Category Archives: Innovation

How Consensus Kills Innovation

How Consensus Kills Innovation

GUEST POST from Greg Satell

“I hate consensus,” legendary Silicon Valley coach Bill Campbell used to growl. The problem, as the authors explain in the book, Trillion Dollar Coach, wasn’t that he didn’t want people to get along, but that an easy consensus often leads to groupthink and inferior decisions. It’s often just easier to fall in line than to engage in vigorous debate.

Research bears this out. In one study where college students were asked to solve a murder mystery, homogenous groups that formed an easy consensus felt more successful, but actually performed worse than more diverse teams that argued and voiced different viewpoints. When everybody agrees, nobody questions.

Make no mistake. If an idea is big enough, some people aren’t going to like it. Some will argue against it passionately and others may even try and actively undermine it. Yet rather than working to silence those voices, we need to learn to bring them to the fore. That’s how we can test our assumptions, consider other alternatives and, ultimately, come up with better ideas.

The Dangers of Consensus

Whenever the Harlem Globetrotters play the Washington Generals, there’s no doubt what the outcome will be, because the point isn’t to have a genuine contest. The games are essentially theatre set up to entertain the audience. All too often, we set up meetings in very much the same way — designed to reach a particular conclusion for the sake of expediency.

Unfortunately, leaders have strong incentives to drive quickly toward a consensus. Listening to dissenting views takes time and energy and we want to get things done quickly and move forward. So, it’s tempting to stock the room with people who are already on board and present the idea as a fait accompli.

Even if a leader isn’t consciously designing meetings for consensus, dissenting views can get squelched. In a famous series of conformity studies done in the 1950s, it was shown that we have a strong tendency to agree with the majority opinion even if it is obviously wrong. Subsequent research has generally confirmed the findings.

The truth is that majorities don’t just rule, they also influence. We can’t count on one or two lone voices having the courage to speak up. That’s why it’s not enough to simply listen to dissenting views, we must actively seek them out.

Uncovering Dissent

The biggest mistake a leader can make is to assume that they have somehow built a culture that is so unique, and that people feel so secure that they will voice their true views. We have to design for debate—it won’t just happen on its own—and there are several techniques that can help us do that.

The first is changing meeting structure. If the most senior person in the meeting voices an opinion, others will tend to fall in line. So, starting with the most junior person and then working up will encourage more debate. Another option is to require everyone to voice an opinion, either through a document or a conversation with a senior leader, before the meeting starts.

Another strategy that is often effective is called a pre-mortem analysis. Similar to a post-mortem analysis in which you try to figure out what went wrong, in a pre-mortem you assume a project has failed in the future and try to guess what killed it. It’s a great way to surface stuff you might have missed.

A third option is to set up a red team. This is an independent group whose sole purpose is to poke holes in a plan or a project. For example, while planning the Osama bin Laden Raid, a red team was set up to look at the same evidence and try to come up with different conclusions. They were able to identify a few key weaknesses in the plan that were then corrected.

Overcoming Opposition

While opening up a healthy discussion around dissenting views helps drive innovation forward, ignoring opposition can lead to its demise. Every significant innovation represents change, which creates winners and losers. There will always be some who will be so vehemently opposed that they will try to undermine an innovation moving forward.

Since my book Cascades was published, I’ve had the opportunity to work with a number of organizations working to drive transformation and have been amazed how reticent many are to identify entrenched opposition and build a strategy to overcome it. Often, they aren’t willing to admit that opposition is relevant or even that it exists at all.

Unlike those who merely have dissenting views, but share objectives and values with the transformation team, entrenched opposition wants to stop change in its tracks. For example, as I have previously noted, it was internal opposition, chiefly from franchisees and shareholders, not a lack of strategy or imagination, that killed Blockbuster Video.

That’s why, much like dissenting views, it’s important to bring opposition to the fore. In Blockbuster’s case, there were various actions that management could have taken to mollify the opposition and address some of the concerns. That wouldn’t have guaranteed success, but it would have made it far more likely.

Innovation Must Be Led

Steve Jobs was, by all accounts, a mediocre engineer. It was his passion and vision that made Apple the most valuable company on the planet. In a similar vein, there were plenty of electric car companies before Tesla, but Elon Musk was the first who showed that the technology can succeed in the marketplace.

Can you imagine what would have happened if Jobs had the iPhone designed by a committee? Or if Musk had put Tesla’s business plan to a vote? It’s hard to see either having had much success. What we would have ended up with is a watered-down version of the initial idea.

Yet all too often, managers seek out consensus because it’s easy and comfortable. It’s much harder to build a culture of trust that can handle vigorous debate, where people are willing to voice their opinions and listen to those of others without it getting personal. That, however, is what innovative cultures do.

Big ideas are never easy. Almost by definition, they are unlikely, fraught with risk and often counterintuitive. They need champions to inspire and empower beliefs around them. That’s why leadership drives innovation and consensus often kills it.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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The Importance of Diversity in Innovation Teams

The Importance of Diversity in Innovation Teams

GUEST POST from Chateau G Pato

In a world defined by rapid change and complexity, innovation is the engine of progress. But what powers innovation? The answer lies in diversity—the rich tapestry of perspectives, experiences, and ideas that diverse teams bring to the table. Diversity in innovation teams is not a luxury; it’s a necessity for creating solutions that resonate with a global audience. Diverse teams challenge assumptions, uncover blind spots, and spark breakthroughs that homogenous groups often overlook. In this article, we’ll explore why diversity is critical to innovation, examine two powerful case studies, and offer practical steps for building inclusive teams that drive human-centered change.

Why Diversity Fuels Innovation

Diversity in innovation teams encompasses more than demographics like race, gender, or age. It includes cognitive diversity—different ways of thinking and problem-solving—as well as socioeconomic, geographic, and professional diversity. This multifaceted approach ensures that teams approach challenges from multiple angles, leading to more creative and effective solutions. A 2015 McKinsey study found that companies in the top quartile for racial and ethnic diversity were 15% more likely to achieve above-average financial returns, while those with gender diversity were 25% more likely to outperform their peers.

But the benefits go beyond numbers. Diverse teams foster psychological safety, where team members feel empowered to share bold ideas without fear of judgment. This environment is critical for human-centered innovation, which relies on empathy to address the needs of diverse audiences. However, diversity alone isn’t enough—organizations must cultivate inclusion to ensure every voice is heard and valued. Without inclusion, diversity can lead to conflict or disengagement, undermining innovation efforts.

Case Study 1: IBM’s Design Thinking Transformation

In the early 2010s, IBM faced a challenge: how to stay competitive in a fast-evolving tech landscape. The company turned to design thinking, a human-centered approach to innovation, and prioritized diversity in its teams. IBM assembled cross-functional groups that included engineers, designers, data scientists, and marketers from diverse cultural, racial, and professional backgrounds. These teams were trained to empathize with users, define problems collaboratively, and prototype solutions iteratively.

The impact was profound. Diverse teams helped shape IBM’s Watson AI platform, ensuring its applications—particularly in healthcare—addressed the needs of varied patient populations. For example, insights from team members with international healthcare experience led to features that supported multilingual patient interactions, improving accessibility. By 2018, IBM reported a 300% increase in ROI for design-driven projects, with diverse teams credited for identifying user needs that might have been missed by less varied groups.

“Our diverse teams brought perspectives that challenged our assumptions and made Watson a truly global solution,” said Phil Gilbert, former President of IBM Design. “Inclusion was the key to unlocking their potential.”

[Image: A diverse IBM team collaborates in a design thinking workshop, using sticky notes and whiteboards to map user journeys. Alt text: A group of professionals from varied backgrounds brainstorming around a whiteboard filled with colorful sticky notes.]

Case Study 2: Procter & Gamble’s Connect + Develop Program

Procter & Gamble (P&G) revolutionized its innovation strategy with its Connect + Develop program, launched in the early 2000s. The initiative sought external partnerships to co-create products, and diversity was at its core. P&G formed teams that blended internal employees with external experts from startups, academia, and global communities, representing diverse industries, cultures, and socioeconomic backgrounds. This approach disrupted P&G’s traditional thinking and led to groundbreaking innovations.

The Swiffer product line is a prime example. A diverse team of chemists, marketers, and external designers from varied cultural contexts collaborated to address unmet consumer needs for convenient cleaning. Insights from team members with experience in emerging markets ensured the Swiffer was affordable and practical for a wide range of households. The result? Swiffer became a $1 billion brand within a few years, contributing to P&G’s reported 50% innovation success rate through Connect + Develop.

“Diversity gave us a window into consumer needs we hadn’t seen before,” said Laura Becker, a former P&G innovation leader. “Our global team members brought ideas that transformed our approach.”

[Image: A Swiffer product prototype being tested by a diverse focus group in a real-world setting. Alt text: A group of people from different backgrounds testing a Swiffer mop in a home environment.]

Overcoming Challenges in Diverse Teams

While diversity drives innovation, it can also present challenges. Differing perspectives may lead to conflict, and unconscious bias can hinder inclusion. To address these issues, organizations must invest in training to mitigate bias, establish clear communication norms, and promote active listening. Leaders should also set shared goals to align diverse teams around a common purpose, ensuring that differences become a source of strength rather than division.

Building Diverse Innovation Teams: Practical Steps

Creating diverse, inclusive innovation teams requires intentional action. Here are five practical steps to get started:

  • Recruit with Purpose: Actively seek talent from underrepresented groups and diverse disciplines to build a robust talent pipeline.
  • Foster Psychological Safety: Create a culture where team members feel safe to share ideas and take risks, using tools like anonymous feedback systems.
  • Use Human-Centered Frameworks: Adopt design thinking or similar approaches to focus on empathy and user needs, leveraging diversity to understand varied audiences.
  • Train for Inclusion: Provide regular training on unconscious bias and inclusive leadership to ensure all voices are valued.
  • Measure and Celebrate Success: Track diversity metrics and celebrate innovations driven by diverse teams to reinforce their value.

By implementing these steps, organizations can harness the full potential of diversity to drive innovation that resonates with a global market.

Conclusion: A Call to Action

Diversity is the cornerstone of innovation in a connected world. The case studies of IBM and P&G demonstrate that diverse teams deliver measurable results—higher ROI, breakthrough products, and solutions that serve diverse audiences. But building such teams requires commitment. As leaders, we must challenge ourselves to recruit inclusively, foster psychological safety, and leverage human-centered tools to unlock creativity. The future of innovation depends on our ability to embrace the full spectrum of human potential. Start today—audit your teams, identify gaps in diversity, and take action to build a more inclusive innovation culture.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Pexels

Guest AI: Grok

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Now is the Time to Design Cost Out of Our Products

Now is the Time to Design Cost Out of Our Products

GUEST POST from Mike Shipulski

With inflation on the rise and sales on the decline, the time to reduce costs is now.

But before you can design out the cost you’ve got to know where it is. And the best way to do that is to create a Pareto chart that defines product cost for each subassembly, with the highest cost subassemblies on the left and the lowest cost on the right. Here’s a pro tip – Ignore the subassemblies on the right.

Use your costed Bill of Materials (BOMs) to create the Paretos. You’ll be told that the BOMs are wrong (and they are), but they are right enough to learn where the cost is.

For each of the highest-cost subassemblies, create a lower-level Pareto chat that sorts the cost of each piece-part from highest to lowest. The pro tip applies here, too – Ignore the parts on the right.

Because the design community designed in the cost, they are the ones who must design it out. And to help them prioritize the work, they should be the ones who create the Pareto charts from the BOMs. They won’t like this idea, but tell them they are the only ones who can secure the company’s future profits and buy them lots of pizza.

And when someone demands you reduce labor costs, don’t fall for it. Labor cost is about 5% of the product cost, so reducing it by half doesn’t get you much. Instead, make a Pareto chart of part count by subassembly. Focus the design effort on reducing the part count of subassemblies on the left. Pro tip – Ignore the subassemblies on the right. The labor time to assemble parts that you design out is zero, so when demand returns, you’ll be able to pump out more products without growing the footprint of the factory. But, more importantly, the cost of the parts you design out is also zero. Designing out the parts is the best way to reduce product costs.

Pro tip – Set a cost reduction goal of 35%. And when they complain, increase it to 40%.

In parallel to the design work to reduce part count and costs, design the test fixtures and test protocols you’ll use to make sure the new, lower-cost design outperforms the existing design. Certainly, with fewer parts, the new one will be more reliable. Pro tip – As soon as you can, test the existing design using the new protocols because the only way to know if the new one is better is to measure it against the test results of the old one.

And here’s the last pro tip – Start now.

Image credit — aisletwentytwo

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Top 10 Human-Centered Change & Innovation Articles of July 2022

Top 10 Human-Centered Change & Innovation Articles of July 2022Drum roll please…

At the beginning of each month we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are July’s ten most popular innovation posts:

  1. What Latest Research Reveals About Innovation Management Software — by Jesse Nieminen
  2. Top Five Reasons Customers Don’t Return — by Shep Hyken
  3. Five Myths That Kill Change and Transformation — by Greg Satell
  4. How the Customer in 9C Saved Continental Airlines from Bankruptcy — by Howard Tiersky
  5. Changing Your Innovator’s DNA — by Arlen Meyers, M.D.
  6. Why Stupid Questions Are Important to Innovation — by Greg Satell
  7. We Must Rethink the Future of Technology — by Greg Satell
  8. Creating Employee Connection Innovations in the HR, People & Culture Space — by Chris Rollins
  9. Sickcare AI Field Notes — by Arlen Meyers, M.D.
  10. Cultivate Innovation by Managing with Empathy — by Douglas Ferguson

BONUS – Here are five more strong articles published in June that continue to resonate with people:

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last two years:

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America Needs to Innovate Its Innovation Ecosystem

America Needs to Innovate Its Innovation Ecosystem

GUEST POST from Greg Satell

The world today just seems to move faster and faster all the time. From artificial intelligence and self-driving cars to gene editing and blockchain, it seems like every time you turn around, there’s some newfangled thing that promises to transform our lives and disrupt our businesses.

Yet a paper published by a team of researchers in Harvard Business Review argues that things aren’t as they appear. They point out that total factor productivity growth has been depressed since 1970 and that recent innovations, despite all the hype surrounding them, haven’t produced nearly the impact of those earlier in the 20th century.

The truth is that the digital revolution has been a big disappointment and, more broadly, technology and globalization have failed us. However, the answer won’t be found in snazzier gadgets or some fabulous “Golden Era” of innovation of years long past. Rather we need to continually innovate how we innovate to solve problems that are relevant to our future.

The Productivity Paradox, Then and Now

In the 1970s and 80s, business investment in computer technology was increasing by more than 20% per year. Strangely though, productivity growth had decreased during the same period. Economists found this turn of events so bizarre that they called it the “productivity paradox” to underline their confusion.

Yet by the late 1990s, increased computing power combined with the Internet to create a new productivity boom. Many economists hailed the digital age as a “new economy” of increasing returns, in which the old rules no longer applied and a small initial advantage, a first mover advantage, would lead to market dominance. The mystery of the productivity paradox, it seemed, had been solved. We just needed to wait for technology to hit critical mass.

Yet by 2004 productivity growth fell once again and has not recovered since. Today, more than a decade later, we’re in the midst of a second productivity paradox, just as mysterious as the first one. New technologies like mobile computing and artificial intelligence are there for everyone to see, but they have done little, if anything, to boost productivity.

Considering the rhetoric of many of the techno-enthusiasts, this is fairly shocking. Compare the meager eight years of elevated productivity that digital technology produced with the 50-year boom in productivity created in the wake of electricity and internal combustion and it’s clear that the digital economy, for all the hype, hasn’t achieved as much as many would like to think.

Are Corporations to Blame?

One explanation that the researchers give for the low productivity growth is that large firms are cutting back on investment in science. They explain that since the 1980s, a “combination shareholder pressure, heightened competition, and public failures led firms to cut back investments in science” and point to the decline of Bell Labs and Xerox PARC as key examples.

Yet a broader analysis tells a different story. Yes, while Bell Labs and Xerox PARC still exist, they are but a shadow of their former selves, but others, such as IBM Research, have expanded their efforts. Microsoft Research, established in 1991, does cutting edge science. Google runs a highly innovative science program that partners with researchers in the academic world.

So anecdotally speaking, the idea that corporations haven’t been investing in science seems off base. However, the numbers tell an even stronger story. Data from the National Science Foundation shows that corporate research has increased from roughly 40% of total investment in the 1950s and 60s to more than 60% today. Overall R&D spending has risen over time.

Also, even where corporations have cut back, new initiatives often emerge. Consider DuPont Experimental Station which, in an earlier era, gave birth to innovations such as nylon, teflon and neoprene. In recent years, DuPont has cut back on its own research but the facility, which still employs 2000 researchers, is also home to the Delaware Incubation Space, which incubates new entrepreneurial businesses.

The Rise of Physical Technologies

One theory about the productivity paradox is that investment in digital technology, while significant, is simply not big enough to move the needle. Even today, at the height of the digital revolution, information and communication technologies only make up about 6% of GDP in advanced economies.

The truth is that we still live in a world largely made up of atoms, not bits and we continue to spend most of our money on what we live in, ride in, eat and wear. If we expect to improve productivity growth significantly, we will have to do it in the physical world. Fortunately, there are two technologies that have the potential to seriously move the needle.

The first is synthetic biology, driven largely by advances in gene editing such as CRISPR, which have dramatically lowered costs while improving accuracy. In fact, over the last decade efficiency in gene sequencing has far outpaced Moore’s Law. These advances have the potential to drive important productivity gains in healthcare, agriculture and, to a lesser extent, manufacturing.

The second nascent technology is a revolution in materials science. Traditionally a slow-moving field, over the past decade improved simulation techniques and machine learning have improved the efficiencies of materials discovery dramatically, which may have a tremendous impact in manufacturing, construction and renewable energy.

Yet none of these gains are assured. To finally break free of the productivity paradox, we need to look to the future, not the past.

Collaboration is the New Competitive Advantage

In 1900, General Electric established the first corporate research facility in Schenectady, New York. Later came similar facilities at leading firms such as Kodak, AT&T and IBM. At the time, these were some of the premier scientific institutions in the world, but they would not remain so.

In the 1920s new academic institutions, such as the Institute for Advanced Study, as well as the increasing quality of American universities, became an important driver of innovation. Later, in the 1940s, 50s and 60s, federal government agencies, such as DARPA, NIH and the national labs became hotbeds of research. More recently, the Silicon Valley model of venture funded entrepreneurship has risen to prominence.

Each of these did not replace, but added to what came before. As noted above, we still have excellent corporate research programs, academic labs and public scientific institutions as well as an entrepreneurial investment ecosystem that is the envy of the world. Yet none of these will be sufficient for the challenges ahead.

The model that seems to be taking hold now is that of consortia, such as JCESR in energy storage, Partnership on AI for cognitive technologies and the Manufacturing USA Institutes, that bring together diverse stakeholders to drive advancement in key areas. Perhaps most conspicuously, unprecedented collaboration sparked by the Covid-19 crisis has allowed us to develop therapies and vaccines faster than previously thought possible.

Most of all, we need to come to terms with the fact that the answers to the challenges of the future will not be found in the past. The truth is that we need to continually innovate how we innovate if we expect to ever return to an era of renewed productivity growth.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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Assessing Market Impact of New Innovations – Revised

Assessing Market Impact of New Innovations - Revised

GUEST POST from Chateau G Pato

Innovation is at the heart of economic growth and societal advancement. Developing a groundbreaking idea or technology is the beginning of a journey. The true challenge lies in assessing the market impact of these innovations. Understanding this impact allows businesses to refine strategies, maximize value, and drive sustainable growth. Let’s delve deeper into this topic with expanded focus on methodologies and broader insights from our case studies.

The Importance of Market Impact Assessment

Market impact assessment involves evaluating how innovations affect market dynamics, competitive landscapes, and customer behavior. This assessment is crucial for several reasons:

  • Identifying potential market size and profitability, helping prioritize resource allocation.
  • Understanding customer adoption and potential resistance, crucial for shaping marketing strategies.
  • Evaluating the impact on existing market players and new entrants, aiding in strategic positioning.

Case Study 1: Tesla’s Electric Vehicles

Tesla redefined the automotive industry with its electric vehicles (EVs). The impact assessment of their innovation provides insights into its success:

Market Entry and Expansion

Tesla entered a market predominantly dominated by internal combustion engines. The initial skepticism was high, but the company leveraged superior technology and eco-friendliness to attract early adopters.

Expanded Impact Assessment

Through continuous innovation in battery technology, software updates, and charging infrastructure, Tesla increased consumer confidence. A comprehensive market impact assessment revealed that Tesla’s innovation not only disrupted traditional automotive businesses but also catalyzed a global shift toward sustainable transportation. This triggered regulatory changes and influenced competitors to accelerate their EV strategies.

Case Study 2: Airbnb’s Sharing Economy Model

Airbnb introduced a revolutionary model in the hospitality sector, connecting homeowners and travelers through a digital platform.

Market Entry and Evolution

Airbnb challenged conventional hotels by offering unique, affordable stays. This required assessing user acceptance and regulatory landscapes.

Expanded Impact Assessment

By continuously analyzing market response, Airbnb identified a growing demand for personalized travel experiences. Success indicators included high platform engagement and a global expansion, reshaping the hospitality industry and driving regulatory scrutiny. The model’s success emphasized the importance of both customer trust and adaptability to local regulations. Continuously evolving based on user feedback allowed Airbnb to maintain its competitive edge.

Tools and Methods for Market Impact Assessment

Effective assessment involves diverse tools and approaches, such as:

  • SWOT Analysis: Identifies strengths, weaknesses, opportunities, and threats related to innovation, facilitating strategic planning.
  • Customer Surveys and Feedback: Collecting real-time consumer insights to gauge acceptance, needs, and satisfaction.
  • Competitive Benchmarking: Analyze industry trends and evaluate how innovations affect competitors and market standings.
  • Data Analytics and Predictive Modelling: Leveraging big data for forecasting trends, market shifts, and customer behavior patterns.
  • Scenario Planning: Testing potential outcomes to prepare strategic responses to various market scenarios.

Conclusion and Future Considerations

The ability to assess the market impact of innovations is critical for leveraging opportunities and navigating challenges. By learning from successful case studies like Tesla and Airbnb, businesses can develop robust strategies to confidently bring innovations to market. Looking forward, incorporating AI and machine learning into market assessments promises even deeper insights, allowing businesses to adapt more swiftly to changing market dynamics.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Unsplash

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Diverse Teams Driving Innovation

Case Studies

Diverse Teams Driving Innovation

GUEST POST from Chateau G Pato

In today’s rapidly evolving business landscape, innovation is not just an advantage—it’s a necessity. Diverse teams, bringing a mixture of perspectives, experiences, and cultures, are uniquely equipped to drive groundbreaking solutions. In this article, we’ll explore two compelling case studies illustrating how diversity is at the heart of innovative success.

Case Study 1: HealthTech Company – Revolutionizing Patient Care

A leading HealthTech company, cognizant of the need for inclusive healthcare solutions, formulated a diverse project team to create an app designed to assist patients with varied medical literacy levels. The team comprised software engineers, UX/UI designers, healthcare professionals, and patients from diverse demographic backgrounds. Each member provided unique insights into the app’s development.

**Challenges & Solutions:** Initially, the team grappled with integrating complex medical data in a user-friendly manner. However, the patient representatives highlighted specific pain points, which engineers and designers addressed through simplified designs and intuitive features.

**Results:** The app, celebrated for its user-centered design, increased patient engagement by 40% and was recognized with multiple industry awards. This success underscored the importance of diverse perspectives in healthcare innovation.

Case Study 2: EcoTech Initiative – Sustainable Energy Solutions

An EcoTech firm, aiming to make strides in renewable energy, assembled a team of environmental scientists, engineers, business strategists, and local community leaders. Their objective was to develop a cost-effective solar energy solution suitable for low-income regions.

**Challenges & Solutions:** The primary challenges were cost constraints and adaptability across different geographies. Local leaders provided insights into cultural and regional needs, guiding the development of adaptable units and cost-reduction strategies using locally sourced materials.

**Results:** The firm introduced a versatile solar panel that reduced costs by 30% and adapted to various landscapes. The project not only accelerated energy accessibility but also won contracts across three continents, demonstrating how diversity can expand market reach.

The Power of Diverse Teams in Innovation

Diverse teams are not immune to challenges, but they excel at turning them into opportunities. This is evident from the case studies above. Diverse perspectives ensure that solutions are comprehensive, culturally relevant, and innovative. By fostering diversity, companies can enhance creativity, ensure broader problem-solving capabilities, and ultimately drive success in a competitive market.

Building a Diverse Team: Key Takeaways

  • **Inclusive Recruitment:** Actively seek candidates from varied backgrounds and disciplines to enrich the innovation process.
  • **Empowerment and Inclusion:** Create an environment where all voices are heard and valued, encouraging open dialogue and collaboration.
  • **Continuous Learning:** Support team members in understanding diverse markets and perspectives through seminars, workshops, and cross-cultural training.

Conclusion

Diversity isn’t just a buzzword—it’s a catalyst for innovation. Whether dealing with technological advancements or regional adaptations, diverse teams bring forth multi-faceted solutions that drive industries forward. Embracing diversity thus emerges as a cornerstone of a robust innovation strategy, paving the way for sustainable success.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Pexels

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Reward Systems that Encourage Innovation

Reward Systems that Encourage Innovation

GUEST POST from Art Inteligencia

Innovation is the lifeblood of any thriving organization. To foster an environment where creativity and novel ideas flourish, companies must design reward systems that adequately incentivize innovation. This article explores key aspects of effective reward systems and provides illustrative case studies of organizations that excel in this area.

The Power of Meaningful Incentives

The foundation of any successful innovation strategy lies in the understanding that incentives can drive behavior. However, the incentives must align with both the organization’s goals and the intrinsic motivations of its employees. Effective reward systems recognize the importance of empowering employees, providing them with the freedom and resources to explore and experiment.

“Innovation comes from the willingness to do something different, not necessarily something bigger. Incentives should spark that willingness.” — Braden Kelley

Case Study 1: Google’s 20% Time

One brilliant example of fostering creativity through rewards is Google’s famous 20% Time initiative. Employees were encouraged to dedicate 20% of their workweek to projects they believed could benefit the company. This policy led to the development of groundbreaking products such as Gmail and AdSense. Google understood that the reward was not just in financial incentives but in the ownership and potential impact of the work.

Google’s approach highlights a few critical elements:

  • Trust in employees’ judgment
  • Time as a currency
  • A culture that embraces failure

While critics argue that the practice faded over time, its essence remains in Google’s flexible approach to project development. This case demonstrates that giving employees the permission and time to pursue side projects can yield valuable innovations.

Case Study 2: 3M’s Innovation Grant Program

3M, an industrial giant known for its innovation, has long utilized a unique reward system to spur creativity. Their Innovation Grant Program provides employees with seed funding to develop new products. Employees who receive these grants are empowered to work with minimal supervision and explore their ideas’ potential.

The well-known invention of the Post-it Note originated from such efforts. Researchers Spencer Silver and Art Fry transformed a failed adhesive experiment into an office supply staple, supported by sustained encouragement and resources from 3M.

Key takeaways from 3M’s approach include:

  • Provision of financial resources to explore ideas
  • Encouragement of cross-departmental collaboration
  • Commitment to a long-term innovation strategy

This approach underscores the power of blending financial incentives with cultural support, demonstrating how companies can effectively harvest internal talent to drive innovation.

The Right Mix of Recognition and Reward

A successful reward system for innovation blends intrinsic and extrinsic motivators. Companies should consider a range of tools, from financial bonuses and promotions to public recognition and personalized growth opportunities. Regardless of the form, the key is ensuring that rewards resonate with the unique motivations of each employee.

For instance, some employees may value public recognition and the opportunity to lead exciting projects, while others might prefer monetary rewards or additional learning and development opportunities.

Expanding the Case Studies

Delving deeper into Google’s approach, it’s pivotal to consider how their 20% Time also led to a culture where risk-taking was less daunting. Allowing room for failure without punitive measures laid the groundwork for continual learning and adaptability.

In the case of 3M, the steadfast support and patience to nurture ideas emphasize the importance of an ongoing commitment to innovation. Their program hasn’t only created new products but strengthened organizational resilience and adaptability over decades.

Conclusion

Designing reward systems that effectively encourage innovation is a nuanced endeavor. By understanding the motivations that drive employees and creating environments that support experimentation, failure, and cross-pollination of ideas, companies can unleash the full potential of their workforce.

Remember, the key lies in the balance — offering both the freedom to explore and the support to succeed. Whether it’s through time allocations like Google’s 20% Time or financial backing like 3M’s Innovation Grant Program, the message is clear: when employees feel valued and trusted, innovation thrives.

As I always say, “A truly innovative organization isn’t defined by its ideas but by its ability to nurture and implement them. This is what reward systems should achieve.”

Extra Extra: Futurology is not fortune telling. Futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: Pixabay

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Empathy: The Currency of Human Connection and Innovation

Empathy: The Currency of Human Connection and Innovation

GUEST POST from Soren Kaplan

Having worked with innovation teams from global companies like Visa, Colgate-Palmolive, Kimberly-Clark, Disney, Medtronic and many others, there’s one consistent success factor when it comes to innovation, no matter what you’re doing: it all starts with the customer.

Companies spend oodles of time and money trying to understand customers. They conduct surveys, hire market researchers, run focus groups, analyze social media, and the list goes on. What’s often missed, however, are customers’ deeper needs and underlying pain points that really matter to them. Quantitative surveys, for example, might give you a sense of a market’s overall sentiment about a topic, but you won’t get to know someone’s personal struggles and underlying motivations from checkboxes on an online form.

Instead, you need to truly put yourself in the customer’s shoes. It’s not just about intellectually understanding their situation. It’s about tapping into the emotions they feel, and even feeling them yourself as part of the process of connecting to their experience.

Empathy Reveals New Opportunities

I recently led a leadership development program for a large health care provider with hundreds of hospitals. They wanted to understand their patients better, so they could come up with innovations to help them stay healthy and avoid costly visits to the doctor and hospital. Initially, the team had ideas to provide promotional materials on how to eat healthier and exercise.

As part of the process, a small team went to visit patients at their homes in rural areas. At one house, they discovered a giant water tank had been built by a company that towered over their patient’s home–and it was slowly dripping water on the roof, creating a whole variety of problems, including causing the beginnings of respiratory issues for the woman living in the house due to mold. The team was shocked.

The team realized that pamphlets about healthy eating and exercise wouldn’t do much to help. They also recognized that in certain cases they might need to provide radically different types of support to their patients as part of ensuring their overall health, beyond just providing traditional health care. They helped the woman contact the water tank company to fix the leak. They have also since expanded their approach around prevention to address various “social determinants of health” in communities like poor quality water, lack of healthy food, and other issues that lead to health issues long before someone shows symptoms of a formal medical issue.

Immersing yourself in the world of your customers through visits, observation, interviews, and other interactions can provide a new perspective around issues, problems, and assumptions.

Capture Concrete Observations

Empathy is a core element of “design thinking,” a common approach used for product and service innovation. It’s also a concept that can be hard to understand when it comes to translating what you might see and hear into something meaningful about the customer. Here’s a template for doing just that from Praxie.com.

Customer Empathy Map

The next time you connect with a customer, consider the following to help capture concrete observations:

  • Say: What does the customer explicitly say?
  • Feel: What are the customer’s emotions?
  • Think: What occupies the customer’s thoughts?
  • Do: What does the customer do in public?

By providing a structure for cataloguing your observations, you can turn what might seem as ambiguous into something tangible.

Turn Observations into Insight

It’s one thing to observe customers. It’s another to translate what you observe into real insights that help catalyze new ideas.

Once you’ve cataloged your observations, take a step back. Consider the ultimate “pain points” that your customer experiences. What are the customer’s top problems or frustrations? Also be sure to consider the “gain” the customer hopes to achieve. What does the customer hope to accomplish or achieve?

Answering these questions helps move general observations into insights that can be used as the basis for generating new ideas.

Give the World Your Empathy

Empathy is the currency of human connection. We all crave it. And when we give it to others, we build and deepen relationships. Try empathizing with others. You’ll see the returns in the form of a better world, and greater innovation.

Image credits: Praxie.com, Pexels

This article was originally published on Inc.com and has been syndicated for this blog.

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Reversible versus Irreversible Decisions

Reversible versus Irreversible Decisions

GUEST POST from Farnham Street

We often think that collecting as much information as possible will help us make the best decisions. Sometimes that’s true, but sometimes it hamstrings our progress. Other times it can be flat out dangerous.

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Many of the most successful people adopt simple, versatile decision-making heuristics to remove the need for deliberation in particular situations.

One heuristic might be defaulting to saying no, as Steve Jobs did. Or saying no to any decision that requires a calculator or computer, as Warren Buffett does. Or it might mean reasoning from first principles, as Elon Musk does. Jeff Bezos, the founder of Amazon.com, has another one we can add to our toolbox. He asks himself, is this a reversible or irreversible decision?

If a decision is reversible, we can make it fast and without perfect information. If a decision is irreversible, we had better slow down the decision-making process and ensure that we consider ample information and understand the problem as thoroughly as we can.

Bezos used this heuristic to make the decision to found Amazon. He recognized that if Amazon failed, he could return to his prior job. He would still have learned a lot and would not regret trying. The decision was reversible, so he took a risk. The heuristic served him well and continues to pay off when he makes decisions.

Decisions Amidst Uncertainty

Let’s say you decide to try a new restaurant after reading a review online. Having never been there before, you cannot know if the food will be good or if the atmosphere will be dreary. But you use the incomplete information from the review to make a decision, recognizing that it’s not a big deal if you don’t like the restaurant.

In other situations, the uncertainty is a little riskier. You might decide to take a particular job, not knowing what the company culture is like or how you will feel about the work after the honeymoon period ends.

Reversible decisions can be made fast and without obsessing over finding complete information. We can be prepared to extract wisdom from the experience with little cost if the decision doesn’t work out. Frequently, it’s not worth the time and energy required to gather more information and look for flawless answers. Although your research might make your decision 5% better, you might miss an opportunity.

Reversible decisions are not an excuse to act reckless or be ill-informed, but rather are a belief that we should adapt the frameworks of our decisions to the types of decisions we are making. Reversible decisions don’t need to be made the same way as irreversible decisions.

The ability to make decisions fast is a competitive advantage. One major advantage that start-ups have is that they can move with velocity, whereas established incumbents typically move with speed. The difference between the two is meaningful and often means the difference between success and failure.

Speed is measured as distance over time. If we’re headed from New York to LA on an airplane and we take off from JFK and circle around New York for three hours, we’re moving with a lot of speed, but we’re not getting anywhere. Speed doesn’t care if you are moving toward your goals or not. Velocity, on the other hand, measures displacement over time. To have velocity, you need to be moving toward your goal.

This heuristic explains why start-ups making quick decisions have an advantage over incumbents. That advantage is magnified by environmental factors, such as the pace of change. The faster the pace of environmental change, the more advantage will accrue to people making quick decisions because those people can learn faster.

Decisions provide us with data, which can then make our future decisions better. The faster we can cycle through the OODA loop, the better. This framework isn’t a one-off to apply to certain situations; it is a heuristic that needs to be an integral part of a decision-making toolkit.

With practice, we also get better at recognizing bad decisions and pivoting, rather than sticking with past choices due to the sunk costs fallacy. Equally important, we can stop viewing mistakes or small failures as disastrous. Instead, view them as information that informs future decisions.

“A good plan, violently executed now, is better than a perfect plan next week.”

— General George Patton

Bezos compares decisions to doors. Reversible decisions are doors that open both ways. Irreversible decisions are doors that allow passage in only one direction; if you walk through, you are stuck there. Most decisions are the former and can be reversed (even though we can never recover the invested time and resources). Going through a reversible door gives us information: we know what’s on the other side.

In his shareholder letter, Bezos writes:

Some decisions are consequential and irreversible or nearly irreversible – one-way doors – and these decisions must be made methodically, carefully, slowly, with great deliberation and consultation. If you walk through and don’t like what you see on the other side, you can’t get back to where you were before. We can call these Type 1 decisions. But most decisions aren’t like that – they are changeable, reversible – they’re two-way doors. If you’ve made a suboptimal Type 2 decision, you don’t have to live with the consequences for that long. You can reopen the door and go back through. Type 2 decisions can and should be made quickly by high judgment individuals or small groups.

As organizations get larger, there seems to be a tendency to use the heavy-weight Type 1 decision-making process on most decisions, including many Type 2 decisions. The end result of this is slowness, unthoughtful risk aversion, failure to experiment sufficiently, and consequently diminished invention. We’ll have to figure out how to fight that tendency.

Bezos gives the example of the launch of one-hour delivery to those willing to pay extra. This service launched less than four months after the idea was first developed. In 111 days, the team “built a customer-facing app, secured a location for an urban warehouse, determined which 25,000 items to sell, got those items stocked, recruited and onboarded new staff, tested, iterated, designed new software for internal use – both a warehouse management system and a driver-facing app – and launched in time for the holidays.”

As further guidance, Bezos considers 70% certainty to be the cut-off point where it is appropriate to make a decision. That means acting once we have 70% of the required information, instead of waiting longer. Making a decision at 70% certainty and then course-correcting is a lot more effective than waiting for 90% certainty.

In Blink: The Power of Thinking Without Thinking, Malcolm Gladwell explains why decision-making under uncertainty can be so effective. We usually assume that more information leads to better decisions — if a doctor proposes additional tests, we tend to believe they will lead to a better outcome. Gladwell disagrees: “In fact, you need to know very little to find the underlying signature of a complex phenomenon. All you need is evidence of the ECG, blood pressure, fluid in the lungs, and an unstable angina. That’s a radical statement.”

In medicine, as in many areas, more information does not necessarily ensure improved outcomes. To illustrate this, Gladwell gives the example of a man arriving at a hospital with intermittent chest pains. His vital signs show no risk factors, yet his lifestyle does and he had heart surgery two years earlier. If a doctor looks at all the available information, it may seem that the man needs admitting to the hospital. But the additional factors, beyond the vital signs, are not important in the short term. In the long run, he is at serious risk of developing heart disease. Gladwell writes,

… the role of those other factors is so small in determining what is happening to the man right now that an accurate diagnosis can be made without them. In fact, … that extra information is more than useless. It’s harmful. It confuses the issues. What screws up doctors when they are trying to predict heart attacks is that they take too much information into account.

We can all learn from Bezos’s approach, which has helped him to build an enormous company while retaining the tempo of a start-up. Bezos uses his heuristic to fight the stasis that sets in within many large organizations. It is about being effective, not about following the norm of slow decisions.

Once you understand that reversible decisions are in fact reversible you can start to see them as opportunities to increase the pace of your learning. At a corporate level, allowing employees to make and learn from reversible decisions helps you move at the pace of a start-up. After all, if someone is moving with speed, you’re going to pass them when you move with velocity.

The biggest risk to irreversible decisions is deciding before you need to. The biggest risk to reversible ones is waiting until the last minute. Make reversible decisions as soon as possible and make irreversible decisions as late as possible.

This article originally appeared on Farnham Street

Image credits: Pixabay, Farnham Street

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