Tag: data governance collaboration

Categories
erwin Expert Blog

Data Governance Readiness: The Five Pillars

In light of the General Data Protection Regulation (GDPR) taking effect in just three months, an understanding of data governance readiness has become paramount. Organizations need to make sure they’re ready to meet the world’s most comprehensive data privacy law’s requirements:

  • Understanding all the systems in which personal data is located and all the interactions that touch it
  • Knowing the original instance of the data plus its entire lineage and how it’s handled across the complete ecosystem
  • Ensuring changes, purges or other customer requests are adhered to in a timely manner
  • Notifying customers of a data breach within 72 hours

GDPR becomes effective in an age of rapidly proliferating customer data. For organizations to meet its demands, data governance (DG) must become operational. Done right, it holds great promise not only for regulatory compliance but also for creating data-driven opportunities that drive innovation and greater value.

The 2018 State of Data Governance Report shows that customer trust/satisfaction, decision-making, reputation management, analytics and Big Data are the key drivers of data governance adoption, behind meeting regulatory obligations.

Data Governance Readiness: Data Governance Drivers

A Question of Approach

There’s no question data governance is important and should be the cornerstone of data management to both reduce risks and realize larger organizational results, such as increasing customer satisfaction, improving decision-making, enhancing operational efficiency and growing revenue. The question is how to implement DG, so it does all that.

The boom in data-driven business, as well as new regulatory pressures, have thrust DG into a new spotlight. But the historical approach to DG, being housed in IT siloed from the parties who could use it the most, won’t work in the age of digital power brands like Airbnb, Amazon and Uber.

Data governance done right requires the participation of the entire enterprise and should be measured and measurable in the context of the business. Fortunately, Data Governance 2.0 builds on the principle that everyone in the organization has a role in the initiative, which is ongoing.

IT handles the technical mechanics of data management, but data governance is everyone’s business with stakeholders outside IT responsible for aligning DG with strategic organizational goals.

This creates an environment in which data is treated as an organizational asset that must be inventoried and protected as any physical asset, but it also can be understood in context and shared to unleash greater potential.

The Pillars of Data Governance Readiness

If you accept that data governance is a must for understanding critical data within a business context, tracking its physical existence and lineage, and maximizing its security, quality and value, are you ready to implement it as an enterprise initiative?

We’ve identified what we believe to be the five pillars of data governance readiness.

  1. Initiative Sponsorship

Without executive sponsorship, you’ll have difficulty obtaining the funding, resources, support and alignment necessary for successful DG. 

  1. Organizational Support

DG needs to be integrated into the data stewardship teams and wider culture. It also requires funding.

  1. Team Resources

Most successful organizations have established a formal data management group at the enterprise level. As a foundational component of enterprise data management, DG would reside in such a group.

  1. Enterprise Data Management Methodology

DG is foundational to enterprise data management. Without the other essential components (e.g., metadata management, enterprise data architecture, data quality management), DG will be struggle.

  1. Delivery Capability

Successful and sustainable DG initiatives are supported by specialized tools, which are scoped as part of the DG initiative’s technical requirements.

We’re going to explore these pillars of data governance readiness in future blog posts and through a new, free app to help you build – or shore up – your data governance initiative. By applying them, you’ll establish a solid data governance foundation to achieve the desired outcomes, from limiting the risk of data exposures to growing revenue.

In the meantime, you might want to check out our latest white paper that focuses on the impending GDPR and how to increase DG expertise because no organization with even one customer in the EU is outside its grasp. Click here to get the white paper.

Data Governance and GDPR: GDPR and Your Business Whitepaper

Categories
erwin Expert Blog

Data Governance 2.0: Collaborative Data Governance

Data Governance 1.0 has been too isolated to be truly effective, and so a new, collaborative data governance approach is necessary.

This rings especially true when considering the imminent implementation of the General Data Protection Regulation (GDPR). Compliance is required from all EU-based companies and those trading with the EU.

It’s extremely likely that your business falls under GDPR’s scope. Failure to comply will leave your company liable for penalties up to €20 million or 4% or annual global turnover – whichever is greater.

With the amount of data a modern business has to manage, and the copious access points, GDPR compliance will require everyone to sing from the same hymn sheet.

This is where Data Governance 2.0 comes in. As defined by Forrester, it is “an agile approach to data governance focused on just enough controls for managing risk, which enables broader and more insightful use of data required by the evolving needs of an expanding business ecosystem.”

The principles of Data Governance 2.0 were designed with modern, data-driven business in mind. This new approach acknowledges the demand for collaborative data governance, tears down organizational silos, and spreads responsibilities across more roles.

Collaborative Data Governance

Collaborative Data Governance – Shattering Silos

As addressed above, modern businesses must deal with volumes of data that legacy systems and policies just weren’t designed to manage. This problem is exacerbated by the variety of data, both structured and unstructured, historically managed by different departments within an organization.

To shatter such silos, organizations can leverage a collaborative data governance approach to foster better data use and accountability. A governance tool that can sort, regulate and manage data access through secure checkpoints and assigned roles is key. Then the right data of the right quality, regardless or format or location, is available to the right people for the right purpose.

Such a data governance tool is paramount not only to help ensure GDPR compliance but also for effective business operations. It’s important to stress that data governance is a key revenue driver.

In this digital age, data is more valuable than oil. But as with oil, it must be refined.

Collaborative Data Governance – The Data Refinery

Data Governance 1.0 was mainly concerned with cataloging data to support search and discovery. However, it fell short in adding value because it neglected the meaning of data assets and their relationships within the wider data landscape.

Many of the IT professionals involved in data governance recognized this, but calls for business leaders to be more active in governance often fell on deaf ears. Now that data has become a more critical business asset, we’re starting to see a shift.

Collaborative data governance encourages involvement throughout the organizational hierarchy. This is especially important now that business leaders, from CMOs to CTOs, are intrinsically involved in data management on a day-to-day basis.

As the best placed individuals in an organization to advocate and implement change, bringing ranking business leaders into the fold helps inform and enable the effort’s return on investment – both in limiting data exposures and driving new opportunities.

In the case of the CMO, data analysis might indicate that email open rates exceed targets, but click-through rates are underperforming. The CMO then can adjust content strategy to provide prospects with more relevant information and calls to action.

To learn more about collaborative data governance and the tool to foster this approach, click here.

Data governance is everyone's business