2017 Trends in Data Strategy

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jz_ds2017_121316Data isn’t just a piece of an organization’s business. It is the business – its fuel, fodder, and force. This past year bore witness to a growing recognition of that fact, which is so important to bringing attention to the need to aggressively define and refine Enterprise Data Strategy. We asked data experts and thought leaders for their perspective on how far Data Strategy has come in the last year, and where it goes next.

Our participants for this article were Jason Fishbain, Chief Data Officer, University of Wisconsin Madison; John Ladley, President, First San Francisco Partners; Thomas C. Redman, the Data Doc and President of Data Quality Solutions;  and  Jim Tyo, Chief Data Officer of Nationwide.

Their insights should be a help to any organization that is contemplating the steps it has taken so far and the steps it should take in the coming year to align its Data Strategy with its data values.

Looking Back at 2016

Our interviewees saw great progress in areas that influence the growth of strong data strategies, but also some misses among the hits.

One trend most respondents applauded was the continuing move by organizations to appoint Chief Data Officers (CDO). The increase in CDO hiring shows that businesses are cognizant of the importance of data assets, Ladley says.

Tyo finds reason to celebrate in predictions that by 2020 nearly 90% of Fortune 500 companies will have a CDO or equivalent:

“The great part about the expansion of the role is the more CDOs we have, the more business models we will have to examine and emulate and the more opportunity for success for the data community,” he says.

As for those who came to the role early on, as did Tyo, they have fought “through the initial risk-heavy onslaught and with the right strategy, could now be in a great position to take advantage of data in a more business-enabling activity,” he says. At Nationwide, every business leader says data is important, which is huge compared to just a few years ago, he says. “Now of course, the intricately complex next question (which is why I love my job) is how do we take advantage to gain a competitive advantage?”

It’s a Data Strategy question that many businesses are asking going into the new year, given the increased focus on the monetization of data that is happening in organizations of all types, including smaller companies, according to Ladley. “Corporate strategy or even vision is now influenced by looking at data as an asset with fungible value,” he says.

On the other hand, not everything is up to speed to fully realize the value of data assets. Ladley points, for example, to a degree of CDO turnover in some organizations that indicates that the role is still being defined, and notes that businesses still are not used to the new role at the leadership table. The “unsettlement” on that front may tie into some cultural issues that still slow down the progress of a data-driven organization that must be propelled by a strong Data Strategy.

Some organizations, Tyo notes, interpret having a data-driven culture as “trying to replace the great legacy and culture that has established brand success.” Not so: It’s the mission and values-driven culture that makes companies great, he says, “and CDOs are merely trying to infuse fact-based, insight-driven methods to enhance how that culture is executed with your clients.”

That said, truly being data-driven will create a transformational change in a company’s business model, Ladley says, affecting management, structure and operations. As Redman puts it, there’s no use in treating the term “data-driven culture” as a sound bite, which is still too often happening.

Looking Ahead to 2017 (and Beyond)

Our respondents weighed in on what will be top-of-mind for business Data Strategy initiatives.

Redman sees work continuing on enabling a true data-driven culture. Becoming data-driven implies deep and profound changes, Redman says, including building an aggressive program to take care of data (largely related to quality and security); putting it to work and, in time, crafting and executing a Data Strategy that is aimed at gaining competitive advantage in marketplaces against tough competitors; and, advancing a management system that recognizes data’s special properties. Also required is “an aggressive program to make better decisions, in both individual and team settings, by bringing more data to the table and integrating that data with intuition in increasingly powerful ways,” he says.

He also says that he’s been personally gratified to see how many people have resonated with the concept he introduced of the Data Provocateur – that is, the person who realizes that there is a better way to deal with departmental data problems and pursues that challenge, thereby serving as a role model for the rest of the company. (See DATAVERSITY’s® recent Q&A with Redman where he further explains the concept, which is covered in his new book  Getting in Front on Data.)

“Going forward, and not considering 2017 specifically, I hope for the following: That the notion of the provocateur will continue to gain traction and that more and more people will step up into this role,” he says. Additionally, he believes that the most forward thinking companies may begin to see the importance of exploiting proprietary data for competitive advantage.

Revisiting Business Intelligence and reporting is in order, too, as “most traditional reporting and BI architectures are becoming dated,” says Ladley. Driving stronger data reporting and analytic foundations also are on Tyo’s list, for this reason: “Nine out of 10 senior business leaders that I talk to list easy, simple and fast reporting and analytics in their top needs for data,” he says.  He believes this largely stems from the “cool factor” of data offices branching into Big Data, IoT, Machine Learning, Artificial Intelligence and so on, but notes that it’s as important to small and medium data, operational reporting and more traditional analytics/modeling needs.

“Under serving [access to proper data] will create shadow organizations or an outsource-first Data Strategy,” Tyo says. To avoid that, data strategies should include creating “an office dedicated to being the provider of choice for your business in all stages of data maturity.”

Tyo also sees that using data for client experience differentiation and Prescriptive Modeling (to drive advice on particular outcomes) will come to the fore, while Ladley believes all companies, whether they need it or not, will be hot for Predictive Analytics – that is, providing actionable insights based on data. “Every CEO wants new insights, even when they can’t even get an accurate operational report,” he says.

Ladley adds that Data Governance, which has remained a key activity – often as part of an effort like Master Data Management (MDM) or Big Data – will be re-aligned from IT or IM to compliance or risk management areas. “Data Governance inside IT does not work. This realization will continue to grow,” he says.

From a vertical perspective – higher education in this case – Fishbain believes that Data Strategy initiatives will revolve around collecting and harnessing new data sources to improve learning. “There is a lot of pressure to lower costs of matriculation for students and to increase graduation rates,” he says. “Data strategies need to align with that pressure.”

What Should be Getting More Attention When it Comes to Data Strategy?

Fishbain advises that more attention be paid to understanding the context around how data is collected and what decisions can be made with the data that is present, as well as what other data sources might be used to truly understand a scenario in order to make a more informed decision. “If a person just looks at the data without the context, is that part of a data-driven culture?” he asks.

Noting that Metadata is required and foundational, Ladley would like to see more enterprises focus on “some serious and useful deployments of good Metadata facilities.” And he wouldn’t mind if their strategies took into greater consideration collaboration around data usage. Most organizations cannot even cooperate around the data being used, he says:

“True collaboration would take organizations past the outdated concept of Centers of Excellence and into a realm where data is a unifying factor across silos, much like finance or budgeting.”

Speaking of silos, “embracing data virtualization in a meaningful way would be something I would like to see traditional silo’d businesses embrace more,” Tyo offers. “Additional federation across sources expanded to consistently leverage enterprise tools and utilities would enhance the overall program and accelerate many facets of CDOs’ strategic objectives.”

For Redman, the positive Data Strategy “points of light” that he’s seen so far haven’t yet added up to a real pattern, and he’s still troubled by companies that won’t learn from their past mistakes around Data Quality and Data Architecture – including seeking short-term relief while leaving the deeper causes unchecked. On top of that, “I don’t think that enough companies are moving fast enough, nor are we as an industry we moving fast enough,” he says.

There has never been a better time to be in the data space, he believes. But “not moving fast enough increases the likelihood that a new management fad will come along – or another crisis,” Redman says. “The Great Recession has deep roots in bad data—we can’t stand another.”

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