Harmonising data can help firms extract value, but success pivots on issues including the identification of business needs, effective data governance and a focus on data quality.
The potential of a harmonised approach to building a strong data management foundation and reporting capability was discussed at A-Team Group’s recent Data Management Summit during a panel moderated by A-Team editor Sarah Underwood and joined by Sue Baldwin, vendor management expert and independent consultant; Chris Johnson, senior product manager, market data at HSBC Securities Services; and Sanjay Vatsa, head of Americas at AIM Software.
Baldwin set the scene saying: “A lot of firms are now taking data seriously. There is definitely more awareness and data is at boardroom level.” The growing importance of data management, and data managers, means increasing scrutiny of the cost and value of corporate data. Johnson commented: “Buying market data can be expensive. It’s a necessity, but also a drag on the business, because per se it’s not making money. The challenge is to get as much value as possible internally.”
Baldwin suggested centralising and harmonising data at enterprise level is a way to achieve this. She said: “Centralisation makes it clearer how data is used, where it sits and how it is shared. It is not the only answer, but it helps.” Making centralisation happen, however, is not easy. Different departments have different uses and terms for data. To harmonise this, there needs to be discussion across departments, an overall understanding of business needs and governance and control of the data.
Vatsa questioned whether central harmonisation is the best way to meet data management challenges. He said: “Centralisation is not a silver bullet. You have to look at what you are doing with the data. A business application approach can give you the same benefits as centralisation.”
He characterised this approach as taking a practical, almost ‘assembly line’ view of data production and use, saying: “Focus on what outputs you are interested in for your clients and rationalise data spend. You need to look at data as part of an assembly line. Check data quality and compliance, and make sure people are using it for what it’s supposed to be used for. The data output has to be reliable, consistent, efficient and flexible to handle different client requirements.”
The panel agreed that a practical focus on extracting value from data is key, whether or not centralisation is the ultimate goal. Johnson said data harmonisation and establishing golden sources are an important part of getting value. New regulations and market direction – such as the commoditisation of derivatives – are also supporting the move to centralised data, he added.
Baldwin agreed, concluding: “Good quality control is important, knowing what all the data elements are, having a good data dictionary. Can harmonisation help you build a strong data foundation? Having data quality ensures standardised data, and that can provide a good foundation.”
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