Lost in translation: How one engineer learned to speak CFO – Chapter 2

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 chapter 2 in the series Lost in translation: How one engineer learned to speak CFO.
The story starts here.

Chapter 2: The Proof

The finance analyst’s name was Elena, and she terrified Marcus.

Not because she was intimidating, she was friendly actually, with a disarming smile and a habit of doodling in the margins of spreadsheets. She terrified him because within the first ten minutes of their meeting, she’d dismantled his entire €180,000 savings calculation with three questions.

“So not €12,000 saved per prototype. Partial savings, timing-dependent.” She made a note. “And this assumption about simulation time, you’re saying the new tool cuts analysis time by 60%. Based on what data?”

“The vendor’s case studies showed…”

“Vendor data.” Elena smiled sympathetically. “Marcus, if I brought vendor promises to the CFO, she’d escort me out personally. We need our data. From our projects. With our engineers.”

Marcus slumped in his chair. “So my whole analysis is worthless.”

“No.” Elena turned the laptop back to him. “Your instinct is right. The value is probably there. But we need to prove it, not assume it. You still have access to that trial license?”

“Two more weeks.”

“Then let’s run an experiment.”

“So my whole analysis is worthless.”

Marcus

The experiment was simple in concept, brutal in execution: take a real project currently in progress, run a parallel analysis using the simulation platform, and measure the difference.

Marcus chose the thermal management system for the new battery pack. The team was three weeks into their analysis using the traditional approach with separate thermal models, separate electrical models, manual iteration between them, constant reconciliation of assumptions.

He rebuilt the same analysis in the integrated platform. Multi-domain from the start. Thermal-electrical coupling handled natively. Battery state-of-charge dynamics linked directly to thermal behavior.

It took him four days of late nights. The traditional approach team was still iterating.

On day six, Marcus had results that matched the physical test data from the previous generation system within 5%. The traditional approach team was still debugging inconsistencies between their separate models.

On day eight, Marcus ran fifteen design variations to optimize cooling flow rates. The traditional team had just aligned their baseline case.

Elena sat beside him, stopwatch app open, logging every hour. “This is good, Marcus. This is really good.”

By the end of week two, the numbers were undeniable. The integrated simulation had delivered the same quality of results in 40% of the time. Marcus had logged 32 hours. The traditional approach team had logged 76 hours and counting.

Elena pulled out her laptop. “Now comes the hard part. We need to turn this into a proper financial analysis.”

“I already calculated the savings: €89,000 based on the time reduction.”

“That’s a benefit estimate. A business case needs more.” She opened a template that made Marcus’s eyes glaze over. “We need to calculate NPV, IRR, and payback period.”

Marcus stared at the acronyms. “I… what?”

Elena looked up. “You don’t know what those are?”

“I mean, I’ve heard them in meetings…” Marcus felt heat rising in his neck. “Net… something Value?”

“Net Present Value. Internal Rate of Return. Payback Period.” Elena’s expression softened. “Okay, we need to back up. These are the fundamental metrics for any investment decision. The CFO will absolutely ask about them.”

Over the next hour, Elena walked him through the concepts. NPV, the total value of the investment accounting for the time value of money. A euro saved next year is worth less than a euro saved today. IRR, the effective annual return rate of the investment, like interest on a savings account but in reverse. Payback period, how long until the cumulative savings equal the initial investment.

Marcus’s head spun. “Why can’t we just show total savings minus total costs?”

“Because money has a time dimension. Would you rather I give you €100 today or €100 in five years?”

“Today, obviously.”

Marcus watched the numbers cascade down the spreadsheet. “And IRR?”

“The discount rate that makes NPV equal zero. Basically, the return rate this investment generates. If our IRR is higher than our cost of capital which is 8%, the investment creates value.”

She built the model in front of him. Initial investment: €47,000 in year zero. Annual savings: €89,000 for five years. Maintenance costs: €5,000 per year starting in year two.

The formulas looked like a foreign language: =NPV(discount_rate, year1:year5) – initial_investment

The result: NPV of €298,445. IRR of 186%. Payback period of 6.3 months.

“That IRR seems impossibly high,” Marcus said.

“It is high. That’s because your payback is so fast, you recover the investment in half a year, then it’s pure benefit for 4.5 years.” Elena leaned back. “These numbers will get the CFO’s attention. But only if they’re defensible.”

“These numbers will get the CFO’s attention. But only if they’re defensible.”

Elena

The second presentation started well. Marcus walked through the parallel analysis experiment, showed the time logs, explained the methodology. Then he pulled up the financial metrics.

“Based on our measured time savings, the investment shows an NPV of €298,000, an IRR of 186%, and a payback period of 6.3 months.”

The CFO’s eyebrows rose. “Walk me through your NPV calculation.”

Marcus’s mouth went dry. He’d memorized the numbers, but the actual methodology… “We used an 8% discount rate to calculate the present value of future savings, then subtracted the initial investment.”

“And the cash flows? Show me year by year.”

Marcus pulled up the spreadsheet, hands slightly shaking. “Year zero, negative €47,000 for the license. Years one through five, positive €89,000 in savings, minus €5,000 annual maintenance starting in year two.”

“So you’re assuming constant savings of €89,000 every year for five years?”

“Based on the measured 60% time reduction in thermal-electrical integration tasks, yes.”

The CFO studied the numbers. “And your IRR of 186%, you understand what that means?”

“It’s the… effective return rate of the investment?” Marcus heard the uncertainty in his own voice.

“It means that if this were a financial instrument, it would be generating returns equivalent to 186% annual interest. Does that sound realistic for a software tool?”

Marcus felt the room closing in. “The payback period is very short, which drives the IRR high…”

“It does. Which brings me to my concern.” The CFO leaned forward. “Marcus, your financial methodology is sound. Elena clearly taught you well. The NPV calculation is correct, the IRR is mathematically accurate, and the 6.3-month payback is compelling.”

Marcus waited for the “but.”

“But you’re one engineer. This analysis shows that if you use this tool on thermal-electrical integration tasks, we’ll see excellent returns. You’re not a bottleneck, though. You’re already productive. What happens when you’re on vacation? What happens on projects that don’t involve battery thermal management?”

“Other engineers could learn…”

“At what cost? What’s the training time? The ramp-up period? And more importantly…” She pulled up his assumptions. “You’ve calculated savings based on R&D engineering time. Concept design and configuration work. That’s 15% of our engineering capacity. What about the other 85%?”

Marcus hadn’t thought about that. He’d been so focused on proving the value for his work, his projects, his domain.

“Your NPV of €298,000 assumes full utilization for five years. One engineer, even working full-time, can’t deliver that utilization on a tool license.” The CFO closed her laptop. “You’ve learned to calculate the metrics correctly. Now you need to calculate them for the right scope. Come back when you can show me it’s valuable for us, not just for you.”

Marcus walked out of the conference room feeling worse than after the first rejection. At least the first time, he hadn’t known what he was doing wrong. This time, he’d learned NPV, IRR, payback period, and it still wasn’t enough.

Stefan found him on the roof terrace, staring at the parking lot.

“Heard it didn’t go well.”

“I had the data. Real data. Conservative assumptions. NPV of €298,000, IRR of 186%, 6-month payback.” Marcus shook his head. “She said I proved it works for me, not for the company.”

“She’s not wrong.”

Marcus turned. “Whose side are you on?”

“Yours. That’s why I’m telling you the truth.” Stefan pulled out a thermos and poured two cups of coffee. He handed one to Marcus. “You built a business case for a personal productivity tool. That’s not what you’re asking for.”

“I’m asking for a simulation platform that could transform how we work.”

“Then prove that. Not that Marcus can run thermal analyses faster. That the engineering department can deliver better results, faster, across multiple domains.” Stefan took a sip. “You’re thinking too small.”

“The CFO literally just told me I’m only 15% of the engineering capacity.”

“So talk to the other 85%.”

That evening, Marcus did something he’d never done before: he called a meeting. Not with his immediate team, but with engineers across departments. Powertrain integration. Controls. Mechanical design. Even some of the older engineers who’d been skeptical of his “fancy new tools.”

Twelve people showed up in the conference room, curious and slightly confused.

Marcus put his laptop away. No slides this time.

“How many of you are working on projects where you need to analyze interactions between different physical domains?” he asked.

Every hand went up.

“How many of you are using multiple software tools that don’t talk to each other?”

The hands stayed up.

“How many of you have had a design fail because the interaction effects weren’t captured until physical testing?”

Uncomfortable nods around the room.

Marcus told them about the simulation platform. Not the technical features this time, but the problem it solved. He showed them the battery thermal management case study, the time savings, the earlier detection of integration issues.

Then he asked: “What if we ran the same experiment on your projects?”

The room came alive. The controls engineer talked about electric motor dynamics coupled with thermal behavior, currently analyzed in separate tools with manual iteration. The mechanical design lead mentioned issues with the hydraulic actuation system they couldn’t currently simulate. The integration specialist described how vehicle-level energy management required coordinating models from six different teams.

“I have the trial license for another week,” Marcus said. “If any of you want to test this on a real problem, I’ll help you set it up. We log the time, compare it to your current approach, and measure the difference. No promises, just data.”

“Why?” asked one of the senior engineers. “What’s in it for you?”

Marcus thought about the CFO’s words. Come back when you can show me it’s valuable for us.

“I’m trying to prove something,” he said. “Not just that this tool works. That we can work differently. Better. And I can’t prove that alone.”

Over the next six days, Marcus barely slept. He ran four parallel experiments with different engineers on different project types:

• Electric motor thermal-electromagnetic coupling (controls team)
• Hydraulic-mechanical interaction in the clutch actuation system (mechanical design)
• Vehicle-level energy management with battery, motor, and thermal systems (integration team)
• Pneumatic system dynamics for the cooling air flow (thermal management)

Each one showed time savings. Not always 60%, some were 40%, one was 75%. But every single analysis delivered results faster than the traditional multi-tool approach.

Elena looked at the financial summary, the NPV calculation broken down year by year, the IRR shown with sensitivity analysis, the payback period illustrated graphically. “I think you’ve learned to speak her language. Whether she approves… that’s about more than just numbers.”

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.

Read more simcenter-amesim reviews

Want to experience the technology firsthand?