The business controller has traditionally played a key role in explaining financial performance. Why is revenue falling short? What is causing cost overruns? How do the results compare to the budget and forecast?
These questions remain relevant. But they primarily focus on what has already happened. The business controller’s greater added value emerges when the focus shifts from explaining to looking ahead. Not just: why are we deviating? But above all: what does this mean for the coming months, what opportunities do we have, and which choice will yield the best results?
This puts decision support at the center.
The Association for Financial Professionals (AFP) counts decision support among the most important activities within finance business partnering, alongside integrated planning and performance & management reporting. In this context, finance supports the business by providing insight into the financial consequences of various courses of action and by jointly developing business cases.
That sounds logical. In practice, however, it requires more than just a good controller and a good spreadsheet. Decision support places different demands on processes, data, and technology.
From Reporting to Decision-Making
A management report may show that the margin in a product group is declining. Decision support begins with the following question: What are we going to do about it?
Do we raise the price? Do we temporarily accept a lower margin to gain market share? Can we reduce costs? What happens to volume when the price rises? And what effect will these choices ultimately have on revenue, profit, and cash flow?
To answer these questions, the controller must be able to compare various options.
The same applies when investing in a new product. The question isn’t just how much development will cost. Management wants to know what the business case looks like under different assumptions regarding, for example, the addressable market, expected market penetration, revenue growth, and margin. What is the payback period? What is the net present value? And what happens if adoption is a year slower than expected?
Decision support therefore means that Finance doesn’t just present numbers, but quantifies choices.
Automation creates room for the controller
That takes time. And that is precisely where many finance teams still face a significant limitation.
When controllers spend a large portion of their time collecting files, verifying data, combining spreadsheets, and correcting formulas, there is less time left for analysis and consultation with the business.
Automation changes that balance.
Consider, for example, automatically importing actuals, consolidating data from different entities, calculating allocations, updating forecasts, or flagging variances. Work that previously had to be done from scratch every month can be increasingly standardized and automated.
That doesn’t mean the controller disappears from the process. On the contrary. The focus shifts from producing numbers to interpreting them.
AI can also play a role here. Technology can identify variances, recognize patterns, speed up calculations, and propose possible scenarios. But a decision isn’t based solely on a model. Context remains essential: Is a decline in revenue temporary or structural? Is a cost savings measure operationally feasible? What level of risk is the organization willing to accept?
Automation thus primarily supports the preparation of decision-making. The final assessment remains a human task.
Connectivity determines the quality of decision support
Moreover, good decision support doesn’t start with the dashboard, but with the data behind it.
Financial decisions are, in fact, increasingly less based exclusively on financial data. A forecast, for example, may depend on sales volumes from CRM, personnel data from HR, order information from ERP, contract information, production capacity, or operational KPIs.
When this information is scattered across different applications and every analysis begins with exports and Excel files, delays occur. Furthermore, the risk increases that different departments will be working with different versions of the same reality.
Connectivity is therefore a key requirement for modern Planning & Control.
That does not mean that all information must, by definition, be stored in a single application. It does mean, however, that relevant systems are interconnected, definitions are consistent, and data is made available for planning and analysis in a controlled manner.
This creates a chain:
operational development → financial impact → forecast → scenario → decision
For example, a change in sales forecasts can have an immediate impact on revenue, capacity, personnel costs, liquidity, and earnings. The controller then does not have to manually reconstruct the relationship between these components every time.
This makes decision support not only faster but, above all, more consistent.
From a Single Forecast to Multiple Scenarios
Good connectivity also enables a different approach to planning.
A traditional budget provides a single forecast. But management decisions rarely take place in a world where only one future is possible.
Suppose an organization is considering introducing a new product. In a business case, various assumptions can be modeled:
- an addressable market of 12,500 organizations;
- an expected market penetration of 6.5% in year three;
- revenue of €4.1 million in year three;
- an initial investment of €1.8 million;
- a payback period of 2.6 years;
- a positive NPV of €2.3 million.
Things get more interesting when the assumptions change. What happens if market penetration in year three is 4% instead of 6.5%? What if implementation costs turn out to be 20% higher? Or what if the average revenue per customer actually grows faster?
Then a business case ceases to be a static document and becomes a decision-making model.
The question shifts from “Is this business case valid?” to “Under what circumstances is this a good investment?”
That is exactly where a business controller can add value.
Good tools enable iteration
Spreadsheets are flexible and remain useful for many analyses. But as models grow larger, more people work on them, and data needs to be updated more frequently, familiar limitations arise: version control, manual links, formulas that are difficult to verify, and models that become heavily dependent on the person who built them.
FP&A platforms are designed to organize planning, forecasting, analysis, and scenario modeling in a more structured way.
A solution such as Unit4 FP&A, for example, supports integrated financial planning, scenario planning, variance analysis, and reporting. Scenarios can be run through the income statement, balance sheet, and liquidity, among other areas, while financial and operational data can be used within the same planning environment.
The main benefit here isn’t simply replacing Excel with another screen.
The benefit arises when an organization establishes a shared model of reality. Actuals, plans, forecasts, and scenarios all use the same definitions and underlying drivers. If an assumption changes, the model can calculate the resulting impact.
This makes iteration much simpler.
For example, a sales manager can submit a new sales forecast. Finance can immediately analyze what this means for margins and cash flow. HR can assess the capacity required to meet those targets. Management can then compare different scenarios side by side.
Planning thus becomes less of a periodic finance process and more of a collaborative management process.
The Business Controller as a Business Partner
Ultimately, this also changes the role of the controller.
The controller who primarily produces reports often only comes into the picture after a development has already taken place. The controller who provides decision support is involved in an issue at an earlier stage.
Not:
“These are last month’s results.”
But:
“If this trend continues, this is where we’ll end up by the end of the year. We have three realistic options. These are the financial implications, these are the key uncertainties, and based on that, option B seems to be the best choice.”
That is finance business partnering in practice.
Financial expertise is still essential for this. But insight into the business, communication skills, and the ability to challenge assumptions are also becoming more important.
Technology won’t take over that role. On the contrary, good technology ensures that the controller spends less time collecting and reproducing information and can devote more time to the discussion that must follow.
From Insight to Action
Many organizations now have access to large amounts of data and increasingly sophisticated dashboards. But more information does not automatically lead to better decisions.
To achieve that, the next step must be taken.
Automation reduces the time required for routine work. Connectivity brings financial and operational information together. FP&A tools make it possible to quickly run through plans, forecasts, and scenarios.
The business controller connects these elements.
Not by making management’s decisions for them, but by highlighting the available options, the underlying assumptions, and the financial consequences of each choice.
As a result, Planning & Control shifts from looking back to looking ahead—and from reporting numbers to supporting decision-making.