Lost in translation: How one engineer learned to speak CFO – Epilogue
Synopsis
Building a simulation business case isn’t only about having the best technology, it’s about explaining its value in a language decision‑makers understand. Marcus wasn’t trying to change his company. He just wanted better tools to do his job. A simulation platform that could model the complex thermal-electrical interactions his current software couldn’t handle. The kind of technology that would turn weeks of guesswork into days of certainty.
He had the technical proof. He had the vendor demos. He even had a business case, at least he thought he had. What he didn’t have was the ability to speak CFO.
This story follows an engineer who discovered that translating simulation capabilities into financial outcomes like ROI, NPV, and payback period is what turns promising ideas into approved investments.
This is a fictional story, with fictional characters working for a fictional company, but it’s built on real experiences. From engineers in various industries including automotive, aerospace, marine, heavy equipment and industrial machinery, and dozens of others who’ve fought the same battle. Engineers who learned that speaking two languages fluently, technical and financial, isn’t selling out.
This is the epilogue of the series Lost in translation: How one engineer learned to speak CFO.
Read here chapter 1, chapter 2, chapter 3 and chapter 4.
Eighteen months later
The simulation platform had expanded to twelve licenses across the Aachen site. The financial results exceeded even the revised projections: €680,000 in measured savings in year one, tracking toward €890,000 in year two.
But the numbers weren’t what Marcus was most proud of.
He was proud of the controls engineer who’d been skeptical in the first meeting, who now ran the monthly simulation user group and had published a paper on multi-domain motor optimization.
He was proud of the templates library, which had grown to twenty-three standardized workflows, contributed by engineers across the department.
He was proud of the office hours, which had evolved into a community of practice where senior and junior engineers collaborated on increasingly complex problems.
And he was proud of the email he’d received last week from the company’s CTO, asking him to present at the annual engineering conference on “How to Build a Business Case That Actually Gets Approved.”
The presentation was in three weeks. Marcus had already started preparing.
This time, he knew exactly what language to speak.
Four years later
Marcus stood in front of the executive leadership team. Not as a nervous engineer pitching a software license, but as the newly appointed Director of Digital Engineering for Stratline Powertrain.
The promotion had come six months ago, recognition for what had started as a single simulation platform and had grown into a comprehensive digital transformation. The Aachen site now had forty-two licenses across engineering, testing, and manufacturing. Other company sites in Belgium, China, and Mexico had adopted the same approach, using Marcus’s business case template and capability-building model.
But today’s presentation wasn’t about what they’d accomplished. It was about what came next.
“We’re seeing our competitors struggle with the transition to electric powertrains,” Marcus said, pulling up a market analysis. “Development cycles are compressing. Complexity is increasing. Traditional prototype-and-test approaches can’t keep pace.”
He showed the data. Competitors spending eighteen months on thermal management development. Supply chain partners missing integration deadlines. Market share shifting to companies that could deliver validated designs faster.
“We’re not struggling,” Marcus continued. “Our average development cycle for battery thermal systems is nine months, which is half the industry average. Our first-prototype success rate is 87%, compared to industry average of 52%. We’re winning contracts because we can guarantee performance before we build hardware.”
The CEO leaned forward. “And you’re attributing this to the simulation platform you championed four years ago?”
“Not just the platform. The capability we built around it.” Marcus pulled up the model library: over three hundred validated simulation templates, covering everything from motor electromagnetics to gearbox acoustics to battery safety. “We have four years of multi-domain models, validated against physical tests, continuously refined by forty-two engineers across multiple sites.”
He paused. “That library is about to become exponentially more valuable.”
Marcus pulled up the next slide: AI-Assisted Engineering Design.
“The AI revolution in engineering isn’t about replacing engineers. It’s about augmenting them with tools that can explore design spaces faster than humans can. But AI models need training data: high-quality, validated, physics-based models that represent real system behavior.”
He showed examples. AI algorithms trained on their motor thermal models, generating optimized cooling designs in minutes instead of weeks. Machine learning models that predicted battery degradation based on their validated electrochemical-thermal simulations. Generative design tools that used their structural-acoustic models to create gearbox housings that were lighter and quieter than anything a human designer would have conceived.
“Our competitors are starting from zero,” Marcus said. “They’re trying to build AI capabilities without the underlying model library to train them on. We have four years of validated, multi-domain models ready to feed into AI systems. We didn’t plan this, we built the simulation capability to solve today’s problems. But it positioned us perfectly for tomorrow’s opportunity.”
“Our competitors are starting from zero”
Marcus
The CTO, who’d been taking notes, looked up. “What’s the investment required?”
Marcus pulled up the business case. He’d learned a lot in four years, but the fundamentals hadn’t changed: NPV, IRR, payback period, all calculated with conservative assumptions and validated against actual data.
“€2.3 million over two years for AI platform licenses, cloud computing infrastructure, and specialized training. Projected NPV of €12.7 million over five years. IRR of 287%. Payback period of eight months.”
“And the competitive advantage?” the CEO asked.
“Unquantifiable in pure financial terms, but measurable in market position,” Marcus said. “We become the powertrain supplier that can deliver custom-optimized designs in weeks instead of months. That can guarantee performance before prototype. That can explore design spaces our competitors can’t even imagine.”
He pulled up the final slide, a quote from an automotive OEM that had recently signed a major contract with Stratline Powertrain: “You’re the only supplier who showed us ten optimized design variants before the kickoff meeting. Everyone else is still asking for requirements.”
“That’s the future,” Marcus said. “And we’re already there.”
After the presentation, Marcus walked back to his office, larger now, with a window overlooking the engineering labs where he’d spent those late nights four years ago, learning to build business cases and run simulations.
Elena met him in the hallway. She’d been promoted too: Senior Finance Manager, and responsible for evaluating all major technology investments across the company.
“They approved it,” she said. “Full €2.3 million, plus discretionary budget for expansion if the pilot results are strong.”
Marcus smiled. “You sound surprised.”
“I’m not. You’ve earned credibility. Four years ago, you were an engineer who didn’t know what NPV meant. Now you’re the benchmark for how to drive technology adoption.” She pulled out her tablet. “The CEO asked me to document your approach as a case study for other initiatives. Mind if I interview you?”
“What do you want to know?”
“What you’d tell an engineer today who’s in the same position you were four years ago. Convinced they have a solution that could transform how the company works, but no idea how to get it approved.”
Marcus thought about that first rejection, the CFO’s dismissal, the months of learning to speak a language that wasn’t native to him.
“I’d tell them that engineering excellence isn’t enough,” he said. “You have to translate technical value into business value. Learn to calculate NPV, even if it feels like a foreign language. Build cases on data, not passion. And most importantly, prove it scales. Nobody funds a solution that only works when you’re personally running it.”
Elena made notes. “And the AI opportunity, did you see that coming four years ago?”
“Not at all. I was just trying to run thermal simulations faster.” Marcus looked out the window at the labs below. “But that’s the thing about building real capability instead of point solutions. You don’t just solve today’s problem. You create options for tomorrow’s opportunities.”
His phone buzzed. An email from an automotive industry publication: Request for interview – How Stratline Powertrain Became the Industry Benchmark for Digital Engineering.
Another from a competitor who’d heard about their AI initiative: Would love to learn about your simulation model library approach.
And one from a university professor: Our engineering students are studying your business case methodology. Would you be willing to guest lecture?
Marcus forwarded them to his assistant to schedule. Four years ago, he’d been fighting to get a single license approved. Now he was fielding requests to explain how they’d become an industry leader.
The transformation hadn’t come from the simulation platform, or the AI tools, or any single technology.
It had come from learning to speak engineering- and business language fluently enough to translate between them. From building capability that scaled beyond one person, one project, one department. From proving value with data, not promises.
And from understanding that the best business cases don’t just justify an investment. They create a foundation for the next opportunity, and the one after that.
Marcus looked at his calendar. Next week: AI platform kickoff meeting. The week after: presentation to the board on digital engineering strategy. The month after: keynote at an industry conference on the future of powertrain development.
Four years ago, he’d wanted to prove that better simulation tools could change how they worked.
He’d proven something bigger: that engineers who learn to speak the language of business don’t just get their projects approved.
They shape the future of their companies. And sometimes, their industries.
Ready to build your own simulation business case?
Marcus’s journey mirrors real transformations happening across the automotive and manufacturing industries. Engineers at real companies like Certia, Practicon, and Cummins have successfully navigated the path from technical vision to CFO approval, and are now reaping the competitive advantages of advanced simulation capabilities.
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