Finance couldn’t scale the way the business did.

What was the role of Finance in the company before Dana?

Finance was the place where financial truth lived. That is the way it should be. Financial data is sensitive. It includes revenue, costs, margin, sometimes payroll, compensation, commissions, and all the information that explains how the company is really performing.

It is also strategic. So Finance was responsible for producing the numbers, validating them, explaining them, and making sure they were distributed with the right level of control.

In practice, that meant FP&A became the team everyone relied on whenever they needed to understand performance. The CEO relied on us. The board relied on us. Business leaders relied on us. Operational teams relied on us. And that made sense.

But over time, it also became the problem.

Why did access to financial data become so difficult to scale?

Because financial data cannot simply be opened to everyone. People often talk about “self-service analytics” as if access were the only issue. But with financial data, access is never just access.

Different people need different levels of visibility. A business leader may need to see the P&L of her perimeter, but not the full company. Someone inside the same business unit may be allowed to see revenue and gross margin, but not salaries. Another person may need operational KPIs connected to financial outcomes, but not the underlying payroll detail.

Then there is interpretation. Financial data is technical. It requires context. It includes rules, allocations, adjustments, mappings, timing effects, and management views that are not always obvious to someone outside Finance. So even when people have access to data, there is always a risk that they misread it, over-interpret it, or draw conclusions that are not aligned with the logic Finance uses internally.

And finally, producing personalized financial views is hard. Once reporting is prepared for the CEO, the board, or leadership, a lot of detail has usually been aggregated to create a clean and coherent view.

But when an operational manager asks for something very specific, you often need to go back to the lowest level of detail, rebuild the view around that person’s perimeter, apply the right adjustments, and make sure the result remains consistent with what has already been communicated at group level.

That is not a small task. It is not just “sending the data.” It is rebuilding financial understanding for a specific audience.

What did that mean for the Finance team?

It meant that every serious financial question had to come back to Finance. And as the company grew, the number of questions grew with it. That is where the tension appeared. The Finance team is not supposed to grow linearly with the business. A company can double in size without doubling the FP&A team. Everyone understands that.

But the need for analysis does grow with the business. More teams. More countries. More products. More customer segments. More decisions. More questions. So the business needed more financial intelligence every year, but Finance could not become a service desk for the entire company.

At some point, the model stopped scaling.

Where did the pressure come from most?

From everywhere. The CEO would ask questions, and of course we would prioritize them. The board would ask questions too. And that was often the hardest part psychologically. You work extremely hard to prepare a board meeting. You align the numbers, you prepare the story, you anticipate the obvious questions. And then, during the meeting, five, ten, sometimes fifteen additional questions come up.

Some are simple. Some are not. You say, “we’ll get back to you.” Again and again. And when the meeting ends, the work does not end with it. It starts again. You now have a list of additional analyses to prepare, none of which had been planned in the team’s workload. And outside leadership, operational teams also had questions. A sales leader wanted to understand margin by customer segment. Operations wanted to understand the cost impact of delays or staffing decisions. A regional manager wanted to know whether performance was really improving or just benefiting from timing effects.

Those questions were legitimate. But they were rarely urgent enough to jump ahead of CEO, board, closing, forecasting, or reporting priorities. So they waited. Or they never got answered.

What was the human impact inside Finance?

It created frustration on both sides. For the business, the frustration was obvious: they needed answers and could not always get them quickly. For Finance, the frustration was quieter, but very real.

The team was already fully loaded with recurring work: reporting, forecasting, closing support, planning cycles, board preparation, data quality, business reviews. Every ad-hoc request felt like another layer added on top of an already full workload. And that is a dangerous dynamic. Because the team wants to help.

Finance people are not trying to block the business. They want the company to make better decisions. They want operational teams to understand the financial impact of what they do. But when you are constantly underwater, every new question can feel like pressure, even when the question is perfectly legitimate.

As a CFO, you start protecting the team. You prioritize more aggressively. You delay some requests. You ask whether an analysis is really necessary. You try not to stretch the elastic too far. Because you know what happens when good analysts feel permanently overloaded and under-recognized. They leave.

Did you want the business to become more autonomous?

Absolutely. That was the paradox. We wanted the business to become more autonomous with financial information. We wanted operational teams to understand their numbers better, ask better questions, and make better decisions without needing Finance to hold their hand every time.

But we also could not simply distribute raw data and hope for the best. The data was too sensitive. The interpretation was too important. The risk of inconsistent conclusions was too high. And honestly, financial education was part of the problem too.

Many people in the company were excellent operators, but they were not trained to read financial data deeply. They did not always know what to look for, what to question, what was meaningful, or what could be misleading.

So we were stuck. We wanted autonomy. But autonomy without governance would have created chaos.

What did you try before Dana?

We tried the obvious things. Better dashboards. More standardized reporting. More structured business reviews. Clearer access rules. More templates. All of that helped. But it did not solve the structural issue.

Dashboards are useful when the question has already been anticipated. But the real world does not work that way. People do not only need to look at a metric. They need to understand why it moved, what changed, whether it matters, what it means for their perimeter, and what they should do next. And every time the question moved beyond the dashboard, it came back to Finance.

We also experimented with AI tools. That was a clear improvement compared to the old world of manual analysis, spreadsheet exports, and repetitive explanations. But generic AI did not solve the real problem either. If people used AI directly on financial data, we still had to ask: is the data complete? Is it governed? Are the assumptions right? Is the output aligned with our management view? Is confidential information being handled properly?

Finance remained accountable for the quality of the numbers and the conclusions people drew from them. So the question was never simply, “Can AI answer questions?” The question was: Can AI answer financial questions in a way Finance can govern, trust, and scale across the company?

So what changed with Dana ?

Dana changed the model. Finance stayed in control of the financial foundation. We still owned the structure, the logic, the mappings, the access rules, the consistency, and the way financial data was distributed across the company.

But Dana became the layer through which people could interact with that financial intelligence directly. That is the important distinction. Dana did not bypass Finance. Dana extended Finance.

Instead of every question becoming a task for someone in FP&A, many questions could now be answered directly, in context, with the same underlying financial foundation. The business gained autonomy. Finance kept governance. That combination is what made the model scalable.

What changed for operational teams?

They stopped waiting for Finance to translate the numbers for them.

A procurement leader could finally track his own spending in real time, understand how much of his budget had already been consumed, adjust decisions earlier in the year, and avoid discovering months later that most of the budget had already been spent. It also removed the need to maintain separate Excel trackers just to compensate for the lack of visibility. An HR leader could finally track individual compensation, headcount evolution, and workforce costs using numbers fully aligned with Finance. Before Dana, HR and Finance often operated with different definitions of headcount and labor costs.

For example, someone leaving the company might disappear immediately from HR reporting, while Finance would still carry a financial impact for months because of garden leave, severance, or deferred compensation. As a result, HR and Finance could look at the same organization and see different numbers.

With Dana, both teams now operate from the same financial reality, which makes workforce planning, compensation discussions, and hiring decisions much more consistent across the company. The difference was not just speed. It was ownership.

People started engaging with financial consequences much earlier in their decision-making process. Finance became less abstract. It was no longer something that appeared once a month in a reporting deck. It became part of how teams managed their business.

What changed for Finance itself?

The team could finally stop acting as the mandatory relay for every financial question. That does not mean Finance became less important. It became more important. But the role changed.

Instead of spending so much time producing personalized answers on demand, Finance could focus on making sure the financial foundation was reliable, governed, consistent, and useful. We could spend more time on the questions that truly required our judgment, our expertise, and our ability to challenge the business. And we could support more people without proportionally increasing the workload. That is what scaling Finance actually means. Not doing more work with the same team until people burn out. Creating a model where Finance can distribute its intelligence without losing control of the financial truth.

What would you say changed most fundamentally?

Before Dana, Finance had become the bottleneck everyone depended on. Not because we wanted to be. Because we were the only team that could safely distribute and interpret financial information. After Dana, the bottleneck around financial data disappeared. The business became more autonomous. Finance remained in control. And the company started making decisions with a much more consistent understanding of the numbers. That is the real shift. Finance no longer has to choose between protecting the integrity of the data and helping the business move faster.

It can finally do both.