Category Archives: Technology

Designing Products for a Global Audience

Designing Products for a Global Audience

GUEST POST from Chateau G Pato

In today’s interconnected world, designing products for a global audience isn’t just a strategy; it’s a necessity. As companies expand their reach across borders, understanding the diverse needs, cultural contexts, and user behaviors becomes critical. To successfully innovate on a global scale, a deep commitment to human-centered design is paramount.

Understanding Diverse Needs

Designing for a global market requires acknowledging and embracing diversity. Considerations such as language, cultural nuances, local regulations, and technological infrastructure can make or break a product’s success overseas. Understanding these elements can help avoid missteps and create products that resonate with users worldwide.

Key Principles of Global Product Design

  • Empathy and Research: Conduct exhaustive research to understand user needs in different regions. Employ methodologies like ethnographic studies and immersive local experiences.
  • Localization: Go beyond mere translation. Consider cultural customs, color symbolism, and local trends.
  • Flexibility and Scalability: Design products that can evolve with changing user needs and technological advancements.
  • Collaborative Design: Involve local designers and experts to bring authentic perspectives into the design process.

Case Study: Airbnb

Airbnb’s success as a global platform lies in its commitment to localization and user-centric design. When expanding into new markets, Airbnb goes beyond text translation. They consider local travel behaviors and integrate culturally relevant elements into their platform.

For instance, in Asian markets, where personal relationships and trust are paramount, Airbnb enhanced its platform with features that allow hosts and guests to exchange more information upfront, fostering trust through transparency. They also adjusted their business model in China to cater to the unique regulatory environment and partnered with local payment providers.

Case Study: Coca-Cola

Coca-Cola’s approach to global product design is a testament to the power of local personalization within a global brand framework. Coca-Cola adapts its marketing strategies and product offerings to suit local tastes and preferences.

In Japan, Coca-Cola introduced more than 100 new products annually, experimenting with local flavors such as matcha and shiso. They focused on understanding local taste trends and innovating accordingly, making them a key player in regional markets.

Challenges in Designing for a Global Audience

Despite the benefits, designing for a global audience entails certain challenges:

  • Cultural Sensitivity: Misinterpretations can lead to alienation. Cultural sensitivity in design choices is crucial.
  • Regulatory Compliance: Navigating varied regulatory environments requires careful planning and flexible design frameworks.
  • Technological Disparities: Varying levels of technology adoption necessitate adaptable designs that work in both high-tech and low-tech environments.

The Road Ahead

The journey of designing products for a global audience is continuous and evolving. It requires a persistent commitment to learning, adaptation, and empathy. Companies that master this approach will not only thrive globally but will also forge deeper connections with their audiences, ultimately driving innovation and growth in unprecedented ways.

As we navigate the complexities of global markets, let us embrace the diversity that defines our world, channeling it into human-centered design innovations that are as varied and dynamic as the people we aim to serve.

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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Transformation Insights – Part Two

Transformation Insights - Part Two

“The world needs stories and characters that unite us rather than tear us apart.”~ Gale Anne Hurd, Producer of Aliens and The Terminator

GUEST POST from Bruce Fairley

In my early years I was fortunate to spend some time on film sets. Unlike how the entertainment industry is portrayed in the Netflix series, The Movies that Made Us, I did not come to blows with any of my directors as Eddie Murphy apparently did with John Landis during the making of Coming to America. Nor did I witness an entire crew mutiny, as James Cameron did on Aliens. Instead, I often saw the same dynamic I’ve witnessed in the tech sector from the first moment I stepped off set and into I.T.

People coming together.

Skilled, diverse, passionate people hard at work fighting against miscommunication, technical issues, and time constraints – coming together to achieve something significant. I referred to this in my previous Transformation Insights post, The Future Always Wins as:

Collaboration Between Complementary Influencers.

This dynamic is as true of a film set as it is of a firm engaged in digital transformation. In both cases, expertise in various areas is required to create a successful whole, with C-Suite leaders in the corporate sphere tasked with providing the articulated vision at the helm. Of course, the success of any endeavor comes down to human-powered action and decision making at every level of execution. And while the challenges of a digital transformation project may not be as bone-breaking dangerous as the stunts in an action film, getting to greatness requires a similar fusion of mind and machine – of talent and technology.

If that sounds like The Terminator, consider that its box office success speaks to the fusion of mind and machine as an unstoppable trajectory – but those who deepen their humanity rather than succumb to machine rule are the heroes that triumph. This was mirrored in the making of the film, which was nearly shut down when the crew put down their tools. Addressing their humanity and acknowledging the value of their contribution changed the story from disaster to blockbuster.

Humans lead – technology serves. Not the other way around.

When that is reversed, dystopia ensues whether on screen or in the boardroom. Having witnessed many occasions in which technology was expediently obtained before its value to the user could be established, I am convinced we have lost the plot in telling a wider, corporate story. Technology was supposed to liberate not enslave. Instead, how many times have you attended a Zoom meeting or prepared weeks for a presentation only to discover the sound not working, the slide deck freezing, or even a hidden ‘on’ button? These may be simple examples, but they rob the intrepid hero of the corporate journey; the chance to shine and advance their creative talent much like the crew of Aliens putting down their tools. Now multiply that by the large scale digital transformation projects I’ve spearheaded, and it becomes clear how a broken axis between human-powered decision making and technology can break the bottom line.

Optimism and momentum towards a more positive, successful outcome hinges on more than technological expertise. It requires an understanding of the whole story – and how the team, tech, leadership, and consumers each play a role. The story you wish to tell about your corporate journey requires buy-in at every level of service – human and tech. Obstacles are not indictments, they are merely obstacles. But they do often require a third-party complementary collaborator that understands how to transform pitfalls into profits.

When I launched the Narrative Group I wanted to amplify the genius of C-Suite executives through the optimization of the business-tech relationship. Similarly to how I observed the inner workings of a set and how all the pieces had to fit together to create a screen success, I spent years observing digital transformation from the inside. Across continents and boardrooms, I learned, led, and transformed as well. This only increased my commitment to helping talented leaders tell their story successfully.

If you’re a C-Suite leader that would like to storyboard the trajectory of your corporate success, please feel free to reach out and continue the conversation at:

connect@narrative-group.com

Image Credit: The Narrative Group

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The Ethics of AI in Innovation

The Ethics of AI in Innovation

GUEST POST from Chateau G Pato

In today’s rapidly evolving technological landscape, artificial intelligence (AI) plays a pivotal role in driving innovation. From healthcare and transportation to education and finance, AI’s potential to transform industries is unparalleled. However, with great power comes great responsibility. As we harness the capabilities of AI, we must also grapple with the ethical implications that accompany its use. This article delves into the ethical considerations of AI in innovation and presents two case studies that highlight the challenges and solutions within this dynamic field.

Understanding AI Ethics

AI ethics refers to the moral principles and guidelines that govern the development, deployment, and use of AI technologies. These principles aim to ensure that AI systems are designed and used in ways that are fair, transparent, and accountable. AI ethics also demand that we consider the potential biases in AI algorithms, the impact on employment, privacy concerns, and the long-term societal implications of AI-driven innovations.

Case Study 1: Healthcare AI – The IBM Watson Experience

IBM Watson, a powerful AI platform, made headlines with its potential to revolutionize healthcare. With the ability to analyze vast amounts of medical data and provide treatment recommendations, Watson promised to assist doctors in diagnosing and treating diseases more effectively.

However, the rollout of Watson in healthcare settings raised significant ethical questions. Firstly, there were concerns about the accuracy of the recommendations. Critics pointed out that Watson’s training data could be biased, potentially leading to flawed medical advice. Additionally, the opaque nature of AI decision-making posed challenges in accountability, especially in life-or-death scenarios.

IBM addressed these ethical issues by emphasizing transparency and collaboration with healthcare professionals. They implemented rigorous validation procedures and incorporated feedback from medical practitioners to refine Watson’s algorithms. This approach highlighted the importance of involving domain experts in the development process, ensuring that AI systems align with ethical standards and practical realities.

Case Study 2: Autonomous Vehicles – Google’s Waymo Journey

Waymo, Google’s self-driving car project, embodies the promise of AI in redefining urban transportation. Autonomous vehicles have the potential to enhance road safety and reduce traffic congestion. Nevertheless, they also bring forth ethical dilemmas that warrant careful consideration.

A key ethical challenge is the moral decision-making inherent in self-driving technology. In complex traffic situations, these AI-driven vehicles must make split-second decisions that could result in harm. The “trolley problem”—a classic ethical thought experiment—illustrates the dilemma of choosing between two harmful outcomes. For instance, should a self-driving car prioritize the safety of its passengers over pedestrians?

Waymo addresses these ethical concerns by implementing a robust ethical framework and engaging with stakeholders, including ethicists, regulators, and the general public. By fostering open dialogue, Waymo seeks to balance technical innovation with societal values, ensuring that their AI systems operate ethically and safely.

Principles for Ethical AI Innovation

As we navigate the ethical landscape of AI, several guiding principles can help steer innovation in a responsible direction:

  • Transparency: AI systems should be designed with transparency at their core, enabling users to understand the decision-making processes and underlying data.
  • Fairness: Developers must proactively address biases in AI algorithms to prevent discriminatory outcomes.
  • Accountability: Clear accountability mechanisms should be established to ensure that stakeholders can address any misuse or failure of AI technologies.
  • Collaboration: Cross-disciplinary collaboration involving technologists, ethicists, industry leaders, and policymakers is essential to fostering ethical AI innovation.

Conclusion

The integration of AI into our daily lives and industries presents both immense opportunities and complex ethical challenges. By thoughtfully addressing these ethical concerns, we can unleash the full potential of AI while safeguarding human values and societal well-being. As leaders in AI innovation, we must dedicate ourselves to building systems that are not only groundbreaking but also ethically sound, paving the way for a future where technology serves all of humanity.

In a world driven by AI, ethical innovation is not just an option—it’s a necessity. Through continuous dialogue, collaboration, and adherence to ethical principles, we can ensure that AI becomes a force for positive change, empowering people and societies worldwide.

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: Microsoft CoPilot

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Cultural Shifts Required for Agile Success

Cultural Shifts Required for Agile Success

GUEST POST from Art Inteligencia

In an era of rapid technological evolution and market dynamism, Agile has emerged as the go-to methodology for organizations seeking agility and resilience. However, the successful adoption of Agile is not just about implementing new processes or tools. At its core, Agile requires profound cultural shifts—a transformation in how individuals and teams think, interact, and operate.

The Imperative of Cultural Change

Agile methodologies promise speed, flexibility, and customer-centric approaches. However, many organizations fail to reap these benefits, primarily because they overlook the critical role of culture. For Agile to truly take root and flourish, organizations must embrace several key cultural shifts:

  • From Control to Empowerment: Agile thrives in environments where teams are empowered to make decisions. This requires a shift away from command-and-control management styles.
  • From Silos to Collaboration: Cross-functional collaboration is vital. Agile demands breaking down silos and fostering open communication and teamwork.
  • From Planning to Experimentation: Agile values iterative learning and adaptation over rigid planning.
  • From Risk Avoidance to Embracing Failure: Creating a culture where failure is seen as a learning opportunity is crucial for innovation.

Case Study 1: Spotify

Spotify’s success with Agile practices is well-documented and provides a compelling case study of cultural transformation. At Spotify, the organization is designed around cross-functional “squads,” each with end-to-end responsibility for their portions of the product. Here’s how Spotify navigated the cultural shifts:

  • Empowerment: Squads at Spotify are autonomous, empowering team members to experiment and make decisions without needing constant approval from higher management.
  • Collaboration: Cross-functional nature of squads ensures deep collaboration across disciplines, promoting knowledge sharing and holistic problem-solving.
  • Experimentation: Spotify encourages a “fail-friendly” culture where trying new ideas is embraced, and projects can pivot or stop based on what they learn quickly.

As a result, Spotify maintains a high capacity for innovation and adaptability, relevant to their fast-moving digital landscape.

Case Study 2: General Electric (GE)

General Electric, a company known for its traditional bureaucratic structure, embarked on an Agile transformation journey in its software development division to keep pace with technological changes and market demands.

  • From Control to Empowerment: GE overhauled their managerial approaches by adopting Lean Startup principles, which gave teams more autonomy to develop innovative solutions quickly.
  • Silos to Collaboration: GE’s Agile journey involved creating collocated, cross-functional teams tasked with tackling specific customer challenges, breaking down traditional silos.
  • Embracing Failure: Teams were encouraged to experiment and iterate, fostering a culture of learning from failure without the fear of repercussions.

While challenges existed, this cultural shift allowed GE to accelerate innovation and better respond to customer needs in their software products.

Navigating the Transition

Transitioning to an Agile culture is not without its challenges. Resistance to change, entrenched habits, and existing power dynamics can hinder progress. Here are strategies to navigate these challenges:

  • Leadership Buy-In: Securing support from leadership is crucial. Leaders must model Agile behaviors and champion cultural changes.
  • Change Agents: Identify and empower change agents who can advocate for and facilitate cultural shifts within teams.
  • Continuous Learning: Promote a culture of ongoing education and training to equip staff with the skills and mindset needed for Agile success.
  • Feedback Loops: Create mechanisms for regular feedback and reflection, allowing teams to learn and adapt continually.

Conclusion

Agile is not just a process but a mindset—a culture. The organizations that successfully navigate the transition to Agile do so by fundamentally reshaping their organizational culture. As seen in the examples of Spotify and GE, the journey to Agile success is challenging but ultimately rewarding, leading to more innovative, responsive, and resilient organizations.

To truly thrive in today’s fast-paced world, organizations must embrace the cultural shifts that Agile demands, fostering environments where empowerment, collaboration, experimentation, and learning from failure are not just encouraged, but ingrained into the very fabric of daily operations.

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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An Innovation Action Plan for the New CTO

Finding and Growing Innovation Islands Inside a Large Company

An Innovation Action Plan for the New CTO

GUEST POST from Steve Blank

How does a newly hired Chief Technology Officer (CTO) find and grow the islands of innovation inside a large company?

How not to waste your first six months as a new CTO thinking you’re making progress when the status quo is working to keep you at bay?

I just had coffee with Anthony, a friend who was just hired as the Chief Technology Officer (CTO) of a large company (30,000+ people.) He previously cofounded several enterprise software startups, and his previous job was building a new innovation organization from scratch inside another large company. But this is the first time he was the CTO of a company this size.

Good News and Bad

His good news was that his new company provides essential services and regardless of how much they stumbled they were going to be in business for a long time. But the bad news was that the company wasn’t keeping up with new technologies and new competitors who were moving faster. And the fact that they were an essential service made the internal cultural obstacles for change and innovation that much harder.

We both laughed when he shared that the senior execs told him that all the existing processes and policies were working just fine. It was clear that at least two of the four divisions didn’t really want him there. Some groups think he’s going to muck with their empires. Some of the groups are dysfunctional. Some are, as he said, “world-class people and organizations for a world that no longer exists.”

So, the question we were pondering was, how do you quickly infiltrate a large, complex company of that size? How do you put wins on the board and get a coalition working? Perhaps by getting people to agree to common problems and strategies? And/or finding the existing organizational islands of innovation that were already delivering and help them scale?

The Journey Begins

In his first week the exec staff had pointed him to the existing corporate incubator. Anthony had long come to the same conclusion I had, that highly visible corporate incubators do a good job of shaping culture and getting great press, but most often their biggest products were demos that never get deployed to the field. Anthony concluded that the incubator in his new company was no exception. Successful organizations recognize that innovation isn’t a single activity (incubators, accelerators, hackathons); it is a strategically organized end-to-end process from idea to deployment.

In addition, he was already discovering that almost every division and function was building groups for innovation, incubation and technology scouting. Yet no one had a single road map for who was doing what across the enterprise. And more importantly it wasn’t clear which, if any, of those groups were actually continuously delivering products and services at high speed. His first job was to build a map of all those activities.

Innovation Heroes are Not Repeatable or Scalable

Over coffee Anthony offered that in a company this size he knew he would find “innovation heroes” – the individuals others in the company point to who single-handedly fought the system and got a new product, project or service delivered (see article here.) But if that was all his company had, his work was going to be much tougher than he thought, as innovation heroics as the sole source of deployment of new capabilities are a sign of a dysfunctional organization.

Anthony believed one of his roles as CTO was to:

  • Map and evaluate all the innovation, incubation and technology scouting activities
  • Help the company understand they need innovation and execution to occur simultaneously. (This is the concept of an ambidextrous organization (see this HBR article).)
  • Educate the company that innovation and execution have different processes, people, and culture. They need each other – and need to respect and depend on each other
  • Create an innovation pipeline – from problem to deployment – and get it adopted at scale

Anthony was hoping that somewhere three, four or five levels down the organization were the real centers of innovation, where existing departments/groups – not individuals – were already accelerating mission/delivering innovative products/services at high speed. His challenge was to find these islands of innovation and who was running them and understand if/how they:

  • Leveraged existing company competencies and assets
  • Understand if/how they co-opted/bypassed existing processes and procedures
  • Had a continuous customer discovery to create products that customers need and want
  • Figured out how to deliver with speed and urgency
  • And if they somehow had made this a repeatable process

If these groups existed, his job as CTO was to take their learning and:

  • Figure out what barriers the innovation groups were running into and help build innovation processes in parallel to those for execution
  • Use their work to create a common language and tools for innovation around rapid acceleration of existing mission and delivery
  • Make permanent delivering products and services at speed with a written innovation doctrine and policy
  • Instrument the process with metrics and diagnostics

Get Out of the Office

So, with another cup of coffee the question we were trying to answer was, how does a newly hired CTO find the real islands of innovation in a company his size?

A first place to start was with the innovation heroes/rebels. They often know where all the innovation bodies were buried. But Anthony’s insight was he needed to get out of his 8th floor office and spend time where his company’s products and services were being developed and delivered.

It was likely that most innovative groups were not simply talking about innovation, but were the ones who rapidly delivering innovative solutions to customer’s needs.

One Last Thing

As we were finishing my coffee Anthony said, “I’m going to let a few of the execs know I’m not out for turf because I only intend to be here for a few years.” I almost spit out the rest of my coffee. I asked how many years the division C-level staff has been at the company. “Some of them for decades” he replied. I pointed out that in a large organization saying you’re just “visiting” will set you up for failure, as the executives who have made the company their career will simply wait you out.

As he left, he looked at a bit more concerned than we started. “Looks like I have my work cut out for me.”

Lessons Learned

  1. Large companies often have divisions and functions with innovation, incubation and technology scouting all operating independently with no common language or tools
  2. Innovation heroics as the sole source of deployment of new capabilities are a sign of a dysfunctional organization
  3. Innovation isn’t a single activity (incubators, accelerators, hackathons); it is a strategically organized end-to-end process from idea to deployment
  4. Somewhere three, four or five levels down the organization are the real centers of innovation – accelerating mission/delivering innovative products/services at high speed
  5. The CTO’s job is to:
    • create a common process, language and tools for innovation
    • make them permanent with a written innovation doctrine and policy

  6. And don’t ever tell anyone you’re a “short timer”

This article originally appeared in Fast Company

Image credit: Unsplash

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Rapid Prototyping Brings Ideas to Life Quickly

Rapid Prototyping Brings Ideas to Life Quickly

GUEST POST from Chateau G Pato

In the fast-paced world of innovation, turning ideas into tangible products quickly is crucial. This is where rapid prototyping, a method that emphasizes speed and iterative development, becomes a game-changer. By accelerating the development process, rapid prototyping helps innovators test ideas, gather feedback, and make improvements efficiently. Let’s dive into the benefits and real-world applications of rapid prototyping, featuring two compelling case studies.

What is Rapid Prototyping?

Rapid prototyping involves creating a working model of a product with minimal resources to test and validate ideas quickly. By leveraging advanced technologies like 3D printing, CAD software, and digital modeling, teams can produce prototypes more efficiently than traditional methods. This hands-on approach allows innovators to explore concepts, discover design flaws, and receive customer feedback rapidly, ultimately leading to better products.

The Benefits of Rapid Prototyping

  • Speed: Rapid prototyping significantly reduces the time between conception and iteration, allowing for faster delivery of products to market.
  • Cost-Effective: Early identification of design flaws leads to cost savings by reducing the need for expensive changes later in the development process.
  • Customer-Centric: By involving customers early, businesses can ensure that the final product meets user needs and expectations.
  • Flexibility: Iterative testing and feedback allow for adjustments and improvements throughout the development cycle.

Case Study 1: Tesla’s Approach to Model Development

Tesla is well-known for its innovation in the automotive industry, and rapid prototyping plays a pivotal role in its development strategy. When designing the Model S, Tesla utilized rapid prototyping to test various components and systems. Using 3D printing technology, Tesla engineers quickly produced and iterated prototypes of essential parts like battery modules and interior components.

This approach allowed Tesla to test and refine designs in record time, uncovering potential issues that could be addressed before mass production. Rapid prototyping enabled Tesla to launch a vehicle that met high-performance standards while maintaining cost-effectiveness. As a result, Tesla solidified its reputation for delivering high-quality, cutting-edge electric vehicles.

Case Study 2: IDEO’s Innovative Product Designs

IDEO, a global design and consulting firm, championed the adoption of rapid prototyping in product design. With a focus on human-centered design, IDEO employs rapid prototyping to transform abstract ideas into functional prototypes quickly. A notable example is their work on the Apple Computer’s first computer mouse.

IDEO created several iterations of the mouse using simple materials, such as foam and plastic, allowing their team to explore ergonomics and usability. These prototypes helped identify critical design features and were key in refining the product before its launch. This rapid, iterative approach enabled Apple to deliver a refined, user-friendly product that set new standards in personal computing.

Embracing Rapid Prototyping

To fully harness the potential of rapid prototyping, organizations should integrate it into their innovation strategies. Here are a few steps to consider:

1. Encourage a Prototyping Mindset

Foster a culture that values experimentation and learning. Encourage teams to think creatively and view mistakes as opportunities for growth.

2. Invest in Tools and Technologies

Equip your team with the necessary tools, such as 3D printers and digital design software, to facilitate quick and cost-effective prototyping.

3. Involve Stakeholders Early

Engage customers, partners, and other stakeholders in the prototype testing process to gather valuable feedback and insights.

4. Iterate and Refine

Embrace an iterative process that focuses on continuous improvement and adaptation based on real-world testing and feedback.

Conclusion

In conclusion, rapid prototyping is an indispensable tool for innovators aiming to bring ideas to life swiftly and efficiently. By embracing this approach, businesses can stay ahead of the competition, create products that resonate with customers, and ultimately drive success in today’s dynamic market. Whether you’re a startup or an established company, integrating rapid prototyping into your innovation strategy can lead to transformative results.

As we continue to innovate, let’s embrace the power of rapid prototyping to turn our ideas into reality—quickly and effectively.

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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Techniques for Effective User Research

Techniques for Effective User Research

GUEST POST from Chateau G Pato

In today’s fast-paced, technology-driven world, understanding your users is crucial. Successful innovation requires insights into users’ needs, behaviors, and challenges. Effective user research uncovers these insights and informs design and business decisions. Here, I’ll share some essential techniques for conducting impactful user research, illustrated with real-world case studies.

Why User Research Matters

Before diving into techniques, let’s understand why user research is essential. It helps in:

  • Identifying user needs: Understand what users want and need from your products or services.
  • Enhancing user experience: Create intuitive and enjoyable experiences by aligning with user expectations.
  • Reducing risk: Avoid costly design flops by validating concepts before launch.

Key User Research Techniques

1. Interviews

Interviews are one of the most direct ways to gather rich, qualitative data. Conducting one-on-one discussions allows for in-depth exploration of user perspectives.

Case Study: HealthTech Startup

A healthtech startup utilized interviews to understand how patients manage chronic conditions. By conducting interviews with patients, caregivers, and healthcare providers, they discovered barriers in medication adherence. Insights gained informed the design of a reminder and support feature within their app, leading to increased user engagement and improved health outcomes.

2. Surveys and Questionnaires

Surveys provide quantitative data that can represent broader user trends. When well-designed, they offer valuable insights into user preferences and satisfaction levels.

3. Observational Studies

Observational studies involve watching users interact with products in natural settings. This technique uncovers real-world usage patterns and potential areas for improvement.

Case Study: Retail Experience

A major retailer used observational studies to analyze customer behavior in their stores. By observing shoppers, they identified pain points in store navigation and checkout processes. This led to strategic store layout changes and self-checkout technology implementations, enhancing convenience and boosting customer satisfaction.

4. Usability Testing

Usability testing evaluates how easily users can navigate a product. By having users perform tasks while observing their interactions, designers can identify and fix usability issues.

5. Focus Groups

Focus groups bring diverse users together to discuss their experiences. Facilitators can explore different perspectives in a dynamic group setting, uncovering collective insights.

Best Practices for Conducting User Research

  • Clearly define objectives: Know what you aim to learn to select appropriate research methods.
  • Recruit the right participants: Ensure your sample accurately represents your target audience.
  • Maintain ethical standards: Prioritize participant privacy and obtain informed consent.
  • Iterate and refine: Use findings to refine hypotheses and improve research processes.

Conclusion

Effective user research is pivotal in crafting solutions that resonate with users and drive business success. By applying these techniques thoughtfully, businesses and innovators can create products that truly meet user needs, leading to greater user satisfaction and loyalty.

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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How will humans change in the next 10,000 years?

Future evolution: from looks to brains and personality

GUEST POST from Nicholas R. Longrich, University of Bath

READER QUESTION: If humans don’t die out in a climate apocalypse or asteroid impact in the next 10,000 years, are we likely to evolve further into a more advanced species than what we are at the moment? Harry Bonas, 57, Nigeria

Humanity is the unlikely result of 4 billion years of evolution.

From self-replicating molecules in Archean seas, to eyeless fish in the Cambrian deep, to mammals scurrying from dinosaurs in the dark, and then, finally, improbably, ourselves – evolution shaped us.

Organisms reproduced imperfectly. Mistakes made when copying genes sometimes made them better fit to their environments, so those genes tended to get passed on. More reproduction followed, and more mistakes, the process repeating over billions of generations. Finally, Homo sapiens appeared. But we aren’t the end of that story. Evolution won’t stop with us, and we might even be evolving faster than ever.


This article is part of Life’s Big Questions

The Conversation’s new series, co-published with BBC Future, seeks to answer our readers’ nagging questions about life, love, death and the universe. We work with professional researchers who have dedicated their lives to uncovering new perspectives on the questions that shape our lives.


It’s hard to predict the future. The world will probably change in ways we can’t imagine. But we can make educated guesses. Paradoxically, the best way to predict the future is probably looking back at the past, and assuming past trends will continue going forward. This suggests some surprising things about our future.

We will likely live longer and become taller, as well as more lightly built. We’ll probably be less aggressive and more agreeable, but have smaller brains. A bit like a golden retriever, we’ll be friendly and jolly, but maybe not that interesting. At least, that’s one possible future. But to understand why I think that’s likely, we need to look at biology.

The end of natural selection?

Some scientists have argued that civilisation’s rise ended natural selection. It’s true that selective pressures that dominated in the past – predators, famine, plague, warfare – have mostly disappeared.

Starvation and famine were largely ended by high-yield crops, fertilisers and family planning. Violence and war are less common than ever, despite modern militaries with nuclear weapons, or maybe because of them. The lions, wolves and sabertoothed cats that hunted us in the dark are endangered or extinct. Plagues that killed millions – smallpox, Black Death, cholera – were tamed by vaccines, antibiotics, clean water.

But evolution didn’t stop; other things just drive it now. Evolution isn’t so much about survival of the fittest as reproduction of the fittest. Even if nature is less likely to murder us, we still need to find partners and raise children, so sexual selection now plays a bigger role in our evolution.

And if nature doesn’t control our evolution anymore, the unnatural environment we’ve created – culture, technology, cities – produces new selective pressures very unlike those we faced in the ice age. We’re poorly adapted to this modern world; it follows that we’ll have to adapt.

And that process has already started. As our diets changed to include grains and dairy, we evolved genes to help us digest starch and milk. When dense cities created conditions for disease to spread, mutations for disease resistance spread too. And for some reason, our brains have got smaller. Unnatural environments create unnatural selection.

To predict where this goes, we’ll look at our prehistory, studying trends over the past 6 million years of evolution. Some trends will continue, especially those that emerged in the past 10,000 years, after agriculture and civilisation were invented.

We’re also facing new selective pressures, such as reduced mortality. Studying the past doesn’t help here, but we can see how other species responded to similar pressures. Evolution in domestic animals may be especially relevant – arguably we’re becoming a kind of domesticated ape, but curiously, one domesticated by ourselves.

I’ll use this approach to make some predictions, if not always with high confidence. That is, I’ll speculate.

Lifespan

Humans will almost certainly evolve to live longer – much longer. Life cycles evolve in response to mortality rates, how likely predators and other threats are to kill you. When mortality rates are high, animals must reproduce young, or might not reproduce at all. There’s also no advantage to evolving mutations that prevent ageing or cancer – you won’t live long enough to use them.

When mortality rates are low, the opposite is true. It’s better to take your time reaching sexual maturity. It’s also useful to have adaptations that extend lifespan, and fertility, giving you more time to reproduce. That’s why animals with few predators – animals that live on islands or in the deep ocean, or are simply big – evolve longer lifespans. Greenland sharks, Galapagos tortoises and bowhead whales mature late, and can live for centuries.

Even before civilisation, people were unique among apes in having low mortality and long lives. Hunter-gatherers armed with spears and bows could defend against predators; food sharing prevented starvation. So we evolved delayed sexual maturity, and long lifespans – up to 70 years.

Still, child mortality was high – approaching 50% or more by age 15. Average life expectancy was just 35 years. Even after the rise of civilisation, child mortality stayed high until the 19th century, while life expectancy went down – to 30 years – due to plagues and famines.

Then, in the past two centuries, better nutrition, medicine and hygiene reduced youth mortality to under 1% in most developed nations. Life expectancy soared to 70 years worldwide , and 80 in developed countries. These increases are due to improved health, not evolution – but they set the stage for evolution to extend our lifespan.

Now, there’s little need to reproduce early. If anything, the years of training needed to be a doctor, CEO, or carpenter incentivise putting it off. And since our life expectancy has doubled, adaptations to prolong lifespan and child-bearing years are now advantageous. Given that more and more people live to 100 or even 110 yearsthe record being 122 years – there’s reason to think our genes could evolve until the average person routinely lives 100 years or even more.

Size, and strength

Animals often evolve larger size over time; it’s a trend seen in tyrannosaurs, whales, horses and primates – including hominins.

Early hominins like Australopithecus afarensis and Homo habilis were small, four to five feet (120cm-150cm) tall. Later hominins – Homo erectus, Neanderthals, Homo sapiens – grew taller. We’ve continued to gain height in historic times, partly driven by improved nutrition, but genes seem to be evolving too.

Why we got big is unclear. In part, mortality may drive size evolution; growth takes time, so longer lives mean more time to grow. But human females also prefer tall males. So both lower mortality and sexual preferences will likely cause humans to get taller. Today, the tallest people in the world are in Europe, led by the Netherlands. Here, men average 183cm (6ft); women 170cm (5ft 6in). Someday, most people might be that tall, or taller.

As we’ve grown taller, we’ve become more gracile. Over the past 2 million years, our skeletons became more lightly built as we relied less on brute force, and more on tools and weapons. As farming forced us to settle down, our lives became more sedentary, so our bone density decreased. As we spend more time behind desks, keyboards and steering wheels, these trends will likely continue.

Humans have also reduced our muscles compared to other apes, especially in our upper bodies. That will probably continue. Our ancestors had to slaughter antelopes and dig roots; later they tilled and reaped in the fields. Modern jobs increasingly require working with people, words and code – they take brains, not muscle. Even for manual laborers – farmers, fisherman, lumberjacks – machinery such as tractors, hydraulics and chainsaws now shoulder a lot of the work. As physical strength becomes less necessary, our muscles will keep shrinking.

Our jaws and teeth also got smaller. Early, plant-eating hominins had huge molars and mandibles for grinding fibrous vegetables. As we shifted to meat, then started cooking food, jaws and teeth shrank. Modern processed food – chicken nuggets, Big Macs, cookie dough ice cream – needs even less chewing, so jaws will keep shrinking, and we’ll likely lose our wisdom teeth.

Beauty

After people left Africa 100,000 years ago, humanity’s far-flung tribes became isolated by deserts, oceans, mountains, glaciers and sheer distance. In various parts of the world, different selective pressures – different climates, lifestyles and beauty standards – caused our appearance to evolve in different ways. Tribes evolved distinctive skin colour, eyes, hair and facial features.

With civilisation’s rise and new technologies, these populations were linked again. Wars of conquest, empire building, colonisation and trade – including trade of other humans – all shifted populations, which interbred. Today, road, rail and aircraft link us too. Bushmen would walk 40 miles to find a partner; we’ll go 4,000 miles. We’re increasingly one, worldwide population – freely mixing. That will create a world of hybrids – light brown skinned, dark-haired, Afro-Euro-Australo-Americo-Asians, their skin colour and facial features tending toward a global average.

Sexual selection will further accelerate the evolution of our appearance. With most forms of natural selection no longer operating, mate choice will play a larger role. Humans might become more attractive, but more uniform in appearance. Globalised media may also create more uniform standards of beauty, pushing all humans towards a single ideal. Sex differences, however, could be exaggerated if the ideal is masculine-looking men and feminine-looking women.

Intelligence and personality

Last, our brains and minds, our most distinctively human feature, will evolve, perhaps dramatically. Over the past 6 million years, hominin brain size roughly tripled, suggesting selection for big brains driven by tool use, complex societies and language. It might seem inevitable that this trend will continue, but it probably won’t.

Instead, our brains are getting smaller. In Europe, brain size peaked 10,000—20,000 years ago, just before we invented farming. Then, brains got smaller. Modern humans have brains smaller than our ancient predecessors, or even medieval people. It’s unclear why.

It could be that fat and protein were scarce once we shifted to farming, making it more costly to grow and maintain large brains. Brains are also energetically expensive – they burn around 20% of our daily calories. In agricultural societies with frequent famine, a big brain might be a liability.

Maybe hunter-gatherer life was demanding in ways farming isn’t. In civilisation, you don’t need to outwit lions and antelopes, or memorise every fruit tree and watering hole within 1,000 square miles. Making and using bows and spears also requires fine motor control, coordination, the ability to track animals and trajectories — maybe the parts of our brains used for those things got smaller when we stopped hunting.

Or maybe living in a large society of specialists demands less brainpower than living in a tribe of generalists. Stone-age people mastered many skills – hunting, tracking, foraging for plants, making herbal medicines and poisons, crafting tools, waging war, making music and magic. Modern humans perform fewer, more specialised roles as part of vast social networks, exploiting division of labour. In a civilisation, we specialise on a trade, then rely on others for everything else.

That being said, brain size isn’t everything: elephants and orcas have bigger brains than us, and Einstein’s brain was smaller than average. Neanderthals had brains comparable to ours, but more of the brain was devoted to sight and control of the body, suggesting less capacity for things like language and tool use. So how much the loss of brain mass affects overall intelligence is unclear. Maybe we lost certain abilities, while enhancing others that are more relevant to modern life. It’s possible that we’ve maintained processing power by having fewer, smaller neurons. Still, I worry about what that missing 10% of my grey matter did.

Curiously, domestic animals also evolved smaller brains. Sheep lost 24% of their brain mass after domestication; for cows, it’s 26%; dogs, 30%. This raises an unsettling possibility. Maybe being more willing to passively go with the flow (perhaps even thinking less), like a domesticated animal, has been bred into us, like it was for them.

Our personalities must be evolving too. Hunter-gatherers’ lives required aggression. They hunted large mammals, killed over partners and warred with neighbouring tribes. We get meat from a store, and turn to police and courts to settle disputes. If war hasn’t disappeared, it now accounts for fewer deaths, relative to population, than at any time in history. Aggression, now a maladaptive trait, could be bred out.

Changing social patterns will also change personalities. Humans live in much larger groups than other apes, forming tribes of around 1,000 in hunter-gatherers. But in today’s world people living in vast cities of millions. In the past, our relationships were necessarily few, and often lifelong. Now we inhabit seas of people, moving often for work, and in the process forming thousands of relationships, many fleeting and, increasingly, virtual. This world will push us to become more outgoing, open and tolerant. Yet navigating such vast social networks may also require we become more willing to adapt ourselves to them – to be more conformist.

Not everyone is psychologically well-adapted to this existence. Our instincts, desires and fears are largely those of stone-age ancestors, who found meaning in hunting and foraging for their families, warring with their neighbours and praying to ancestor-spirits in the dark. Modern society meets our material needs well, but is less able to meet the psychological needs of our primitive caveman brains.

Perhaps because of this, increasing numbers of people suffer from psychological issues such as loneliness, anxiety and depression. Many turn to alcohol and other substances to cope. Selection against vulnerability to these conditions might improve our mental health, and make us happier as a species. But that could come at a price. Many great geniuses had their demons; leaders like Abraham Lincoln and Winston Churchill fought with depression, as did scientists such as Isaac Newton and Charles Darwin, and artists like Herman Melville and Emily Dickinson. Some, like Virginia Woolf, Vincent Van Gogh and Kurt Cobain, took their own lives. Others – Billy Holliday, Jimi Hendrix and Jack Kerouac – were destroyed by substance abuse.

A disturbing thought is that troubled minds will be removed from the gene pool – but potentially at the cost of eliminating the sort of spark that created visionary leaders, great writers, artists and musicians. Future humans might be better adjusted – but less fun to party with and less likely to launch a scientific revolution — stable, happy and boring.

New species?

There were once nine human species, now it’s just us. But could new human species evolve? For that to happen, we’d need isolated populations subject to distinct selective pressures. Distance no longer isolates us, but reproductive isolation could theoretically be achieved by selective mating. If people were culturally segregated – marrying based on religion, class, caste, or even politics – distinct populations, even species, might evolve.

In The Time Machine, sci-fi novelist H.G. Wells saw a future where class created distinct species. Upper classes evolved into the beautiful but useless Eloi, and the working classes become the ugly, subterranean Morlocks – who revolted and enslaved the Eloi.

In the past, religion and lifestyle have sometimes produced genetically distinct groups, as seen in for example Jewish and Gypsy populations. Today, politics also divides us – could it divide us genetically? Liberals now move to be near other liberals, and conservatives to be near conservatives; many on the left won’t date Trump supporters and vice versa.

Could this create two species, with instinctively different views? Probably not. Still, to the extent culture divides us, it could drive evolution in different ways, in different people. If cultures become more diverse, this could maintain and increase human genetic diversity.

Strange New Possibilities

So far, I’ve mostly taken a historical perspective, looking back. But in some ways, the future might be radically unlike the past. Evolution itself has evolved.

One of the more extreme possibilities is directed evolution, where we actively control our species’ evolution. We already breed ourselves when we choose partners with appearances and personalities we like. For thousands of years, hunter-gatherers arranged marriages, seeking good hunters for their daughters. Even where children chose partners, men were generally expected to seek approval of the bride’s parents. Similar traditions survive elsewhere today. In other words, we breed our own children.

And going forward, we’ll do this with far more knowledge of what we’re doing, and more control over the genes of our progeny. We can already screen ourselves and embryos for genetic diseases. We could potentially choose embryos for desirable genes, as we do with crops. Direct editing of the DNA of a human embryo has been proven to be possible — but seems morally abhorrent, effectively turning children into subjects of medical experimentation. And yet, if such technologies were proven safe, I could imagine a future where you’d be a bad parent not to give your children the best genes possible.

Computers also provide an entirely new selective pressure. As more and more matches are made on smartphones, we are delegating decisions about what the next generation looks like to computer algorithms, who recommend our potential matches. Digital code now helps choose what genetic code passed on to future generations, just like it shapes what you stream or buy online. This might sound like dark science fiction, but it’s already happening. Our genes are being curated by computer, just like our playlists. It’s hard to know where this leads, but I wonder if it’s entirely wise to turn over the future of our species to iPhones, the internet and the companies behind them.

Discussions of human evolution are usually backward looking, as if the greatest triumphs and challenges were in the distant past. But as technology and culture enter a period of accelerating change, our genes will too. Arguably, the most interesting parts of evolution aren’t life’s origins, dinosaurs, or Neanderthals, but what’s happening right now, our present – and our future.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Image Credit: Pixabay

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Transforming Business Processes with Machine Learning

Transforming Business Processes with Machine Learning

GUEST POST from Chateau G Pato

In today’s rapidly evolving landscape, businesses depend on innovative solutions to remain competitive. One such transformative force is machine learning (ML), a subset of artificial intelligence (AI) that enables systems to learn and improve from experience without being explicitly programmed. By integrating machine learning into business processes, organizations can uncover insights, enhance decision making, and drive efficiencies. Let us delve into how machine learning is revolutionizing business operations through real-world examples.

Understanding Machine Learning

Machine learning algorithms build mathematical models based on sample data, known as training data, to make predictions or decisions without being explicitly programmed to perform the task. There are three primary types of machine learning:

  • Supervised learning: The model is trained on labeled data.
  • Unsupervised learning: The model works on unlabeled data to find hidden patterns.
  • Reinforcement learning: The model learns by receiving feedback from its environment.

Case Study 1: Optimizing Supply Chain Operations

Company: XYZ Manufacturing

XYZ Manufacturing, a global leader in consumer electronics, faced challenges with forecasting demand, managing inventory, and optimizing their supply chain. They turned to machine learning to address these issues.

By implementing supervised learning models, XYZ Manufacturing improved demand forecasting accuracy by 30%. These models analyzed historical sales data, market trends, and seasonality to predict future demand. As a result, the company reduced excess inventory and improved product availability.

Additionally, XYZ Manufacturing utilized unsupervised learning algorithms to optimize their logistics network. The algorithms identified patterns in transportation data, leading to more efficient routing that decreased shipping costs by 20% and reduced delivery times.

Case Study 2: Enhancing Customer Experience in Banking

Company: ABC Bank

ABC Bank, a leading financial institution, sought to improve its customer experience and service offerings. With the help of machine learning, they developed a personalized recommendation engine.

The bank utilized supervised learning to analyze customer transaction history, demographics, and preferences. This analysis enabled ABC Bank to offer tailor-made financial products and services to its customers, increasing cross-selling opportunities by 25% and enhancing customer satisfaction.

Furthermore, ABC Bank deployed reinforcement learning in its fraud detection systems. The model learned from various transaction patterns to detect anomalies and suspicious activities in real-time, reducing fraudulent transactions by 40%.

The Future of Machine Learning in Business

Machine learning is no longer a futuristic concept but a present-day reality driving substantial change across industries. As organizations continue to explore ML applications, we anticipate further advancements in process automation, intelligent decision-making, and personalized experiences.

However, it is crucial for leaders to adopt a human-centered approach when implementing machine learning. Ensuring transparency, addressing ethical considerations, and fostering continuous learning will empower businesses to harness the full potential of machine learning responsibly and sustainably.

Conclusion

Machine learning is transforming how businesses operate, creating opportunities to enhance efficiency, accuracy, and customer engagement. By learning from industry pioneers like XYZ Manufacturing and ABC Bank, organizations can navigate the complexities of machine learning adoption and unlock new avenues for growth and innovation.

As we embrace this technological revolution, let us remain committed to a vision where machine learning augments human creativity and intelligence, steering us toward a future brimming with possibilities.

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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The Key to Product Success is Putting Users First

The Key to Product Success is Putting Users First

GUEST POST from Chateau G Pato

In the fast-paced world of innovation, one principle remains constant: the key to product success is putting users first. As organizations vie for consumer attention, understanding and catering to user needs is paramount. This article explores this concept through case studies, demonstrating how a user-centric approach can lead to groundbreaking products.

Understanding User-Centric Design

User-centric design is more than a buzzword; it’s a philosophy that places the user at the heart of the development process. By focusing on real user problems, companies can create products that are not only functional but also add tangible value to people’s lives.

Case Study #1: Airbnb’s Rise by Solving Real Problems

The story of Airbnb is an exemplary illustration of user-centric design. Founded in 2008, Airbnb began as a simple solution to afford rent. The founders, Brian Chesky and Joe Gebbia, faced a real problem: expensive lodging during busy conference periods. Their response? Rent out air mattresses in their apartment.

From this basic idea, Airbnb evolved by listening intently to user feedback. Early users desired more than just basic accommodations; they wanted unique, personable experiences. By addressing this, Airbnb built a platform that catered to adventure seekers, budget travelers, and everyone in between. Key features were developed based on user input, such as host reviews and detailed profiles, enhancing trust and community.

“Airbnb’s success lies in its ability to align its platform with the evolving needs of its user base, creating an ecosystem where both hosts and guests thrive.”

Case Study #2: How Slack Became Essential for Teams

Slack’s journey to becoming a leading collaboration tool is another testimony to user-centered innovation. Initially started as a communication platform for their internal game development team, the creators of Slack realized that their tool had a universal application that could solve communication woes for many organizations.

Slack’s growth strategy was heavily driven by user feedback. They engaged with beta testers to understand the core issues with existing communication tools. Slack’s features like channels, integrations, and an intuitive interface were direct responses to user needs for more efficient and organized communication.

Even as it scaled, Slack maintained a strong connection with its users, regularly implementing feedback to enhance user experience. This commitment to understanding and responding to user feedback allowed Slack to rapidly become the default workspace for teams worldwide.

“Slack’s user-centric focus transformed it from a small internal tool to a must-have for businesses, simply by addressing user pain points effectively.”

The Principles of User-Centric Success

What can we learn from Airbnb and Slack? Some core principles guide successful user-centric innovation:

  • Empathy: Understand users’ needs, desires, and pain points deeply.
  • Iterative Design: Regularly test ideas and prototypes with real users to refine and improve.
  • Feedback Loops: Create channels for continuous user feedback and be ready to adapt.
  • Value Creation: Ensure that your product not only solves problems but does so in a way that enhances the user’s life.

Conclusion

Putting users first is not just a strategy; it’s an ideology that converts products into essential parts of users’ lives. Whether it’s creating unforgettable travel experiences like Airbnb or simplifying team collaboration as Slack does, the common denominator of successful innovations is their unwavering commitment to user needs. As you embark on your product development journey, remember: the closer you get to your users, the closer you are to success.

By continuously prioritizing the user, businesses can cultivate loyalty, drive growth, and achieve unprecedented levels of success, solidifying their place in the market as indispensable tools, services, or experiences.

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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