How to get your data management strategy right

Nicole Grootveld-Sandig, Chief Operating Officer at MN, explores how to data strategy right including understanding how information is used and building teams with strong data capabilities

Fund Operator POSTED ON 11/16/2020 5:46:06 PM

Fund Operator: What is the basis for an ideal service model? How does this differ across asset managers?

Nicole Grootveld-Sandig: I don’t feel that there is an ideal service model, it really depends on the framework that asset managers need to work in because if it is institutional or retail, they will be entirely different service models.

From an institutional perspective, we see that the reporting that needs to take place to downstream regulators on the portfolios are deepening every year.  Going from high-level portfolio information down to complete look through information.

As there is a need on the one hand to have deep insights into the portfolios and to give more data to different regulators, we are seeing that on the back end at least, you have to be more in control of the data.

"The ideal service model is to have control on the data lineage on your output"

This is different from the front end with the basic input data that you might have less control on.

The ideal service model is to have control on the data lineage on your output, whether it is in your reports, audited statements, or downstream regulator reports.

However, you can be a little more flexible around how you ensure that the quality of your inputs is governed 

Fund Operator: It may not be plausible or necessary for there to be an ideal service model but what are the essential functions that should be retained across the board? How do you decide which data management functions to retain?

It is important that people understand how data is used.

The traditional term might be data stewards, but business owners also take more responsibility for defining data requirements and use cases and testing to ensure the data is high quality.

Also, data architects are important. Especially in relation to the aspects of storage, accessibility, and technical aspects of how data flows to the organisation.

This needs to be understood internally because this is a key success criterion for getting data used properly in the organisation. 

"Data architects are important"

Another example that we are seeing in this sector is services around the gathering, cleansing and preliminary data quality checks, especially on complex data like private equity or infrastructure loans.

It is in these more illiquid asset classes that high quality data is becoming more important. You may want to use data aggregators because it is actually quite expensive or resource intense to really ensure good quality for this asset class.

The specialists for me are more in the aggregation of data that needs to come into the organisation. Everything that I need for data use, lineage, and control I prefer to keep in the organisation.

Fund Operator: Is a strategic in-house data management capability an essential component for firms to react to unfolding events? 

Nicole: It depends on your business model and we have very few institutional clients who we really need to be able to provide strategic advice as a fiduciary manager.

Having a strong data capability is dependent on having people who really understand the investment process, and the context of data quality within this process.

Having the technical expertise to understand how you get the data into analytical tools and how you get the data into presentation tools is important.

"Having a strong data capability is dependent on having people who really understand the investment process"

As an institutional investor, we need to be accountable for our investment advice and decisions. Therefore, reporting is quite complex in terms of accountability.

Everyone has to present portfolio performance and information, such as tracking errors and costs.

However, the complexity in having to present different types of data in the right context back to clients means that you need to not only have people who are very good at analysing data, but also very good at interpreting the message of the analytics that they want to get across to clients and presenting this well.

We are seeing that the presentation of data is becoming more complex and is widespread.

On the one hand, you have huge data dumps to the regulators and then you have drill down, power BI dashboards that need to be built for end users of all kinds.

"The presentation of data is becoming more complex and is widespread."

You need to have more business people or data people who can help the data presentation but this is not always seen as being part of data management capabilities, which is really the core of getting your data to a good state in a cost effective way.

It depends on how you define data management capabilities, and I would say that the quality and knowledge of its use is the core capability.

Around this, you have technical capability and this combination of capabilities that makes it strategic.


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