Buyside challenges : Technology infrastructure : Data strategy

DERIVING VALUE FROM THE DATA.

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Anna Pajor, Lead Consultant, Capital Market Intelligence at GreySpark Partners.

Capital markets data is produced by, analysed by and consumed by many different types of industry professionals. This data is so universal that everyone from data entry clerks to senior executives interacts with it on a daily basis. As such, it is important for all types of buyside firms to utilise strategic data management practices, which can help them better understand their client base as well as opportunities in the market to serve that client base. However, implementing the technology needed to support such a data strategy is a complex task. The complexity is twofold – several technologies are introduced at the same time, which then creates a need to drive cultural alignment within the firm toward the solutions.

GreySpark Partners’ experience advising capital market participants of all sizes means that we frequently witness situations within capital markets firms wherein the word ‘data’ is being discussed only in the context of problems that the company is experiencing. Low-quality data warehoused by a firm often requires recurring data cleansing projects, and reports-centric thinking frequently results in an overflow of useless, spreadsheetbased reports as business-critical issues are being overlooked. In those situations, the IT department is typically blamed for mismanaging the firm’s data.

The long-standing pain related to data management prevents many capital markets firms from seeing the data as an asset. For numerous firms, the value of data is hidden, especially if they are relying only on pre-set reports or spreadsheets as a source of conveying the data the firm accumulates as actionable information (see Figure 1). The firms that are aware of the existence of best practices for data management as well as the technology solutions that can aid in the implementation of data strategy are heading for a new a stage in their development as a company wherein data management is straightforward and knowledge about the business environment the firm operates in is built up based on the data accumulated over time.

The data wave is coming

Even if a capital markets firm is not seeking a competitive edge through enhanced utilisation of the data at its disposal, concerns about data management will inevitably emerge in the future. Clients are now demanding more sophisticated analysis and proofs of the performance of their investments, and firms must be able to automate these reports to avoid drowning their clients and themselves under spreadsheet reports. The rise of risk-on/risk-off behaviour means that clients are price sensitive and less loyal in their willingness to set and forget where they park their investments for the long-term. Instead, they require fact-based proof of above-average performance by their investment managers.

Additionally, capital markets regulations and the resulting raft of new compliance rules are incentivising investment houses to streamline their data management practices to fulfil reporting requirements.

Also, increases in the volume of diverse types of data that firms now must process is another reason why it is important for organisations of all sizes to build and implement a cohesive data strategy. The general electronification of capital markets activity is a driving force in the industry, which means that human relationships are increasingly substituted by electronic interactions. At the same time, the volume of data created by new levels of automated trading activity with brokers, clients and markets is growing. Generally speaking, these new volumes of data are a function of the current information age and, in the case of financial services, the need for their efficient management is exacerbated by demand for data required by regulators and other types of market entities. This data deluge will not abate, and it is critically important that all organisations have a strategic response in place now to respond to these pressures.

Navigating the storm

The concept of treating data as an asset should be the central pillar of a successful data strategy for any type of capital markets organisation. Treating data this way means that all of the firm’s other strategic objectives become corollaries of this idea. The principal deduction from the idea of treating data as an asset is that the data must then be used to drive business benefit, whether it is in the form of increasing revenues, reducing costs or increasing market share.

In exploring the implications of managing data as an asset, five strategic objectives emerge that, in concert, support the end goal of using data to deliver real business benefits. These strategic objectives are shown in Figure 2.

No wetware

Avoiding automation and relying on human intervention – the wetware solutions – in standardised processes are the biggest flaws in any firm’s data management practices. Using wetware means that process management becomes management-by-exception; the processes become more convoluted as exception handling, reconciliation and data cleanup or de-duping bolt-ons are added. This is a vicious circle as more human intervention is added in an attempt to maintain high quality of the data.

Wetware solutions should be avoided at all costs, including using low-cost offshore centres that may appear cheaper than a software solution. Wetware data management is a false economy because the true costs of doing so, including opportunity costs, are never correctly estimated. The long-term result of fixing data problems by using an army of cheap human resources is a reduction in the value of the data that will ultimately affect the firm’s bottom line in a negative manner.

Swim or sink

For many organisations, justifying investment in new technology is not a straightforward task because the main benefits from the effort that the task demands are intangible or are expressed as opportunities rather than as immediately profitable business benefits. Instead, the benefits of the new technology are observed over several years and, in cases of visualisation tools and ‘Big Data’ – as with any disruptive technology – the benefits cannot be fully appreciated while the technology is still maturing.

The justifications for the investment are shown in Figure 3 and are only a starting point for a broader discussion with potential technology implementation project sponsors. An in-depth investigation for other, organisationspecific opportunities that the implementation project could yield is needed, not only to create stronger justification for the spending, but also to understand what business benefits and opportunities would be enabled by the investment.

The new land of data-led superiority

A successful data strategy relies on a set of different technologies. All the elements illustrated in Figure 4 are necessary to support an effective capital markets data strategy, although specific technology choices must be made according to a firm’s unique requirements. The full value of this model is realised only when the pervasive application of the relevant technology services is made available at every tier in the architectural model. A mature data organisation is supported by a complete architectural vision of data-related services that transcends business siloes and unlocks maximum utility from the data throughout the organisation.

GreySpark Partners produced a series of reports to guide financial institutions through a transformation from a state wherein data is treated as a regulatory burden or technology overhead to a state wherein data management is considered central to generating bottom line results. Those reports are available at: research.greyspark.com. Additional contributors: Bradley Wood, Bruce Craven, Jonathan Parsons.

www.greyspark.com

 

© BestExecution 2014

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