All companies 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. That includes their data, which makes a strong enterprise data governance strategy a must.
For example, say you want to answer a simple question like, "Who are my most profitable customers?" To do so, you need to be able to gather data from around the enterprise on customers, the products they buy and the costs involved in marketing and selling to them. Just figuring out how much revenue is associated with a given customer may be no trivial task. If it's a complex multinational company, you need to be sure your sales teams have correctly identified that operations they have invoiced are part of the broader entity. It's easy enough to figure out that Shell UK is part of Royal Dutch Shell, but what about Pennzoil or Jiffy Lube? They're also Shell subsidiaries.
The data to support calculations of profitability is scattered among different applications. Even if you have a standard ERP system, is there just one instance of it? What about hierarchies of classifications for customer, product and sales data? Do you have just one perfectly consistent set of data classification hierarchies globally? Even if you miraculously do, what happens when you acquire another company, which has its own applications and hierarchies?
How data governance can help companies
The reality is that almost all large companies have data silos that contain inconsistent data and classifications. It requires a major effort to align data collection, creation and classification across organizational boundaries, and thus, data governance has become one of the core elements of an overall data management strategy.
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Data governance is a set of processes to actively manage and control data and how it's used in an organization. Here are the key benefits that can be expected from a successful data governance program.
1. Greater efficiency
If you have well-governed data and the ability to do 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 profits; clearly measuring that enables you to better target your marketing and sales investments. Understanding product profitability enables you to weed out underperforming product lines and invest in ones that show promise. Analysis of business processes can reveal opportunities for improvement -- but only if the data underlying those processes is reliable.
2. Better data quality
Despite significant IT investments, maintaining good data quality remains an intractable problem. A study published in 2019 by software and services provider Experian Data Quality found that 95% of organizations feel the impact of poor data quality and that, on average, 29% of all customer data is viewed as "suspect." The effects of data quality issues can be profound, which is why data quality improvement is a key part of the remit of a data governance program. Although there are no magic bullets here, a start is to at least regularly audit and measure your data quality as part of the governance process.
3. Better compliance
In industries like healthcare and finance, there are significant penalties for poor regulatory compliance. For example, pharmaceutical companies spend $20 billion a year on marketing to doctors in the U.S. alone and are required by law to track their expenditures. Failures to comply with regulations have led to multiple billion-dollar settlements with the U.S. Department of Justice since 2009. With these sorts of sums involved, accurate and auditable reporting of data is crucial. GDPR and the California Consumer Privacy Act also add new compliance requirements on the use of personal data about customers in various sectors. Without solid data security and governance, companies could face fines and lawsuits.
4. Better decision-making
If you have a sound base of data, your organization will be able to confidently make better business decisions. You can plan, monitor and act on marketing promotions, price adjustments, product strategy and other aspects of business operations in a more informed way. That all depends, though, on end users having access to accurate data for strategic planning, business intelligence and data analytics applications.
5. Improved business performance
Ultimately, the benefits described above should lead to increased revenue and profits. It really does seem that high-performing companies take data governance more seriously than other organizations do. For example, a 2018 McKinsey report found that "breakaway companies" were twice as likely to say they had a strong data governance strategy. Improving business performance should be the goal of any corporate initiative, and data governance clearly has an important part to play in that.
How to build a data governance strategy
This used to be seen as an IT problem, but there has been an increasing realization that the IT department doesn't have the authority to set and enforce uniform data standards. Business managers need to drive such initiatives; so that they do, a data governance program typically has a steering committee of senior executives and other data owners that makes policy decisions. It should also create a process to resolve arguments over which data classification is the "correct" one, with the authority to make business units change their systems and processes to conform with the designated standard.
The steering committee is supported by a dedicated data governance team that manages the program and by data stewards -- usually, business users throughout the organization who have at least part-time responsibility for overseeing data sets and enforcing the 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 staff and nine part-time data stewards.
Once the governance structure is in place, how do you achieve your goals and get the benefits that an effective data governance strategy provides? The participating companies in The Information Difference benchmark database take a detailed survey. Statistical analysis shows that the companies that reckon themselves most successful at data governance have significantly different behaviors than those that rate themselves less successful.
In particular, successful data governance programs include the following:
- a clear process for resolving disputes;
- detailed documentation of business processes;
- regular data quality audits;
- a risk register that lists data-related business risks;
- data models for key business data domains; and
- policies to limit access to critical and sensitive data.
These programs also have a mission statement, a business case, training on data governance, and a process for communicating progress and results. The various steps outlined here show you the path to success for your data governance program.