Where would we as a society be without good governance? Presumably we’d still be hunting and gathering while throwing rocks at neighboring tribes if they dared to wander too close. Good governance allows for a group of people to all put their shoulders to the wheel and push in the same direction. It has taken our species from our nomadic and insular tribal beginnings to the globalized powerhouse that we see today.
Good governance focuses effort and enables progress. With a simply stunning amount of knowledge and insight hidden within the data contained in the systems of a company, Business Intelligence (BI) – the technology that allows organizations to exploit data – represents an opportunity simply too great to pass over.
And so we come to the issue of data governance. Your business data can almost be seen as a microcosm of society, in that good data governance is imperative if you are looking for your organization grow and evolve through data. In such a data-driven environment a business will never realize the full potential of its business intelligence efforts if the data isn’t well managed. You can have the most advanced and capable BI software on the planet, but if the data it’s being fed isn’t properly managed, the quality and depth of its results will be severely compromised.
So what exactly are we talking about when we discuss data governance? Data governance is perhaps best defined as the overall management of the usability, integrity, availability and security of data used by an organization. It is about managing and controlling data in order to capitalize on it in the most comprehensive way that you can, and to gain the most accurate and greatest amount of knowledge and insights possible.
Put simply, data governance is about making the most of what you’ve got. This manifests itself in a variety of ways. An organization with good data governance will ensure that they maintain a Single Source of Truth (SSoT) – an unchallengeable source of all the crucial data needed to run your business. An organization’s SSoT serves to make vital data uniform. It avoids different departments within an organization retaining slightly differing versions of the same data – for example, a customer may be listed as Megacorp by marketing, Megacorp Ltd by accounts, and Megacorp Pty Ltd by sales.
Another manifestation of data governance is the need for an organization as a whole to gain an understanding of its data practices. In order for any BI strategy to succeed, particularly one that puts power in the hands of an end user (such as programs featuring self-service components), terms must be clearly defined and understood across the organization. This process can help to clarify the benefits and potential of a BI solution to otherwise skeptical employees.
Good data governance will clearly define terms, will put in place strict data-handling systems and procedures, and will demarcate the roles of each individual using BI.
91.7% of firms in NewVantage Partners' 2019 study said their primary driving factor for investing in big data was to perform more competitively by using big data for transformation and greater agility. In the midst of trying to maintain this competitive edge, though, many executives have pointed to the fact that their organizations weren’t paying close enough attention to data governance, leading to their BI programs offering up (in the best case) less than optimal or (in the worst case) entirely unreliable results. It poses the question - what’s the point in having a BI program if you can’t trust the insights that it generates?
The dangers of badly governed data don’t just present themselves in missed opportunity. The truth is that bad governance can result in mistakes that can cripple an organization, particularly those that find themselves in heavily regulated industries. By way of example, mismanaged data for a healthcare provider could result in unintended breaches of compliance, the mistreatment of patients, and could open the organization up to security threats.
As an ever-increasing amount of external data is brought in to assist a company to generate insights, data governance becomes all the more important. Defining and managing in-house data is one thing, but doing the same to the constant flow of third party data is quite another. This is particularly the case for BI solutions with self-serve functions, as end-users will generally be unable to verify the accuracy and legitimacy of the data – they’re obliged to put their full faith in it. If an organization’s data governance processes aren’t where they should be this could have severe consequences for the business decisions that are made off the back of these end user generated insights.
Good data governance requires serious will. It’s a long-winded, complex process that can take years to get to a satisfactory level. But for those willing to invest the time and resources, it’s sure to pay big dividends into the future. Aside from the senior executives’ worries about data governance, there is still an overwhelming feeling of positivity surrounding BI and big data:
If your business is willing to take the leap into BI, it’ll need to also take the leap into data governance. It’s simply a matter of due diligence. Data governance represents the foundation of all meaningful BI activity, and will ensure that your organization is ready to navigate the data-heavy business landscape of the future. It’s not just a set of systems and controls; it’s a mindset.
One important step is to get to the next level of your Business Intelligence understanding. You can start with our guide "What is Business Intelligence," which will help you make determinations about:
If you are ready to discuss your specific challenges or what CSG can offer, you can contact us to learn more about how to start implementing your solution.
Learn the truth about data truth: SSOT vs. MVOT