How Sirion traded fragile, spreadsheet-based finance for enterprise-level FP&A with Drivetrain

When Sirion implemented NetSuite a few years ago, Yati Agarwal, the company’s Chief Financial Officer, did not anticipate the complexities that ensued. Her lean finance team soon found themselves overwhelmed with spreadsheet crashes, version control issues, GL clean-up, vendor-level mappings, and multi-version forecasting.

She knew that in order to optimize her team's skills and time, she would need to implement FP&A software to eliminate the burden of manual data operations and the constant threat of their Excel models and workflows crashing.

The company’s spreadsheet-based FP&A had become untenable

The core operational problem was the inherent complexity in the company’s Excel spreadsheets, which frequently crashed under the weight of it. And implementing NetSuite didn’t eliminate the finance team’s need for Excel, and to make matters worse, that process made working with them even more difficult. Agarwal said, “Even with NetSuite implemented, the entire financial planning and modeling process was very, very manual.” For example, the finance team had to do a lot of work on the data in the GLs for each of their entities in order to work with it in NetSuite. To do that, they first had to download the GL for each entity and use Excel to create a common key between them. Then they had to figure out the mapping on MIS.

Customizing the data at a vendor by vendor, payment by payment level across seven geographies was extremely difficult. The mappings were very, very complex, and Excel just wasn’t cut out to manage those. This and all the other data challenges came to a head right before a board meeting. The Excel file crashed and all the data the finance team had prepared to present to the board was wiped out and would only open in recovery mode.

This is the kind of thing that keeps CFOs and their teams up at night. Afterward, Agarwal and her team were constantly aware of the fragility of their system and the prospect of recurring data loss amid the backdrop of looming board meetings and corrupt files. This only added to the Excel burden. Agarwal said that in response, her team was “starting to do monthly, quarterly forecasts, and then keeping so many versions and having the backup data for each version and then connecting with the payroll and with the headcount—it was just becoming a nightmare.”

This spreadsheet-induced crisis wasn't a NetSuite issue—it was simply that Sirion had grown to the point that using NetSuite with Excel, with all its inherent limitations, had created an unsustainable process riddled with manual workflows.

Rigid spreadsheets and manual workflows undermining data credibility

Excel is known for its flexibility. But, when businesses like Sirion grow in their complexity, they often start bumping (or, in this case, crashing) into its limitations. For Sirion, this not only led to fragile workflows, it also created accountability gaps. Agarwal explained, “Excel gives you only so much flexibility. You can just go and edit stuff on the fly, and you get tempted to type in numbers there. When you have to explain the logic after two years, you don't remember you added 220 there.”

Structuring costs and preparing accurate data that could be confidently presented to the board and investors was always a challenge. This was, in part, because spreadsheets are static in nature. In order to ensure the data is up to date for financial reporting requires a ton of manual effort.

Agarwal said that, when it came to financial reporting, there were a lot of things Excel couldn’t do, such as bifurcating costs into COGS and OpEx or slicing and dicing the data to present it in different ways. “Let's say I wanted to see travel across the company. I couldn't have done it on Excel because, in Excel, my dimensions used to get limited,” she said. Recalling the work involved in getting the data organized to present to the board, Agarwal said, “I had to take the GL maps per the NetSuite data, and then classify them into multiple categories. Being able to figure it out was not that easy.”

Agarwal knew that without an FP&A tool in place, and in the presence of fragile and static Excel spreadsheets, maintaining their financial models, not to mention their credibility with the board and investors, would always be a challenge.

Complexities of available enterprise FP&A tools and adoption barrier

Agarwal decided to evaluate a few FP&A tools. However, she soon realized the adoption risk of the larger FP&A tools. The demos confirmed her doubts. One prospective vendor she contacted refused to build a proof of concept.

Implementation and ease of use were key criteria for Agarwal because she knew that choosing a complex platform that comes with long onboarding times would further burden her already-stretched team with training and take longer to realize any value. So, she focused her search on finding a platform that had the right mix—an easy-to-use UI and enterprise-level capabilities, without the added headache of implementation specialists and customer support. And after her experience with the vendor refusing to do a POC, finding a service provider that would partner in a way that would feel like an extension of her small finance team also became part of her criteria.

The Solution

When Alok Goel, Co-founder and CEO/CFO at Drivetrain, reached out to Agarwal, she was already evaluating enterprise FP&A tools. Agarwal and Goel had several professional connections in common, and when she learned that a member of her team had used Drivetrain at his earlier workplace, she decided to explore the platform.

After seeing the POC and how quickly Drivetrain was able to build it, Agarwal knew the company and platform could meet her three core requirements:

• An approachable UX for a mid-skilled and small finance team
• Quick proof-of-concept builds that showed immediate potential
• A collaborative implementation cadence that set the tone for continued partnership

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How Drivetrain Helped

1. Faster month-end closures—involving data verification and analysis

With Drivetrain’s native integration for NetSuite, Agarwal’s team was able to easily connect the two platforms to automate data consolidation and validation. This significantly reduced the time required for the monthly close and reporting process by eliminating all the cumbersome manual data operations. With their data reliably flowing in from NetSuite the team was able to view everything in Drivetrain to verify it.

Monthly closures now happen on the accrual planned date—a deadline routinely pushed back two weeks or more due to all the data consolidation and verification challenges when using spreadsheets to do the work.

Today, the first cut of the data is ready for verification by the 10th of each month, and the finance team only has to spend a couple more days on their analysis and reporting. With Drivetrain, the ever-present spreadsheet chaos and month-end fire-fighting was replaced with a predictable cadence built on reliable data.

2. Dynamic and flexible financial models without hard-coded formulas

Drivetrain also enabled Agarwal and her team to replace the rigid, hard-coded formulas in their Excel models with dynamic allocation models that allow for exceptions and overrides on the formulas while ensuring auditability. Agarwal explained, “With Drivetrain, there's more flexibility, and that helps us in planning and in actualization because then we don't have to hard code the formula. We can say 50% of this headcount is going here, 50% is going there, etc. It gives us a good way to override our own formulas. Formulas or concepts are set up for the baseline, and whenever there's exception handling, we are able to manage the exceptions on the surface.”

In addition to providing more flexible, agile modeling, Agarwal’s team was able to answer questions and field requests faster. What used to take two days of manual work now just takes a few clicks.

3. Peace of mind with diligence-ready reporting discipline

For Agarwal, one of Drivetrain’s most valuable contributions, beyond the easy integration with NetSuite and other key business systems and the robust modeling capabilities, was the structural discipline the platform encouraged in terms of her team's thinking and analytical approach.

As the finance team started using Drivetrain, they began to feel more confident about their data. Now, even in the face of pushback, they could leverage Drivetrain to quickly provide reliable data to defend their assumptions.

Agarwal witnessed the pay-off firsthand when investors requested historical pipeline data which, before adopting Drivetrain, could have become a major crisis.