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January 11, 2017 at 06:29 AM
This article was co-written by Richard Jackson and Jake Taylor, managing directors and co-founders of Jackson Analytics.
The 21st century is all about data. That has big implications for investment managers who need to achieve critical mass in order to be profitable and grow their businesses to sustainable levels.
In today’s digital world, your firm’s marketing data — performance record, attribution and analysis information, even your assets under management — is your product. That data is the evidence that proves that you are able to do what you say you do, and that you have been able to do it consistently, on an absolute or relative basis, over time. Both prospective and existing clients, as well as the consultants that vet and monitor managers for them, rely on that evidence to make hiring decisions, increase investment allocations, recommend a firm to others and remain invested for the long term.
No matter how alpha-laden your track record is, no matter how compelling your investment story may be, if investors cannot find your data, your firm might as well be a tree falling in the forest — no one sees it, no one hears about it and no one even knows it is there.
Data is important in every facet of the investment business. It drives the research that analysts produce. Their judgments drive portfolio managers’ decisions to buy, hold and sell. Data is also important for proper regulatory compliance, sound operations and efficient trading. Finally, data, in the form of performance returns and portfolio analysis, drives marketing, sales and, ultimately, revenues. In today’s digital environment, this type of data is not only a manager’s product; it is a resume.
Challenges to Efficient Data Management
Spending too much on the front end
It is easy to understand why data is so important to money managers, but many continue to put too much emphasis on the front end at the expense of the data that potential asset owners really care about: performance. Over the years, we have asked managers where they get the biggest return on their investment. The nearly unanimous response is “security research and analysis.” Consultant Joel Bruckenstein recently quantified this, reporting that between 50% and 90% of the average firm’s tech budget is spent on investment management tasks like research and rebalancing, InvestmentNews reported in October.
The front end is important, but unless a firm invests in packaging that alpha — and all the supporting analytics and portfolio characteristics that go with it — and distributes it in all the places a prospective client might be looking for it, we are back to the tree-falling-in-theforest scenario.
(Related: AI, Machine Learning Not Ready for Financial Firms)
Spending too much on the middle office
According to results from the 2015 InvestmentNews Adviser Technology Study, firms are shifting their IT spend to focus primarily on client-facing technology and productivity enhancements. Devoting significant portions of IT spend to the middle office may be a great move for mature, profitable firms with a critical mass of AUM under their belts, but it is not going to help smaller firms still hoping to grow their business to a sustainable level.
Why Managers Have a Hard Time Managing Data
With so much at stake, why do most managers struggle to manage and effectively distribute their marketing data? Firms are overwhelmed by the volumes of performance, portfolio and analytical data produced over a 90-day period, especially if they manage multiple investment strategies. Reporting that data through client reviews, marketing collateral, pitch books and DDQs/RFPs/RFIs — and distributing it to over 40 consultant databases — in a timely way that assures the data integrity regulators demand is a labor-intensive task. It is no surprise that putting together things like fact sheets and client reports remain the No. 1 marketing pain point for investment managers, according to an October report by Kurtosys, a financial services data management platform.
Experienced eyes are critical
There is one important element of data management that cannot be eliminated: The human element. It takes trained, experienced professionals to verify, organize and interpret the data.
