"If only we knew what we know."
This knowledge-sharing lament, attributed to Lew Platt, the late CEO of Hewlett Packard, captures how hard it is for large, global organizations to take advantage of all the breakthroughs, discoveries and day-to-day advances made by far-flung departments, business units and individual employees.
Global insurer MetLife is trying to make the most of its internal expertise by bringing together 100 of its brightest data scientists and analytics leaders for a three-day big data event being held this week at a hotel near company headquarters in New York.
The brainstorming and networking event features "ideation" sessions around companywide business challenges as well as a technology expo with vendor and partner exhibitors and a parade of next-generation startups that will get a chance to pitch their technologies to MetLife data champions.
"We realized that we have a wealth of talent around data science within our organization, but the network is widely distributed," says Pete Johnson, MetLife's VP for Enterprise Data and Application Services. "We wanted to bring our people together to help them get to the next level."
[ Want more on MetLife big data innovation? Read Why NoSQL Databases Are Gaining Fans. ]
MetLife data specialists work in facilities across the U.S. as well as in Tokyo, Kuala Lumpur, London, Dubai, Mexico City and elsewhere. The company is also building a technology hub in Cary, N.C. (home of SAS and top analytics school N.C. State University), where the company expects to hire as many as 1,000 employees.
The talent represented at this week's event includes insurance actuaries, marketing experts who do customer segmentation and predictive campaign work and deep quants involved in investment analysis.
The idea behind the brainstorming event is to share discoveries and best practices. Groups in the U.S., for example, have done text analysis and sentiment analysis work that has helped MetLife understand and make effective use of net promoter scores, a fairly new customer loyalty metric that has gained use along with the rise of social networks. A group in Japan, meanwhile, has excelled in modeling customer attrition, an achievement that helps MetLife understand which customers are leaving and why so it can take steps to retain those customers.
Leaders of MetLife's three-year-old Innovation Program kicked off an inter-event competition on Monday whereby three broad challenges were presented: new product development, customer retention and operational effectiveness. Teams worked into the night on Monday to come up with ideas for harnessing new data types and new big data technologies to drive breakthroughs in these areas. The winning ideas were to be presented in a separate session on Tuesday.
"We have traditional models and data-analysis techniques in all three areas, but as we're gearing up for the data explosion, we want to open our minds to new possibilities," Johnson says.
Employees are trading tips on emerging technologies now in use at MetLife, including NoSQL databases, Hadoop and data visualization tools. As InformationWeek has reported, MetLife is making extensive use of MongoDB, using the NoSQL database to power an internal view of customers as well as a new business-to-consumer mobile app called Infinity.
The most basic goal of this week's event is simply making it easier for data-savvy employees to get to know each other. That's something that isn't always easy for large companies like MetLife, which has more than 64,000 employees.
"It's not just about knowing what others are doing within the company, it's about getting to know each other as individuals, so you feel comfortable enough to call somebody for advice," Johnson says.
Does your company know what it knows? Do you have data experts working in different departments, business units and countries that rarely if ever cross paths? Take a page from MetLife's playbook and gather your best and brightest data-savvy employees.
MetLife simply invited key vendors including IBM, Informatica and EMC to participate in its expo, but if you can promise a high-level audience of technology influencers, you might even be able to ask for event sponsorship support. The biggest payoff, however, will be in putting good ideas to work across your organization.
"Attrition modeling is low-hanging fruit because it's easy to retain top customers by providing a higher level of service, yet that's not something we're doing in every country," says Johnson. "This kind of event will help propagate that kind of capability around the globe."