4 strategies for setting business leaders’ expectations of big data

It’s difficult to describe how different types of data, from different sources, in unknown states of readiness and usefulness, can drive value. 

“The real value of big data is often intangible. But if you’re hoping to secure funding, vague estimations won’t do.”

—Dean Lane, founder of the Office of the CIO

Business leaders are eager to capitalize on the value of big data, including its vaunted ability to boost revenue, engage customers, and drive product development. But there’s nothing simple about managing, integrating, and testing terabytes of this unstructured information.

You need to explain that big data doesn’t just mean a vast amount of data, but vast amounts of different types of data from different sources, in different states of readiness and usefulness. As a result, it is often difficult to communicate the realities of big data to your peers on the executive team.

Dean Lane, founder of the Office of the CIO, a San Francisco–based IT consultancy, stresses the importance of learning to respond openly and realistically to questions regarding an organization’s data-crunching capabilities. But, he points out, not everyone on the executive team views the role of big data in the same way.

“IT leaders are more focused on the tactical aspects of big data like costs, project management, security, validation, and verification,” says Lane. “The rest of the C-suite, on the other hand, is more concerned with deriving meaning from the data. They care about what it will reveal, what marketing campaigns it will be used for, and how to design a project around it.”

Despite these different perspectives, Lane says, “The opportunity for an alliance between IT leaders and business executives is huge.”

He offers four steps on how IT leaders can help business executives make big data and its deliverables top priorities:

  1. Put yourself in the line of business leaders’ shoes. Integrating and cleansing data is likely the priority for IT leaders. But, Lane says, setting realistic expectations starts with “understanding what business challenges the organization is facing, what the business leaders are hoping to gain from data analytics, and what they’re expecting in terms of project delivery.”
  2. Find a partner. Team with another executive to present a strong business case for data crunching, says Lane. The more internal support you can demonstrate for an idea, the greater the chance of buy-in from others.
  3. Discuss business implications. You need to be prepared to answer detailed business questions. According to Lane, “a CFO is most likely to ask how much money you’ll need, how long you can expect a particular model or system to remain in existence, and what impact the system will have on other departments.”
  4. Estimate costs. “The real value of big data is often intangible. But if you’re hoping to secure funding, vague estimations won’t do,” Lane points out. In this case, consider starting with a pilot project to test and prove the value of your idea. “IT leaders can’t just look at the cost of servers,” warns Lane. “Instead, they need to figure out the cost of dedicated consultants, project accountants, training, software maintenance costs, and the internal manpower needed to keep things running.”


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