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Data Governance Trends in 2018

By   /  January 24, 2018  /  No Comments

data governance trendsData Governance isn’t what it used to be. That’s not a criticism at what it has been in the past. It’s just a heads up that going into 2018; Data Governance is evolving in exciting new ways as it takes on even greater urgency for organizations of every size.

In the past, says Kelle O’Neal, Founder and CEO of First San Francisco Partners, Data Governance meant Data Security and control, whereas today the focus is on value.

Governance should be about ensuring that data adds value to the enterprise, as well as enabling the enterprise to derive value from data,” she says.

Governance, then, involves identifying what the entity needs from the data and creating the guidelines, organization, and resource plan to make that happen; understanding how data can be used to promote the goals of the entity; and, leveraging data in new ways to improve customer identification and retention, and reduce costs and risk, she explains.

Building on that perspective, Ken Kring, Principal at PGTIT, explains that Data Governance today should mean “the continual cleaning and integration of data to drive profitable behaviors of customers and employees on an ongoing basis.”

Ramon Chen, Chief Product Officer at Reltio adds:

“Data Governance used to be the responsibility of IT and, in larger organizations, groups dedicated to this discipline, but today governance is a company-wide responsibility.”

Today its reach extends to more types of businesses, too. Highly regulated industries such as healthcare and life sciences, financial services, and government services always have taken Data Governance seriously, of course. But cross-industry regulations – such as the General Data Protection Regulation (GDPR) act that goes into effect in May of the new year – has raised the awareness of all companies about the need to do so, he says.

Others concur about how Data Governance is no longer an isolated, IT-focused discipline. Data Governance, says erwin Product Marketing Manager Danny Sandwell, should be a partnership of major business and IT stakeholders, working together to enable data-driven innovation and strategic advantage while mitigating data-related risks. ”Early indications,” he says, “point to the adoption of a Data Governance 2.0 approach,” which focuses on making Data Governance everyone’s business to support these ends.

The movement of Data Governance into the business area from IT is the big indicator that enterprises see Data Governance as critical business, says John Ladley, President, First San Francisco Partners.

Donna Burbank, Managing Director, Global Data Strategy adds:

“As more business users have a more direct relationship with data as part of Self-Service Data Analysis, it’s important to coordinate business and technical teams through formal Data Governance committees.”

It’s a key part of mitigating the pain that comes from poorly managed data that individuals and departments are feeling first-hand: the time spent searching for the right data, manipulating the data in order to cleanse or reformat it to be fit for purpose, and fleshing out core business rules and definitions, she says.

On top of all that, most leaders in the data space also point out the need to acknowledge the interdependent relationship between Data Governance and Data Strategy.

As Burbank says:

“In addition to creating the processes that allow for robust data that can be used for strategic advantage, governance bodies often have the right people in the room that can contribute to building a data strategy from both a business and technical perspective.”

O’Neal weighs in that in her view:

“The only way you can have a Data Strategy without any governance is when that Data Strategy is so new it hasn’t been implemented yet. Governance is a key part of any Data Strategy, so I believe that assessing how governance adds value to the organization is an early priority and activity that should be outlined in a Data Strategy.”

Read on to discover other insights into the evolution of Data Governance in the year ahead – and how your organization can take additional steps to drive efforts forward – from these data experts:

Donna Burbank: As data becomes more of a strategic asset, she sees more and more organizations inquiring about how to implement governance in order to manage that asset effectively. Starting with a small “quick win” approach – that is initiating Data Governance for one particular use case and/or department to establish the value of the effort is a good idea.

“Once this win has been established and an organizational and technical foundation has been established, it’s a logical next step to expand across the wider organization,” says Burbank. The nice thing about taking this tack is that rather than having to continually force the governance program, stakeholders generally ask to be included in the program. “Once the value proposition is proven, everyone wants to see value for their own project,” she says.

Burbank also advises creating a Data Governance structure that aligns closely with people’s day jobs, so that as little ongoing effort as possible is required for maintenance.

“Typically, a dedicated, resource-intensive up-front effort is required to establish the overall Data Governance framework in terms of organizational structure, roles, and processes,” she says.

Once the framework is up-and-running as part of ‘business as usual’ activities, less effort will be needed to raise and resolve data-centric issues when the right people are already in the right loop.

There will be continuing competitive struggles for companies that don’t embrace Data Governance – and sooner rather than later, too. “I’d go back to the old adage of ‘If you don’t have time to do it right, do you have time to do it again?’” she says. “Effort is required either with or without Data Governance. Without Data Governance, this effort is often spent reworking data, searching for data, and reacting to Data Quality issues.” With it, that effort can be put towards using data for strategic advantage.

Ramon Chen: “The evolving global regulatory landscape means that businesses of all sizes need some way to manage Data Governance across all their teams,” Chen believes. “From IT to business, governance is now a corporate discipline and requirement that must be taken seriously.”

He sees Master Data Management (MDM) as a focal point for driving and enforcing Data Governance waning, though. That is “eue to the cost to stand up an on-premises offering that includes investments in hardware, MDM and other disparate tools, IT experts, and the lengthy requirements and time to implement” across a wide variety of stakeholders, as well as because of its focus on profile data and not actual transactions.

“Companies who deploy MDM are still left to stitch together information through Data Warehouses and Data Lakes to get a complete understanding of where they stand in complying with regulations such as GDPR’s ‘right to be forgotten,” he says.

Organizations that don’t approach Data Governance in a more effective manner may put themselves at ever-greater risk, especially in the face of an evolving global regulatory landscape. “The consequences can range from continued security breaches, legal action and fines from non-compliance to competitive losses due to data being exposed, and more,” he says.

“Technology and modern Data Management platforms should handle Data Governance as a natural by-product. This approach also ensures that companies are not focused on ‘compliance as a burden.’”

Kelle O’Neal: With new regulatory requirements continuing to be announced, organizations that haven’t started governing their data are going to start falling farther and farther behind, as well as be out-maneuvered by their competitors that know how to leverage their internal assets.

“I’m not saying that every company has to have a large-scale, complex governance practice,” O’Neal says. “I’m saying that companies that don’t assess how to better understand and leverage their data in the context of their business goals, and who don’t put in place programs to act on that assessment, will fall behind.”

Similar to Burbank, O’Neal points to taking an incremental approach to extending governance to new parts of the enterprise. “It’s virtually impossible to have a ‘boil the ocean’” approach to implementing governance,” she says. And as companies look to governance to assist them in optimizing their data, not just controlling it, they’ll make additional investments in technology in order to leverage more and diverse types of data.

Along with that, there “will be investments in people and process to ensure that technology is implemented and used in a way that’s relevant to the business strategy of the company,” she says.

Indeed, the process and people investments will be critical to dealing with the fact that many companies still have a hard time understanding how to collaborate around governance. “They know they need to do it – they just aren’t clear on delineation of accountability and how/when to engage with each other,” says O’Neal.

Danny Sandwell: GDPR has been a real catalyst for investing in Data Governance, but businesses are recognizing that if they are to make the investment, it needs to impact a business’s top-line in addition to the bottom line, he says. That means that regulatory penalties; reputational risk (as trusted custodians of personally identifiable information); and missed opportunities all factor into what will propel companies to push for stronger Data Governance.

And that push will manifest in ways including:

“More dedicated roles, more well-defined Data Governance operating models and increased investment in software solutions that enable Data Governance 2.0,” he says.

Simply put, Data Governance is the foundation of an Enterprise Data Strategy, Sandwell believes. “Without it, there is too much exposure and risk associated with all aspects of the strategy – that is, proper usage, visibility and trust, and enterprise data fluency,” he says.

 

Photo Credit: Sergey Nivens/Shutterstock.com

About the author

Jennifer Zaino is a New York-based freelance writer specializing in business and technology journalism. She has been an executive editor at leading technology publications, including InformationWeek, where she spearheaded an award-winning news section, and Network Computing, where she helped develop online content strategies including review exclusives and analyst reports. Her freelance credentials include being a regular contributor of original content to The Semantic Web Blog; acting as a contributing writer to RFID Journal; and serving as executive editor at the Smart Architect Smart Enterprise Exchange group. Her work also has appeared in publications and on web sites including EdTech (K-12 and Higher Ed), Ingram Micro Channel Advisor, The CMO Site, and Federal Computer Week.

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