How Data Governance Can Improve Your Bottom Line
Do you trust your data? Companies small and large should be thinking about ways to improve the integrity of their data.
Do you trust your data? It’s a question that makes many marketers uncomfortable—and rightfully so.
According to a study from Experian, 91% of organizations are plagued by common data errors. In addition, most U.S. companies believe that nearly 25% of their data is inaccurate. These are startling numbers.
As marketers, we have access to millions of data points that span the Web, advertising, in-store, CRM, email, and much more. Inaccurate data not only means wasted time, but wasted and potentially detrimental efforts.
It’s no secret that the world of big data is growing. Organizations that can harness this data, synthesize insights, and take actions faster than their competitors will win. But how do we collect and ensure the accuracy of all of this data?
That’s where data governance comes in. Data governance refers to the availability, usability, integrity, and security of an organization’s data. While data governance isn’t a new idea, it has quickly become a hot topic among marketers who are looking for a way to wrangle and wield the vast quantities of data they have available to them.
The growing need for data governance is resulting in some companies completely rethinking their operations. Organizations that are leading the charge in this field have even gone so far as to build out full data governance teams led by chief data officers.
Why You Should Care About Data Governance
Here are some potential problems you could encounter without a solid data governance strategy:
- Wasted time: This is true especially if the data you have isn’t available to you or isn’t in a format or program that’s usable.
- Wasted effort: Poor data integrity can mean optimizing for the wrong things or making decisions that may actually lose money.
- Security risks: The last thing you’d want is your proprietary data being compromised by hackers or falling into the hands of your competitors.
Data governance doesn’t have to be an “enterprise-only” thing. Companies small and large should be thinking about ways to improve the integrity of their data. Remember the old moto: garbage in, garbage out.
The Six Pillars Of Data Governance
The path to trustworthy, accessible, and secure data starts with an understanding of the pillars of data governance. Many online points of view offer different perspectives, but here’s a useful framework:
1. Accountability and oversight: Define who in your organization has ownership and accountability for all of your data. This should be a team of people that provide oversight, stewardship, quality assurance, and maintenance of your data.
2. Data standards: Define and document technical requirements, templates, processes, and naming conventions.
3. Process: Define processes for how data is made available, how to access it, who can access it, and how issues are reported and solved.
4. Data management and quality assurance: Define and implement technology to manage your data and to perform routine auditing and testing to ensure accuracy. This can include tag management systems, data management platforms, and auditing software.
5. Security: Define and implement layers of security spanning encryption, hosting, and access for your data.
6. Retention, disposal, and maintenance: Define and implement procedures for retaining critical data, disposing of antiquated or unusable data, and maintaining clean and accurate data collection.
Getting Started With Data Governance
So are you ready to get started on the path to ensuring that your data is accessible, usable, accurate, and secure?
The first step we recommend is to plan your approach by making sure the right stakeholders are on board and by using the pillars of data governance as a roadmap. Getting buy-in from the right people makes a huge difference. We recommend creating a business case based on the time and money you’ll save, the opportunity to increase revenue, and the reduction of risk.
Once you gain alignment, you’ll need to identify the problem areas in your data collection that need to be addressed as well as the technology and tools needed to get the job done.
Expect it to take some time, especially when it comes to implementing and conducting quality assurance audits of your data. This is where strong expectation setting and technical expertise come in handy.
While the journey can take time, the results are tremendous. It can be the difference between being a market leader versus a market laggard.