In an era of increasing demand for transparency, there’s a lot of talk about data governance. Despite the lack of a universal definition, most commentators agree that internally generated data is a crucial business asset that must be properly accounted for, managed and stored.

But many organisations also rely on data from external sources and governing that is a challenge that’s easy to underestimate. Lessons can be learned from the work of service providers within the investment management industry. A new handbook points the way towards systematised data governance.

Successful business decision-making requires the right data, of the right quality, at the right time. All organisations must be confident that their crucial data is accurate, timely and secure. Good data processing ensures that data is collected, validated, stored and distributed effectively. And good data governance ensures that the correct data is being sourced to meet business objectives.

Most data that is acquired from external sources is in effect rented, in a similar way to iTunes songs and Kindle books are. Use must therefore remain within the terms of the appropriate license agreement. Almost all organisations are highly competent at data processing but many struggle with data governance. Why?

Governance of internal data is fairly straightforward. The data is owned, easy to understand, and simple to control. But many organisations acquire crucial data from external sources. Such data is often complex, provided under strict license terms and combined with internal data, processes and systems.

Data governance is a far bigger challenge when data originates from disparate external sources and has multiple uses and destinations. The cost of getting it wrong can also be high and may extend far beyond financial and operational risk: a brand or business reputation may also be at stake.

Data, The Lifeblood Of Financial Services

The financial services industry consumes vast quantities of data from many diverse sources: publishing financial data is a major industry in itself, estimated to be worth $22.68 billion. Many financial institutions and investment management firms have built up a good understanding of internal data from a data governance perspective because they own and control the data.

Governing external data is less advanced but the gap is slowly being bridged. A new Data Governance Handbook for the investment buy-side offers practical leadership and guidance for those wishing to improve data governance or gain a deeper understanding of the key issues. The handbook is the result of extensive research and consultation within the global investment management community.

The publication of the handbook reflects the growing importance of transparency and the challenge of governing external data. Investment management firms need to improve their data governance because:

  • Commercial pressures demand cost reductions and increased efficiency
  • Compliance with data owners’ licensing terms has become harder as data complexity increases and volumes grow
  • External regulations require increased disclosure of data provenance and use.

Research suggests that many investment management firms do not have proper control of their data or the processes for managing data. The effective management of data has become a major operational challenge for investment managers worldwide. The research focused on index data and benchmarks, which are growing in volume, increasing in complexity and are inherently difficult to manage.

Independent research also suggests that, while most investment management firms have implemented strong data processing they are less efficient at controlling data use, particularly when data originates from multiple sources. In practice, firms need to understand where data has come from, how it has been processed, what it has been used for, and who received the results.

The Need For Control

The Data Governance Handbook considers the case of index and benchmark data but the principles may be extended to the governance of other data types. The handbook suggests that a more useful understanding of data governance can be achieved by breaking it down into its five interdependent elements:

  • Procurement – controlling data purchase
  • Management information – monitoring and reporting data use to support effective decision making
  • Usage management – controlling data use
  • Decommissioning – ensuring data is not used if it no longer required
  • Compliance management – ensuring data use is in line with guidelines and restrictions.

Dividing data governance into constituent parts allows firms to build an enterprise- wide view of data management without disrupting day-to-day operations.

Three Stages Of Best Practice

The handbook offers a path to improved data governance in three practical stages: taking stock, getting control, and moving forward. Each of the stages has to be applied to all of the above elements, and the three stages must be followed in series. The approach is fundamentally prescriptive, but stresses the need for flexibility to accommodate evolving business needs.

A key requirement is that all data should have an ownership structure. Although seemingly obvious, this is a widespread challenge. Many firms find it difficult for business owners to accept data ownership responsibilities and in practice data ownership can be fragmented. The handbook outlines a structured approach to data management with unambiguous ownership at every stage of the data lifecycle.

There is general agreement that the investment management industry has some way to go on the journey towards best practice data management. But it is ahead of most other sectors, because it is heavily regulated. The publication of the handbook marks an important milestone on the road to industry best practice. For the first time, the investment management industry has a practical guide that addresses the external data challenge.