By Neal Silverman | Traction Technology | March 2026
What Is Open Innovation? A Practical Guide for Enterprise Teams
Most enterprise innovation programs start the same way. A team is formed. A mandate is issued. A portfolio of internal initiatives is assembled and tracked. The program runs for a year or two, produces some pilots, and then runs into the same ceiling: the best ideas for what to build next are not inside the organization.
Open innovation is the structured practice of solving that problem — engaging external sources of ideas, technology, and expertise as a deliberate part of the innovation process rather than a supplement to it.
This post is a practical definition of open innovation for enterprise teams: what it is, how it actually works, when it produces results, and what separates organizations that run open innovation programs well from those that run expensive, inconclusive challenges and then wonder what went wrong.
The Standard Definition — and Why It Is Not Enough
The concept of open innovation was formalized by Henry Chesbrough in 2003, who described it as a model in which organizations use external as well as internal ideas and paths to market. The original framing was about IP and licensing strategy as much as ideation — the idea that valuable knowledge flows in both directions across organizational boundaries, and that managing those flows deliberately produces better innovation outcomes than treating the organization as a closed system.
That definition is correct but it is not the definition that helps an enterprise innovation team plan and run an open innovation program. For a practitioner, open innovation is the structured practice of sourcing ideas, technologies, and solutions from outside the organization — through challenges, partnerships, startup engagement, or academic collaboration — and managing the resulting submissions through a governance process that produces pilots and decisions rather than reports.
The distinction matters because open innovation programs fail when they are designed to the first definition and not the second. An organization that opens a challenge, receives five hundred submissions, and has no structured process for evaluating them has practiced the theory of open innovation without building the infrastructure that makes it produce outcomes. The submissions expire. The submitters lose faith. The program is quietly discontinued.
What separates open innovation programs that produce outcomes from those that produce activity is governance — the structured workflow that connects an external submission to an internal evaluation, to a pilot decision, to a measurable result. Why enterprise innovation pilots fail before the technology gets a chance to prove itself is almost always a governance problem, not a technology problem. Open innovation programs are particularly vulnerable to it because the volume is higher, the submitters are external, and the stakes for organizational credibility are visible outside the company.
The Three Models of Open Innovation Enterprise Teams Actually Use
Enterprise open innovation programs take different forms depending on the problem being solved. The three most common models are challenges, startup engagement programs, and academic or research partnerships. Each has a different use case, a different governance model, and a different failure mode.
1. Innovation Challenges
An innovation challenge is a structured call for solutions to a defined problem, open to external participants — startups, entrepreneurs, independent developers, researchers, or members of the public — with a defined submission period, evaluation process, and outcome pathway.
Challenges work best when the problem is clearly defined and the evaluation criteria can be standardized. They produce the most value when the organization has a genuine intent to pilot the winning solutions — not to publish the results or announce the partnership, but to run a structured test in a real operational environment.
The failure mode for challenges is submission overload without evaluation infrastructure. A well-promoted challenge at a large enterprise can attract hundreds or thousands of submissions. Without a structured intake process, standardized evaluation criteria, and a governance workflow that routes qualifying submissions to internal champions, the program collapses under its own volume. Submissions go unreviewed. Participants receive no response. The organization learns nothing actionable from the process.
The pharmaceutical industry has been one of the more sophisticated practitioners of challenge-based open innovation — using them to source solutions for specific drug discovery, clinical operations, or manufacturing problems where external expertise materially exceeds internal capability. How a global pharma company used open innovation challenges to move startups from application to pilot illustrates what the governance infrastructure behind a functional challenge program looks like in practice.
2. Startup Engagement Programs
Startup engagement programs are structured relationships between large enterprises and early-stage companies, designed to give the enterprise access to emerging technology and give the startup access to enterprise validation, distribution, or revenue.
These programs take several forms: accelerators, where startups receive resources and mentorship in exchange for access and sometimes equity; pilot programs, where startups run structured tests inside the enterprise in exchange for commercial potential; and scouting programs, where internal teams systematically identify and evaluate startups in relevant technology categories before the organization has a specific use case to fill.
The governance challenge for startup engagement programs is different from challenges. The volume of inbound interest from startups at large enterprises is high and constant — and most of it is irrelevant to current program priorities. How innovation teams actually use startup databases — and where they break down covers the specific limitations of the database-first approach to startup engagement and what a structured evaluation workflow looks like instead.
The failure mode for startup engagement programs is the reverse of challenge programs: too little structure, not too much volume. Programs that are managed through spreadsheets and email produce inconsistent evaluations, lose institutional memory when team members change, and make it impossible to report on program outcomes with any credibility.
3. Academic and Research Partnerships
Academic partnerships connect enterprise innovation programs to university research, government labs, and independent research institutions — typically for longer-horizon technology exploration that internal R&D teams cannot resource, or for access to specialized expertise in emerging technology domains.
These partnerships are less common than challenges or startup programs at most enterprises, but they are disproportionately valuable in industries with long innovation cycles — pharmaceuticals, energy, advanced manufacturing, defense — where the gap between research and commercial application is wide enough that building internal capability to bridge it is not practical.
The governance model for academic partnerships is different from the other two: the timeline is longer, the output is less defined, and the success metrics are harder to standardize. Programs that treat academic partnerships with the same governance structure as a startup pilot tend to terminate them prematurely when they do not produce measurable results on a quarterly cadence.
What Open Innovation Programs Actually Require to Work
The organizations that run open innovation programs that produce outcomes share four operational characteristics that are absent in programs that produce activity without results.
A Defined Problem Before the Submission Window Opens
The quality of open innovation submissions is determined by the quality of the problem statement. Organizations that open challenges or engagement programs with vague mandates — "we are looking for innovative solutions in the sustainability space" — receive submissions that are equally vague and equally difficult to evaluate against a consistent standard.
Effective open innovation programs define the problem at a level of specificity that allows a submitter to understand whether their solution is relevant before they invest time applying. This means a defined operational context, measurable success criteria, a clear description of the constraints the solution must operate within, and an explicit statement of what the organization is and is not willing to do with a winning submission.
The effort required to write a high-quality problem statement is significant. It requires internal alignment on what problem is actually being solved, which business unit owns the outcome, what IT and security constraints apply to any solution, and what the commercial pathway looks like for a startup that wins. Most open innovation programs that fail do so because this alignment never happened before the submission window opened.
Evaluation Infrastructure That Can Handle the Volume
A well-promoted challenge at a large enterprise can receive hundreds of submissions in the first week. Without structured intake — standardized fields, automated routing, scoring criteria defined before submissions arrive — the evaluation process becomes manually intensive and inconsistent. Why idea capture matters — and why traditional idea management tools are not enough covers this distinction: the tools that work for capturing internal ideas are not the same tools that work for managing the volume and external stakeholder complexity of an open innovation program.
Evaluation infrastructure for open innovation means: a structured intake form that captures the information required for evaluation, automated routing to the internal evaluator most qualified to assess each submission category, a standardized scoring rubric applied consistently across all submissions in a category, and a governance gate that produces a binary decision — advance or decline — with documented rationale for each submission that reaches it.
The organizations that manage this well treat open innovation evaluation the same way they treat internal idea evaluation: as a governed workflow with decision gates rather than a review process that produces recommendations. The difference is whether the process produces decisions or produces more deliberation.
An Explicit Pilot Pathway for Qualifying Submissions
The most common failure mode for open innovation programs that make it past the evaluation stage is the pilot pathway problem: a submission advances through evaluation, receives positive internal feedback, is designated as a priority — and then waits six months for someone to figure out how to actually run a pilot with an external company.
This is a governance design failure, not a problem with the submission. Innovation pilot management for external partners involves a different set of considerations than internal pilots: NDA and IP agreements need to be in place before technical access is granted, the external partner needs a defined point of contact and a clear scope of work, IT security review timelines need to be built into the pilot schedule rather than discovered mid-engagement, and the commercial pathway — what happens if the pilot succeeds — needs to be defined before the pilot begins rather than after it ends.
Programs that design the pilot pathway before the challenge launches — not as a generic framework but as a specific process with named owners, defined timelines, and clear decision criteria — move qualifying submissions from evaluation to active pilot in weeks rather than months.
Institutional Memory That Survives Team Changes
Open innovation programs are particularly vulnerable to institutional memory loss because they generate high volumes of structured data — submission records, evaluation scores, decline rationales, pilot outcomes — that are valuable as historical context but rarely captured in retrievable form. Why innovation portfolios break down without institutional memory applies directly to open innovation: the evaluation rationale that explains why a category of submissions was consistently declined is exactly the institutional knowledge that prevents an organization from running the same unproductive challenge two years later.
The structural solution is a platform that captures open innovation program data — challenge parameters, submission records, evaluation scores and rationale, pilot outcomes — in a format that belongs to the organization rather than to the individuals who ran the program. When the program manager who ran the last three challenges leaves, the institutional knowledge stays.
Open Innovation vs. Internal Idea Management: When to Use Each
Enterprise innovation teams frequently manage both internal idea programs and open innovation programs, and the relationship between them is often unclear. The distinction matters because the governance requirements are different, the evaluation criteria are different, and the organizational stakeholders who need to be involved are different.
Internal idea management is optimized for employee-generated ideas — capturing them at scale, evaluating them against strategic priorities, and advancing the ones that meet a threshold into structured development or piloting. The evaluation criteria are primarily internal: strategic fit, resource requirements, technical feasibility given current capabilities, and alignment with existing roadmaps.
Open innovation is optimized for externally sourced solutions to defined problems — challenges that require external expertise, technology categories where the internal development cost is prohibitive, or market signals that require a broader view than internal teams can generate. The evaluation criteria include external factors: market validation, startup viability, IP position, integration complexity, and commercial terms.
The programs are complementary, not competing. An internal idea program surfaces the problems worth solving. An open innovation program sources external solutions to the problems that internal capabilities cannot address efficiently. The organizations that run both well use a connected platform where an internal idea can initiate an open innovation challenge — the idea identifies the problem, the challenge sources the solution.
What Open Innovation Platforms Actually Support: A Comparison
Not all innovation management platforms handle open innovation with the same depth. The table below compares the capabilities that enterprise open innovation programs require across the platforms most commonly evaluated for this use case.
The capability that separates Traction from the rest of this list is the connection between open innovation and pilot management in a single platform. Every other platform manages submissions through evaluation — and then requires the organization to move qualifying submissions into a separate system to run the pilot. That handoff is where open innovation programs lose momentum and where institutional memory breaks down.
What Good Open Innovation Looks Like at Scale: The Pharma Example
The pharmaceutical industry offers the clearest examples of open innovation programs that have matured into repeatable, outcome-producing processes. The industry's structural characteristics — long development timelines, defined regulatory gates, high tolerance for external partnership, and deep pockets for pilot investment — make it a natural environment for open innovation at scale. How a global pharma company used open innovation challenges to move startups from application to pilot illustrates the specific infrastructure that produced those outcomes.
What makes pharma open innovation programs instructive for teams in other industries is not the specific technology categories being evaluated — it is the governance discipline. The programs that produce outcomes treat challenge design as a distinct capability, maintain evaluation standards across challenge cycles, document decline rationales with enough specificity to inform the next challenge, and build pilot pathways before submissions arrive rather than after.
Those disciplines are not specific to pharma. They are the operational characteristics of any open innovation program that produces outcomes rather than reports.
Open Innovation Examples in Practice
Open innovation is used across industries wherever the pace of technological change exceeds what an internal R&D organization can build alone. While the specific technologies vary by industry, the operational structure of successful programs is remarkably consistent: a defined problem, an external sourcing mechanism, structured evaluation, and a pilot pathway for qualifying solutions.
Consumer Goods — Product and Packaging Innovation
Consumer goods companies frequently use open innovation challenges to source sustainable materials, packaging technologies, and new product concepts. A global CPG company might open a challenge for biodegradable packaging solutions, receive submissions from materials startups and university labs, and pilot the most promising candidates with a manufacturing partner.
Energy — Decarbonization and Industrial Technology
Energy companies often run open innovation programs focused on emerging decarbonization technologies such as carbon capture, hydrogen production, advanced batteries, and industrial electrification. These programs frequently combine technology scouting with targeted startup challenges to identify solutions that can be tested in operational environments.
Financial Services — Risk, Fraud, and Data Infrastructure
Large financial institutions use open innovation to identify new approaches to fraud detection, identity verification, payments infrastructure, and regulatory technology. Startups with specialized AI or data capabilities can often move from evaluation to pilot quickly because the operational problem is clearly defined and the success metrics are measurable.
Manufacturing — Automation and Industrial Efficiency
Manufacturers frequently use open innovation to identify robotics, predictive maintenance, computer vision, and supply chain optimization technologies. Because these solutions can often be tested within a single plant or facility, manufacturing environments are well suited for structured pilot programs with emerging technology vendors.
Across industries, the pattern is consistent: internal teams define the problem, external innovators propose solutions, and structured evaluation determines which opportunities move to pilot.
The difference between programs that produce outcomes and those that produce reports is whether that process is governed.
FAQ
What is open innovation?Open innovation is the structured practice of sourcing ideas, technologies, and solutions from outside the organization — through challenges, startup engagement programs, or research partnerships — and managing the resulting submissions through a governance process that produces pilots and decisions. The term was introduced by Henry Chesbrough in 2003 to describe a model in which organizations deliberately use external as well as internal knowledge flows as part of their innovation process.
What is the difference between open innovation and closed innovation?Closed innovation treats the organization as a self-contained system — ideas originate internally, are developed internally, and are commercialized internally. Open innovation treats the organizational boundary as permeable — valuable ideas and technologies can originate externally, internal capabilities can be licensed or partnered externally, and the most efficient path to a solution is not always the internal one. Most large enterprises operate on a hybrid model: internal programs for incremental improvement and open innovation for problems where external expertise or speed is required.
What is an open innovation challenge?An open innovation challenge is a structured call for solutions to a defined problem, open to external participants — startups, researchers, developers, or the public — with a defined submission window, evaluation process, and outcome pathway. Challenges work best when the problem is clearly defined, the evaluation criteria are standardized, and the organization has a genuine intent to pilot qualifying submissions rather than publish the results.
What is an open innovation platform?An open innovation platform is software that manages the full lifecycle of an open innovation program — from challenge design and external submission intake through evaluation, pilot governance, and outcome documentation. Purpose-built open innovation platforms like Traction Technology connect the open innovation workflow to internal idea management and pilot management in a single connected system, so that qualifying submissions move from evaluation to active pilot without leaving the platform.
Why do open innovation programs fail?The most common failure modes are: a vague problem statement that produces submissions that cannot be evaluated against a consistent standard; insufficient evaluation infrastructure to handle submission volume; no defined pilot pathway for qualifying submissions, so they stall after evaluation; and institutional memory loss when program staff change. Programs that address all four failure modes before the submission window opens produce outcomes. Programs that address them reactively tend to produce one expensive, inconclusive challenge cycle and then reduce scope or discontinue.
What is the difference between open innovation and idea management?Idea management is optimized for employee-generated ideas — capturing them at scale, evaluating them against internal strategic priorities, and advancing the ones that meet a threshold. Open innovation is optimized for externally sourced solutions to defined problems. The programs are complementary: internal idea management surfaces the problems worth solving; open innovation sources external solutions to problems that internal capabilities cannot address efficiently. The organizations that run both well use a connected platform where the two workflows are linked.
How does open innovation relate to technology scouting?Technology scouting is a proactive, continuous process of identifying and evaluating emerging technologies in relevant categories before the organization has a specific use case to fill. Open innovation is typically reactive — a defined problem triggers a challenge or engagement process. The programs are complementary: technology scouting surfaces categories worth monitoring; open innovation challenges source specific solutions within those categories. Traction's technology scouting platform connects both workflows, so that scouting insights can initiate an open innovation challenge without leaving the platform.
What industries use open innovation most effectively?Pharmaceuticals, energy, advanced manufacturing, financial services, and consumer goods have the most mature open innovation programs at the enterprise level. Common characteristics across industries: long enough innovation cycles to justify external sourcing, defined operational constraints that make the problem statement specific enough to produce high-quality submissions, and organizational tolerance for external partnership at the pilot stage. Industries with very short innovation cycles or very low tolerance for external IP involvement tend to run less productive open innovation programs.
Related Reading
- Why Enterprise Innovation Pilots Fail Before the Technology Ever Gets a Chance
- What Is Pilot Management Software? How Enterprise Teams Move Beyond Project Management
- How to Design Innovation Decision Gates That Actually Work
- Why Innovation Portfolios Break Down Without Institutional Memory
- Case Study: How a Global Pharma Company Used Open Innovation Challenges to Move Startups from Application to Pilot
- What Is Innovation Management? A Practical Definition for Enterprise Teams
- How Innovation Teams Actually Use Startup Databases — and Where They Break Down
About Traction Technology
Enterprise innovation programs that produce outcomes run on Traction.
Before we built the platform, we ran these programs manually — years as technology scouts and innovation analysts for global enterprises, evaluating vendors, managing pilots, and supporting open innovation challenges from the inside. We built Traction because the tools we needed did not exist.
Traction is the platform where enterprise innovation gets done — from the idea an employee submits to the open innovation challenge that sources the solution, through the pilot a business unit runs to the outcome a board approves, in one connected system with institutional memory at every step. Recognized by Gartner as a leading Innovation Management Platform and trusted by innovation teams at global enterprises across manufacturing, financial services, pharma, and professional services.
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