Case Study 7: Driver-Based Budgeting & Advanced Scenario Forecasting (Infor)

Budgeting took too long.
Scenarios were hard to model.
And decisions lagged behind reality.

A mid-sized manufacturing and distribution company relied on large, spreadsheet-driven budget models built quarterly. Each cycle required 20–30 hours of manual data entry, formula checks, and consolidation across departments.

In a stable environment, this was manageable.
In a volatile one, it was risky.

Raw material prices fluctuated. Labor rates changed. Demand shifted quickly. Yet finance couldn’t easily answer basic “what-if” questions without rebuilding models from scratch.

By the time forecasts were updated, assumptions were already outdated.

Why This Was Really a Modeling Problem

This wasn’t about budgeting discipline.
And it wasn’t a lack of financial knowledge.

The real issue was the structure of the model.

The company already had:

• Actuals and commitments in Infor
• Operational drivers like volumes, headcount, and production rates
• Department-level accountability

But spreadsheets tied everything together with fragile formulas. One change rippled unpredictably. Scenario planning was slow. Collaboration was painful. And errors were hard to detect.

Finance spent more time maintaining models than using them.

Quantitative Impact of the Legacy Approach

Each quarterly budget consumed up to 30 hours of senior finance time.

That meant:

• Less time for scenario planning
• Fewer decision-ready forecasts
• Limited ability to respond quickly to cost inflation or demand swings

The cost wasn’t just time — it was missed agility.

Solution Overview

We built a custom driver-based FP&A platform, fully integrated with Infor.

Instead of budgeting line by line, the model shifted to business drivers.

Users entered key assumptions — volumes, headcount, production rates, material costs — and the system automatically calculated:

• P&L
• Balance sheet
• Cash flow

Budgets, forecasts, and scenarios updated instantly — without rebuilding spreadsheets.

How the Model Works

The system pulls real-time actuals, commitments, and operational data from Infor.

From there:

• Drivers replace manual formulas
• Financial statements are calculated automatically
• Scenarios are created by adjusting assumptions — not rebuilding models

Finance teams can finally answer:

“What happens if costs increase 5%?”
“What if demand drops next quarter?”
“How does this affect cash and working capital?”

In seconds, not days.

Key Capabilities

• Unlimited scenario planning
  Base, upside, downside, inflation, and custom scenarios with instant side-by-side comparisons.
• Driver-based modeling
  One set of assumptions drives all financial statements — no broken formulas.
• AI-assisted forecasting
  Historical trends and driver correlations suggest baseline forecasts and surface anomalies early.
• Real-time collaboration
  Multiple users work simultaneously with version control, comments, and audit trails.
• Interactive dashboards
  Dynamic charts, variance analysis (budget vs actual vs forecast), sensitivity testing, and what-if simulations.
• Rolling forecasts & alerts
  Forecasts update automatically as actuals change, with alerts when assumptions drift.
• Built-in validation controls
  Guardrails prevent formula errors and protect data integrity.

The experience was designed to feel simple — even as models became more powerful.

Implementation Approach

Weeks 1–3
Infor API integration, historical data import, driver-based modeling engine, validation controls, and initial prototypes

Weeks 4–5
Scenario management, collaboration features (locking, comments, audit trails), and usability refinement

Week 6
Custom reporting, advanced what-if simulations, AI forecasting logic, and dashboards

Weeks 7–8
User training, performance optimization, parallel testing vs spreadsheets, and full rollout

Results

The impact was immediate:

• Quarterly budgeting time reduced from 20–30 hours to under 8 hours
• 115+ hours saved annually
• Faster, more accurate forecasts in volatile conditions
• Stronger scenario planning and decision confidence
• $11,500+ in annual savings from labor efficiency and improved financial agility

Most importantly, finance moved from spreadsheet maintenance to forward-looking decision support — helping the business plan faster, adapt sooner, and allocate resources with confidence.