging marketplace this kind of intellectual property.

Yefim Natis and I look at the more mature IP marketplace for data itself, predicting that many organizations will become either sellers or buyers of data via formal online data marketplaces. We identify a dozen distinct implications of this for businesses, government organizations, chief data officers (CDOs) and the current and emerging crop of data brokers.

Valerie Logan has observes that there’s incredible room to improve the way we “speak data” throughout the organization. Valerie predicts the initiation of deliberate competencies in information literacy, or what she has coined, “Information as a Second Language” (ISL).

And finally, Andrew White and I, building on our infonomics research, expect that the prevalence of equity analysts today evaluating companies’ data and analytics capabilities (including their information portfolios) will spark organizations to develop internal information valuation and auditing practices. Information is not considered a balance sheet asset, but financial analysts and companies (if not the accountants, yet), are starting to recognize it as one.

I hope you get a chance to read this publication in its entirety, and share your thoughts on it here.

(About the author: Doug Laney is vice president and distinguished analyst, Chief Data Officer Research and Advisory, at Gartner. This post originally appeared on his Gartner blog, which can be viewed here. Follow him on Twitter @Doug_Laney #infonomics #GartnerDA (data & analytics)

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