6 trends in data and artificial intelligence for 2021 and beyond
The gap is widening between data leaders and data laggards. From external data to customer experience analytics, this is what leaders are focusing on.
The last year has shown the value of innovative uses of data and analytics, as companies shifted to accommodate rapidly changing circumstances. At the same time, other firms struggled to keep up, with some wrestling with issues of how to gather, use, and manage data.
“The gap has widened between those who are leaders in analytics and those who are laggards,” according to Cindi Howson, chief data strategy officer at analytics platform provider ThoughtSpot.
At the recent MIT CDOIQ Symposium, Howson outlined six trends in data, analytics, and artificial intelligence that can help orient data leaders in a shifting landscape.
COVID-19 forced companies to react and pivot quickly to stay afloat. Now it’s time for firms to be more strategic and intentional about where they focus innovation and investment efforts, Howson said.
There are some lessons to be learned from the beginning of the pandemic, though. While fear of the unknown often holds organizations back from investing in new initiatives, the pandemic showed the benefits of pivoting quickly and investing in new things. Restaurants that quickly embraced online ordering and medical providers that adopted telehealth options came out ahead, she said.
As companies try to keep up that momentum for transformation, Howson recommended three things to keep in mind:
Things like supply chain and operating costs don’t matter if a company doesn’t hold on to customers, Howson said. Businesses have many touch points with customers, from in-person and digital sales to call centers. “Bringing all this data together so you have a holistic view of the customer is important,” Howson said. This is where newer concepts such as data fabrics and data lakehouses might be valuable. Companies should also be sure to analyze different forms of interactions, such as using voice analytics to look at how customers interact with chatbots or call centers.
External data can provide valuable early warning signs about what’s going on. For example, Hershey’s Chocolates used external data during the pandemic to predict a growth in the number of people using chocolate bars for backyard s’mores and a decline in sales for smaller bars of candy for trick-or-treating.
To take advantage of external data, companies should start with a business problem, and then think about what possible data could be used to solve it, Howson said. Companies might need to modernize data flows — some companies haven’t leveraged external data because they’ve been focused on internal data, while others have found data hard to transfer.
