How CFOs can modernize their data stack for strategic success

Finance teams face challenges with underutilized data; a recent webinar explored how CFOs can modernize data infrastructure effectively.

Finance teams are overwhelmed with underutilized data, leading to misinterpreted trends and missed opportunities. Outdated systems and siloed operations further exacerbate this problem. However, emerging technologies promise to revolutionize finance function by improving reliability, encouraging growth, modernizing data infrastructure and making data accessible to everyone in the team.

In a groundbreaking webinar hosted by CFO India, in association with Alteryx, a leading expert and financial pioneers convened virtually to delve deep into how CFOs can make the most of their internal data and what they can do to modernize their existing data stack. The distinguished panel featured Sachin Kataria, Alteryx Evangelist, along with CFOs Sridhar Radhakrishnan from Tata Consulting Engineers, and Sachin Bansal from Wipro Consumer Lighting, Wipro Enterprises. The discussion shed light on the transformation of data stack through automation, with a particular emphasis on changing mindsets, creating value, and addressing key challenges. The discussion was expertly moderated by Seema Menon, Director & COO, CFO Collective – An IMA Company.

Assessing data maturity and ecosystem

• Sridhar highlighted the importance of a comprehensive data maturity assessment across the organization, considering technology, processes, people, and data itself to identify areas for improvement.
• Sachin Bansal acknowledged the complexity of his company’s legacy and modern data systems, suggesting AI as a key tool to unlock deeper insights in the future.

Sachin Kataria’s three-pronged approach to data utilization

1. Get the right data: Enable knowledge workers to easily access and integrate data from different sources without needing complex technical solutions.
2. Get the data right: Empower knowledge workers to independently handle data quality issues, perform transformations, and conduct analyses without technical expertise.
3. Keep the data right: Implement data governance, quality checks, and collaboration tools to ensure data is trustworthy and accessible, thus encouraging broader usage.

Use case: Automating monthly P&L

Sridhar described a process improvement automation project aimed at streamlining his company’s monthly profit and loss (P&L) reporting. The project sought to improve efficiency, transparency, and data accessibility for better decision-making across business units.

Hidden costs associated with data

Sachin Kataria highlighted several hidden costs associated with data:

• Security vulnerabilities: Systems with large amounts of data are more prone to cyberattacks, leading to high costs for addressing breaches and complying with regulations, along with potential reputational damage and legal issues.
• Lack of data agility: If most of the data is unused and outdated, maintaining it requires significant labour and resources, hindering innovation and resulting in opportunity costs.
• Poor data quality: Low-quality data leads to inaccurate models and outputs, resulting in poor decision-making and financial losses that can be substantial over time.

Sachin emphasized the importance of addressing these hidden costs to avoid negative financial and operational consequences.

Budgeting and investment

Sachin Bansal advised prioritizing initiatives with clear revenue or profit impact. Sridhar and Sachin Kataria acknowledged budget limitations and emphasized focusing on urgent problems first, delaying less critical projects. Sachin Kataria further explained that continued investment in a modern data stack hinges on early positive experiences and financial assessments, emphasizing the importance of financial metrics like cost of inaction and opportunity costs.

Achieving a balance between data quality and security with data democratisation

Sridhar detailed establishing a cross-departmental “pseudo data office” to oversee data management and measurement. He stressed continuous communication with stakeholders to ensure report relevance and suggested a tiered approach to data access based on user roles.

Evaluating data stack modernization efforts

Sridhar advocated for measuring modernization success through cycle times, customer satisfaction surveys, and error rates in reports. Sachin Bansal emphasized the importance of data availability speed and accuracy. Sachin Kataria highlighted four key pillars: accessibility, accuracy, governance, and security/compliance.

Where to begin

According to Sridhar, prioritizing control-focused tools and incrementally implementing solutions within budget constraints could be a good starting point. Sachin Bansal advised starting small with readily available tools rather than waiting for advanced technologies while Sachin Kataria stressed the necessity of a comprehensive data strategy, driven by top-level ownership, for effective deployment of a modern data stack.

Adapting data strategies for business growth

Sridhar recommended aligning financial processes with company size, postponing advanced systems for smaller firms. Sachin Banal emphasized fostering a company-wide data-sharing culture. Sachin Kataria highlighted differing data approaches between SMEs and large enterprises, initially led by finance, potentially evolving with growth. Collective ownership ensures a pervasive data vision for innovation and effectiveness.

Closing thoughts

The session illuminated the evolving role of CFOs in modernizing their data stack. It emphasized the importance of CFOs adopting a tech-savvy mindset, leveraging automation to generate value, and proactively addressing potential hurdles in their quest to derive meaningful insights from data.