At RIMES’ recent Chicago forum, members of the buy-side community representing large asset managers and custodians discussed their current data challenges. Stringent regulations, diverse user demands and common assumptions are all putting pressure on their efforts to use data in an efficient, productive manner.
In the current environment, Gartner, the world’s leading information technology research and advisory company, has developed its own approach, questioning the basic assumptions that underlie existing data management best practices. To help the firm present this unique view to a wide audience, RIMES has hosted several round tables across the world.
Mary Knox, Gartner’s director of research with a focus on Banking and Investment Services, helped clarify this outlook at the recent event in Chicago through the use of an interactive presentation.
Data best practices
Knox started out by delving into the myriad data challenges that employees face. She emphasized that many best practices are based around assumptions that are outdated, such as:
- More data is always better
- Data is a finite resource
- We can control our data
- There is one golden truth
- Users understand data
Knox went on to outline the various challenges that make best practices based on these assumptions ineffective. She placed these difficulties into three sets, which include:
- About data: These involve a need for increasing volume, velocity, detail and speed of data.
- Inhibitors: This includes factors that both inhibit – and provide demand for – information. Regulation and compliance are both examples. Cost of data and data management also serve as inhibitors, as do security and privacy requirements.
- Opportunities: Data is becoming increasingly complex, and at the same time, more people are using it. There is an expanding array of cases.
One natural outcome of situations like this is different user groups having distinct requirements. For example, marketing staff may not need high quality data. However, employees working in compliance will likely require very accurate information.
Prioritizing for heterogeneous audiences
Knox spoke to these difficulties, emphasizing that when facing myriad challenges, companies must prioritize and determine what data is really important to their business. After identifying this key information, they should investigate how it is being used.
If multiple users are looking at the same data set, institutions should ensure that every department using the information receives it in a fit-for-purpose form.
Knox took a minute to cull the input of participants, asking if they are struggling with these same data challenges.
One attendee, an investment performance analyst for an Investment Advisor, maintained he was indeed having a hard time with these specific roadblocks.
“We struggle with it every day,” he stated. “Being in a performance department, you aren’t back office, you aren’t front office, [and] you are touching all parts of the organization. Your investment personnel want data that is actionable and ex-ante, whereas your marketing people are looking for … the stuff they can fill out an RFP with.”
“You really have so many different end users, so you are trying to make them all happy, but you are also trying to make your job as efficient as possible,” the participant added.
Meeting complex needs
When all the different approaches are considered, it inevitably leads to the conclusion that more hybrid approaches need to be taken to data architecture, Knox stated. She said that companies must figure out which data should be centralized, along with the information that should be spread out.
Working with these models can result in having varying levels of consistency at a firm, Knox maintained. In addition, buy-side firms can centralize data, and that information could still have the characteristics of decentralized data.
As more organizations prepare for hybrid environments, some financial institutions are considering opening up their bank systems in pursuit of a hybrid architecture to facilitate access and use. The desired outcome of these efforts is enabling external programs to work with and access the data of internal systems.
These initiatives are producing many challenges, and Knox highlighted difficulties in industry-wide communication. She said that industry messaging standards are getting some use, but in certain cases, they are being implemented in a nonstandard fashion. Many are realizing that common messaging formats are insufficient, and that semantics need more work.
Data management vs. data governance
The presentation emphasized that while data governance and data management are different, both are essential for hybrid architectures to succeed. One particular slide from Gartner noted that while the former puts the needed policies and principles in place, the latter is crucial for everyday operations.
In addition, the forum noted that data governance advocates must attain the buy-in of senior executives to achieve successful implementation. While this much is crucial, buy-side staff who want these initiatives to be effective must also get mid-level managers, as well as the rank and file, on board.
Aside from the need to overcome this hurdle, data governance advocates face many other challenges. One participant talked about prioritization, noting that doing so effectively can be quite difficult, since it involves taking many different factors – including business initiatives and pain points – into account.
The individual suggested that in addition to thinking about these fundamental matters, buy-side staff determine what they are doing well right now, and also what has been commoditized.
Another attendee stated that while his institution recognizes the importance of data governance, it takes time and effort to continuously improve a company’s framework. He reported that his institution is in the formative stages, assessing its pain points and figuring out a plan.
Before crafting their own set of information policies and procedures, data governance advocates should reconsider the assumptions they are using. Looking into hybrid architectures could also be of benefit. If buy-side firms want to expedite these efforts, they can speak with RIMES about developing sound data governance strategies.
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