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Using AI to Advance Analytics

Sam Wong, senior director for data, analytics, and AI with Mark Anthony Group, discusses how advanced analytics is at work in today’s enterprise.

In this latest “Speaking of Data” podcast, data and analytics expert Sam Wong discusses a variety of enterprise AI and analytics use cases. Wong is senior director for data, analytics, and AI with Mark Anthony Group, a beverage and spirits manufacturer. [Editor’s note: Speaker quotations have been edited for length and clarity.]

For Further Reading:

In the Know on Generative AI with Fern Halper

The Five Ds for AI Project Deployment Success

How Generative AI Is Changing How We Think About Analytics

Wong began by explaining that the main focus of his ML/AI efforts today are sales and marketing -- primarily the sales team.

“We’ve been piloting some AI and ML models, both 7, to create a platform to help the sales reps be more efficient and effective with their accounts,” he said. “One side effect has been that this emphasis on AI has allowed us to accelerate and elevate our other practice areas, such as data management, data engineering, and so on.”

“A real advantage has been the top-down support for our analytics program, starting with our founder,” Wong said. “He invested in setting up an incubation pod, which allowed us to develop, test, and learn very quickly.” In addition to accelerating development, this approach has also increased enthusiasm across the organization to share and reuse these use cases.

When asked about the use cases where AI has been used, Wong described a project he’d been working on for his marketing department.

“We’ve been helping [our marketers] analyze their customer interview videos,” he said. “Originally, in order to evaluate things such as customer sentiment for a flavor or brand, the marketing team would have to manually transcribe the video before they were able to gain any insight.” However, Wong’s team is now able to incorporate generative AI to build a summary of the video transcript in parallel with the marketing team’s efforts. He explained that as the AI’s output improves, he will be able to save dozens of hours of manually going through content and creating the summary.

“The lesson we’ve learned,” he said, “is to not force a solution and to let innovation take hold as part of the process.”

However, Wong pointed out, implementing AI is not without its challenges, especially regarding people issues. “People are initially concerned that their jobs are at stake,” he explained, “but what we’re looking for is a combination of the AI and the human side working together.”

[Editor’s notes: You can listen to the entire podcast on demand. Wong will be speaking at the upcoming TDWI Executive Summit, presenting a case study about accelerating a data management program.]

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