Big data initiatives are quickly becoming strategic priorities for many credit unions.
But finding a leader for your big data project could be challenging.
Businesses face a data analytics talent gap with significant shortages at all levels, according to Deloitte Development LLC’s Analytics Trends 2014 report.
Professionals who can deliver data-backed insights that create business value are especially hard to find, the report states.
A CUNA Marketing & Business Development Council white paper offers five steps to build a big data team:
1. Break down big data talent needs. Typically, you’ll need talent in four key areas: business analysis, analytic expertise, data technology expertise, and visualization expertise.
2. Scan your internal landscape. You likely already have people who know the business, possess data-crunching capabilities, and make data-driven decisions.
3. Fill talent gaps. This will be easier once you know exactly what you need and what you already have. Augment teams by recruiting selected capabilities on a limited basis.
4. Cross-train to cultivate collaboration. The goal is not to make everyone an expert on everything, but to establish a common language the group can use to collaborate effectively.
Cross-training also helps ensure the group shares a vested interest in the outcome.
5. Empower your explorers with freedom. You can’t throw all these people together and demand an instant return on investment.
Give staff freedom to explore big data without the pressure to produce a revenue-generating idea immediately.
“Discussions about perceived talent deficits center on data scientists who bring deep statistical and analytical capabilities to the table,” the white paper notes. “Big data is too big for one title to tackle. We need to build big data teams.
“The bottom line is that big data talent isn’t ready-made. Your big data team members will evolve over time as they learn from one another and are reshaped by the new world of big data.”