While companies may be accustomed to formulating analytics questions revolving around past performance, to get the most of out of big data, queries should link tactical and strategic-level objectives.
That’s the advice that John Lucker, principal and global advanced analytics modeling leader at Deloitte, points out in a recent TechRepublic article.
Lucker describes these questions as “crunchy,” because they are key to generating meaningful answers for operations.
For example, a chief marketing officer can ask for list of the company’s next 1,000 customers and information about how a sales team will win them as opposed to asking for a report about current market demographics and sales results over the past six months, Lucker adds.
This question is meaningful because it requires understanding of multiple dimensions of strategy and operations, including:
- Product strategy
- Customer segments
- What drives people to buy products
- What drives customer to leave and signals that they may leave
- What drives sales deals to close
“In general, I get the sense that most CXOs do not feel that they have a good handle on how to get the most out of their big data analytics,” notes Lucker. “They say that they do analytics, but it’s hard for them to define exactly what value they are getting from it. Initially, when we visited companies, we thought that they would be strong in the area of business intelligence, but what we are finding is that most companies need help in making their data meaningful.”
For companies to get to the crunchy questions, leaders need to ask their analytics teams to start designing more strategic and forward-looking questions as opposed to historical queries. First, ensure that teams have a firm grasp on strategy and how strategy filters down to operations, he suggests.
Putting the right tools in the hands of modern data analysts is also key to aligning questions that will bring meaningful, actionable insights to the organization.
Take, for example, a recent research report from Aberdeen Group that notes that four out of five line-of-business data analysts who are using data discovery tools use dashboards that display tactical and operational tools.
Furthermore, these modern data analysts are 55 percent more likely that other users to have interactive data visualization tools.
“These line-of-business thinkers can engage all relevant data in one place and dive down from intriguing findings for deeper analysis,” according to the report. “Modern data analysts obtain information within the decision window 20 percent more often than all other users. They figure out the information they or their team needs and go get it.”