Nailing Manufacturing Software GTM — The Founder Guide

Authors: Kim Dang, Jess Burley, Christoph Gras, Sam Baker

Despite the promise of breakthrough software to unlock Industry 4.0, we’re still stuck in analogue. Why? There’s an adoption gap.

Go-to-market remains one of the biggest hurdles for founders trying to scale within complex, risk-averse manufacturing environments.

That’s because the reality of manufacturing makes GTM hard. Customers behave very differently from classic Enterprise SaaS buyers: journeys are non-linear, solutions aren’t plug-and-play, and growth depends more on asset footprint than on user seats.

On a deeper, cultural level, Europe also simply needs better technology buyers who create more structured demand for industrial software.

This is about to change, fast, as the economic, geopolitical and environmental pressure to (re)industrialise Europe builds, and the urgent buyer pool for industrial software grows with it.

Here, we draw on the experience of founders who are already cracking the code building companies like Aris Machina, Makersite, Carbon Re, Apple, Agilox, ProGlove and Northvolt, as well as corporate buyers and experts from across our portfolio and network, to distil top tactics that actually work.

In this guide, we share eight golden lessons, packed with case studies and resources, to help early-stage B2B manufacturing SaaS founders nail their GTM strategy and meet the moment.

Because there’s no time to lose.

The urgency: Why the 4th (Re-)Industrial Revolution can’t wait

A Shifting Macro Environment

Recent geopolitical and economic shifts have been global and profound. The era of hyper-globalisation that shaped the late 20th and early 21st century has slowed dramatically. Global foreign direct investment has been in decline for more than 15 years, and global trade growth is stagnating. Recent shocks such as the war in Ukraine and escalating rivalry between the United States and China have accelerated this trend.

Long-held assumptions about global manufacturing competitiveness are shifting beneath the feet of Western Europe and the US.

Implications for Western Manufacturing

We are already seeing consequences of this new reality: trade wars, sanctions, reshoring and nearshoring strategies. As a result, supply chains are fragmenting, production costs are rising, and nations are turning inwards to secure critical industries.

Many economies, including and especially Europe, are recognising that the efficiency offered by globally optimised supply chains comes at a cost, namely dependency and fragility. Trust between former allies has eroded, and the narrative has shifted toward re-industrialisation, sovereignty, and resilience, each taking their own political incarnation in Europe and the US.

At the same time, manufacturers face a convergence of unprecedented challenges: physical climate risk, breakneck development in AI and robotics, unbridled inflation, soaring energy costs, and acute talent shortages.

The operating environment has never been more volatile.

The Industrial Investment Gap

For decades, Western VCs have chased asset-light, software-first models -from enterprise SaaS to consumer apps, lured by their speed, margins, and capital efficiency. This focus came at the expense of industrial technologies that require longer time horizons and greater upfront investment.

As a result, the digital transformation of Europe’s industrial base has been hamstrung.

• Less than half of European enterprises use an ERP system, and more than 50% of the MES market is services revenue (vs software).
• Even among manufacturers who consider themselves ‘Industry 4.0 transformed’, one third are still collecting most or all of their data with non-digital processes.

These are messy, ad hoc, under-instrumented operations.

In contrast, China overwhelmingly directed both state and private capital towards high volume, heavily automated and highly advanced manufacturing. This focus has consolidated China’s position as the “world’s factory,” while Western economies are only now rediscovering the competitive importance of deep and technologically advanced industrial foundations.

THE question now is: can Europe leverage the fourth industrial revolution, powered by industrial software and AI, to transform its industrial base into a global manufacturing powerhouse defined not by cost, but by productivity, sustainability, and anti-fragility?

The opportunity

The standardisation paradigm

The potential for automation to revolutionise the way we manufacture, generate energy and process materials is clear and well-discussed. What is often underestimated, though, is the challenge of process standardisation. A significant portion of industrial processes involve human input.

If there’s one thing we can be sure about when it comes to humans, it’s our tendency to deviate and overestimate our capacity for individual optimisation. Thus, the processes where agentic AI and robotics could add most value are mostly not prepared for automation.

→ Tools that enable robust, repeatable and standardised processes in industrial settings are a key part of the automation stack of the future.

Automating the boring

Humanoids strolling through lights-out factories is an exciting vision of the future, no doubt, but it’s far from the lowest hanging fruit for industrial robotics today.

Applications like passive data collection, moving materials around a shop floor and managing warehouse inventory, or presenting parts to assembly stations are where the nearest-term value can be delivered.

Today you need deep robotics & integration expertise for this, eliminating that skill gap is a huge opportunity.

→ These are the parts of industrial value streams we are most interested in backing today.

Visibility = currency

The most impactful thing you can do for an industrial ops manager is improve visibility of performance. Most ops managers today spend at least as much of their time figuring out where to apply focus in their value stream as they do fixing problems.

Dealing with the rabid complexity of pen and paper production records, unsearchable ERP data and broken (or non-existent) integrations is a huge drain on productivity.

We need tools that solve this messy data problem and use it to map value streams, analyse bottlenecks and give focus to front-line production teams.

We’re excited to see a vanguard of powerful solutions emerging in Europe today as breakthroughs in robotics and software including physical AI transform what’s possible even a few years ago, and experienced entrepreneurship, industrial expertise meet an urgent need to accelerate Europe’s clean industrial upgrade.

The challenge

So, if the need is clear and solutions are being built, what makes this such a tough sell? It’s simply the nature of the beast.

1. Overworked operators, thin digital bandwidth
High production pressure, ever leaner staffing, and short-term targets leave little bandwidth for digital initiatives. Most factories simply lack the IT capacity to operationalise new software, creating a “do-it-for-me” adoption bias where tools that require internal ownership rarely stick.

2. High local accountability, low centralisation
Meanwhile, decades of M&A have left many industrial groups with fragmented IT stacks and cultures. Centralisation is expensive and politically slow, so plants run as semi-independent profit centres with their own P&L and CapEx. Each site behaves like an SMB buyer, demanding local ROI before HQ considers rollout.

3. Accountability over functionality
After painful legacy experiences, manufacturers have learned to value accountability over capability. They pay for uptime, installation, or pay-per-output, not for another license that “enables possibilities”. They buy ownership of outcomes, not access to tools.

As a result, founders face:

• Sales cycles measured in quarters (or years), not weeks
• Decentralised budgets that fragment big accounts into dozens of small deals
• A “proof-over-promise” culture demanding upfront validation, leading to heavy pre-sales cost and pilot purgatory
• Complex legacy stacks that make implementation costly and inflate CAC

For founders building in the space, the path to market depends on where they fit into the “Manufacturing Tech Stack”.

Here’s how we look at it.

The Manufacturing Stack GTM Landscape

We define the product as software that powers, optimises, or orchestrates physical operations in asset-heavy, process-driven manufacturing. In this GTM guide, we focus on software-led solutions, including AI-native systems, sold into existing factories.

While there are many ways to describe the manufacturing tech landscape, from a GTM perspective we separate two dimensions that are often collapsed into one:
(1) The technical architecture of the factory stack, and
(2) The autonomy operating on top of it

This enables us to see where value truly accrues.

Dimension 1: Stack Layers (the “What”)

These layers describe the functional architecture of modern factories, how data is generated, transformed, and used for decision-making. They represent today’s human-led production stack.

• Layer 1: Control & Execution: Where work happens. Software that interfaces directly with machines: PLCs, CNCs, robots, sensors, and real-time control systems.
• Layer 2: Ops Intelligence: Where the factory becomes visible. Software that observes and analyses live operations: OEE, bottlenecks, anomalies, quality signals, operator workflows.
• Layer 3: Decision Intelligence: Where decisions are made. Software for planning and orchestration: scheduling, routing, simulation, digital twins, costing, and capacity planning.

Most industrial software today sits somewhere in Layers 1–3, monetising through SaaS, hardware-enabled SaaS, or increasingly, Service-as-a-Software where deep domain expertise is packaged into semi-productised services.

Dimension 2: Autonomy Levels (the “How”)

This describes who operates the stack: humans, agentic AI, or vertically integrated systems.

• Level 1: Assisted Automation. Software helps, humans decide: The system provides guidance, recommendations, alerts, vision assistance, or workflow automation — but humans remain in control of actions and machine adjustments.
• Level 2: Closed-Loop + Agentic Automation. Software acts on the system: AI starts to close specific loops: tuning machine parameters, adjusting set-points, steering processes, re-planning schedules, or continuously correcting robot execution, without human initiation.
• Level 3: Vertical Integration: Companies collapse multiple stack layers into a fully integrated hardware + software system (robotic cells, microfactories, autonomous machines). These are effectively automation OEMs/System Integrators with proprietary control, perception, and planning built in.

In this series, we focus on the go-to-market mechanics of companies operating in Level 1 and Level 2, that is, assisted automation and closed-loop/agentic automation, across the three software layers of the modern manufacturing stack.

These are the companies selling software into existing factories, navigating real procurement cycles, and scaling within brownfield environments.

We do not focus on vertically integrated OEMs (Level 3) in this piece, since their GTM mechanisms work differently from software. That said, many of the core lessons around the people side of GTM, from mastering internal politics to tailoring your pitch, apply across levels.

Europe’s Opportunity: Compete by Upgrading, Not Copying

The Fourth Industrial Revolution offers Europe a historic opportunity to redefine its industrial competitiveness through intelligence, adaptability, and sustainability.

Realising this opportunity requires strategic execution in bringing industrial innovation to market, predicated by technological readiness. GTM strategy is the decisive bridge between innovation and impact.

Manufacturing software, including physical AI, robotics, and deep-tech companies operates in a domain with long adoption cycles, risk-averse customers, and heavily scrutinised ROI.

Crafting effective GTM in this environment means navigating all of this whilst dancing with regulators, procurement teams and IT engineers whilst delivering clear, outcome-driven value.

This series aims to help founders master precisely this dance.

It is critical pioneering solutions successfully commercialise their world-class industrial innovation and unlock clean, competitive, production at scale. Here, we share hard-won field insights from industrial founders leading the way.

Jump in: Lesson 1 — Perfecting the pitch: The art of making industrial buyers care

Where better to kick it off than with the first job of sales - understanding your buyer’s critical need and framing your solution as the best on the planet to solve it.

From scouring board reports to identify the KPIs your ICP truly cares about, to serving up tangible early wins, here are top tactics, resources and learnings from 30+ industrial tech founders, experts and corporate buyers designed to make every conversation count. READ LESSON 1.

You are reading our Manufacturing Software GTM Founder Guide for early-stage B2B manufacturing SaaS founders.

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 (Juna.ai), Thibaud Martin (Altrove), Omar Fergani, Josh Vernon (CarbonRe), 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.

Authors: Kim Dang, Jess Burley, Christoph Gras, Sam Baker.

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!