New, Improved Data Management Technology for Asset Managers – Now Available to All Firms!
I am of an age that grew up in an era when not everyone in the street, including ourselves, had a telephone or a television, yet we would not consider ourselves especially hard up. More recently, many of us remember a time when it was only the brash City types carrying their brick like mobile phones who could conduct conversations out in the open street. There are numerous examples of technology adoption filtering its way down from the wealthy early adopters to the mass consumers. It’s only a matter of time!
I mention this only because it seems that in many ways data management technology and practices seem to have followed a similar path. Not too long ago the world of data management projects seemed to encompass only the very largest asset management firms, some of which had the budgets and resources to implement enterprise data management tools to enable aspects of data validation, data mastering and operational data storage. And the mid-tier managers looked on as data management project teams seemed to get bigger, projects lasted longer and large scale re architecture got under way. And even when the initial phase and deliverables were complete there still seemed to be a small army of contractors and IT staff involved in maintaining and evolving the data management environment. No wonder data management projects were not high on the agenda for many mid-tier firms – it was just too expensive.
And then someone suggested that firms should also adopt data governance to give higher levels of control, understanding, quality and better visibility over data. By now firms were becoming wise to the costs of data management projects and again the business benefits seemed to be lagging somewhat.
So, bringing us right up to the present day, is there evidence that implementing data management technology is easier and cheaper and, more to the point, yielding noticeable business benefits, within the range of mid-tier and smaller investment management firms?
Certainly, the need for better data management practices is clear for all sizes of firms. The recognition that data as an asset is a key component of this. Also, commercial, reputational and regulatory pressures are higher than ever and firms must be seen to be in control of their data. Clients can see when a firm is not on top of the data and will switch managers if they think that this lack of control presents a higher level of risk to them.
So, the key questions for a mid-tier firm looking at data management solutions might be:
Can we introduce data management technology that will make an immediate positive impact on our operational processes whether that be implementing an EDM, applying MDM processes or simply guaranteeing better data quality across our key datasets and processes?
Does that technology allow those data processes to be configured and maintained from within the business and operational roles rather than having a heavy reliance on IT resources and specialist skills?
Can I achieve ‘practical’ data governance and have visibility over how data moves through my organisation, who owns that data and what data quality controls we maintain?
With the latest data management solutions, the answer is categorically yes to all three and note the overriding question contained in all three – can I see an immediate benefit of implementing this technology?
The more modern data management solutions have been developed with a bigger focus on what the consumer, in this case the firm’s Operations groups, really needs. These are the teams who will get the most benefit from data management technology and their requirements are growing all the time.
So how has this been achieved?
Traditional data management technology within the financial services sector has, until recently, been focussed around ETL/data hub type tools which involve a reassessment of the firm’s technical data architecture, and the way data is captured, processed and distributed. While this approach is perfectly valid it instantly puts data management solutions firmly in the technical infrastructure category and somewhat divorced from the real business needs. For many mid-tier firms, their data infrastructure is not particularly a problem area. The real challenge is giving the data analysts the tools and visibility over their data sets regardless of the underlying technical architecture. This is where meta data modelling comes into its own. With the advent of more modern toolsets, firms can now enjoy data management applications that are solely focussed on developing best practices over how data is processed, mastered, governed and checked for data quality – in other words business applications, owned and maintained by the Data Management and Operations teams and configured in isolation from the underlying architecture.
Secondly, modern tools have removed a lot of the complexity of configuring data management processes. The ability to set up matching, mastering and data quality rules without any coding or technical configuration is readily available – no requirement for specialist technical skill sets, no need for rigid data models and therefore implementation that is achievable at a fraction of the cost in terms of skills and resources of traditional ETL tools.
Thirdly, the introduction of user friendly applications for Operations users is a key deliverable to making data management accessible and beneficial to the business. It is only when Operations users can have direct control and visibility over their data processes that the organisation will reap the benefits of good data management practices. Users should have dashboards and visibility over all data flow. They should have workflow tools to manage data issues, Business Intelligence tools to provide graphical analysis over data sets and processes, and above all visibility and transparency over every aspect of the data journey including its governance.
Data management technology for asset management companies has moved along way in the last few years and can now be enjoyed by all tiers regardless of their size, wealth or complexity. It’s a good time to be in data management.
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