The RIMES Round table on Data Governance, held in Boston in March 2014, gave industry participants the opportunity to discuss best practices that companies are implementing to ensure that they have the proper data policies and procedures.
Managed data services provider RIMES Technologies Corporation provided the round table at FIMA 2014. It was attended by several large investment managers, custodian banks, and other asset owners.
Participants who took part in the discussion noted that their companies are at many different levels of maturity in terms of creating and implementing proper data governance procedures.
Some financial institutions are more concerned with having a proactive approach to data management than others. This largely depends on what stage the business is in. Recently formed organizations might be more likely to be reactive in terms of managing their data.
Various factors drive data governance initiatives
The round table, which was held twice to accommodate the schedules of participants, addressed the current state of economic conditions, and detailed the various pressures that are motivating companies to enact data governance initiatives.
One major factor is compressed budgets. Buy-side financial institutions, and in particular asset managers, are striving to do more with less. At the same time that they are focusing on reducing their costs, these organizations are making an effort to cope with greater data demands. For example, many portfolio managers have been evaluating their performance with a greater number of benchmarks.
To cope with these pressures, financial institutions need to make more efficient use of their existing resources. These organizations should strive to be selective about the data service providers they work with, and the tools they use, if they want to get the results they are looking for and stay within their budget.
Major firm program manager notes data governance efforts
A program manager of Data Governance for a major global financial institution noted that his organization benefits from a multilayered approach to data governance adherence. He provided more detail, specifying that these procedures have been adopted at both the company-wide level, and also in individual business lines.
“We have data governance in place. We have it basically in pockets, but also at the enterprise level,” the program manager said. “We have policies in place, but we have more things that we are working on, which is why I said that it’s a work in progress.”
“We have stuff that’s at the business level, and stuff that’s at the division level … It’s more than emerging, since we’re actually doing it … As you do it, you realize there’s more work,” he added.
In addition, the senior management of his firm led the charge to implement these crucial policies, and realized the value of doing so.
The person noted that there was widespread acceptance of the need for proper data governance, and that people at all levels of the business bought in to this idea.
“Everyone seems to get it,” he said. “Everyone seems to understand.”
However, even amid all these positive developments, the individual emphasized that this work is never done. He said that as the company encounters new pressures, it must continually change its approach to data governance.
Challenges undermine optimal data governance
In addition, many financial institutions are struggling with cultural challenges that could potentially undermine their data governance initiatives. While some organizations buy in to the importance of having the right policies and procedures for their data, certain companies are not aware that they have data challenges until these problems boil up to the surface.
In order to make the best possible use of their key information, financial institutions need to have staff at all levels sold on the importance of data governance. Unfortunately, many organizations lack this crucial component of success. While senior management may buy in to the need for data governance, operational staff may not share the same sentiment.
Challenges also arise when company use of data is disorganized. For example, many financial institutions have separate departments that harness this vital information and fail to communicate with each other about exactly what they are using.
If an asset manager pays for a wide range of benchmarks, the departments that use them might not articulate which ones they are leveraging and which ones they are not. In addition, a financial institution can easily have benchmarks that none of its staff use.
Companies frequently do not specify who has ownership of important data. Financial institutions frequently have several people who make use of this information. However, it may be the case that nobody is willing to step up and take responsibility for it.
Difficulties can also arise because of the separation of those who manage data and the individuals who are focused on achieving business objectives. As a result of this situation, the people who prioritize the company meeting its goals may not use data in the most efficient way possible. Having a top-down approach, in which any data management procedure must be justified with a strong business case, can make it so that no piece of information is superfluous or unused.
Finally, financial institutions sometimes hold data that has errors. If companies have information that is inaccurate, it could undermine their ability to make informed decisions. Making the wrong moves constitutes reputational risk, as it could undermine a company’s public image.
While companies are facing these various challenges, recent regulatory measures may compel many to establish solid data governance initiatives. In some instances, data vendors may also provide their clients with financial incentive to adopt the proper data governance infrastructure. More specifically, these service providers may conduct audits on their customers and provide an invoice for failing to follow contractual agreements.
Mid-size company rep provides input
A director of performance and attribution for a mid-size organization noted how important benchmarks can be to clients, and also the benefit that is created when key individuals take ownership of data management. He elaborated on how his team has taken over responsibility in this particular area.
“Our director of technology was specifically devoted to any time that a benchmark came in, he was kinda the only guy who could do something … He’s been working to build tools to give my team, the performance and attribution team. We’re the benchmark managers now.”
The company representative emphasized the importance of having a team take responsibility for benchmarks.
“It’s good to have ownership of it in a certain group in a firm … because really, you could say anybody owns it.”
The individual noted that more of his clients have been asking for custom benchmarks that they can leverage to evaluate their performance. For example, he spoke of a benchmark that was primarily composed of the performance of the Treasury Bill and represented other key factors, but to a smaller extent.
The representative noted that his particular group has taken ownership of key data. He said that the company’s director of technology built the system that was used, and knew how it worked. This key player had been working with the representative to provide his team with the ability to develop new benchmarks.
Round table singles out 4 major data governance themes
While many companies are making an effort to move toward obtaining optimal data governance, the round table touched base on some major themes that firms should consider when evaluating their progress.
1. Understanding the stages of maturity
For the first major theme, RIMES identified four stages that companies encounter as they progress toward establishing and maintaining an ideal data governance framework.
- Non-existent – This is for organizations that have not yet prioritized creating the proper data management policies.
- Emergent – Companies that have just started working on developing the proper policies and procedures will likely fall into this category.
- Work in progress – A far greater fraction of businesses are at this point in their progression. To reach this stage, companies will need to invest some time into establishing the proper data governance infrastructure.
- Mature – Very few companies have reached this final level of development. In order to get there, organizations might want to establish the proper data governance policies at many different levels of the business. In addition, financial institutions should engage in continuous improvement initiatives to ensure that staff repeatedly inspect and strengthen these procedures.
2. Major drivers of initiatives
In this section, the round table reviewed the major factors that are driving companies to take part in data governance initiatives. These include:
- Companies are making an effort to reconcile the pressures of rising expenses, benchmark data that is increasingly complex and growing regulatory scrutiny.
- Ensuring that data is as accurate as it is thorough, and relevant. Companies can encounter significant challenges if their information holds errors, or if they do not have all the data they need. Alternatively, information that does not help inform business decisions may be more of a distraction than anything.
- Financial institutions must focus on using data in a way that complies with vendor agreements. Firms that fail to make good on their side of the supplier-client agreement may incur additional costs.
3. Company organization and employee buy-in
How is a financial institution organized to achieve data governance? How does having employee buy-in at all levels of a business affect the success of these initiatives? Best practices suggest having staff members in all these places on-board is critical.
This segment identified three levels that can be the impetus for adopting proper data governance.
- Executive mandate – The senior management of a company can help drive implementation of proper data governance initiatives by providing a top-level mandate. These individuals might form a Data Governance Council to ensure that staff put forth the proper effort.
- Management Direction – The managers of a financial institution also play an instrumental role in the adoption of any data governance framework, and can make crucial contributions to company strategy and oversight by forming a Data Governance Office.
- Operations – People working at this level can be invaluable for creating and implementing the ideal set of policies and procedures since they are at the ground level, and are involved in actually performing the tasks that ensure data is managed effectively.
4. Best practice
This section invited participants to consider several actions they can take to ensure that they have best practices in place.
Gathering data can be a time-intensive task, which is why companies should have clearly defined goals before they begin the process.
Decommissioning benchmarks when they are no longer needed is another best practice, and financial institutions might benefit from developing a specific process to ensure that this is achieved.
Equally, it’s important for companies using data to remain compliant with the terms of their vendor contracts. Organizations might benefit from developing and implementing procedures to ensure that this goal is met.
Buy-side financial institutions looking to establish an optimal data governance structure might benefit from considering the major points that were covered in this round table, and the suggestions on how a managed service provider could help achieve best practices in data management.