Meeting playbook¶

Everything you'd want at hand in the room. Question banks · intelligent statements · hypotheses · red & green flags · opening pitch · technical glossary.

Opening pitch (≤30 seconds)¶

"I work at the interface of structural FEM, battery-pack architecture, and validation. What interests me about Forward is the way you combine materials, process thinking, and simulation to make difficult structures decision-ready early. I'd like to understand where you see the biggest remaining bottlenecks in battery-enclosure development — and where someone with strong load-path, crash, and validation experience could create leverage."

Why-FE statement (one line)¶

"I'm interested in Forward because you're operating in exactly the zone where next-generation battery systems get won or lost: translating new materials and manufacturing concepts into structures that can actually survive validation, cost pressure, and regulatory scrutiny."

Question banks¶

Pick a few from each. Don't run through them like a list — use them as a kit.

Leadership¶

Which revenue streams are most strategic for FE over the next two years: engineering services, benchmark intelligence, testing/pre-compliance, sustainability consulting, or something else?
Which battery-enclosure programs have moved closest to OEM release, and what blocked the rest?
Where do you think FE can win repeatedly against larger engineering houses rather than just occasionally?
How do you decide when to stay a pure development partner vs. when to push for IP, methods licensing, or a recurring-data product?
What portion of customer demand today is being pulled by regulation vs. cost pressure vs. innovation scouting?
How important is China-derived technology intelligence to your European and Japanese business today?
What did opening Shanghai change commercially that remote China engagement could not?
How do you avoid becoming a "demonstrator company" rather than a "series impact company"?
Which offerings have the best gross margin and the best repeatability?
How do you think about Mitsui strategically today — market access, commercial leverage, or ownership legacy?
What technical domain do customers most underappreciate until late in a project?
Where do you see the biggest misconception about composite battery housings in OEM organizations?
What kind of technical hire creates the most business value fastest inside FE?
What would have to be true for FE to scale meaningfully without diluting its specialist edge?
If you had to cut one activity area and double down on one, what would they be?

Technical managers¶

How do you define the system requirements cascade from vehicle to pack to enclosure to plaque?
At concept stage, which load cases kill bad architectures fastest?
How do you decide whether a concept should be thermoplastic-intensive, SMC-heavy, or metal-hybrid?
What are your standard correlation gates between coupon, subsystem, component, and full-system validation?
Where does FE rely most on external labs today?
How do you handle strain-rate sensitivity, temperature dependence, and manufacturing effects in early cards?
How do you translate customer-specific abuse cases into generic reusable methods?
Which joining or sealing failure mode surprises customers most often?
What are the hard-to-model behaviors you still have to cover with engineering judgment?
How do you handle fast architecture exploration without losing physical realism?
How much of your workflow is solver-limited vs. data-limited?
What manufacturing-simulation outputs most often change the structural design?
Where are tolerance sensitivities highest in large battery covers and trays?
What has changed most in customer expectations since stricter thermal-propagation rules gained momentum?
If you had one more great CAE engineer, where would you deploy them first?

Battery-enclosure-specific¶

What is the toughest unsolved problem in composite or thermoplastic HV battery housings?
Where do metals remain technically superior?
Where do thermoplastics or composites provide non-negotiable value?
How do you design for bottom impact and rocker-to-pack load transfer without overbuilding mass?
How do you handle venting, deflagration pressure, and particle erosion in early concepts?
What do you consider a credible subsystem proxy for full-pack thermal-runaway performance?
How do you think about serviceability and repairability vs. structural efficiency?
What failure modes drive the flange and sealing concept most strongly?
Which architecture is currently most promising for true cost-down at mass-market OEM scale?
What evidence is still required before customers trust composite-intensive housings for broad series adoption?

CAE & material-card¶

How do you build first-pass proxy cards when material data are incomplete?
What is your minimum viable test matrix before you trust a new crash card?
How do you incorporate fiber orientation and process history into structural cards?
How do you correlate insert behavior and fastener pull-out in the enclosure context?
Which solver/modeling choices are most customer-dependent?
How do you manage uncertainty ranges rather than just single deterministic results?
Where does mold-flow or warpage most often invalidate a "good" structural concept?
How do you handle temperature-conditioned crash or abuse scenarios?
Which outputs are hardest to communicate convincingly to non-CAE stakeholders?
What part of the simulation pipeline is most ready for automation without sacrificing trust?

Business strategy & profitability¶

Which project types have consistently low margins and when do you say no?
Where can FE charge for value delivered instead of engineering hours consumed?
What do you think customers will buy repeatedly from FE even without a new vehicle platform?
Are benchmark reports and teardown insights already a meaningful business line?
What is FE's strongest pricing power today?
How do you protect know-how in multi-partner demonstrator projects?
What is your most scalable offering that still uses FE's core strengths?
How do you balance custom customer work with investment in reusable internal assets?
Where do you see the best opportunity for subscription-like revenue?
Which KPI best predicts good projects for FE — margin, reuse potential, strategic account value, or something else?

AI & digital engineering¶

Which engineering tasks consume expert time but add little differentiated value?
Where would automated pre-processing save the most time today?
How standardized are your report structures, load-case libraries, and validation templates?
Do you already use any internal knowledge-search or semantic retrieval across old projects?
Would you trust AI to suggest architecture options, or only to accelerate evaluation of human-generated options?
Where is traceable evidence capture weakest today — requirements, simulation assumptions, test correlation, or decisions?
How much time is currently spent rebuilding similar models instead of reusing structured assets?
Would a material-card assistant be valuable if it exposed assumptions and uncertainty explicitly?
What customer-facing digital tool would create the most commercial leverage — benchmark dashboard, cost/LCA calculator, or compliance cockpit?
What kind of AI proposal from a candidate sounds useful rather than generic?

China, global markets & customer demand¶

What are Chinese OEMs doing today in battery-housing architecture that European OEMs still underestimate?
What have you learned from Chinese battery teardowns that Western clients found genuinely actionable?
Are Chinese customers mostly ahead on cost engineering, architecture aggressiveness, vertical integration, or speed?
Where is Japan still distinct in engineering priorities vs. Europe and China?
What work is best done locally in China vs. centrally in Munich?
How do global customers use FE's China insights in actual product decisions?
Which kinds of customers ask for teardown intelligence instead of classic development support?
Are customers looking more for "what China is doing now" or "what will matter in Europe next"?
Where is regional regulation divergence most painful for enclosure development?
Which region is currently generating the strongest commercial pull for FE?

Sustainability, LCA & circularity¶

How do you stop LCA from becoming an after-the-fact presentation rather than a design input?
What assumptions matter most in battery-enclosure LCAs and where are customers often sloppy?
How do you compare low-mass / high-process-energy concepts against heavier but mature metal routes?
What does a realistic circularity story look like for SMC vs. thermoplastic battery housings?
How do customers react when sustainability and cost objectives conflict?
Which end-of-life pathway is most credible for the concepts you are publicizing?
How do you handle recycled-content uncertainty in early engineering development?
What will upcoming ELV and product-footprint expectations change in enclosure design decisions?
Where is mono-materiality genuinely helpful, and where is it marketing overreach?
Which sustainability metric actually changes customer decisions — CO₂, recycled content, disassembly effort, or total value recovery?

Scaling indicators (is FE actually scaling, or just doing isolated projects?)¶

How many projects reuse a common internal method or data asset from earlier work?
What percentage of new business comes from repeat customers?
Which internal tools have become standardized across regions?
Are your benchmark/teardown products sold repeatedly or still mostly bespoke?
How often do early feasibility projects convert into deeper engineering phases?
What capabilities are now mature enough to quote with confidence rather than estimate loosely?
Which partner relationships are systematic rather than one-off?
Do your battery programs share common architecture building blocks?
What has become faster in the last 18 months because FE learned and standardized something?
What commercial offering today could double revenue without doubling headcount?

Questions to avoid¶

These will sound naive, adversarial, or premature:

"So… are composites really safe enough for batteries?"
"Why not just use aluminum?"
"Can AI do all of this soon?"
"Do OEMs even care about LCA?"
"Why don't you just become a Tier 1?"
"If the tech is good, why isn't it everywhere already?"
"Are your demonstrators basically marketing?"
"Can you share confidential customer names or programs?"
"How much profit do you make exactly?"
"Isn't this just another engineering consultancy?"

Intelligent statements you can make¶

Use these as natural inserts, not a checklist:

"The hardest battery-enclosure problem is rarely one discipline; it's the coupling between load path, thermal event, sealing, and manufacturing variation."
"I find the plaque-to-pack translation problem more interesting than the material brochure."
"The architecture decision should probably be made with cost, cycle time, and regulation pull visible from day one."
"Bottom impact and rocker integration seem like the places where enclosure strategy becomes vehicle strategy."
"I'm less interested in abstract lightweighting than in mass that survives validation without exploding test cost."
"A good material card isn't just a CAE asset — it's a commercial accelerant."
"The real value in AI here is probably not generative ideation but reducing friction in repetitive engineering loops."
"China teardown intelligence becomes valuable when it changes architecture choices, not when it stays as a slide deck."
"If a concept can't tolerate realistic assembly variation and sealing sensitivity, it isn't mature."
"The most scalable offering may be a decision framework, not just an engineering project."

Hypotheses to test¶

FE's clearest growth engine is battery enclosures, not general body engineering.
FE is consciously moving from bespoke consulting toward repeatable intelligence/testing offerings.
Public thermoplastic battery-cover messaging reflects a deliberate strategy to target higher-volume automotive economics.
FE's biggest technical bottleneck is material-card and correlation maturity.
FE's biggest commercial bottleneck is conversion from demonstrator to series mandate.
China intelligence is becoming a genuine product line, not just a supporting activity.
Sustainability work is a sales enabler for new materials, not just a separate consulting niche.
FE would benefit more from internal workflow automation than from flashy customer-facing AI first.
FE's strongest moat is cross-disciplinary architecture judgment under uncertainty.
FE risks strategic spread if robotics and other adjacencies grow faster than process discipline.

Red flags¶

They cannot name any programs that moved beyond demonstrator stage.
They speak mostly about materials, not validation and launch gates.
They cannot explain how they correlate plaque/subsystem/system performance.
They overclaim recyclability without giving an end-of-life pathway.
They have no crisp answer on recurring revenue.
They describe AI only as marketing or brainstorming.
They cannot explain where they add value vs. partners.
They avoid discussing cost models and tooling amortization.
They treat China only as a sourcing story, not a speed/architecture-learning story.
They have no standard answer on why a customer should choose FE over a bigger house.

Green flags¶

They talk naturally in requirement cascades and trade spaces.
They can separate concept feasibility from series feasibility without hand-waving.
They have reusable internal methods, templates, or data assets.
They are candid about where metals still win.
They discuss sealing, venting, inserts, and tolerances in the same breath as materials.
They can explain how they de-risk before expensive full-pack tests.
They have a clear point of view on regulation-driven productization.
They can describe how benchmark intelligence feeds real engineering programs.
They show evidence of repeat business or repeatable offerings.
They are interested in automating engineering quality, not just reducing headcount.

How to position your background¶

As directly valuable¶

You bring exactly the load-path mindset needed to connect battery architecture, crash behavior, and enclosure validation.
You understand why bottom impact, side intrusion, and rocker integration cannot be solved as isolated local checks.
You can help formalize subsystem correlation and decision confidence, not just run models.
You can bridge CAE outputs with physical validation planning and failure interpretation.
You can help turn composite/thermoplastic concepts into customer-trusted structural evidence.

AI + CAE automation, without sounding generic¶

Lead with a specific bottleneck — pre-processing, report generation, requirements traceability, or test-correlation cleanup.
Frame AI as a margin and speed tool for expert workflows, not a replacement for engineering judgment.
Talk about reproducibility and traceability before "innovation."
Suggest internal pilots on one enclosure family rather than company-wide transformation.
Emphasize knowledge capture — turning old projects into searchable, reusable engineering assets.

Technical glossary — terms to be ready to discuss¶

Material-card calibration · strain-rate sensitivity · morphology matrix · subsystem correlation · BETR · TaG · UL 2596 · thermal propagation · GB 38031-2025 · R100 thermal propagation · bottom impact · side pole intrusion · rocker integration · pack-to-body load path · venting strategy · pressure relief · flange sealing · IPX7 / IPX9 · organosheet overmolding · PP-LGF · STAMAX · Tepex · epoxy SMC · EMI/EMC shielding effectiveness · crash pulse translation · PFMEA · warpage prediction · push-down analysis · dimensional stack-up · circularity · ELV · LCA · PEF · TRL · MRL · tooling amortization · cycle-time economics