Your Financial Forecasting Is Broken. Here’s How To Fix It.

Financial forecasting is one of the most important things your finance team does, and one of the hardest to get right. You can spend weeks poring through historical data, only to find that your forecast no longer reflects reality a few months later.

The good news is that forecasting accuracy is not just a matter of working harder. It is a matter of working differently.

Here’s how to build a financial forecasting process that holds up.

Many finance teams rely solely on historical data and linear analysis when building annual financial forecasts. The problem is that those forecasts can become irrelevant within months, whether due to market volatility, shifts in consumer behavior, or conditions no one saw coming.

As McKinsey Partner Ankur Agrawal puts it, finance teams are often not explicitly discussing how external factors and impending market shifts could affect forecasts. The pandemic made this painfully clear for organizations that had built their projections entirely on prior year performance.

A stronger approach combines internal data with external signals and end-market trends. Specifically, building scenario analyses that account for unexpected and worst-case outcomes gives your team the ability to respond proactively when things do not go according to plan.

What this looks like in practice

• Build rolling forecasts that incorporate external market indicators alongside internal data
• Run scenario analyses that include best-case, base-case, and worst-case outcomes
• Use a continuous planning platform like Planful to build what-if scenarios in minutes, so your team can focus on analysis rather than scrambling to rebuild models under deadline pressure

Financial forecasting does not happen in a vacuum. Finance teams need visibility into other departments’ performance and goals to build accurate projections. When data is siloed across Sales, Marketing, HR, and Operations, it becomes tempting to fill the gaps with guesswork.

The better path is to open lines of communication between Finance and the rest of the business. As Paul Rogan, former Group CFO at Challenger Financial Services, explains, the key is how you react when a forecast needs to change. That means getting executives and leadership actively thinking about both upside and downside scenarios, and responding with intention.

Connecting with your CIO, CMO, COO, CTO, and CHRO ensures that operational activity is aligned with financial goals.

How Planful supports cross-functional collaboration

Planful’s FP&A platform helps teams break down data silos through robust two-way data integration. You get access to financial and non-financial data from ERP, HCM, CRM, data warehouses, spreadsheets, and more, all from a single source of truth. Every input is traceable to its source, and collaboration across teams happens directly within the platform.

Financial forecasting is time-consuming by nature. Many CFOs acknowledge that their forecasts are not particularly accurate and that the process takes far too much time.

Automation addresses both problems. It improves data accuracy and reduces the manual burden that leads to finance team burnout. KPMG found that 42% of respondents identified automating the financial forecasting process as their top priority.

Automation does not replace human judgment. It frees your team to focus on the high-value work that requires it: evaluating data, identifying trends, and translating insights into business recommendations.

How Planful reduces forecasting cycle times

Planful uses predictive technology to automate repetitive data entries, eliminating the manual copying and pasting that slows teams down and introduces errors. The result is forecasts built in hours, not days.

As Mike Petrauskas, Manager of FP&A at Elgin Equipment Group, describes it, Planful has eliminated much of the time previously spent consolidating Excel spreadsheets, saving plant controllers, the corporate controller, and his team hours every month.

In today’s environment, historical data alone is not enough. Accurate financial forecasting requires external context, cross-functional collaboration, and the right technology to bring it all together. Trying to manage all of that manually is possible, but it is slow, error-prone, and unsustainable.

A modern FP&A platform like Planful supports continuous planning, scenario modeling, and automation so your team can respond to market shifts faster and spend more time on the analysis that actually moves the business forward.

 

• Financial forecasting breaks down when it ignores external factors like market volatility and shifts in consumer behavior
• A modern forecasting process depends on collaboration, shared data, and continuous scenario planning
• Automation reduces forecasting cycles from weeks to days and frees Finance to focus on analysis rather than spreadsheets

---

Ready to build a more accurate, efficient financial forecasting process?

Get started with Planful demo

---

Why is the financial forecasting process so often inaccurate?

Forecasting breaks down when teams rely only on historical data and linear trends. External factors like market shifts, changes in customer behavior, and macroeconomic conditions can quickly make those forecasts obsolete. Data silos across Sales, Marketing, HR, and Operations also weaken assumptions and reduce overall accuracy.

How can you improve the financial forecasting process at your company?

Start by combining internal data with external indicators and running scenario analyses that test best-case, base-case, and worst-case outcomes. Make forecasting cross-functional by bringing in input from business partners rather than working in isolation. Then layer in automation to reduce manual data work and free your team to focus on analysis and decision support.

How does Planful help modernize the financial forecasting process?

Planful centralizes financial and operational data so teams can build forecasts from a single source of truth. The platform supports continuous planning, scenario modeling, and automation of repetitive tasks, reducing cycle times and improving forecast reliability. Finance spends less time consolidating inputs and more time guiding business decisions.