PodChats for FutureCFO: Mining data intelligence – the secret sauce of finance transformation

Transformation imperatives tend to revolve around modernising processes and systems to enable more agile operations that can adjust to the increasingly unpredictable nature of day-to-day life, whether we mean unplanned downturns or new opportunities that, at times, seem to come out of nowhere.

With market volatility, digital disruption, and regulatory uncertainty appearing to be the norm rather than the exception in 2025, finance leaders will be hard-pressed to accelerate transformation initiatives and get them up and running quickly.

Data intelligence is at the heart of this transformation—a critical enabler of strategic decision-making, operational efficiency, and regulatory compliance. As Asian organisations pivot toward data-driven finance, CFOs must leverage advanced analytics, AI, and unified data strategies to secure competitive advantages while addressing regional challenges.

Understanding data intelligence

Data intelligence is not merely about collecting data; it involves understanding patterns, trends, and narratives that emerge from that data. Lavan Verma, head of FP&A and Data Intelligence – APAC at ManpowerGroup, says, "Data intelligence is about transforming the raw data into actionable insights that drive better decision-making in business."

He elaborates that data intelligence is a strategic enabler within the finance context, empowering leaders to make proactive decisions based on predictive insights.

"For CFOs, data intelligence is essential for assessing market expansion opportunities, optimising resource allocation, and enhancing overall operational efficiency. By leveraging data intelligence, finance leaders can better evaluate macroeconomic indicators, hiring trends, and sales patterns to predict future needs and challenges." Lavan Verma

The value of data intelligence in finance

Enhancing decision-making: One of the primary benefits of data intelligence is its ability to improve decision-making. In a rapidly changing business landscape, CFOs require real-time insights to adjust strategies effectively. Verma notes, "In finance, data intelligence can work as pillars to achieve better forecasting, budgeting, and strategic planning."

Moreover, the importance of storytelling in data intelligence cannot be overstated. As finance professionals transition from number crunchers to strategic advisors, the ability to convey complex data insights understandably becomes crucial.

"At some point, everybody's interested in the storytelling; nobody is interested in the data," Verma emphasises, highlighting the need for finance teams to articulate the significance of their findings.

Driving efficiency: Data intelligence is also pivotal in driving operational efficiency. Verma believes that by using data analytics, finance leaders can streamline processes such as demand forecasting, resource allocation, and customer experience improvement. For instance, he points out, "In our industry, reducing time to hire or time to fill an order is an example of data intelligence."

Furthermore, the finance function must evolve to become more tech-savvy. As Verma states, "Finance is no more finance; it is techno finance." This evolution underscores the necessity for ongoing training and skill development in data analytics tools.

Key considerations for building a data intelligence practice

As organisations strive to develop effective data intelligence practices, several key considerations emerge for CFOs and heads of data in Asia. Verma identifies three essential components for establishing a robust data intelligence framework: people, processes, and technology.

People: Upskilling finance teams to interpret complex data is paramount. "If this is not done, nothing can be achieved," Verma asserts, emphasising the need for skilled professionals to extract actionable insights from data.

Processes: Implementing standardised processes and agile data governance frameworks ensures data accuracy and compliance. In a globalised business environment, adhering to regulations like GDPR is vital for maintaining organisational integrity.

Technology: A unified, cloud-based platform that integrates diverse data sources is essential. Verma highlights the importance of access to real-time data, stating, "We need to have a unified cloud-based platform to integrate diverse data sources into one data lake."

Overcoming challenges

Despite the benefits, CFOs and data leaders must also know the challenges of implementing data intelligence. Data silos often exist within large organisations, creating fragmented systems that hinder access to a single source of truth. "The first challenge that comes to my mind is data silos," Verma explains, noting that these silos can delay insights and impede decision-making.

Additionally, a skills gap poses a significant challenge. Many finance teams may lack the technical expertise to analyse complex data models. Verma urges, "We need finance teams to learn a bit of technical expertise," underscoring the need for training in tools like Python and machine learning algorithms.

Measuring success

Establishing clear metrics for success is vital when implementing a data intelligence practice. CFOs should define key performance indicators (KPIs) that align with organisational objectives. Reflecting on the financial forecasting practice, Verma advises, "Set KPIs around forecasting accuracy rates," which will help evaluate the effectiveness of the data intelligence initiative.

Data intelligence as a transformation agent

In 2025, data intelligence is set to play a transformative role in the finance function. The KPMG report, CFO agenda for elevating finance, puts data intelligence at the core of the CFO agenda, explaining that establishing finance as the value multiplier and integrator while enabling enterprise data and reporting strategies, proper governance, and practical decision support.

For CFOs and heads of data in Asia, understanding the nuances of data intelligence is critical for driving informed decision-making and operational efficiency. By focusing on the key pillars of people, processes, and technology, finance leaders can establish robust data intelligence practices that enhance organisational performance and position their companies for future success in an increasingly data-driven world.

In this rapidly evolving landscape, mastering data intelligence is not just a competitive advantage but a necessity for finance professionals aiming to thrive in the modern business environment.

"Mastering data intelligence transforms a finance professional into an indispensable business partner. It enhances their critical thinking, decision-making ability and storytelling skills." Lavan Verma

Click on the PodChat player to hear Verma's thoughts on mining data intelligence: the secret sauce of finance transformation.

1. How do you define data intelligence?
2. What is data intelligence in the context of an organisation (as viewed from the Board and C-suite and operations)?
3. How does this translate in the world of the finance function?
4. What is/are needed for data intelligence in the finance function (technology, process, etc)?
5. What are the benefits data intelligence brings to its practitioners? (viewed from a career perspective)
6. What are the potential challenges for the CFO and finance team in the execution and delivery of data intelligence?
7. Any best practices in the design, execution and performance of data intelligence?
8. We have seen technology evolve rapidly in the last couple of years. How will these technologies influence finance in the years ahead?