Exclusive: How Syniti's data-first approach is driving digital success

Syniti, a global leader in enterprise data management, has been on a mission to help organizations harness the power of their data for nearly three decades.

Established in 1995 under the name BackOffice Associates, the company underwent a significant transformation, changing its name to Syniti approximately seven or eight years ago following a series of acquisitions.

Today, Syniti is recognized for its unique blend of software and services that support business transformation initiatives across the globe.

Gaj Pasuathy, who has served as Senior Vice President of Delivery since 2022, explained Syniti's value proposition to TechDay in a recent interview.

"We offer both software and services that help organizations harness the power of their data to support all their business transformation initiatives," he said.

One of the key challenges Syniti helps its customers overcome is the often-overlooked impact of data on business performance.

"From customer to customer, their goals or improvements might differ, but what's common is the underlying data needs to be in a state to support that business," Pasuathy said. This is particularly crucial for organizations embarking on initiatives such as AI, analytics, or system upgrades.

Syniti's global footprint is extensive, with a significant presence in North America, followed by Europe, and then Asia Pacific and Japan. Pasuathy noted that Syniti is looking to expand further into the ANZ region, particularly as it is one of the largest markets within Asia Pacific alongside Japan.

This expansion is part of a broader strategy to invest more heavily in these regions, which Pasuathy described as "exciting."

What sets Syniti apart in the competitive landscape of data transformation is its approach to integrating both business and technical perspectives.

"Most organizations in this space tend to be very technical and IT-centric, but we've tried to address the market by focusing more on what the business needs and how data facilitates that," Pasuathy explained.

This dual focus is embodied in Syniti's consultants, who are described as "techno-functional" because they understand both business processes and the technical aspects of data and systems.

Syniti's work spans various industries, but Pasuathy highlighted the natural resources sector as one where the company has had considerable traction. As these companies transition from traditional energy sources like coal and iron ore to more sustainable ones like lithium and copper, mergers and acquisitions have become commonplace.

Syniti plays a crucial role in integrating the acquired companies' data and systems, ensuring a smooth transition and continued business efficiency.

One standout success story involved a natural resources company struggling with warehouse space due to duplicate equipment entries in their system. Syniti's intervention led to the elimination of these duplicates, resulting in annual savings of $10 million in storage costs. "That's just one data point," Pasuathy noted, emphasizing that there could be many similar issues within an organization that, when addressed, lead to significant savings and efficiency improvements.

Another example from the food and beverage sector involved a company struggling with cash flow due to misaligned payment terms. Syniti's analysis revealed that most vendors were being paid earlier than necessary, reducing the company's cash on hand. By addressing this discrepancy, Syniti helped the company improve its cash flow significantly.

These examples illustrate the importance of clean data in driving business success, a concept central to Syniti's philosophy. "Before you embark on a data analytics initiative, you need to make sure the data is right to support it," Pasuathy advised.

This data-first approach is critical for businesses, particularly in regions like ANZ, where the emphasis on digital transformation is growing.

However, achieving clean data is not without its challenges. Pasuathy explained that organizations must assess their maturity in terms of data standards and monitoring capabilities.

"Depending on where an organization stands, they may require different levels of support, whether it's implementing software, restructuring the organization, or simply understanding what data is critical."

Data migration is another area where Syniti's expertise shines, particularly in large-scale enterprises. Pasuathy noted that companies often take data for granted during migration, focusing more on systems and processes.

"One thing that's consistent is the data that moves across because that's what the organization is built on," he said. Addressing data quality early in the process ensures that when the new system goes live, it's fully supported by accurate and reliable data.

Data governance is also a crucial pillar of Syniti's approach, helping organizations maintain data quality over time. "Having a governance layer in place means that even as you perform your normal business as usual activities - that data quality stays at a high level," Pasuathy explained. 

Looking ahead, Syniti is investing in generative AI to further enhance its offerings. Pasuathy shared that the company is currently conducting proof-of-concept trials with customers in North America, with plans to integrate these AI capabilities into the platform by 2025.

"We're building a way to automate that end-to-end process," he said, explaining that AI agents could eventually help organizations "identify critical data points and generate the necessary reports to support business goals."

However, despite these advancements, Pasuathy emphasized that AI is "not a replacement for human expertise."

"If we can add efficiencies and still have human interaction with those AI agents, then I think we get the best of both worlds," he said.

As Syniti continues to evolve, its focus remains on helping organizations understand the critical role of data in their success.

"Having that organizational change and incentivizing everyone in the organization to see the importance of data is probably the most critical aspect."