All businesses face the need to measure and analyze their business performance. The bigger the organization, the bigger the problem, with various operating companies, business units and departments all having their own priorities and ways of doing things. This includes how they manage their data, making strong corporate data governance essential.
For example, suppose you want to answer a seemingly simple question such as “Who are my most profitable customers?” To do this, you need to be able to collect data across the business about customers, the products they buy, and the costs involved in marketing and selling. Even if you can, just figuring out how much revenue is associated with a given customer might not be a trivial task.
For example, if it’s a complex multinational, you need to ensure that your sales teams have correctly identified that the transactions they invoiced for purchases are part of the larger entity. It’s easy enough to figure out that Shell USA and Shell UK are part of parent company Shell PLC, but what about Pennzoil or Jiffy Lube? They are also subsidiaries of Shell.
Why Effective Data Governance Matters
To complicate matters further, the data to support profitability calculations and other types of analysis is typically scattered across different applications. Even if you have a standard ERP system, is there only one instance? What about customer, product and sales data classifications? Do you have a single, perfectly consistent set of data classification hierarchies? Even if you do it by some miracle, what happens when you acquire another company that has its own applications and classification hierarchies?
The reality is that almost every large enterprise has data silos that contain inconsistent data and are not accessible to users across the organization. This requires a major effort to align the collection, creation, classification, formatting and use of data across organizational boundaries. As a result, data governance has become one of the essential elements of an overall data management strategy.
How Data Governance Can Help Businesses
Data governance is a set of processes for actively managing and controlling data and its use in an organization. This involves developing internal data standards and policies, and procedures for applying them to ensure data is accurate, consistent and used correctly. Here are the main benefits that a successful data governance program can produce in an organization.
1. Greater efficiency
If you have well-managed data and the ability to perform business analytics with it, you can improve operational efficiency in many areas. A rule of thumb is that 20% of your customers provide 80% of your profit; Accurately measuring which customers are best for the business allows you to better target your marketing and sales investments. By understanding product profitability, you can eliminate underperforming product lines and invest more money in promising ones. Analyzing business processes can reveal opportunities to improve them, but only if the data underlying those processes is reliable.
2. Better data quality
Despite significant IT investments, maintaining good data quality remains an insoluble problem. A study published in 2019 by software provider Experian Data Quality found that 95% of organizations feel the impact of poor data quality; more concretely, respondents to a 2020 Gartner survey estimated that poor quality data costs their organizations an average of $12.9 million per year. The effects of data quality issues can be profound, which is why data quality improvement efforts are a key part of data governance programs. Improving data quality reduces operational errors and increases analysis accuracy. While there is no silver bullet, a good start is to create a data quality mindset and regularly audit and measure data quality levels as part of the governance process.
3. Better compliance
In healthcare, financial services and other industries, there are significant penalties for non-compliance with regulations. For example, pharmaceutical companies are required by law to track their marketing and advertising spend. Failure to comply with regulations has led to multi-billion dollar settlements and others amounting to hundreds of millions of dollars with the US Department of Justice since 2009. With these types of sums involved, the communication clarifies and verifiable data is crucial. GDPR, the California Consumer Privacy Act, and other data privacy laws also add new compliance requirements regarding the use of personal customer data in various industries. Without strong data security and privacy protections backed by effective governance, companies could face fines and lawsuits.
4. Better decision making
If your organization has a strong database, it will be able to confidently make better business decisions. Executives and workers can plan, monitor and act on marketing promotions, price adjustments, product strategy, customer service and other aspects of business operations in a more informed way. However, it all depends on end users having access to accurate data for strategic planning, business intelligence, and advanced analytics applications.
5. Improved business performance
Ultimately, the benefits described above should lead to increased revenue and profits. It really seems that successful companies take data governance more seriously than other organizations. For example, a 2018 McKinsey survey found that “dissident companies” were twice as likely to strongly agree that their data governance strategy enabled them to identify and prioritize important data assets. Improving business performance should be the goal of any business initiative, and data governance clearly has an important role to play in this regard.
6. Improved company reputation
In addition to tangible financial gains, effective data governance can help improve how an organization is perceived by customers. For example, high-quality data enables better customer interactions by sales reps and customer service representatives. Ideally, this leads to higher levels of customer satisfaction and increased customer retention, which should further improve business performance.
How to build a data governance strategy
Data governance was once seen as an IT problem, but there is a growing realization that IT lacks the power to set and enforce uniform data standards. Business leaders must lead such initiatives; to ensure they do, a data governance program typically includes a steering committee of senior executives and other data owners that makes policy decisions. It must also resolve arguments over which definition or classification of data is “correct,” with the power to compel business units to change their systems and processes to conform to the designated standard.
The steering committee is supported by a data governance team that manages the program and by data stewards – typically data savvy business users across the organization who have at least part-time responsibility for overseeing datasets and enforce data standards. In a data governance benchmarking database run by my analyst firm, The Information Difference, the average company has four full-time data governance employees and nine part-time data managers.
With the governance structure in place, how do you achieve your goals and reap the benefits of an effective data governance initiative? Companies participating in The Information Difference benchmark database respond to a detailed survey. Statistical analysis of the responses shows that the companies that consider themselves the most successful in terms of data governance have very different behaviors from those that consider themselves the least successful.
In particular, successful data governance programs include the following:
- a clear dispute resolution process;
- detailed documentation of business processes;
- regular data quality audits;
- a risk register that lists business risks related to data;
- data models for key business data domains; and
- policies to limit access to sensitive or business-critical data.
These programs also have a mission statement, business case, data governance training, and a process for reporting progress and results. The different steps described here show you the way to a successful program that will deliver the expected benefits of data governance in your organization.