Building an Organization for Active Intelligence

There is no disputing the importance of data. But the era of digitalization initiatives simply to break down data silos or capture more data is already behind us. As Deloitte puts it, organizations today are drowning in data yet starved for insights.

To succeed, organizations need timely and relevant insights to help them make better business decisions or to improve the customer experience. Or in the words of Chong Yang Chan, managing director of Qlik for ASEAN, they need active intelligence.

Why active intelligence matters

CDOTrends had the opportunity to speak with Chan at the sidelines of QlikWorld Tour Singapore last week. According to him, organizations are increasingly leveraging active intelligence to stand out from the competition.

“With active intelligence, an organization can capitalize on real-time or the most recent data to form an up-to-date profile of their customers. They can then make use of these actionable insights to make highly relevant offers,” he said.

Customers don’t want to be given an offer that is not relevant, explains Chan. He observed that a 40-year-old customer at a certain stage of their life journey would probably not be enamored to receive a promotion optimized for someone in their twenties.

And even governments are turning to active intelligence. He said: “Governments are also anticipating the needs of their citizens instead of being reactive. Government agencies are adopting what the business is doing in terms of customer profiling and lifetime value.”

He cited his seamless experience with the Baby Bonus Scheme following the birth of his child: “I didn’t have to apply separately for it; it was just one click. The government now comes in and anticipates what you need.”

Putting data to work

Active intelligence has uses in every façade of business. Chan highlighted the credit worthiness checks that financial institutions do when customers apply for a loan as an example.

“The traditional way of checking a customer’s creditworthiness is by looking at data sources from six months ago. But financial standing can change overnight. To overcome this problem, some banks use very creative nontraditional data sources to verify the creditworthiness of their customers.”

“They may look at the way a customer banking customer transacts; the inflow and outflow of money to their savings account can say a lot about them. Also, how frequently are they paying their bills? All these observations are used to derive a credit score.”

Another use of active intelligence would be to detect financially distressed customers early. This allows financial institutions to intervene early by offering a loan restructuring when there is still an opportunity to do so.

“The window of opportunity might be narrow and getting smaller. For you to take action in time, your data must be always available and be in the moment,” explained Chan.

Of course, data might come in through various avenues, and the onus is on organizations to stay versatile: “Nowadays you walk into a bank branch maybe once a year, but you might interact with your bank’s mobile app 20 or 30 times a month.”

Building an active data culture

Unfortunately, many organizations do not leverage analytics as part of their business workflows but rely on it as an independent guide separate from work processes and decision-making, says Chan. So, how can businesses establish an active data culture?

“To drive analytics, organizations need to drive it using a top-down approach,” said Chan. He shared the anecdote of an irate CEO who called up his CIO upon realizing that department heads are not using a data dashboard made available to them.

“To encourage the organization to make use of a dashboard, for example, the CEO should ask for supporting evidence or data points from the dashboard before going ahead with a business recommendation.”

“By driving the decision from the top down with his division managers, the CEO ensures that these managers, when they talk to their team, will also insist that they use data to support their recommendations.”

Finally, it is worth noting that many organizations are not benefitting from active intelligence due to the inaccessibility of data. They might be exporting data on an ad-hoc basis, storing their data in Excel spreadsheets, or making manual requests through IT.

Access to insight is hence an issue, given that it might take weeks or months before the data is available – by which point the business requirements might well have changed.

Chan has this recommendation that businesses can use to gauge their progress: “From the moment a problem is identified, how long does it take for stakeholders to gain the insights they need from the data?”

Paul Mah is the editor of DSAITrends. A former system administrator, programmer, and IT lecturer, he enjoys writing both code and prose. You can reach him at [email protected].​

Image credit: iStockphoto/GOCMEN