Mukund Raghunath, Founder and CEO of Acies Global, speaks with Della Shea, Head of Operational Risk, Data, and AI at CIBC, in a video interview about how Acies stands out from its competitors, successful client use cases, and how AI will impact analytics going forward.

Raghunath highlights that Acies has a unique approach and provides end-to-end support to clients, helping them scale and make their intelligence more consumable. This includes everything from organizing data and building pipelines to conducting analysis, developing custom applications, and writing APIs to connect insights with business applications.

According to Raghunath, the team’s commitment to continuous improvement instead of a one-time effort sets them apart. They ensure that data science remains consumable throughout the process and that application development accounts for future analytical needs. By maintaining an ongoing feedback loop, they create what he describes as a digital continuum, which distinguishes the approach from others in the industry.

Highlighting successful client use cases Raghunath mentions Acies’ work with a major electronics manufacturer on the East Coast. The company had invested in an enterprise system for supply planning and demand forecasting, but the forecasts generated were too generic and failed to meet the company’s specific needs. While the system provided accurate predictions for about half of the SKUs, the other half showed significant discrepancies. As a result, the merchandise and demand planning teams were not utilizing the platform effectively, leading to a suboptimal return on investment.

To address this, the Acies team developed forecasting models outside the core system by incorporating additional data sources and building driver models. These improvements led to a 15-20% increase in forecast accuracy. However, the challenge didn’t stop there. Since the enterprise system had essential workflow components, the enhanced forecasts needed to be integrated back into the platform. This required a deep understanding of the system’s technology, constructing data pipelines, and developing APIs to ensure that planners could seamlessly access and use the improved forecasts in their daily operations.

In another example, Raghunath describes working with a large online travel company that faced a different challenge — managing millions of daily website visitors while identifying the most valuable customers. The company needed a way to prioritize high-value users and align product and marketing strategies accordingly.

Given the scale and complexity of the data, the first step was understanding user behavior. Some visitors actively engaged with the site, while others remained passive, making it difficult to track and assess their value. To solve this, his team built a customer lifetime value model that not only estimated each user’s long-term worth but also identified the specific marketing and behavioral factors driving their value.

The initial phase focused on experimenting with different revenue and cost metrics to accurately determine customer lifetime value. Once that was established, the next step was to develop data pipelines that enabled the system to process and apply these insights daily. Additionally, they built a portal that allowed product and marketing leaders to run scenarios, allocate budgets effectively, and measure the return on investment of their strategies.

Sharing thoughts on AI’s impact on the analytics space, Raghunath says that AI is a top priority for Chief Data Officers (CDOs), Chief Analytics Officers (CAOs), and CEOs with many viewing it as an area for active experimentation. While some applications already incorporate automated intelligence and can be scaled efficiently, many others require proof-of-concept testing to determine both their effectiveness and long-term cost viability.

Raghunath notes that his team is conducting numerous AI experiments for clients, particularly in sales enablement, where they analyze multiple market and customer signals to refine targeting strategies and identify the most effective next steps for engagement.

CDO Magazine appreciates Mukund Raghunath for sharing his insights with our global community.