For years, finance leaders have debated when the time would come to embed Artificial Intelligence (AI) into their operations. That time is no longer in the future. AI has become a business imperative—a driver of efficiency, agility, and competitive advantage for CFOs under mounting pressure to deliver more with less.
This is not just theory. It’s happening today. And Rinnai Australia is a standout example.
In just 12 months, Rinnai has modernised its finance platform, embedding IBM Planning Analytics (PA) with support from Octane Software Solutions. The result? A finance function that has freed up 40 hours per week of manual effort, cut reporting cycles from weeks to four days, reduced reliance on spreadsheets by 50%, improved staff morale, and positioned the business for AI-driven forecasting, predictive models, and even faster M&A integration.
This story, and what other CFOs can learn from it, will be at the centre of the upcoming CFO Lunchtime Live Webcast, hosted by CFO Magazine’s James Solomons, featuring Dilend Chawda (Rinnai Australia), Darksha Nadesewaran (IBM ANZ), and Amendra Pratap (Octane Software Solutions).
Like many growing businesses, Rinnai faced the challenge of fragmented finance processes. Over the years, the organisation had grown in complexity through multiple subsidiaries and M&A activity. Finance was juggling different tools—from Cognos and TM1 to Essbase and Oracle OACS—with high spreadsheet dependency for budgeting and reporting.
The result was:
Long reporting cycles: Subsidiaries took weeks to close, delaying group-level insights.
Spreadsheet chaos: Dozens of versions, late-night reconciliations, and version-control headaches.
3-month budgeting cycles: A bottom-up approach involving countless files, links, and manual inputs.
Staff fatigue and low morale: Finance teams were bogged down in reconciliation and data wrangling rather than analysis.
The system simply wasn’t fit for a fast-moving organisation that needed real-time insights, scenario planning, and agility in the face of market volatility.
1. Building a Modern Platform with IBM Planning Analytics
In mid-2024, Rinnai partnered with Octane SoftwarIn mid-2024, Rinnai partnered with Octane Software Solutions to modernise its finance platform with IBM Planning Analytics. Within weeks, the first modules were live:
August 2024: Group month-end reporting (P&L, Balance Sheet).
October 2024: Product profitability reporting—allocating operating profit down to individual products.
November 2024: Logistic demand planning—12-month SKU-level forecasting.
December 2024: Budget suite for 2025—integrated with sales, costing, workforce, capex, and manufacturing recovery cubes.
June 2025: Subsidiaries fully integrated—Xero trial balances from subsidiaries consolidated into group reporting.
This was a swift, phased deployment that made transformation tangible within months, not years.
2. Quantifiable Benefits Delivered
The outcomes have been both immediate and measurable:
40 hours/week saved: Automation of data consolidation and reporting removed manual wrangling.
Reporting cycle cut to 4 days: Down from weeks for subsidiaries.
50% fewer spreadsheets: Dramatically reducing version errors and reconciliation headaches.
Budgeting accelerated: From a painful 3-month cycle to a streamlined, collaborative process.
Staff morale uplift: Finance staff moved from data entry to analysis, improving job satisfaction and retention.
The shift has not just been technical—it has been cultural. Finance is no longer the bottleneck, but the enabler.
3. AI Foundations and Next Steps
Rinnai’s transformation has built the foundation for AI adoption. Already, the company is:
Running predictive models for working capital management.
Leveraging IBM PA Assistant (built on watsonx) for natural language queries, commentary automation, and outlier analysis.
Piloting agentic AI assistants (Watson Orchestrate) to automate workflows.
Experimenting with generative AI in Planning Analytics and Oracle—using natural language prompts for “Ask Rinnai” use cases.
From Rinnai’s journey, there are clear takeaways for other finance leaders:
Be bold and act early: Legacy systems will only get more expensive and harder to fix.
Start with a strong foundation: Modernising reporting, budgeting, and forecasting enables AI to scale.
Quantify benefits: Measure and communicate outcomes like hours saved, cycle time reduced, and morale lifted to keep momentum.
Embed governance and culture: AI adoption requires upskilling teams and embedding robust controls.
Think strategically: Modern platforms don’t just support finance—they enable faster M&A integration, strategic planning, and long-term growth.
What stands out most from the Rinnai story is how the role of finance has shifted. With automation and AI taking on manual processes, the finance team is now focused on:
Providing forward-looking insights through predictive analytics.
Partnering with the business on strategy, pricing, and resource planning.
Supporting growth through faster M&A integration.
Driving continuous improvement through new AI features and enhancements.
Finance has moved from a reactive scorekeeper to a proactive strategist.
The Rinnai story proves that AI in finance is not a distant dream—it’s a present reality. With vision, leadership, and the right partners, CFOs can deliver faster, smarter, and more resilient finance functions that directly enable business growth.
The question is not if finance leaders should adopt AI, but how quickly they can embed it into their organisations.
Don’t wait until it’s harder and more expensive. Join us for this webcast and see how you can start your journey today.