72% of Firms Still See Relief Ahead as Forecasting Confidence Slips

Why It Matters

Reduced confidence signals tighter capital allocation and shorter planning horizons, prompting finance leaders to adopt more dynamic forecasting approaches. The trend highlights sector‑specific risk exposure that can affect pricing, cash flow and investment decisions.

Key Takeaways

• 27% of firms report high uncertainty in March 2026
• 72% expect uncertainty to improve in 12 months
• Goods firms report 47% high uncertainty, outpacing services
• Uncertainty adds 2.9% of revenue cost; high‑uncertainty firms 6.2%
• Finance leaders need agile forecasting models for volatile markets

Pulse Analysis

The latest PYMNTS Intelligence report underscores a subtle but meaningful shift in corporate forecasting sentiment. While a solid majority of executives still anticipate a decline in uncertainty over the next twelve months, the optimism has cooled from 78% in January to 72% in March. This dip reflects a broader transition from tariff‑driven disruptions to heightened geopolitical tensions, forcing finance teams to navigate a more complex risk landscape. The data also reveal that goods‑oriented firms are disproportionately affected, with nearly half reporting high uncertainty compared with their service‑sector peers.

Financial implications are stark. The study estimates that uncertainty costs firms an average of 2.9% of revenue, but companies operating under the highest uncertainty see that figure more than double, at 6.2%. Those numbers translate into tangible pressures on pricing strategies, cash‑flow forecasting, inventory management, and capital‑expenditure planning. As a result, many organizations are tightening controls, shortening planning windows, and scrutinizing investment decisions more closely. The sector‑specific exposure suggests that supply‑chain volatility and input‑cost fluctuations remain critical pain points for manufacturers and distributors.

For finance leaders, the takeaway is clear: traditional static budgeting models are no longer sufficient. Companies need forecasting frameworks that can accommodate rapid scenario shifts, integrate real‑time data, and deliver actionable insights under pressure. Leveraging advanced analytics, AI‑driven predictive tools, and rolling forecasts can help firms stay ahead of emerging shocks while preserving strategic agility. In a market where volatility is the new normal, the ability to model multiple outcomes quickly will differentiate resilient businesses from those that falter.