Unpacking a Decade-Long Evolution of the Finance Function
The ‘guardians of enterprise value creation’, finance teams have experienced a massive transformation in the last ten years. One that has sparked debates about innovation and adaptation.
In this webinar, we get to the bottom of this undeniably impressive evolution to understand why businesses are relying heavily on the finance function to help them ride out unprecedented challenges.
We’re throwing it back to a time when spreadsheets and Salesforce reigned supreme and the finance team was acting more as custodians than advisors. With many finance teams still pushing through with spreadsheets and a pipework of frustrating bottlenecks; we reveal critical insights to set you on the path to success.
The short answer? It’s all about flexibility…
Find out how you can
- Go beyond the traditional ‘preservation’ role of Finance
- Move away from process-heavy, siloed approaches
- Break free from webs of spreadsheets before they snap, toward a future-proof tech stack
- Manage revenue recognition as contracts get more complex
Finance in 2030: Toward the end of the webinar (channelling our inner Tony Stark), — we discuss the finance operating model ten years down the line.
Speaker
Madhu Jagannathan, CFO at LOB
- Two decades of experience in the world of finance and startups
- Formerly worked with EY, Wipro, Microsoft, and Dropbox
Hosted by
Apurv Bansal, Cofounder and CEO of Zenskar
Webinar Summary
Q. Can you provide some background on your career and experiences?
I started my finance career in the late 1990s at Ernst & Young, then moved on to technology companies like Wipro, Microsoft, and Dropbox. At Dropbox, I was first introduced to the SaaS business model. Now, I'm the CFO at Lob, a company disrupting the world of direct mail.
Q. How has the finance function evolved in the SaaS industry over the last decade?
In 2014, SaaS was already established, but the tools and infrastructure to support these models were still in early stages. A lot of the work was done manually, relying heavily on spreadsheets. Today, we have better third-party products that resolve many of these challenges, streamlining the process.
Q. What did the finance tech stack look like 10 years ago, and how has it changed?
10 years ago, we relied heavily on spreadsheets. Salesforce was the default CRM, but data was often siloed. Today, there are more integrations and tools available, making the finance function more agile. We also now consider build vs. buy options for systems that can scale with the company.
Q. How has the use of spreadsheets and tools evolved for finance teams?
Tools have made finance teams more data-driven, helping to validate decisions with actual data rather than intuition. While spreadsheets were once the go-to, now, with more complex data requirements, tools are necessary for fast, data-driven decision-making and analysis.
Q. How has the expectation for finance professionals changed with the introduction of advanced tooling?
The job has become more data-driven. Leaders expect finance teams to provide insights based on historical data and run A/B tests. With the right tools in place, teams can quickly respond to business needs, whereas spreadsheets couldn’t support this kind of agile decision-making.
Q. Can spreadsheets still support modern finance tasks, or is there a better solution?
While spreadsheets are useful in the early stages of a company, as the business scales, the limitations of spreadsheets become apparent. For more complex tasks like detailed sales analysis, a dedicated tool that can slice and dice data is necessary. The tools today help manage and analyze larger datasets more efficiently than spreadsheets.
Q. What makes spreadsheets less ideal for complex data analysis?
Spreadsheets are limited in terms of volume and flexibility. They lack user controls, making it harder to ensure data integrity. With more robust tools, you can automate checks, collaborate more efficiently, and scale the analysis to meet the growing needs of the business.
Q. How does the flexibility of a tool compare to a spreadsheet when it comes to analyzing complex data?
Tools offer the flexibility to handle larger datasets and more complex analyses. While spreadsheets are more adaptable in some cases, they lack the checks and balances and are prone to errors. Good financial tools allow you to track changes and scale operations more effectively.
Q. What does flexibility in financial tools mean, and how should it be evaluated?
Flexibility in financial tools means the ability to adapt to business model changes, such as adding new products or switching pricing models. It should be easy to introduce new SKUs or pricing structures without hitting roadblocks. This adaptability is key to ensuring your tool can scale as the business grows.
Q. Why is flexibility in finance tools crucial for businesses?
As business models evolve, the tools we use must evolve with them. If a finance tool isn't flexible, it can limit a company’s ability to respond quickly to market demands or changing strategies. Agility is a competitive advantage, especially for startups.
Q. How do evolving pricing models impact revenue recognition?
The introduction of complex pricing models, such as usage-based or hybrid models, complicates revenue recognition. As businesses grow and offer more customized deals, finance teams need to ensure they allocate revenue correctly across different line items, in compliance with standards like ASC 606.
Q. Can revenue recognition complexities be managed in a spreadsheet, or is a tool better suited for this?
While spreadsheets can work early on, they become cumbersome as revenue recognition complexities grow. A dedicated tool can handle these complexities more efficiently and ensure compliance with the latest accounting standards. A spreadsheet approach can lead to errors and delays, especially when dealing with hybrid pricing or bundled products.
Q. How do pricing model changes affect the finance team’s work in revenue recognition?
Pricing model changes introduce new complexities, such as the need to allocate revenue between different products and services. These changes require careful attention to compliance and the ability to adjust processes to reflect new pricing strategies. Tools are essential for automating these adjustments.
Q. What role does flexibility play in evaluating revenue recognition tools?
Flexibility is key in revenue recognition tools because business models often evolve. Tools need to accommodate changes in pricing models, products, and services. A rigid tool that can’t adapt to these changes will cause more problems in the long run, making it important to evaluate tools that offer customization and scalability.
Q. How do third-party tools integrate with existing systems like ERP and CRM?
Integration is critical to avoid data silos. Third-party tools should seamlessly integrate with CRM and ERP systems like Salesforce and NetSuite. This ensures that data flows smoothly across systems without requiring manual uploads or creating discrepancies between tools.
Q. How do you evaluate the flexibility of a tool when implementing a revenue recognition system?
When evaluating a tool for revenue recognition, it's important to assess whether it can adapt to changes in business models and pricing strategies. You should also look for tools that allow for easy updates to rules and configurations without relying on consultants, ensuring that it remains relevant as the business evolves.
Q. What is the importance of automation in the finance function, and how will AI play a role?
A. Automation in finance increases efficiency and reduces human error. With AI, we can expect a more natural interaction with tools, using plain language to make decisions or process transactions. The future of finance tools is likely to involve AI-driven systems that handle complex tasks more intuitively, improving productivity and decision-making.
Q. How do you foresee AI changing the finance function in the next decade?
AI will make finance functions more intuitive by reducing the need for manual inputs. Instead of navigating through complex interfaces, finance teams will interact with systems using natural language to input data and retrieve reports. This will make finance operations faster and more effective, driving smarter decision-making.
Q. What advice do you have for finance professionals as AI continues to evolve in the finance industry?
Finance professionals should stay curious and embrace these technologies. The goal is not to be replaced by AI but to use it to be more effective and smarter. Being open-minded and prepared to learn new tools will help finance teams stay ahead and leverage technology to deliver better results.
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