Data is the fuel for every modern enterprise. Business functions—including marketing, security, privacy, finance, and sales—require confidence in the data they use to make informed decisions. Bad data ultimately leads to bad decisions.
Most enterprises lack a proper understanding of their data and lack confidence in its truthfulness. A big reason this happens? Enterprises are struggling to maintain a single source of truth. Business units use multiple sources and systems to obtain their data, so they frequently rely on their own inconsistent and incomplete versions of truth to make important decisions.
To get real value from your data, it’s important for all executives, stakeholders, and everyone on your team to have access to the same data. To achieve this, data needs to be presented in the right way. Having a single source of truth gives decision-makers an overview of the initiative’s resources and possible problems that may interrupt the successful implementation of a data strategy.
We often pigeonhole data governance, thinking it is only about having a specific set of standards, policies, and procedures in place. Yet there is plenty of business value to extract here—including using data governance to govern and maintain a single source of truth.
How to Maintain and Sustain a Single Source of Truth
Power BI gives individuals the ability to maintain a single source of truth. However, this BI tool is only effective when the people using Power BI are effective. It’s all about the process—and governing your organization so everyone moves in the right direction together to keep that single source of truth intact.
It’s one thing to say “We validated our data sets.” And every time you go to query against this data set or build a report off of this data set, you know that it’s a hundred percent accurate and no one can question the data. But, how do you maintain and sustain that single source of truth? With proper data governance.
1. Gain Leadership Buy-In and Alignment on the Front End
Successful application of a data governance strategy requires effective management of the organization’s dynamics that allow for change. A critical step in governing a single source of truth is gaining executive buy-in.
The executive team has the power to influence finances, resources, culture, and the acceptance of new business practices across the entire enterprise. Leadership should be aligned around data governance efforts by setting and sharing goals and objectives that will be most beneficial in promoting consistent high-quality data across so business units have access to consistent, high-quality data.
2. Drive Accountability with Data Owners and Stewards
Creating a single source of truth is a team effort, so everyone needs to be involved in data governance. In addition to the IT, finance, and analytics teams, rolling out a data governance framework also needs data owners and data stewards, where responsibilities are delegated between those who define the meaning of data (steward) and those who control access to that data (owner).
Every person makes unique decisions and brings a unique perspective and skillset to your data governance efforts. Because of the unique nature of each of these roles, enterprises need to clarify roles and responsibilities for each part of the data governance framework. Establishing a Power BI Center of Excellence (CoE) is also helpful in ensuring a high level of integrity in the tools people are using and the information they are accessing to make decisions.
3. Be Vigilant with Shadow Analysts
Shadow analysts crop up whenever different business units have their own analysts. They often run an analysis with their own tools and improvise their work processes through unauthorized practices that operate outside the oversight and control of the organization. These siloed workflows will only unravel your efforts to govern a single version of the truth.
To mitigate risks shadow analysts create, organizational and IT leaders must establish policies and implement strategies that anticipate and manage information. These policies should aim to serve the needs of both the data analysts and the business.
Similarly, deploy monitoring and mapping of the most confidential and sensitive data with the help of file analysis applications, with active policy controls that promptly alert and protect your organization when data is out of compliance.
If you have a decentralized analyst structure, ensure the analyst team is actively communicating and collaborating. It fosters a great understanding of the true needs, experience, and feedback of users on existing and new technologies.
4. Use a Change Management Model to Evolve
Every business develops and evolves through a lifecycle from startup, growth, and maturity, to decline or renewal. Your single source of truth will develop and evolve alongside the business, so from time to time, you will need to make changes to the business mindset as well.
A change management model comes in handy to know where your business currently lies on its data governance path, and how it can get to the next level of business growth. To successfully make it through any evolutionary phase, you need to hunker down and formalize all your workflows—including the operating systems.
Also, maintain a growth mindset in the early stages of the change lifecycle. This way positivity, innovation, and experimentation help your enterprise embrace challenges and continue moving towards a permanent state of business maturity.
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With a single source of truth, business processes become more accurate and streamlined. But, that’s only half of it. All critical business decisions are made based on the most relevant data available, which is why maintaining a single source of truth should be a top priority.
Need help governing a single source of truth at your enterprise? Collectiv’s Power BI Visioning Program is a great option for your team.
