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Forum Summaries

The RIMES 2016 Client Forums – Toronto, Chicago and Boston

In the last quarter of 2016, RIMES conducted Client Forums in Toronto, Chicago and Boston, focused on the concept of data management maturity and its supporting policies and practices, as implemented within buy-side financial services organizations.  Forrester Consulting, a research-based consulting firm, adapted their existing data management maturity framework – called Systems of Insight – to the particular needs of the buy-side, and also expanded upon the results of the RIMES 2016 Buy-Side Survey. A guided survey of 100 data management/operations professionals and data business users was conducted by Forrester on RIMES’ behalf.

Forrester’s research indicated that firms strive to excel at both data execution and data strategy, but the majority end up being effective in only one or the other.  Only 10% manage to achieve excellence in both. Unsurprisingly, organizational and technological challenges were identified as the most common hurdles to data management expertise.

This matches the findings of the RIMES 2016 Buy-Side Survey, which revealed that more firms are now prioritizing and focusing on good data governance.  Yet, in spite of this focus, almost two-thirds of buy-side organizations admit that data governance remains a work in progress, with only 14% believing their data governance to be mature and 23% stating their data governance is merely emergent.

The forums were conducted by a member of RIMES’ Product Management Group, who presented the findings of the Forrester research and Forrester’s recommendations on improving data management maturity.  At the end of each presentation, RIMES asked several questions to help set the framework for attendees to discuss their experiences with the concepts of data management maturity and data governance within their organizations.

Data Execution vs. Data Strategy: The Forrester Findings

 

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All buy-side organizations face a set of recurring and ad hoc data tasks and projects that may consume the time and resources needed to design and implement longer-term data governance practices.  Yet, in an environment of market uncertainty, complex investment strategies and data requirements, increasing competition and regulatory demands, good data governance policies and practices are acknowledged as critical to long-term business success.

From its research, Forrester found that 40% of organizations are focused on moving data from target to source and responding to data requests in an ad hoc manner.  However, they struggle in the broader business-oriented practices of data measurement and assessment.  These organizations were termed Data Tacticians and they were relatively weak in both data execution and data strategy.

Twenty-four percent of organizations excelled at data delivery and were very good at meeting SLAs for accuracy and timeliness.  However, they were not aligned with business outcomes.  These organizations were termed Data Managers and they were relatively strong in data execution, but weak in data strategy.

Twenty-six percent of organizations linked their data to specific business objectives and were strong in data measurement and governance.  But, they struggled with more practical aspects of data execution.  These organizations were termed Data Strategists and they were relatively weak in data execution, but strong in data strategy.

Finally, 10% were able to combine superior business focus with process management to support decision-making and governance at scale.  While they never stopped trying to improve, they were relatively strong in both data execution and strategy.  These organizations were termed Data Experts.

The Broader Discussion

When asked, “How would you describe the level of maturity for data governance in your organization –Mature, Work in Progress, Emergent or Non-existent?”, only 1 attendee at each forum felt their organization’s data governance policies and procedures were mature.  But, they understood the constant effort and challenges to achieve and maintain that level.

“We come up just short of mature {…}.  But, we have a change control process for data, where we reconcile and reload it every month.   We’ve made an active business decision to make sure the data is right every month.”

As with the outcome of the RIMES Buy-Side Survey, the majority of forum attendees felt their organizations’ data governance efforts were a ‘work in progress’.

“We had a mature data governance process, but the organization “outgrew” the effectiveness of the process that was in place.  Now, we’re trying to re-build to a point where we have global, secure, multi-level data governance in place around it.  Those are some of the challenges we’re working through.”

A handful of attendees admitted they felt their organizations’ data governance efforts were emergent.  Almost no one volunteered that their organization’s efforts were non-existent, but one attendee was open about their firm having no Data Governance Officer, and no immediate or future plans to appoint one.

It appears the road to data management maturity is a long and winding one, with most firms being at some point along the way.

To find out what might be driving buy-side data management practices, the attendees were asked, “What are your primary goals when it comes to improving data management, and why?” Data quality was, unsurprisingly at the forefront…

“Just one sentence {…} is ’data quality’.  I can stand behind the data that the business is publishing.  I have enough confidence in it.  If the business is publishing something and they’re not confident, then when it goes to 5 different places and we have to verify last-minute stuff, that’s not when we have done our job.  When we publish and we certify with 100% guarantee, then, yes, it is certified and you can go ahead and use it.  That’s my biggest goal – the business has to be comfortable {…}.”

This led to a discussion about the definition of ‘data quality’…

“To have more accurate data.”

“I definitely think data quality and timeliness – that’s the first step.  If we don’t have that, our customers aren’t going to be coming back.  We have to do that before we can do anything.  But, then we still need to work in terms of other things, like process performance.  We’re looking at those things internally.   But, without those in the first chunk there wouldn’t be the need for the rest of it.”

In addition to data quality, data governance, efficiency and cost control were also highlighted…

“It’s always a battle between the front office vs. the back office {…}.  I believe most investment firms see the front desk as the most important thing because they’re the revenue generator.  So, their opinions definitely dominate a lot of things.  So, I see a trend that data governance becomes more important, especially after, say, a financial crisis, because of regulation requirements {..}.”

 “Efficiency and control are goals.  They can be used to manage costs.”

One attendee said their firm went from a data team of zero to one of almost “infinite budget” (~ 5 to 10 people).  A complete lack of proper data management was holding back their business.  They couldn’t move forward.  They had a realization they needed to manage it (the data) better.

Attendees were then asked, “What are your biggest challenges regarding data management, and in which of these 3 areas – Technology and architecture-related, Operations management-related or Organizational alignment-related?” This question led to a diverse set of responses…

“Data across an organization is different, and used differently by different departments.”

One attendee mentioned that they had a hard time tracking securities throughout the different systems and environments at their firm, due to the fact that they use different identifiers for a single security.

“Our company has had a steady diet of acquisitions.  So, we are very focused on integration and consolidation, and it’s simply that every time we get past one hurdle, there’s another one.  That has a big impact on different areas of our organization.”

“We’re a subsidiary of a large bank, so our IT is essentially their IT.   They have tried to automate a lot of our reporting, but it all relies on the underlying data.  Whenever there’s an issue {…} our follow-up is we have to open a ticket with their IT and they’re not close enough to the business.  So, every time we have an issue we almost have to start at the beginning and explain to them what the procedure is that we’re trying to get them to troubleshoot and what the desired outcome is.”

 “Legacy IT systems.  Perhaps complete ignorance of the importance of data management.”

Or, perhaps an inability to focus on the big-picture strategy of data management when daily data delivery requirements are enough to keep you busy all day?

“When you look, they’re hiring another FTE.  How do you measure the costs of not having good data management?”

“Biggest challenge – it’s not just ‘press a button and the data is there’.  The expectations are higher than the reality.”

“People and technology are the biggest challenges.”

“Localized departments have to give up control.”

“Building trust with various user groups.”

Organization and technology challenges appear to be common themes across all firms.  The resources, funding and general effort required to address those may make effective data management a desirable, but ever-distant, goal for many firms.

Finally, the attendees were asked where they would place their organization on the data management maturity grid – Data Expert, Data Strategist, Data Manager or Data Tactician – and why.

At all 3 forums, the first attendee to volunteer a response to this question took a few moments to do so.  Only 1 attendee said their firm was a Data Manager.  A few others seemed to agree.

“Trying to establish a data team responsible for the both governance and execution.”

“The hardest thing is the data folks being the last line before it goes out to the users.  The last person who touched or sent the data typically gets the blame for any issues.  It’s not always justified.”

“I see it more like I’m a representative of the team {..} within data management, and if I look at it on my team, I could place people into all those four buckets.  And, that’s how we kind of define the roles {…}.  And you need all four of them and it’s not like one of them is more important than another.  Those are all four key roles in order to have a sensible data management team.  From a team perspective, you want people with all these skills.  That’s how I look at it.”

This attendee had an interesting perspective on the team approach that played on the outcome of the Forrester study itself.  Respondents were asked questions that described their organizations – not their skills and success at data management as individuals.  While one person (i.e. a department head or C-level officer) can be responsible for a firm’s data management maturity, no single person can be tasked with doing both the tactical and strategic tasks that successful data management maturity requires.  A team, with individuals who handle each aspect of data execution and data strategy, is more likely to be successful in the aggregate.

Summary

The Forrester research indicated that:

  • There is evidence that firms with good data management practices are effectively leveraging them to support key business objectives
  • Many are struggling with technology and data deficiencies, in one or more areas
  • Enhancing their measurement capabilities can help buy-side firms toward their goal of data management maturity because data measurement and analytics support key business objectives. This is both a goal and an indicator of data management maturity
  • While the path to data management maturity may seem clear, actual implementation may be challenging. A one-size solution does not fit all

The forum discussions supported these findings by Forrester.

 

RIMES would like to thank all our forum attendees.  Their willingness to give their valuable time and feedback to our research efforts is a big part of what makes RIMES the market leader in managed data services.

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