Lesson 5: Post Sales Implementation - Productising the Deployment
You are reading our Manufacturing Software GTM Founder Guide for early-stage b2b manufacturing Saas founders. Skip back to: The Intro, Perfecting the pitch, The Art of Industrial Selling, Scaling Across Plants, Escaping Pilot Hell.
In industrial software, early deployments often look more like consulting than SaaS.
Complex, asset-heavy environments demand hands-on work, custom integration, and deep user engagement. That’s normal to start with but the real risk is staying in that mode and becoming a “services company in disguise.”
The goal is to start intentionally unscalable -then design for repeatability.
After speaking with top founders and operators building manufacturing software across Europe in our portfolio and network, we distilled how teams successfully make that shift.
In the latest edition of our GTM Series, we unpack how deployments evolve as the product becomes increasingly standardised, scalable, and customer-driven, in four major phases, corresponding roughly to early plant rollouts.
1) Temporarily Lean Into Co-Development
In the earliest stages, deep, high-touch collaboration is a strategic advantage. Sitting on-site, joining weekly calls, and adapting quickly helps you uncover what actually drives ROI, not just what customers claim they need.
Early service intensity is especially important in industrial settings where capability-building and change management are essential. Forward-deployed engineering is non-negotiable at this stage: both to drive true adoption and to maximise learning about the deployment environment. See the chapter 3 section on “Win Locally with Change Management” for more details.
→ FOUNDER TIP: Find your shop floor ambassador early and make it worth their while. Every plant has someone whose opinion the floor actually listens to. Often a veteran shift supervisor or line operator, rarely the person who signed the contract. Identify them early, genuinely involve them in shaping the deployment, and visibly act on their feedback.
The hardest person to win over is usually the most valuable one to have on your side. Make it worth their while: index into making their life easier, and be sure to give them recognition with the plant leadership.
2) Map Common Patterns Across Customers
Use the early, hands-on phase to spot what’s repeatable so you can begin standardising it. Look for patterns in:
- Frequent workflows or configurations
- Integrations that appear across multiple deployments
- User behaviours that shape product expectations
- Common setup needs and data models
- Shared KPIs (e.g., energy, yield, downtime)
- Typical dashboards or reporting structures
These become the seeds of product features, templates, and automation later on. Think in terms of “productised services”, repeatable frameworks you can package, price, and deploy consistently.
Be careful here: many plants are unique in their processes and you’ll likely need to go to first principles to identify truly transferable solutions.
Example: Carbon Re productised its deployment by automating a typical sequence (data collection → cleaning → ML modelling → control integration), turning a once‐manual process into a scalable engine.
→ FOUNDER TIP: Capture everything in a standardised format. During on-site co-development, your team should log every workaround, request, and integration. These notes become your product roadmap and your future onboarding playbook.
Every feature request - internal or customer-driven-should enter through a standard template capturing:
- The problem (not the proposed solution)
- Who experiences it (role/site/team)
- Frequency and severity
- Impact on ROI or outcomes
- Workarounds currently used
3) Reduce Support Load Over Time
You should start with high-touch support, but your product should make itself easier to deploy with every iteration. As documentation improves and configuration becomes self-service, customer intensity naturally decreases.
The goal is to turn every deployment into a little less effort, a little more automation, and ultimately-frictionless scaling.
Sometimes reducing support load also means saying no to one-off features.
→ FOUNDER TIP: Invest in self-service before you invest in more people. If your instinct is to grow your Customer Success or Forward Deployed Engineering teams, pause and ask whether a playbook, config wizard, or template would solve 80% of the problem more scalably.
As one partner at a leading consulting firm that advises on digitalisation projects in manufacturing put it: “You are in the lead at the first plant. Second plant, they’re in the lead. Third plant, you’re coaching.”
4) Reframe “Consulting” as Part of the Product Value
Certain customer groups, particularly when deploying mission-critical or regulated systems, expect significant support. Instead of downplaying the service component, position it as part of a complete solution package.
The key is to:
- Price for the service
- Control the scope and have a process for expanding it
- Continuously convert learnings into product features and automation
Service is the bridge to a scalable product, and the customer benefits just as much as your team does from the learnings encountered during deployment. Bring the value of that experience into your product offering, both for that client and future customers.
→ FOUNDER TIP: By this stage, it’s time to define your “service ceiling”. Make explicit what your team will do (e.g., onboarding, integrations, training) and what it won’t do (e.g., custom feature builds, client-specific workflows) and publish this internally. This keeps consulting value-add without letting scope creep swallow your roadmap.
5) Tracking and Maintaining Early Engagement
The period between go-live and the three-month mark is when most industrial software deployments either take root or quietly die. Users are forming habits, workarounds are being established, and any unresolved friction gets baked into how the plant operates. You notice churn risk at month six when the real failure happened in week four.
The signals to watch closely:
- Overrides and workarounds: operators bypassing your system to do things the old way is the earliest and most honest signal that something isn’t working
- Login frequency and active users: are the right people actually using it, or just the champion? If the product is working, active users should grow across shifts and production lines
- Champion engagement: regular short check-ins (not formal reviews) with your internal advocate to surface what’s being said on the floor that won’t make it into a support ticket
If adoption stalls, resist the instinct to add features or training sessions.
The problem is almost always trust or workflow fit, not capability. Go back on site, sit with the actual users, and treat it as a co-development moment rather than a remediation exercise.
Re-engaging the shop floor ambassador at this stage (and being transparent with plant leadership about what needs to change) is far more effective than trying to fix it remotely.
→ FOUNDER TIP: Set explicit 30/60/90 day adoption milestones with the customer before go-live: not after things go wrong. Agreeing upfront on what “good” looks like (which users, which workflows, which metrics) gives you a shared basis for early conversations and makes it much easier to raise concerns without it feeling like a crisis. If you’re having to define success at month two, you’re already behind.
After Nailing Implementation Comes Optimising Pricing
Now that you’ve nailed productising your deployment, the next question is: how do you price the product? Pricing is a critical part of sales and of capturing the value you create. In the next chapter, we dive into how to design a pricing model that reflects your impact and scales with your customers. STAY TUNED!
Authors: Jess Burley, Kim Dang, Christoph Gras, Sam Baker.
With thanks to Sid Khullar (Aris Machina), Maximilian von Düring (AiSight), Alex Grots (ProGlove), Yohann Rousselet (BAC), Sabine Erlinghagen (Siemens Grid), Matthias auf der Mauer (AiSight, Juna.ai), Thibauld Martin (Altrove), Omar Fergani, Josh Vernon (Carbon Re), Daniel Schütt (Ekko.io), Fabian Veit (Celonis / Make), Benjamin Benharros (Alteia), Pascal Mies (Schwenk Materials), Mladen Milicevic (Unchained Robotics), Alexander Fitzgerald (Isembard), Matthias Stammen (Source.ag), Michel Lutz (Total Energy), Albertsson Adam & Erik Johansson (Volvo Ventures), Till Rosnick (WEPA), David Niedermaier (Agilox), Elena Ballesteros (Hitachi Ventures), Sander Njissen, Finn Stadler (Possehl Group), Dr. Christopher Schneider.
About us
Planet A is an early-stage European tech VC backing founders solving the world’s greatest systemic challenges. We use rigorous scientific impact assessments to identify solutions the world cannot afford to ignore. Investments include Carbon re, Aris Machina, AUAR, INERATEC, Makersite, C1, HIVED, traceless materials and 44.01. Follow us on LinkedIn!
