Outsourcing Investment Management Performance Measurement
The future's bright, the future's outsourcing?
| Date: | July 2004 |
| Author: | Jim Trotter |
| Price: | £500 to non-members of the Investit Intelligence Member service |
Many asset management companies are considering outsourcing performance measurement functions. But, before they do this, they need to understand exactly what role their performance teams play and carefully consider how much value an outsource provider can add, compared to an in-house function. This report is an invaluable decision-making tool.
The role of performance teams has changed considerably over the last 15 years. The detail, frequency and timeliness of performance measurement team deliverables has become more aggressive. Asset managers and their clients now want monthly, weekly and even daily performance information - the average performance team now spends more time on regular production and maintenance tasks than it does on value-adding analytics.
A prime driver to outsource is to handover routine production activity - much of which is regular checking of back office results. In addition, many asset management companies see outsourcing as a way of accessing superior staff and systems. Perhaps surprisingly, cutting cost isn't a major factor. While smaller companies may see some savings, the complexities of larger companies' models means economies of scale are hard to achieve. However, the size and importance of performance measurement functions makes outsourcing a complex task. Asset managers will benefit from guidance.
This report explores all of these issues and offers useful and, importantly, practical guidance on the problems asset management companies face when considering outsourcing performance measurement - and how to address them.
Investit's Intelligence research is based on interviews with 23 asset managers and performance measurement practitioners and 10 outsource providers.
Table of contents
| Management Summary | 3 | |||
| 1.0 | Introduction | 5 | ||
| 1.1 | Report structure | 6 | ||
| 1.2 | Methodology | 7 | ||
| 1.3 | A glossary | 8 | ||
| 2.0 | What are Corporate Data Projects? | 13 | ||
| 2.1 | What do we mean by a corporate data project? | 14 | ||
| 2.2 | The evolution of corporate data | 18 | ||
| 3.0 | Why are Corporate Data Projects Important? | 23 | ||
| 3.1 | Changes in the regulatory environment | 24 | ||
| 3.2 | Client servicing | 24 | ||
| 3.3 | Investment performance | 24 | ||
| 3.4 | New product initiatives | 25 | ||
| 3.5 | Operational efficiency | 25 | ||
| 3.6 | Outsourcing | 26 | ||
| 3.7 | Increased demands for business intelligence | 26 | ||
| 3.8 | IT drivers for change | 26 | ||
| 4.0 | Market experience of Corporate Data Projects | 29 | ||
| 4.1 | Experiences of the investment managers | 30 | ||
| 4.2 | Experiences of the vendors | 37 | ||
| 4.3 | Infrastructure vendors | 43 | ||
| 4.4 | Retail industry experience | 44 | ||
| 4.5 | Alignment between investment managers and vendors | 46 | ||
| 5.0 | Approaches Adopted | 49 | ||
| 5.1 | Project management and governance | 50 | ||
| 5.2 | Responsibilities for data management | 52 | ||
| 5.3 | Approaches to corporate data architectures | 55 | ||
| 6.0 | Key messages | 61 | ||
| 6.1 | The time is right for data projects | 61 | ||
| 6.2 | The benefits are both strategic and specific | 62 | ||
| 6.3 | Key points for consideration | 63 | ||
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