In today’s fast-moving world, digital transformation isn’t just a buzzword. It’s a real force changing how businesses think, create, and compete. Corporate innovation labs are at the center of this change. They’re no longer just experimental corners of companies — they are becoming the engines of future growth. Let’s explore 30 powerful statistics that show how digital transformation is shaping these labs and what it means for businesses.
1. 87% of companies believe digital transformation will disrupt their industry, yet only 44% are adequately prepared for it
Understanding the Reality Gap
When nearly 9 out of 10 businesses expect digital to shake up their industry, it’s clear we’re in the middle of a revolution. But here’s the problem — less than half of these businesses are truly ready for it. This mismatch between expectation and preparation is where innovation labs have a huge opportunity.
Innovation labs should be seen as proactive tools, not reactive safety nets. They need to help companies move beyond seeing digital transformation as an external threat and start seeing it as something they can lead.
What Labs Can Do
First, labs need to audit their readiness. What tools, processes, and talent do they already have in place? Where are the gaps? Start simple. Review your current tech stack. Check for outdated systems or manual workflows that slow you down.
Next, focus on training. Even the best ideas fail if your team can’t execute them using modern tools. Innovation labs should create in-house learning programs around digital fluency — especially in areas like data literacy, no-code tools, and agile project management.
Also, don’t try to change everything at once. Pick one or two internal challenges and digitize those. Maybe it’s automating how ideas are submitted and tracked. Or using AI to shortlist user feedback from product tests.
Finally, stay close to the customer. If your competitors are struggling to change, being more responsive and digital-savvy gives you a head start.
2. 70% of corporate innovation labs have integrated digital transformation initiatives as a core priority
Embedding Digital at the Heart of Innovation
When something becomes a priority for 7 out of 10 innovation labs, it’s no longer a trend. It’s a requirement. Digital transformation has moved from the sidelines to the main stage, and labs are no longer allowed to ignore it.
Integrating digital doesn’t just mean using tech. It means rethinking how innovation is done. From idea generation to testing and scaling — digital should touch every step.
Getting Started with Integration
Start by breaking down silos. Many innovation labs still work like separate islands. When digital transformation becomes a core focus, it forces collaboration between IT, marketing, R&D, and customer support.
Adopt a “digital by default” mindset. When planning a new initiative, ask: How can digital tools help us do this faster, better, or cheaper? This question alone can lead to smarter experimentation.
Also, bring in digital KPIs. Traditional innovation metrics like number of ideas generated or patents filed don’t tell the whole story. Add measures like data utilization, speed to insight, or automation rate.
And remember, integration is not a one-time task. Make regular digital reviews a habit. Evaluate what worked, what didn’t, and which tools need upgrading.
3. 56% of innovation labs report increased speed-to-market due to digital tools
Speed is the New Strategy
In innovation, timing is everything. Getting a product to market fast can be the difference between being a leader and an afterthought. More than half of innovation labs now say that digital tools are helping them move faster — and that’s a game-changer.
Think about how long it used to take to test an idea. With today’s digital platforms, you can prototype in hours, get feedback in days, and iterate in real-time.
How to Gain Speed
Start by switching to agile workflows. Ditch the old waterfall model where everything is planned months in advance. Use tools like Kanban boards, Slack integrations, and sprint planning apps to stay nimble.
Use low-code and no-code platforms. These let non-technical team members build prototypes or even launch simple apps. You don’t need to wait for engineering teams to write custom code.
Automate where you can. Use tools to automate user surveys, schedule product tests, or collect analytics. This reduces manual work and speeds up learning cycles.
Also, reduce decision bottlenecks. Empower your teams to make small decisions without layers of approval. Create clear guidelines on what can be tested independently and what needs senior review.
The faster your lab moves, the more ideas you can test, and the better your chances of hitting a breakthrough.
4. Labs using AI tools report a 3.4x higher rate of successful product launches
The Power of Artificial Intelligence in Innovation
When you hear that AI boosts product launch success by over three times, it’s clear this isn’t hype. AI doesn’t just make things faster — it makes them smarter. From analyzing trends to predicting outcomes, AI helps labs focus their energy where it matters.
This doesn’t mean you need to build your own AI. Today, there are tons of ready-made tools that help you apply AI in simple, practical ways.
Making AI Work for Your Lab
Start by identifying high-effort tasks with low value. AI is great at automating things like sorting feedback, clustering ideas, or forecasting trends. Tools like ChatGPT, Google AutoML, or even Excel with AI plugins can be powerful additions.
Use AI for testing too. Predictive analytics can show which features customers are likely to use. Sentiment analysis tools can help you understand user reactions without manually reading every comment.
Even better, use AI to build custom user personas or simulate market conditions. This gives your prototypes a stronger real-world foundation, even before launch.
But remember, AI is only as good as the data you feed it. Invest time in cleaning and organizing your internal data. If your lab is still storing insights in random slides and emails, fix that first.
Once your data flows freely and your team gets comfortable with AI, you’ll start seeing results — not just faster launches, but smarter ones.
5. 62% of labs say digital transformation has improved collaboration between departments
Breaking Down Barriers with Digital Tools
Innovation doesn’t happen in isolation. It takes input from marketing, IT, customer support, finance, and even legal teams. But traditionally, these departments have worked in silos. They’ve had their own systems, goals, and ways of working. That’s a recipe for slow progress and missed opportunities.
Now, more than half of labs report that digital transformation is making collaboration easier and more effective. That’s not just a nice benefit — it’s essential to innovation.
How Labs Can Enhance Collaboration
Start by setting up a central digital hub for communication. This could be as simple as a shared Slack workspace or a collaboration platform like Microsoft Teams or Notion. What matters is that everyone involved in a project can see the same information and contribute in real-time.
Use shared dashboards for tracking experiments, updates, and results. Tools like Trello, Asana, or Airtable allow every stakeholder to know what’s happening — without digging through emails.
Make transparency part of your lab culture. Schedule short, regular check-ins with cross-functional teams. Keep meetings focused, but make sure everyone gets to voice concerns or share input.
Digital tools can also help you collect input at the idea stage. Set up open innovation portals or forms where anyone from any department can submit an idea or solution. Then use voting or ranking systems to prioritize them.
When collaboration becomes part of the process, not an afterthought, your innovation efforts become smarter, faster, and more aligned with the company’s real needs.
6. Digital-first labs are 2.5x more likely to meet their innovation KPIs
Why Digital-First Means Results-Driven
KPIs are how labs measure success. Are we launching enough pilots? Are we increasing customer satisfaction? Are we building things that generate revenue?
Here’s the secret: labs that lead with digital tools are much more likely to hit their targets. They aren’t guessing — they’re using data to track progress and digital tools to adapt quickly.
A digital-first lab doesn’t just use technology. It builds its workflows, metrics, and decisions around it.
How to Go Digital-First
Start with measurement. Identify the 3–5 metrics that truly define success for your lab. It might be number of experiments per quarter, percent of ideas reaching pilot, or speed from idea to market. Then choose digital tools that help you track those metrics in real-time.
Next, simplify your workflows. Use tools like Miro or Figma to digitally map out your innovation process, from idea intake to scaling. When every step is visible and trackable, it’s easier to spot bottlenecks and fix them fast.
Train your team to think digitally. Encourage them to ask: Can we automate this? Is there a tool that does it better? Do we have data to back this decision? These questions shift the mindset from manual to measurable.
Also, connect your KPIs to business outcomes. Don’t just track ideas — track impact. That could mean increased revenue, better retention, or faster response to market changes. Digital-first labs don’t stop at activity — they focus on results.
7. 75% of labs use cloud platforms to streamline prototyping and experimentation
The Cloud Advantage
Gone are the days when building a prototype meant installing complex software or waiting for IT support. Today, three out of four innovation labs are using cloud platforms to design, test, and deploy experiments faster than ever.
Cloud tools let you work from anywhere, collaborate in real time, and access powerful computing without needing your own servers. They also make scaling easier when an idea takes off.
Leveraging the Cloud for Innovation
Start by picking the right platforms. For design, tools like Figma and Canva operate fully in the cloud. For development, platforms like GitHub, AWS, or Firebase allow you to deploy test environments quickly.
Encourage your team to use collaborative documents and dashboards instead of sending files back and forth. Google Workspace, Notion, and Monday.com help you move fast without losing track of your work.
Security matters too. Make sure you follow best practices for access control, backups, and encryption. Many labs work with sensitive data or early-stage ideas that require protection.
Finally, use the cloud for testing. A/B testing tools, remote usability testing, and heatmaps can all be cloud-based. This lets you gather insights without setting up physical labs or expensive infrastructure.
With the cloud, your lab can become lighter, faster, and more flexible — exactly what innovation demands.
8. Labs implementing agile + digital frameworks reduce cycle times by 45%
Agility Meets Technology
Innovation is all about moving fast without breaking everything. Agile frameworks help teams focus on delivering value in small chunks. When you combine that with digital tools, you get speed with structure — and that’s powerful.
Labs that embrace agile plus digital reduce their cycle times by nearly half. That means faster launches, quicker feedback, and more learning.
Building an Agile Digital Lab
Start with agile basics. Create cross-functional squads that can work independently. Use short sprints (usually two weeks) to test and build. Hold regular stand-up meetings to check progress.
Digital tools make this smoother. Use tools like Jira or ClickUp for sprint planning. Use digital whiteboards like Miro for ideation. Automate reporting so your team spends more time doing and less time updating spreadsheets.
Create feedback loops. Agile works best when you learn quickly and apply it fast. Set up automated surveys, user interviews, and internal reviews as part of each sprint.
Keep your backlog prioritized and public. Let everyone see what’s coming next. This helps align stakeholders and reduces interruptions.
Most importantly, focus on delivering something usable in every sprint. Even if it’s a clickable mock-up or a short video demo, having something to show builds momentum.
When labs go agile and digital together, they stop spinning wheels and start making real progress.
9. 68% of innovation labs use real-time analytics to guide development decisions
From Gut Feel to Data-Led
Innovation used to be driven by instinct. Someone had a big idea, pitched it, and the team ran with it. That still happens — but now it’s backed by data. Nearly 7 out of 10 labs are using real-time analytics to make better choices.
Real-time data helps you know what users are doing, not just what they say. It shows you where people click, where they drop off, and what features they actually use.
Making Data Work for Innovation
First, make sure you’re collecting the right data. Use tools like Mixpanel, Google Analytics, or Amplitude to track user behavior on your test products. If you’re running experiments on websites or mobile apps, this is essential.
Next, visualize the data. Dashboards help everyone — not just analysts — understand what’s happening. Tools like Looker Studio or Tableau let you create clear visuals for daily decisions.
Don’t wait for monthly reports. Use real-time alerts to catch problems or trends as they happen. This helps you adjust your experiments before they fail or miss the mark.
Involve your team in reviewing data. Make it a habit to end each sprint with a quick look at what the numbers say. Encourage questions like: What surprised us? What worked better than expected? What needs a change?
When you start using analytics to steer decisions, your lab becomes more focused, more confident, and more effective.
10. IoT-enabled innovation labs report a 29% boost in operational efficiency
The Internet of Things Advantage
IoT — or the Internet of Things — connects physical objects to the internet so they can collect and share data. In innovation labs, this means everything from smart sensors in prototypes to connected devices in testing environments.
When labs use IoT tools, they get real-time feedback from the physical world. That leads to better testing, faster problem-solving, and almost a third more efficiency.
Using IoT in Your Innovation Lab
Start with small wins. Add sensors to physical prototypes to track usage, temperature, or movement. Use simple devices like Arduino or Raspberry Pi to run early experiments.
Use IoT platforms like Azure IoT or AWS IoT Core to manage the data. These tools let you visualize sensor input, trigger alerts, and store logs for later analysis.
Improve testing environments. Use smart plugs, connected lights, or motion sensors to automate repetitive testing tasks or simulate real-world conditions.
Create digital twins — virtual models of physical products that use IoT data to mirror real behavior. This helps you test ideas without needing to build full physical versions.
IoT helps innovation labs move beyond the screen and into the real world. It bridges the gap between software and hardware and gives you insights that would be impossible otherwise.
11. Only 37% of labs have a dedicated digital innovation strategy
Why Strategy is the Missing Link
Many innovation labs use digital tools. They experiment with AI, try agile methods, and run pilots. But here’s the issue: only a third of them have a real strategy for how all this fits together.
That’s like driving a sports car without a map. You might move fast, but you won’t know where you’re going. A digital innovation strategy isn’t just about picking tools — it’s about aligning technology with business goals.
How to Build a Digital Innovation Strategy
Start by asking what problems your company needs to solve. Is it reducing costs? Reaching new customer segments? Speeding up product development? Your digital strategy should serve those goals.
Next, define your digital innovation pillars. These are areas you want to focus on — like automation, data-driven decisions, or customer experience. Each pillar should guide what tools you use and what experiments you run.
Map out your talent needs. Strategy isn’t just about software — it’s also about people. Identify the skills you need to execute. Maybe it’s machine learning, rapid prototyping, or UX design. Then plan how to hire, train, or partner.
Measure your progress. Pick a few KPIs that reflect your digital maturity. For example: number of digital experiments run, adoption of automation, or usage of customer data in product decisions.
Finally, communicate the strategy. A simple one-pager that explains your goals, tools, and timelines can align your team and earn buy-in from leadership. When everyone knows the plan, execution gets easier.
12. Labs leveraging digital twins have reduced prototyping costs by 33%
The Smart Way to Prototype
Prototyping is essential in innovation. But building physical versions of new products can be expensive and time-consuming. That’s where digital twins come in.
A digital twin is a virtual version of a product, process, or system. It reacts like the real thing, but exists in software. Labs that use digital twins are saving serious time and money — often cutting a third of their costs.
Making the Most of Digital Twins
You don’t need to be a giant company to use this tech. Start with basic simulations. Use 3D modeling tools like SolidWorks, Unity, or even Blender to create a digital version of your product.
Run tests in virtual environments. Check for stress points, failure conditions, or user interactions. This helps you fix flaws before you build anything physical.
Combine your digital twin with IoT data. If your product is connected (like a smart device), feed real-time usage data back into the model. This creates a feedback loop that sharpens your design.
Use the twin to train your team. Let marketers, support teams, or salespeople interact with the virtual product. It gives them context, speeds up training, and improves internal understanding.
Digital twins are not just for engineers. They’re tools for faster learning, better design, and more informed decisions. Once you use them, you’ll wonder how you worked without them.
13. 82% of innovation labs see data as the foundation for competitive advantage
Why Data is the New Gold
We often say “knowledge is power,” but in today’s world, it’s data that drives everything. The vast majority of innovation labs now treat data as their core advantage. Not ideas. Not creativity. Data.
That doesn’t mean creativity is dead — far from it. But the best ideas come from insights. And insights come from data.
Becoming a Data-Driven Lab
Start by organizing what you already have. Many companies are sitting on years of product feedback, user logs, survey results, and internal reports. Use a tool like Airtable, Notion, or a custom database to centralize it.
Make data accessible. If only one person knows how to pull a report, you’ve got a bottleneck. Create self-service dashboards that let any team member explore trends or run filters.
Encourage curiosity. Ask your team to bring data to every idea session. Challenge assumptions. For example: “We think users want feature X. What does the data say?”
Don’t just collect data — interpret it. Invest in tools that visualize patterns or flag anomalies. Use AI to find hidden relationships. Even simple charts can spark powerful insights.
And finally, protect your data. Use secure systems, follow privacy laws, and stay transparent with users. Data is your asset, but it’s also your responsibility.
When you treat data as your foundation, innovation stops being random. It becomes targeted, scalable, and much more successful.
14. 59% of labs reported increased engagement with external startups post-digital transformation
Partnering for Growth
Innovation doesn’t always happen inside your own building. In fact, more labs are finding success by working with external startups. After going digital, almost 6 out of 10 labs say they’ve built stronger startup partnerships.
Startups bring speed, creativity, and risk-taking. Corporate labs bring resources, experience, and scale. Together, they can build better solutions faster.
How to Work with Startups
Start by identifying gaps in your roadmap. What ideas are important, but too risky or time-consuming for your team to pursue internally? That’s where startups can help.
Set up a partnership framework. Will you run joint pilots? Offer funding? Give access to customers or infrastructure? Be clear about the terms so everyone knows what to expect.
Use digital platforms to scout partners. Join startup hubs, accelerators, or open innovation portals. Platforms like AngelList, Crunchbase, or even LinkedIn can help you find strong matches.
Treat startups as partners, not vendors. Involve them in planning sessions, share your insights, and align on goals. The more open the relationship, the more value you’ll both get.
Also, move fast. Startups don’t operate on six-month planning cycles. If you want to keep them engaged, streamline your legal, procurement, and testing processes.
When corporate labs and startups work together in a digital-first way, the result is not just faster innovation — it’s better innovation.
15. Labs using low-code platforms accelerate MVP delivery by 5x
Faster Builds with Less Code
Launching a minimum viable product (MVP) used to require full development teams, months of coding, and lots of back-and-forth. Not anymore. Low-code platforms have changed the game.
Labs using these tools are building MVPs up to five times faster. That means they can test more ideas, gather more feedback, and make better decisions — all without burning through time or money.
Using Low-Code in Your Lab
Low-code platforms like Bubble, OutSystems, or Webflow let non-engineers build working apps, dashboards, or tools. You drag and drop components instead of writing every line of code.
Start small. Use low-code to build internal tools — like an experiment tracker, a survey app, or a simple customer portal. This gives your team confidence and shows value quickly.
Pair low-code with real user testing. Launch your MVP to a small audience, collect feedback, and iterate weekly. Because changes are easier, you can respond much faster.
Involve cross-functional teams. Let marketers, designers, or product managers contribute directly. This speeds up the process and brings diverse perspectives into the build.
Even your engineering team benefits. By handling the simple stuff with low-code, developers can focus on complex, high-impact problems.
Low-code isn’t about replacing developers — it’s about speeding up experimentation. In innovation labs, that’s exactly what you need.
16. 66% of innovation labs reported enhanced customer co-creation through digital interfaces
Creating With Customers, Not Just For Them
Traditionally, innovation labs built solutions and then tested them on customers. But in today’s world, customers want to be part of the creation process. Two-thirds of labs now say digital tools have helped them co-create better with their audience.
This isn’t just about feedback — it’s about real collaboration. Digital interfaces like live prototyping, interactive surveys, and online communities make it easier than ever to involve users early and often.
How to Co-Create Digitally
Start with listening tools. Platforms like Typeform, Maze, or UserTesting allow you to collect rich insights directly from your target audience. Use them during brainstorming, not just at the end.
Build shareable prototypes. Tools like Figma, Marvel, or InVision let you create clickable mockups that users can interact with remotely. Gather reactions on flow, features, and usability — before you write a single line of code.
Host virtual idea jams. Set up online sessions where customers can suggest features, rank priorities, or react to early concepts. Even a private Facebook group or Slack channel can work.
Track engagement. Use heatmaps, click trackers, and user recordings to see what people really do with your concepts. This adds depth to what they say.
Most importantly, make co-creation a cycle, not a one-time task. Keep customers in the loop as you test, revise, and scale. When people feel involved, they’re more likely to adopt what you create — and promote it too.
17. Digital collaboration tools reduced project delays in labs by 41%
Killing the Wait Time
Innovation labs often struggle with delays. A great idea gets stuck in approvals, communication falls through, or files are lost in endless email threads. But digital collaboration tools are changing that.
Labs that use these tools effectively are reducing project delays by nearly half. That’s a major productivity boost — and one that pays off in faster launches and fewer missed opportunities.
Using Digital Tools to Stay on Track
First, centralize communication. Use tools like Slack, Teams, or Discord to create real-time, organized channels for every project. No more searching through emails.
Second, manage tasks clearly. Platforms like Asana, ClickUp, or Monday.com help you assign, track, and update work across teams. Everyone knows who’s doing what, by when.
Use shared documents. Google Docs, Notion, and Confluence allow for real-time editing, version control, and commenting — perfect for keeping everyone aligned.
Integrate notifications and reminders. Connect your tools so that progress updates trigger alerts automatically. This keeps projects moving and prevents follow-up from falling through the cracks.
Lastly, make it a rule to keep everything visible. Project timelines, goals, blockers — put them in shared dashboards. This not only reduces confusion but also builds accountability.
When communication improves, coordination follows — and delays disappear.
18. 72% of labs noted increased executive buy-in due to clearer ROI from digital innovations
Show the Value, Earn the Support
Innovation labs often struggle with one thing: getting leadership to support bold ideas. But that’s changing. Nearly three-quarters of labs now say they’ve earned more executive backing thanks to the clearer return on investment (ROI) that digital tools provide.
Why? Because digital transformation makes results easier to track, measure, and explain. You’re not just saying “we launched something.” You’re saying “we launched this, it cost X, and it generated Y.”
Proving ROI in Your Lab
First, define what success looks like. ROI doesn’t have to mean revenue right away. It could be time saved, process streamlined, customer retention improved, or risk reduced.
Track inputs and outputs. Use simple spreadsheets or analytics dashboards to show how resources (like time, tools, or money) lead to measurable outcomes.
Create short case studies for your experiments. Even a one-pager that shows “before and after” numbers helps executives understand the impact of your work.
Use storytelling with data. Don’t just show charts — explain them. Show the problem, the experiment, and the result. Make it personal. Add a customer quote, a team insight, or a quick video clip.
Keep leadership updated with short, regular briefs. When your lab becomes known for showing impact clearly, buy-in comes more naturally. You’ll have the trust — and the budget — to do even more.
19. AI-enhanced decision-making improved project success rates by 39%
Smarter Choices, Better Results
Innovation is full of choices — which idea to pursue, which feature to build, which user segment to target. Making those decisions can be hard, especially with limited time and data. That’s where AI comes in.
Labs using AI to guide decisions are seeing almost 40% better success rates. Not because AI replaces humans, but because it gives them better inputs and sharper predictions.
Putting AI into Your Decision Flow
Start with prioritization. Use AI tools like predictive analytics to score ideas based on potential impact and feasibility. This helps you avoid wasting time on low-potential bets.
Apply AI to user feedback. Use sentiment analysis tools to process hundreds of customer comments and detect trends. You’ll quickly see which features matter most and what pain points to solve first.
Use machine learning to simulate outcomes. Whether it’s pricing models, churn prediction, or feature adoption, AI can show you possible futures — and help you choose the best path.
Don’t forget visual AI. Tools like DALL·E or Runway can help you generate fast visual content or mockups to speed up the design phase.
Always validate AI output with human judgment. AI helps you narrow the field — it’s your team’s job to make the final call.
By making decisions faster and smarter, you give your lab more chances to win
20. Labs adopting machine learning reported a 22% increase in market responsiveness
Staying Ahead of the Curve
The market moves fast. Trends shift, competitors launch new features, and customer needs evolve overnight. Labs that use machine learning are better at keeping up. They react quicker, spot changes earlier, and adjust faster.
This increase in responsiveness — over 20% — isn’t just a number. It means getting ahead of problems, seizing new opportunities, and staying relevant.
Using Machine Learning to Move Fast
Start with trend spotting. Use ML tools to scan social media, forums, and reviews for early signs of change in customer sentiment or demand.
Apply ML to segmentation. Traditional customer segments can be static. Machine learning can detect new behavioral clusters, allowing you to target messaging or features more accurately.
Use ML models to forecast demand. Whether you’re managing digital inventory or product usage, smarter predictions mean fewer surprises.
Connect your data streams. The more real-time data your models have access to, the faster they’ll learn and respond. Integrate CRM, analytics, and user data into a central system.
Use feedback loops. ML gets better the more it learns. Set up systems where outcomes of experiments feed back into the model, so your predictions get sharper over time.
Machine learning isn’t just about tech. It’s about building a lab that sees, learns, and adapts faster than anyone else.
21. 64% of labs report better alignment with core business units post-digitization
Connecting Innovation to the Business
A big challenge for corporate innovation labs has always been staying aligned with the rest of the company. Labs often get so focused on new ideas that they drift away from what the core business needs. But that’s changing.
More than 60% of labs say that going digital has actually improved their alignment with the main business units. Why? Because digital tools increase visibility, improve communication, and help teams collaborate in real time.
Building Stronger Bridges to the Business
First, create shared dashboards. Use tools like Looker Studio or Power BI to track your lab’s progress in a way business units understand. Show how your work links to company goals like customer satisfaction, efficiency, or revenue.
Involve business units early. Before launching any major experiment, ask how it might impact sales, service, or operations. This helps you avoid duplication and gain allies across departments.
Make reporting consistent. Schedule regular updates with department heads, not just executives. Even a 15-minute monthly sync can keep teams connected and engaged.
Also, use digital tools to invite collaboration. Open up access to prototypes, testing feedback, and backlog priorities. When teams can see what you’re working on — and how it helps them — they’re more likely to support and adopt your ideas.
Digitization is not just about faster innovation. It’s about making that innovation matter across the company.
22. Only 28% of innovation labs currently leverage blockchain, but 61% plan to explore it
Blockchain: The Next Frontier?
Blockchain is often associated with cryptocurrency, but its real power goes far beyond that. It offers secure, transparent, and decentralized systems that can change how companies manage data, contracts, and transactions.
While less than a third of labs are using blockchain now, nearly two-thirds are looking into it. That’s a strong signal — and a huge opportunity.
Starting Smart with Blockchain
First, understand the use cases that make sense for your company. These might include secure data sharing, tamper-proof records, digital identity management, or transparent supply chains.
Pick a single problem to solve. Don’t try to reinvent everything. Focus on a clear pain point — maybe tracking product authenticity or automating contract approvals.
Use platforms like Ethereum, Hyperledger, or Polygon to test blockchain applications without needing to build from scratch. These tools offer frameworks and APIs you can customize.
Partner with blockchain startups. Many are looking for corporate collaborators and can help you move fast with proof-of-concepts or pilots.
Train your team on the basics. Even a simple workshop or self-paced course can demystify blockchain and help your staff spot relevant opportunities.
Blockchain isn’t just for finance or crypto. For labs, it can become a powerful tool to build trust, automate complexity, and drive transparency — all key ingredients in innovation.
23. Labs with digital transformation programs attract 3.1x more internal investment
Show the Value, Earn the Budget
Budgets are tight. Every team wants more funding, but only those that prove their value get it. Labs that have embraced digital transformation are seeing over three times more internal investment — and that’s no coincidence.
When your lab works faster, smarter, and with more transparency, stakeholders notice. And when you show clear ROI, funding follows.
Getting the Resources You Need
Start by documenting your wins. Every successful experiment, cost-saving pilot, or customer insight should be captured, shared, and celebrated. Make impact visible — not just within your team, but across the organization.
Use digital tools to create easy-to-read reports and dashboards. Visualize how your work connects to key business metrics. The clearer your value, the easier it is to justify more funding.
Share your roadmap. Show what you’ll do with additional investment. Break down how new tools, talent, or infrastructure will lead to bigger or faster wins.
Create executive champions. Regularly update leaders with bite-sized progress reports. Invite them to demos or customer tests. When they see your work in action, they’re more likely to advocate for you.
Remember: investment isn’t just about money. It’s also about trust, attention, and internal influence. Digital maturity builds all three.
24. Digital training programs led to a 47% increase in lab staff productivity
Empower Your Team
Innovation starts with people. No matter how advanced your tools are, they’re only as effective as the people using them. That’s why labs that invest in digital training see nearly 50% more productivity.
Training doesn’t just make people more capable — it makes them more confident, more collaborative, and more likely to try new things.
Building a Learning-First Lab
Start with a skills assessment. What digital tools does your team already know? Where are the gaps? Focus training on high-impact areas like data analysis, rapid prototyping, or automation.
Offer multiple formats. Some people like live workshops, others prefer self-paced courses. Use platforms like Coursera, Udemy, or even YouTube to provide flexible options.
Create a culture of learning. Celebrate when someone learns a new tool or method. Encourage knowledge-sharing sessions where team members teach each other.
Tie training to outcomes. Don’t just track course completion. Track how the training improved productivity — faster testing, better reports, or smoother collaboration.
Also, train for the future. Don’t just teach today’s tools — teach your team how to stay current, evaluate new technologies, and adapt to change.
When your people grow, your lab grows with them.
25. 53% of labs cited cybersecurity concerns as a major barrier to further digital adoption
Don’t Let Security Slow You Down
Going digital opens up amazing possibilities — but it also brings risks. Over half of innovation labs say that security concerns are slowing down their adoption of new tools and technologies.
That’s understandable. But it doesn’t mean you have to stop. It means you have to be smart.
Balancing Innovation and Security
First, involve your security team early. Don’t wait until deployment to run checks. Make them part of your planning and design process.
Use secure platforms. Choose tools with strong reputations for compliance, encryption, and data protection. Check for certifications like ISO 27001, SOC 2, or GDPR compliance.
Set access controls. Not everyone needs to see everything. Use roles, permissions, and two-factor authentication to limit risk.
Train your team on digital hygiene. A single phishing email or bad password can cause major damage. Make sure everyone knows how to protect their devices, data, and systems.
Create backup plans. Have clear protocols for data recovery, breach response, and system failure. Being prepared reduces stress — and speeds up recovery if something goes wrong.
Innovation and security are not enemies. With the right systems and habits, your lab can be both bold and safe.
26. Labs using virtual and augmented reality saw a 36% boost in user testing efficiency
Seeing is Believing
User testing is vital, but traditional methods can be slow, costly, and limited. That’s why labs using virtual reality (VR) and augmented reality (AR) are gaining an edge. They report over a one-third increase in testing efficiency — which means faster feedback, clearer insights, and quicker improvements.
These tools immerse users in realistic environments where they can interact with prototypes in real-time. It’s like inviting people into your product before it even exists.
Making VR and AR Work for Testing
Start with simple VR mockups. Use tools like Unity or Unreal Engine to build interactive experiences. Even basic simulations can reveal how users behave, navigate, or respond to features.
For physical products, use AR apps that overlay virtual elements onto real-world settings. Apps like Adobe Aero or Reality Composer let you test how something looks, fits, or functions in context — whether it’s packaging, signage, or hardware.
Run remote sessions. VR and AR allow you to test with users anywhere in the world. No need for labs or travel — just send them a link or headset.
Capture behavioral data. Track where users look, what they touch, and how they move. This gives you deeper insights than surveys alone.
And don’t limit this to customers. Use AR/VR to get faster internal feedback from sales, support, or manufacturing teams. Their input can improve usability and scalability early on.
With immersive testing, your ideas don’t just look good — they work better too.
27. 79% of labs say digital transformation helped them pivot faster during crises (e.g., COVID-19)
Resilience Through Digital
The COVID-19 pandemic tested every business. Those who couldn’t adapt quickly faced major disruptions. But nearly 8 out of 10 innovation labs say digital transformation helped them pivot faster — not just survive, but stay useful during the crisis.
That’s the hidden power of digital: it gives you options. It makes you more agile, more connected, and more resilient when the unexpected hits.
Building Crisis-Ready Capabilities
Start by enabling remote work. Use cloud tools, secure VPNs, and real-time collaboration platforms so your team can work from anywhere without missing a beat.
Digitize your core processes. Move from paper to platforms. Automate manual steps. This not only saves time but also keeps your lab running when teams are distributed.
Use digital listening tools. Track changes in customer behavior, competitor activity, and market signals. During a crisis, fast insights are priceless.
Diversify your channels. Don’t rely on a single way to test, market, or deliver ideas. Use social platforms, digital prototypes, and online user panels to stay flexible.
Finally, make learning part of your process. After every disruption, review what worked, what didn’t, and what you need to build next. The goal isn’t to avoid crises — it’s to become strong enough to bend without breaking.
28. Labs with centralized data infrastructure report 2.8x better decision agility
The Power of One Source of Truth
Data is everywhere — but that’s not always a good thing. When teams pull numbers from different systems, it creates confusion, duplication, and delay. Labs that centralize their data infrastructure are nearly three times more agile in decision-making.
Why? Because they’re faster, clearer, and more confident in their choices.
Creating a Centralized Data Setup
Start with a data audit. Identify where your data lives — surveys, analytics, CRMs, spreadsheets, customer platforms. Map it out.
Use integration tools like Zapier, Segment, or custom APIs to bring everything into a central dashboard. Tools like Tableau, Google BigQuery, or Snowflake are great for managing large datasets.
Set clear data definitions. Agree on what metrics mean — like “active user” or “conversion.” This prevents misinterpretation and builds trust.
Make dashboards available to everyone in the lab. When your entire team can access real-time data, they can make decisions faster and with less friction.
Regularly clean your data. Remove duplicates, fill in gaps, and update tags. Clean data leads to clean decisions.
When your lab runs on one shared source of truth, you cut debate, increase speed, and execute with precision.
29. Digital integration improved IP generation rate by 31% in leading labs
Innovating Smarter, Not Just Faster
Intellectual property (IP) — whether patents, trademarks, or trade secrets — is a major output of innovation labs. And digital integration is making a big difference. Top labs are generating 31% more IP thanks to better collaboration, faster idea capture, and clearer documentation.
This isn’t just about having more ideas. It’s about capturing and protecting the right ones.
Strengthening Your IP Pipeline
Use digital idea platforms like Ideanote or Brightidea to capture ideas as they happen. Don’t rely on notebooks or scattered email threads. Digital logs are timestamped, searchable, and shareable.
Build templates for documenting concepts, prototypes, and iterations. This helps your team describe, compare, and refine ideas in a consistent format — crucial for filing patents later.
Involve legal and compliance early. Give them access to idea portals or dashboards so they can flag potential IP as it develops.
Track which projects lead to IP. Look for patterns — certain tools, team setups, or customer involvement may increase your IP yield.
Celebrate inventors internally. Highlight team members who contribute to patents or novel solutions. This creates a culture of innovation and ownership.
When you integrate digital tools into your IP workflow, you don’t just innovate more — you innovate better.
30. Innovation labs with mature digital ecosystems are 4x more likely to scale innovations enterprise-wide
From Lab to Launchpad
It’s one thing to test new ideas. It’s another to scale them across the entire business. Labs with mature digital ecosystems — the right tools, processes, and culture — are four times more likely to do just that.
Scaling doesn’t happen by luck. It happens when everything is connected, from early insight to enterprise rollout.
Building a Scalable Digital Ecosystem
Start by designing with scale in mind. Build pilots using the same platforms and standards your business uses. That way, scaling is a matter of turning on access — not rebuilding from scratch.
Use modular systems. Design tools, processes, and assets that can be reused or adapted for different teams or markets.
Document everything. From learnings to code to user flows, make sure your projects are clear and transferable. Use wikis, shared folders, and centralized repositories.
Involve downstream teams early. Include operations, IT, and customer-facing roles in your pilot testing. Their input ensures you’re building something they can support.
Finally, track adoption. Once an idea rolls out, measure uptake, usage, and ROI. Share those wins to fuel momentum for future innovations.
When your lab becomes a launchpad — not just a playground — your whole company starts to innovate together.
Conclusion:
Digital transformation isn’t optional. It’s the key to making innovation labs faster, smarter, and more connected to the business. These 30 statistics aren’t just numbers — they’re road signs. They point to what’s working, what’s changing, and what your lab can do to stay ahead.
