According to the Washington Post, the Securities and Exchange Commission is turning to quantitative experts from non-traditional backgrounds to stay ahead of the complex, ever-changing markets that make up the US financial system. Traditionally, the regulatory agency filled its ranks with lawyers, but new hiring requirements have brought on experts with specialized quant skills and those who have worked on Wall Street who are “hip to its tricks.”
Perhaps the most out-of-the-box hire is a Princeton-trained nuclear physicist who is currently investigating what caused the May “flash-crash” in the US market. In the article, Gregg Berman points out that the SEC job is not that far removed from his physics experiments on Princeton’s particle accelerator:
“Experimental physics is about drawing conclusions from very messy data, and finance and economics and the type of work within the division that I’m at the SEC is about trying to draw conclusions and make recommendations based on lots of data, data from the marketplace that can be quite messy as well.”
MREB view: Ah, the joys of “messy data.” We have talked in-depth about the abundance of information at our hands, and how the next differentiated insight may not come from new projects but from truly understanding and analyzing our accumulated knowledge. The question is, how can we get our hands around all of the disparate information at our organization? In addition to all the past projects and specialized knowledge on your own team, how can you integrate the specialized (usually tacit) knowledge in other departments? And once you’ve got the information, do you need a nuclear physicist to bring it all together?
Combining information from multiple departments can sometimes seem like a translation project: no database or knowledge source uses the same language. To help you find and combine data, identify a common pathway. FedEx screens its operational data assets for relevance based on customer touchpoints to improve its use of internal data assets. If you’re working specifically with your friends in IT to get access to the data, try Lincoln Financial’s Business Needs-to-IT translation worksheet.
Once you’ve collected the data, the question becomes what to do with it. The SEC is tapping new, non-traditional skills sets to sift through its messy data; perhaps it’s time for organizations to focus more on analysis and synthesis as well. Motorola for one has created a dedicated synthesis role, providing specific responsibilities, deliverables, and skills for staff members charged with integrating disparate pieces of information to build a holistic picture for the organization.
Members have been asking about the role of data analysis in their departments lately, and we’d love to hear from you. Do you think cross-project, cross-source analysis should have a more prominent spot on the research team? How are you bringing together disparate data sources to create new insights for your organization?