How to Build a Big Data Team in Five StepsPrint
Forward-thinking companies are assembling cohesive, multidisciplinary groups from disparate departments to experiment with big data techniques and applications.
4. Cross-train to cultivate collaboration.
Once your team is in position, cross-training is critical. For example, we recently helped an insurance industry client pull together a big data team, helping them train the analytics members on insurance and the insurance business members on analytics. The goal was not to make everyone an expert on everything, but to establish a common language that the group could use to collaborate effectively.
Enabling team members to trade places also helped ensure that the group shared a vested interest in the success of the outcome. In addition, it exposed each of the team members to different work cultures. Don’t forget the importance of designing incentive structures that foster brainstorming and build a collective mindset.
5. Empower your explorers with freedom.
It’s also important to realize that you can’t throw all these people together and demand an instant return on investment. You should give them the freedom to explore big data without the pressure to produce a revenue-generating idea right off the bat. In the exploratory stage, their purpose is to investigate big data’s possibilities and to report their findings.
The thing about big data is that it constantly demands that business and technology executives sidestep their comfort zones. That includes how you think about sourcing and managing your talent.
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.
Once the team is capable, it can be replicated and institutionalized in different parts of the organization. You are investing in the creation of a high-powered big data team that you can deploy across business units many times over.
Building a team that has the right skills to explore big data is part of the adventure, and it’s a process that will take time. Not because we are missing talent, but because we are seizing a new opportunity.
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