Data Management

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Scott Gillespie, Quadron Data Solutions
Scott Gillespie, Quadron Data Solutions
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Who’s Afraid of Big Data?

What big data can do for financial organizations and how to prepare for it.

Scott Gillespie, Quadron Data Solutions
Scott Gillespie, Quadron Data Solutions

Big data promises a new kind of knowledge and understanding for broker-dealers that will overhaul firm productivity. We all know the theories of what we can do with big data and how it relates to product management, easier customer engagement, and improved information access. With these tools, questions about which clients have the highest returns per effort and time expended, or about how to best organize an advisor’s time, can now be answered. Even so, the implementation of big data strategies has stalled on how to take advantage of these possibilities. How do you go about actually integrating big data into your firm?

Tackling these issues head-on can help firms avoid complicated entanglements when they consider their big data policies. Building big data early into their technology plans forces firms to address how their structures do or do not align with big data goals and ultimately increases their probability of success. Here's what firms should look out for when addressing big data's ever-increasing role in practice management, user dashboards and customer relationship management (CRM) systems.

Practice Management

Big data will transform effective practice management – that much is certain. Practice management relies on understanding how individuals efficiently and productively conduct their professional lives. Big data can provide critical metrics that benchmark productivity and inform advisors of the results of their efforts. As such, big data can arm professionals with information they can use to understand how to better manage their own time.

Practice management not only looks at which advisors are the most productive, but also explores which specific tasks and methods these advisors are using to be more productive. A variety of other metrics can be used as benchmarks, including client asset acquisition, revenue on assets, revenue mix, AUM and revenue by client, and client retention among others. Mining this information over a large number of advisors over a number of years through big data methods could supercharge these analyses of practice management standards.

The major hurdle against firms taking full advantage of big data's possibilities is whether they have access to the data providing this information. For a variety of reasons, firms traditionally have not prepared or kept the kind of records that could facilitate big data analyses of practice management. Even if there are dedicated systems (or even if firms wish to outsource the analysis of their practice management to another firm), that's just not possible so long as the raw data is missing. Firms should be attentive to their record-keeping in relation to practice management metrics early in their big data plans if they wish to fully implement big data analysis of those metrics.

CRM Systems

Customer relationship management systems have become increasingly sophisticated. CRM systems hold a wealth of data: how often an advisor contacts each client, how much time they spend with each client, communication campaigns with their results, and how often a client requests service. Combining CRM systems with big data metrics can be leveraged for a wide variety of improvements.

The intersections of CRM systems and big data share a lot with practice management – understanding how CRM systems are utilized and the data implications can inform new practice management strategies. To this end, advisors should use big data to analyze customer interactions against revenue per client to better organize their time, maximize revenue and improve productivity.

Big data can also use CRM systems to improve operational efficiency. These systems can be used to process paperwork more quickly. Robust CRM systems can pull together all of a customer’s personal information and records for every meeting automatically so that the advisor doesn't have to, and feed account opening systems saving data reentry.

Systems that track and provide easy-to-use repositories can supplement CRM systems for big data analysis. Ultimately, better aligning CRM systems, practice management, and big data strategies is necessary for firms to fully take advantage of big data’s possibilities.

User Dashboards

All the best data and analysis in the world is completely useless without an easy and viable way to quickly find and digest that information. That's where dashboards come in. Management and advisors both want dashboards that can be used to consolidate analysis to quickly check on important business goals.

Here, firms should be aware of the tools they provide for their employees and how they consolidate those tools. Does the broker-dealer use a portal or some other content management system? Is it centralized or dispersed? The dashboard should integrate with those tools so that and be readily accessible for easy and regular use by your employees.

Firms should approach their dashboards the same way they approach the rest of their big data implementation plans -- with great foresight. Dashboards are where everything -- practice management, CRM systems, and a whole host of other aspects of the business -- come together. Firms should take inventory of present technologies and how to structure them so that more advanced big data capabilities can be supported. Big data can provide firms with a lot in the future, but it requires the right kind of foresight and infrastructure now. Acknowledging that early-on will reduce consternation and pain later.

Scott Gillespie is a Senior Consultant at Quadron Data Solutions, where he assures the company's technology products and services meet and exceed clients' business requirements. Scott is also the Managing Partner of TransAd Partners LLC, the consultancy affiliate of Fetter Logic, Inc. Scott has more than 25 years of experience in the securities industry, and he is an expert in brokerage operations and technology.

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