Data Management Challenges: A Vendor Review
Interest and debate concerning Data Management continues and shows no sign of abatement. Following a year of turmoil during which many in our industry have been forced to re-examine priorities and budgets, we took the opportunity to pose a short series of questions to some of the leading data management vendors to assess their views on the state of the market and their thoughts on the immediate future.
Our thanks go to Cadis, SmartCo, GoldenSource, Asset Control and Eagle for participating. The questions and their responses are as follows:
ISC: 2009 was a difficult year for the financial services industry, how has it affected your organisation?
Cadis: 2009 was a strong year for us with six new client wins. To support our growing customer base, we have expanded globally with several senior hires and office openings in Hong Kong, Luxembourg and Sydney.
This comes from our absolute focus on helping clients achieve measurable ROI in under six months. The ability to complete proof of concepts in as little as three weeks, along with our 100% successful implementation record, demonstrates that we can solve their data management challenges.
SmartCo: 2009 has indeed been a very difficult year across all of the financial industry.
SmartCo managed to get positive results, add clients and generate profits, but we had to adjust our growth plans.
Since 2008 Q2, we have seen a decrease in the number of “mature” data management projects launched by financial market institutions. We have also noted that many projects that had already started have been postponed between 6 & 12 months, in a few cases projects have been cancelled altogether.
GoldenSource: The challenges in the marketplace have accelerated a lot of our product, price and delivery plans. Our sales focus has shifted a bit quicker to the Far-East than planned, and we moved forward with a more flexible and componentised product and pricing policy. Although painting the E (enterprise) in EDM as the big obstacle is a caricature – it is true that our solutions strategy of pre- configuring smaller pieces of the data puzzle has been successful.
In general – the market has been challenging and highly competitive, but it is testament to the underlying strength of the data management market that we (and many of our competitors) have continued to sell.
Asset Control: While 2009 was a very difficult year in the industry overall, the underlying causes of the events created a renewed focus on the criticality of underlying data and valuations to an organization’s ability to properly assess its risks and conduct its business affairs. As a result, we saw an increased level of serious inquiries and opportunities to pro- vide data management software and services to the financial services community.
Eagle: While 2009 was difficult for the industry overall, for our data management clients and prospects the circum- stances clarified the need to prioritize managing risk and complying with regulations. As a result, Eagle experienced a lot of activity around implementing new or bolstering existing data management systems. Eagle’s data management solution is designed to allow clients to drill deep into portfolios and provide a timely and complete assessment of exposures to issuers, industries, currencies and other crucial factors. Given these capabilities, we have received a lot of positive attention from clients and prospects around the world.
In 2009, Eagle expanded into the APAC and EMEA regions, mainly through needs for data management. Asia was one of the areas where business grew the most, and as a result we opened an office in Singapore to meet demand.
ISC: What do you regard as the primary issues facing your clients in 2010?
Eagle: Clients must be able to do more with less, whether it is people or systems addressing the need. Value for the dollar is paramount. Many clients came to us asking for more ways to leverage their Eagle systems and we were pleased to discuss ways we could alleviate business pressures. We counsel our prospective data management clients to consider technologies that can solve immediate business needs and accommodate the longer term enterprise data management vision of their organization There is a lot of focus on partnering with a vendor that has sustainability in this current landscape of firms shutting down, merging and being acquired. Much more due diligence is happening now with vendors’ financials and 5-year goals being scrutinized. Current prospects are more open to partnering with an experienced vendor with proven methods that help them to define and achieve their data management strategy over the long term.
Cadis: The increased regulatory environment will lead to greater demands for quality data and there will be a continued focus on staying in line with budgets and increasing ROI.
SmartCo: Within our core do- main of data management most financial institutions have set aggressive objectives focused on efficiency, auditing and flexibility.
New regulations are being constantly announced and many institutions are not ready to face those new challenges. Flexibility to over- come constraints in terms of pricing and valuation processes or data administration and auditing facilities are being viewed as critical. These constraints cannot be overlooked as regulators, internal clients and external customers are requiring answers. Our clients are trying to analyze and addressed these issues in a timely and accurate way – which is never as easy as it seems.
The recent crisis also highlighted the importance of a having proper operational and risk management policies. These policies highlight the importance of ensuring all data is sourced from the same place, audited, processed and stored in a way that ensures continuity through accurate, timely and accessible data. The impacts in term of organisation and IT systems may be significant for banks not yet prepared.
GoldenSource: The same one as in the past few years – to move forward with a data management strategy that is not short- sighted, but having to do so with limited means. Telescope vision with monocle money if you like…
All of our clients are trying to do more with less. There is increased scrutiny from investors, auditors and regulators – often without enough specific guidance. In order to cope with these challenges, our customers have to assess their responsiveness. At the same time, budgets and staffing remain flat, thus creating opportunities for vendor solutions to address these issues.
ISC: What are your primary areas of focus in product development?
Asset Control: We have been focusing on supporting our clients’ needs for additional capability around exposure analysis and reporting. Also, they are looking to better leverage the strengths of existing infrastructure investments. Our continued emphasis on providing enhanced integration tools will help our customers get more out of their existing investments in data and applications, gain a better understanding of their risks.
Eagle: Product development is focused on supporting our commitment to global expansion with fully multilingual solutions. Another major focus is delivering the very best user experience to accelerate system productivity, lower training and support costs and deliver that return to our clients’ bottom lines.
Cadis: Our primary focus in product development is empowering people who use the data to manage the data. We are further enhancing our dashboard and overall control layer across the top of our software to enable senior managers have a single, customisable view of their entire operations.
SmartCo: Our product plan includes numerous technological and functional enrichments, that can be grouped into two major categories of needs:
Address new needs with new modules. As an example we forecast an increase in the number of business entities data management projects. In most cases the project is trying to achieve better links between securities, issuers, counterparties and risk groups.
In response SmartCo is further enriching our Business Entities module. We also expect Financial Institutions to look for new data quality metrics and processes that can be easily audited when required, and are working closely with them on this effort. Our R&D team is in full creative mode at the moment!
Go international. More and more banks are centralising processes and systems that used to be split across business units and run independently. Activities formerly supported in different entities must now be supported through centralized data management. While costs can be shared the responsibilities must be clearly identified. As you would expect the larger companies have the larger problems as the connectivity and needs can be very diverse and require very specific solutions. We are always working with them to make our solution more flexible, scalable and ready to meet the requirements of these very complex projects.
GoldenSource: Integration of market and reference data, derivatives valuation, golden copy pricing, technical scalability and great usability.
ISC: Does a Data Governance framework at your clients make any difference to how effective your product is for them?
GoldenSource: It is a classic case of “you can’t manage what you can’t measure”, so the biggest benefit to our business case is having a customer who can answer “how will you measure the success of this data project”. With- out a standardised and consensual data governance framework, the answer to that question is too often departmental, operational and ultimately short-sighted.
AssetControl: Absolutely. Our clients all have an appreciation for the role that a solid data governance framework can have in creating operational efficiencies and reducing risk. This has driven investment in Asset Control’s solutions. Without senior management sponsorship surrounding data governance, data management processes and policies may not be executed in an optimal manner.
Eagle: The existence of a Data Governance framework does not impact the effectiveness of Eagle’s Data Management solution, but it does provide the business with immediate and meaningful examples of the value we can provide. If a firm has pushed through the discussions and analysis required to de- fine a Data Governance framework, they are ready and able to understand how Eagle’s solutions can be part of a sustainable technology infrastructure to execute their processes and support their policies. These clients further understand, and require, an appropriate degree of flexibility to address the change that they know is inevitable—change in the industry, change in their business strategy and change in their governance frameworks. Data is the lifeblood of the investment process, but until recently, most areas of the business regarded it as a commodity to be delivered by market vendors and IT systems. The evolution of data governance has turned the tide so that more and more data is regarded as the business asset that can deliver real insight, and thus outperformance, if handled right.
Cadis: Absolutely, we have several data governance structures on our client wiki as examples of how to set up an effective structure. This is for either centralised or de-centralised operating model. There is not a one size fits all model. We work closely with our clients to help them implement a data governance structure if they have not done so themselves.
SmartCo: Absolutely. If you have a clear idea of your objectives, you can define the details of your targeted processes and KPI. Clear processes and KPI allow the Data Management teams to optimise through the use and the customisation of our application, we feel certain we have unrivalled functionality and flexibility!
One of SmartCo’s strengths is our ability, once implemented, to adapt to any new requirement with al- most no delay at very low cost. A Data Governance framework helps the end users and the project team to define efficiently what changes must be done, when and how. Like any project, with good and detailed requirements you get better results!
ISC: One of the most prominent pieces of jargon within Data Management is 'single version of the truth' – how applicable is this for your clients?
Data coming from different sources often have different names, identifiers, etc; the most difficult part of the job is to relate them all together. Once this is done, you can consolidate all the information you have, define the pieces you prefer and generate a “preferred version of the truth”. This will only be one version of the truth among many other possible versions.
Within the daily operations of these firms, it is clear that all IT systems do not speak the same language. Typically each business line has its own historical, legal or commercial constraints. If they can all work from the same “version of the truth”, they have at least put a baseline in place. However, our experience tells that reaching that baseline can often be the most difficult part of the process as old habits are difficult to break. There are cases when it is necessary or advantageous to manage different versions of the truth simultaneously while ensuring they are sourced correctly, coherent together and the downstream integration between systems is correctly done.
GoldenSource: Very applicable – and a lot of the debate about the validity of “single version of the truth” and “golden copy” is false, because they mean different things to different people – it is too easy to make sweeping statements about the logical fallacy of the concept of “single version of the truth”, when the simple operational realities for our customers boil down to a simple home truth – as long as there is no industry wide data-quality insurance scheme, multi source validation is absolutely necessary to protect our customers from the results of poor quality data. The most robust way of doing multi- source validation is what is usually referred to as a golden copy engine.
AssetControl: The “truth” of a data element depends on what that element is and how it is being used by the business. Certain data attributes do have single views of the truth. For example, a coupon rate on a particular bond should not vary. Other attributes, however, do not lend themselves so easily to “single versions of the truth”. Classifications and derived values are only two examples of attributes that defy single definitions of value for legitimate reasons. Our clients understand that sometimes multiple right answers are needed, where the capability and flexibility of the Asset Control solutions can acquire, validate, en- rich and distribute their data as best suits the needs of their business.
Eagle: A “single version of the truth” in the strictest sense is not daily practice at the majority of our clients. If it were, the world of data management would be a much more boring place! There are valid business reasons for different managers, units and downstream systems to need specific sources or transformations. The key elements in delivering these needs are consistency and quality; the ability to ensure that the requirement will be met on schedule with high quality data. To achieve this, data must be vetted and validated at various stages with appropriate rules, automation is a must for coping with volumes and changes cannot re- quire weeks of coding to deliver. The combination of a time-tested data model, highly scalable application architecture and exception- based workflows allow Eagle users to define and use their versions of the truth to execute their daily business strategies.
Cadis: That’s a dated view, due to competing business requirements with regards to time, quality and structure.
It is far more important to understand the data that is being distributed and where it is residing (OMS, Risk, Performance, etc.) as these are the systems which are relevant to specific parts of the business.
Our clients find that the true value of data management is giving the business users (fund managers, traders, risk managers, compliance officers, operations, etc.) the data that they need when they need it, in the right format. They also want to audit who got what.
ISC: How do you counter the criticism that data management solutions are over- priced and due to their complexity, commonly fail to deliver the proposed benefits?
Cadis: By and large it’s a fair comment, data management projects should be based on successful implementation, not never ending consultation. Rapid ROI will create greater traction.
Clients need data management systems that work for them and cater to their individual business needs. We believe that the unachievable goal and focus on a single version of the truth is one of the key reasons for this perception. Cadis has a 100% successful implementation record which sets us apart from such criticism
SmartCo: Our customers have not provided this type of feedback. The internal or external solution selected for answering these data management issues is probably the basis for such criticism.
In most instances, projects that have failed are projects which have not been supported by a Data Governance framework defined at the highest level. EDM projects per definition require collaboration between the data management team and all the different departments and activities of the company. For some of them, EDM just seems to represent a cost and not a gain. If this collaboration is not facilitated and sponsored at the right levels, these projects become a sunk cost rather than a framework for success.
GoldenSource: Data management solutions are not over-priced – they are undervalued – because too many projects are stuck in an ops or IT driven depart- mental ROI dead end. There is un- fortunately no easy or generic way to show the economic benefits of better data quality, because that formula depends on how people answer the question “what do you do with your data?”. Because data is used at every point of the investment cycle (financial and operational) doing a soup-to-nuts risk and reward analysis is seen as too difficult or too big. The only way to overcome this dilemma and short- cut the analysis-paralysis phase, is something called long term vision – which is a notion that has unfortunately become alien in some areas of our industry.
AssetControl: Asset Control’s data management solutions are used by more than 50 financial organizations around the world, including banks, broker- dealers, hedge funds and investment managers, service providers and insurance companies. Therefore we believe that effective data management is achievable for all, as long as the solution offers lower total cost and faster implementation. For example, lower cost of implementation, reduced ongoing maintenance and rapid implementation can be achieved by solutions that offer reduced data acquisition and management costs, more effective use of other tools within the organization, and capabilities that allow for configuration, rather than customization that is heavily reliant on specialized technical staff.
Eagle: The resulting cost of NOT having a data management solution is bound to be higher than the price of implementing one. The list of data management issues is very long, and adds up to a firm’s inability to exe- cute confidently on their business strategy, which translates into big dollars subtracted from the bottom line. Often the most problematic price related to data management is that of projects gone awry be- cause of lack of: initial requirements definition and analysis, proper sponsorship or showing clear deliverables that demonstrate business versus technology value. As stated before, our most successful clients are those that analyzed and defined a data management framework with clear ownership of decisions and sound management of the project. They have also planned for future sys- tem updates that need to take place to address regulation changes or new security types.
ISC: What must companies do to ensure they maximise their return on investment in EDM technology?
Eagle: Organisations that invest the up-front time to properly analyze and define their data management strategy, and that staff the initiative properly, will be in the best position for maximising the return on their technology investment. As they begin to execute on their data management strategy it is imperative to focus on a program of delivering solutions for business problems and not one of “solving data management.” It is critical to partner with a vendor whose solution has stood the test of time and provides real examples of how they solve data management business problems. Good vendor partners will strive to deliver lower total cost of ownership, proven return on investment and scalability for mergers and acquisitions over the long run.
Cadis: Companies must focus on achieving measurable ROI in timeframes of less than a year – this includes things such as legacy system decommissioning, vendor data rationalisation, new business system implementations. There is no point for companies to take on EDM technology that will take years to be up and running.
SmartCo: The project must be understood and appreciated by all the branches of the organisation, including the end consumers (front office, back office...) and the support departments (mainly IT) as well as Senior Management. Everybody must agree on the interest and importance of the project before it starts. A project sponsor must be as- signed and be given all the authorisations and resources he needs internally for running the project correctly.
Accurately defining the objectives before the project starts is imperative. Do not consider only the financial “Return on Investments”, but also all the qualitative aspects of the project: improved quality, better STP, better risk management...We suggest a definition of KPI that can be easily followed up.
Companies should be realistic in the project and avoid the “big bang” approach for a step by step methodology. Difficulties related to change process should not be underestimated.
You are making a choice for 5 or 10 years at a minimum, and your current needs may change a lot in the future. Make sure that the EDM solution chosen offers sufficient flexibility. It should always be a success factor and never become a constraint for the application management or the business.
GoldenSource: Think big, start small, repeat.
AssetControl: Data management projects can provide many opportunities for cost savings. Examples include removing manual control environments, al- lowing for sharing of cleansed data, and reducing unnecessary duplicative sources. A common mistake with any project – not just data management – is to start with too broad of a scope. Firms should create reasonable goals, establish stretch milestones, and maintain open communication. There can always be later project phases after an initial series of successes. In fact, many of our clients’ implementations start with a smaller data management project that becomes a foundation upon which other successful projects can be built.
ISC: Do you think Asset Managers can successfully outsource Data Management?
AssetControl: It is certainly achievable as long as the firms understand the pros and cons of doing so. There is no one right answer that works for every- one and firms need to balance the potential loss of control and flexibility against the cost and structure required to run the operation.
Eagle: Asset managers can successfully outsource by fully understanding their business model and choosing the right outsourcing partner who can provide a spectrum of services that meet their current and projected needs. The key here is recognizing that the definition of successful of data management outsourcing will depend on the business needs and will almost always result in a hybrid approach where some aspects are outsourced and others kept in house or relation between out- source servicer and asset manager. Some asset managers would benefit most from a model that provides off-site management and maintenance of their data management systems and solutions and access for their staff to run the business of their data. While others are best served by a more comprehensive model that includes staffing the business operations. Though even these situations re- quire collaboration between the service provide and asset manager to accommodate the questions and changes that arise from market conditions and corresponding business changes.
Cadis: Yes, asset managers can outsource data management if and only if vendors offering the service are able to pro- vide the business users with the data that they need when they need it.
SmartCo: There is no one universal answer; it really depends on each specific business case and institution. Outsourcing data management processes is not an easy task, especially for the largest groups, but yes we believe most asset managers could do it.
Still, we advise caution: the success of a data management project cannot be measured only from a financial ROI standpoint. Outsourcing is a temptation that also often means less business agility, different processes and new difficulties.
GoldenSource: Yes, parts of data management can be outsourced – not all of it. While most firms think their needs are unique, 80/20 rule does apply, and Asset Managers can outsource discrete functions like pricing as a very pragmatic first step.