An Open Innovation Lab is an organized space – physical or virtual – where companies, startups, customers, suppliers, research institutions, and sometimes even the public sector collaborate to develop new products, services, or processes. Open collaboration is central to this approach.co-creationCo-creation – a term that's becoming increasingly important in today's business world. But what exactly does it mean? Essentially, it's about... Click to learn more), rapid experimentation, prototyping, and structured real-world testing. Unlike traditional research conducted in isolation, an Open Innovation Lab opens its doors to the outside world and establishes a secure framework for collaborative learning, intellectual property, and data.
Why an Open Innovation Lab?
Because good ideas rarely stop at departmental boundaries. A lab shortens the process: you get from problem to prototype, from hypothesis to reliable result, faster. This reduces risk, lowers development costs, and increases the chance that a solution will truly hit the market. And it brings fresh thinking into the company – without disrupting your core processes.
How exactly does it work?
An Open Innovation Lab functions like an operating system for experiments. The process is usually recurring:
1. Problem framing: Instead of "We need feature X," the focus is on "Which user problem has priority?" Real data, interviews, and field observations provide the foundation.
2. Scouting & Co-Creation: External partners are involved: startups, suppliers, universities, and sometimes communities. Joint workshops create a shared understanding and initial solutions.
3. Rapid Prototyping: Prototypes are created in days, not months – from clickable dummies to functional test models. The goal: learning, not perfection.
4. Field testing: Pilot projects in real-world environments, with real users. Metrics are defined in advance to ensure a clear final verdict.
5. Decision & Scaling: Check stage gates: Stop, Iterate, or Scale. If a pilot proves successful, specialist departments or product teams take over – with Budget, Roadmap and operating concept.
Typical building blocks of an Open Innovation Lab
Governance: Clear rules regarding IP, data, security, compliance, and ethics. Without these, there is no trust.
Roll: Lab Lead (responsible for portfolio and quality), Sponsor (management, Budget and Blocker Removal), subject matter experts, Legal/Privacy, IT/Data Security, Procurement, Data/Engineering.
Infrastructure: An open studio for workshops and prototyping, digital collaboration, testing environments, and access to data sandboxes. Physical is good, but a hybrid model works just as well.
Process templates: Short sprints with checklists, experiment canvas, risk and impact assessment, standard contracts for collaborations.
Community: Regular demo days, open Q&A sessions, and learning reports. Visibility protects against "innovation in secret".
Concrete examples
Industry (SMEs): A machine manufacturer invited its customer service department, two suppliers, and a university of applied sciences to participate in a project to reduce downtime. The result after six weeks: a prototype for condition-based maintenance that reduced downtime by 18% in the pilot phase. The service department will handle scaling, including training, parts logistics, and the pricing model.
City administration: In the lab, the city is testing parking sensors in a limited area. After three months, data shows a 12% reduction in traffic searching for parking. Based on clear tender criteria, the solution will be rolled out to other districts.
Healthcare: A hospital group is co-creating a digital admission process with nurses and patients. A low-fidelity prototype reveals bottlenecks, while a second prototype halves waiting times in the pilot project. A governance board clarifies data storage, consent, and... Audit trailsAn audit trail is a traceable record documenting who did what, when, whether it was changed, decided upon, or submitted for approval within a system. For SMEs... Click to learn more.
How to set up an Open Innovation Lab
Start with focus: Choose three measurable challenges that address real business goals (cost, time, quality, revenue). Not a "nice to have" playground.
90-day plan: Weeks 1-2: Define governance, roles, and stage gates. Weeks 3-4: Refine challenges and involve partners. Weeks 5-10: Conduct two to three experiments with clear objectives. KPIsThe KPI definition is simple: A KPI is a prioritized metric directly related to a specific business objective. Key Performance Indicators not only show you... Click to learn moreWeeks 11-12: Evaluation, decision-making, scaling roadmap.
Budget Separate cleanly: Exploration budget (small, fast, risk-tolerant) vs. scaling budget (larger, with a business case). This is how you prevent endless pilot projects without commitment.
Think about scaling early on: Plan for operational, support, and security requirements as early as the second sprint. Otherwise, the prototype will remain a prototype.
Measurement and KPIs
Time-to-Prototype: Days until the first testable artifact.
Cost-per-Learning: Euros per confirmed or refuted hypothesis.
Pilot-to-Scale Rate: Percentage of pilots transitioning to scheduled service.
Business impact: e.g. savings, additional sales, lead times, error rates.
User impact: Adoption rate, NPS/near-satisfaction scores, support tickets per user.
IP Outcome: e.g. new intellectual property rights, licenses, standards – if relevant.
Law, IP and data – what's important
Before starting, define who owns what: results from joint sprints, preliminary work, data access. A common approach is for everyone to retain their preliminary work, while new work is either shared (with a fair licensing system) or assigned based on clear contributions. Confidentiality, export controls, and industry standards should also be considered. Information securityImagine you have a treasure chest full of valuable information. This chest contains everything your company knows about business partners, customer data, internal strategies, and more... Click to learn more and Privacy PolicyData protection safeguards the personal data of natural persons from unlawful processing, misuse, and loss of control. For SMEs, data protection therefore means: You consciously decide which data you collect,... Click to learn more These are not appendices, but rather part of the process design. A quick practical tip: A lightweight template contract accelerates initial experiments, while a more comprehensive contract is used before scaling.
Risks and anti-patterns
Innovation Theater: Pretty posters, no effect. Antidote: hard, business-oriented KPIs and stage gates.
Pilotitis: Many pilots, but nothing scales. The remedy: early involvement of line managers and clear hiring criteria.
IP leaks: Sharing too much too soon. Antidotes: tiered transparency, defined data spaces, and role-based access control.
Tool fixation: Tools rarely solve cultural or governance problems. Process and attitude come first, tools come second.
Silo reflexes: If departments don't cooperate, everything falls apart. The antidote: shared goals, incentive systems, visible results within 6-12 weeks.
Best practices from practice
Start small, but make a visible impact. CEO sponsorship helps, but the real boost comes from measurable results. Plan every sprint with a "kill list": What needs to happen for us to stop? This saves time and money. Budget and sharpens decisions. And enables psychological safety: mistakes made early and cheaply are desirable – mistakes that are delayed are expensive. In a project with a Family businessA "family business" is more than just a business run by a family. It's a special type of business in which ownership and... Click to learn more It was precisely this clarity that made the difference: two ideas were cleanly completed after two weeks, the third delivered savings in the seven-figure range in three months – and the team was allowed to implement it themselves.
Frequently asked questions
What does "Open Innovation Lab" mean in one sentence?
An Open Innovation Lab is a structured framework in which internal teams, together with external partners, can quickly and securely develop, test, and transfer new solutions to the market or into processes – with clear rules for IP, data, and success measurement.
Who should participate in an Open Innovation Lab?
You need a mix: subject matter expertise (problem knowledge), technology/engineering (feasibility), legal/data protection (framework), procurement (contracts), IT/InfoSec (security), controlling (business case), and real users. You bring in external partners strategically for... ExpertiseWhat does "know-how" mean? Quite simply: It's the ability to know and be able to do something. This is less about theoretical knowledge and more about... Click to learn more or market velocity. An experienced lab lead keeps everything together and protects the velocity.
How does an Open Innovation Lab differ from traditional R&D or an accelerator?
Traditional R&D typically optimizes internally and over the long term. An accelerator primarily supports external startups. The Open Innovation Lab combines these approaches: it solves very specific business problems with internal and external resources, in short cycles, with direct piloting in real-world applications – and has a defined path to scaling.
How do I find the right topics for the lab?
Start with concrete goals: What are the pain points? Costs, lead time, downtime, quality, revenue. Formulate problems in a user- and data-driven way ("How do we halve complaints in region X?" instead of "We need app Y"). Check: Measurable within 12 weeks? Is access to data/test environment secured? Is a sponsor available? If not, it's not a good lab candidate.
How do I protect intellectual property and confidential data?
With tiered contracts and transparent rules: a confidentiality agreement before data exchange, clear ownership logic for preliminary work and deliverables, defined data rooms, access rights based on the need-to-know principle, logging, and deletion periods. Sensitive data is only handled in pseudonymized test environments. Before scaling, an extended contract should be drawn up that regulates licenses, liability, maintenance, and support.
Which KPIs are suitable for management?
Implement a core dashboard: Time-to-Prototype, Cost-per-Learning, Pilot-to-Scale Rate, Business Impact (savings, additional revenue), User Impact (adoption, satisfaction), Risk Indicators (safety and compliance findings). Add domain-specific metrics for each case, such as error rate in production or no-show rate in service.
How long do projects in an Open Innovation Lab take?
Typically, it takes 2-4 weeks to develop the first prototype, 6-12 weeks for a pilot project, and 3-6 months to decide on scaling. If it takes longer, it usually indicates a lack of focus or decisiveness. Smaller steps with clear learning objectives are preferable to a grand plan that stalls.
Does an Open Innovation Lab have to be a physical location?
No. A physical space is helpful for co-creation and hardware testing, but many labs operate in a hybrid model: on-site for workshops, virtual for sprints, and field testing. Crucial factors are clear processes, reliable stakeholder availability, and quick access to test environments and data.
How does a pilot project become a real product or process?
Plan the handover early: Define operations, support, security, training, migration path, and more as early as the second sprint. BudgetEstablish clear go/no-go criteria (e.g., target metric achieved, acceptable TCO, compliance OK). Designate an owner within the line organization who possesses the necessary resources. Without this "landing strip," the project remains with the pilot.
How much does an Open Innovation Lab cost – and is it worth it?
Ongoing costs depend on team size, infrastructure, and the number of cases. Take a pragmatic approach: a small core team, streamlined processes, and a limited exploration budget per case. ROI comes from avoided bad investments, faster time-to-market, tangible savings, and new revenue. Good labs document "abandoned ideas" as successes – the money saved is recouped. Budget is impact.
What typical mistakes should I avoid?
Vague goals, overly broad cases, lack of SponsoringSponsorship is a contractually regulated partnership based on performance and consideration: A sponsor supports a sponsored party with money, resources, services, know-how or reach and receives... Click to learn moreUnclear IP/data rules, late involvement of the line organization, tool overkill, and "pilotitis." Remedies: small, measurable challenges, 90-day cycles, standard contracts, early operational planning, simple dashboards, and consistent decisions at stage gates.
Is an Open Innovation Lab also suitable for medium-sized businesses or the public sector?
Yes. Especially where resources are scarce, a lab helps to minimize risks and demonstrate results quickly. Short decision-making processes are a plus for medium-sized businesses. In the public sector, clear procurement processes and transparency are essential – pilot zones, data protection-compliant test environments, and clear evaluation make all the difference.
Do I need special methods – and if so, which ones?
You don't need a battle of methods. Principles are more important: start with a problem-centered approach, formulate hypotheses, quickly prototype, test with users, measure objectively, and make clear decisions. Whether you WorkshopA workshop is an interactive event that allows you to learn new things, exchange ideas, or work on a specific project in a collaborative environment. Click to learn more Whether you call it Sprint A or Sprint B is secondary – the main thing is that the pace remains high and the bar is clear.
How do I recruit colleagues for the lab?
Showcase small, real successes. Invite people to demo sessions, share learning reports in clear language, and offer opportunities to participate for a limited time (e.g., a sprint). Recognition systems help: Those who successfully implement an idea gain visibility and responsibility – not just applause.
Personal conclusion and recommendation
A good open innovation lab isn't a showroom, but a decision-making engine: learn quickly, stop boldly, and scale consistently. If you want to get started now, begin with a single, measurable challenge and a clear 90-day roadmap. Keep governance lean, metrics rigorous, and communication open. If you need sparring for setup, governance, or the first sprints, Berger+Team provides pragmatic support behind the scenes – the goal: impact in weeks, not years.
