Category Archives: Technology

The Role of Leadership in Agile Environments

The Role of Leadership in Agile Environments

GUEST POST from Art Inteligencia

In today’s rapidly changing business landscape, agility is no longer a luxury—it’s a necessity. As organizations strive to become more adaptive and responsive, the role of leadership in cultivating and sustaining agile environments has become increasingly vital. Leadership in these contexts requires a distinct set of skills and a mindset that supports continuous learning, collaboration, and innovation.

Understanding Agile Leadership

Agile leadership goes beyond traditional command-and-control structures. It involves empowering teams, fostering an environment of trust, and enabling people to experiment without fear of failure. Leaders must guide teams to align their efforts with the organization’s strategic goals while promoting an adaptive culture. They should be catalysts for change, encouraging individuals to embrace agility in their thinking and everyday tasks.

Key Characteristics of Agile Leaders

  • Visionary Thinking: Agile leaders maintain a clear vision and help teams understand the broader purpose behind their work.
  • Empowerment: They trust their teams to make decisions and support them with the resources needed to succeed.
  • Adaptability: Agile leaders thrive in change and are comfortable pivoting strategies as necessary.
  • Facilitators of Collaboration: They encourage open communication and collaboration across all levels and departments.

Case Study 1: Spotify’s Tribes Model

Background

Spotify, the music streaming giant, is renowned for its innovative approach to agile organizational structures. Early in its growth, Spotify realized the limitations of traditional development and management methodologies.

Agile Leadership in Action

The company adopted the ‘Tribes’ model, where cross-functional teams called ‘squads’ are grouped into larger ‘tribes.’ Each tribe focuses on a distinct part of the product but aligns with the company’s overarching goals. Leaders at Spotify play a crucial role in fostering a culture of autonomy and alignment.

Agile leaders, called ‘Tribe Leads,’ focus on strategic alignment and resource sharing, while allowing squads the freedom to choose their methods and tools. They emphasize servant leadership, enabling teams to innovate and experiment freely.

Results

The results of this leadership approach are evident in Spotify’s continual product innovation and ability to adapt to market changes swiftly. The strong emphasis on collaboration and empowerment has made Spotify a model for agile transformation.

Case Study 2: GE Aviation’s Learning Culture

Background

GE Aviation recognized the need to transform its organizational culture to remain competitive in the complex aerospace industry. The company faced challenges in maintaining efficiency while driving innovation.

Agile Leadership in Action

GE Aviation adopted agile methodologies by restructuring teams into smaller, more flexible working groups. Leaders shifted from directing teams to facilitating learning and development. A crucial aspect of this change was the establishment of a ‘Learning Culture’ where continuous improvement was incentivized.

Leaders played a vital role by modeling curiosity and vulnerability, showing that it’s acceptable to acknowledge limitations and seek collective improvement. This transparency built trust and encouraged teams to take initiative.

Results

The leadership transformation at GE Aviation led to increased innovation and time-to-market improvements. By nurturing an environment where learning is integral, leaders helped the company navigate complex challenges and maintain its position as an industry leader.

Conclusion

The role of leadership in agile environments cannot be understated. Effective agile leaders are those who facilitate innovation, empower teams, and adapt to evolving circumstances. The case studies of Spotify and GE Aviation illuminate how empowering leadership can drive transformation and success. As organizations continue to embrace agility, the capabilities and influence of agile leaders will increasingly define their trajectory in a competitive landscape.

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.

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The Role of Data in Innovation Measurement

The Role of Data in Innovation Measurement

GUEST POST from Art Inteligencia

In the rapidly changing landscape of business, innovation is no longer a luxury—it’s a necessity. Organizations that innovate effectively sustain competitive advantages, while those that don’t risk obsolescence. But how do we know if innovation is truly driving growth, or if our efforts are falling flat? The answer lies in data-centric innovation measurement. By utilizing data, companies can gain insights into the effectiveness of their innovation strategies, allowing them to pivot when necessary, double down on successes, and drive sustained growth. This article highlights the critical role of data in measuring innovation and examines how two organizations successfully harnessed data to enhance their innovation processes.

The Importance of Data in Innovation Measurement

The contemporary business environment is characterized by rapid technological advancements and evolving consumer demands. Measuring innovation purely by outputs—like the number of new widgets produced—is an outdated approach. Instead, companies must leverage data across various dimensions such as market impact, customer satisfaction, and internal process efficiency.

Data helps organizations ask the right questions: Are new products meeting customer needs? Is there a reduction in time-to-market? Are internal innovation processes becoming more efficient? With data, we move from asking “Are we innovating?” to “Are we innovating effectively?”

Case Study 1: Improving Product Development at Company X

Company X, a leader in consumer electronics, was experiencing slowed growth despite significant investment in R&D. By leveraging data analytics, they transformed their innovation measurement strategy.

Company X adopted a data-driven approach to gather insights on customer preferences, market trends, and user feedback. By integrating artificial intelligence, they analyzed massive datasets to recognize emerging consumer needs and market gaps. The results were astounding. Within a year, Company X launched two new product lines that exceeded initial sales targets by 35%.

Data-driven insights enabled Company X to make informed decisions about product features, marketing strategies, and sales projections. Rather than relying on intuition or historical success, they used empirical evidence to guide their innovation efforts, resulting in significant market share gains and an enhanced brand reputation.

Case Study 2: Enhancing Internal Processes at Company Y

Company Y, a multinational healthcare provider, faced inefficiencies in its product development cycle. They launched a data initiative to streamline their innovation processes, aiming to cut costs and time-to-market.

By implementing a data warehouse and analytics platform, Company Y consolidated data from various departments, including R&D, marketing, and operations. This centralization enabled them to identify bottlenecks and redundancies. Understanding these inefficiencies allowed Company Y to adopt agile methodologies, iterating more rapidly, and responding to changing market conditions with greater speed and precision.

The use of data not only reduced their product development timeline by 40% but also improved cross-departmental collaboration. This streamlined process fostered a culture of innovation, empowering employees to propose and test new ideas efficiently. Ultimately, this led to a 25% increase in successful product launches within two years.

Key Takeaways

These case studies underscore the transformative potential of data in innovation measurement. Whether enhancing product development or optimizing internal processes, data provides the clarity needed to make informed, impactful decisions. As businesses continue to operate in a data-rich environment, the ability to harness this information for innovation measurement will become increasingly vital.

In conclusion, data is not just an auxiliary component of innovation; it is at the heart of measuring and guiding it. Organizations that fail to incorporate data into their innovation measurement strategies risk falling behind. The future belongs to those who embrace data, wielding it as a tool for innovation excellence. Through data, we can not only measure innovation but strategically drive it, ensuring continuous growth and relevance.

If you’re looking to jumpstart innovation measurement in your organization, start by evaluating your current data capabilities, identifying key metrics aligned with your strategic goals, and building a culture that consistently values and leverages data-driven insights. The potential is immense—transform your approach today.

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: Pexels

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The Role of Recycling in the Circular Economy

The Role of Recycling in the Circular Economy

GUEST POST from Chateau G Pato

The concept of the circular economy is redefining how we think about production and consumption. It challenges the traditional “take, make, dispose” model and instead offers a systemic approach to economic development designed to benefit businesses, society, and the environment. At the heart of this transformative model lies the important practice of recycling. Recycling is not just a process; it’s a pivotal component of a larger paradigm striving to ensure that sustainability is woven into the fabric of our societies.

Recycling: The Backbone of the Circular Economy

Recycling involves the collection and processing of materials that would otherwise be thrown away as trash and turning them into new products. In the circular economy, recycling is crucial for maintaining a closed-loop system that keeps resources in use for as long as possible. By converting waste into valuable inputs for new processes, recycling reduces the demand for virgin resources, thereby conserving energy and mitigating environmental degradation.

“In a world with finite resources, recycling is no longer a choice, but a necessity for sustainable growth.” – Braden Kelley

Case Study 1: Sweden’s Recycling Revolution

Sweden is often heralded as a global leader in recycling, boasting one of the highest recycling rates in the world. An impressive 99% of household waste is diverted from landfills. The country has achieved this through a combination of government initiatives, public engagement, and innovative waste management practices.

The success of Sweden’s model is largely attributed to its efficient waste-to-energy systems. Only 1% of waste ends up in landfills, with much of it being converted into energy used to heat homes. Furthermore, Sweden has established a robust deposit system for beverage containers, encouraging citizens to recycle through financial incentives.

This comprehensive approach not only reduces environmental impact but also supports the economy by creating jobs in the recycling and energy sectors. Sweden’s forward-thinking models showcase how recycling can play a significant role in realizing a truly circular economy.

Case Study 2: The Ellen MacArthur Foundation and the New Plastics Economy

The Ellen MacArthur Foundation, an influential leader in promoting the circular economy, has been instrumental in addressing the global plastic waste crisis. Through its New Plastics Economy initiative, the foundation advocates for recycling as a critical component of holistic plastic management.

At the core of this initiative is collaboration across the plastics value chain, including businesses, policymakers, and innovators. By redesigning packaging, enhancing collection methods, and fostering recycling technologies, the initiative aims to tackle plastic waste at its source, promoting a circular lifecycle for all plastics.

This initiative has led to groundbreaking partnerships and commitments from major global brands to increase recycled content and improve recycling processes. By transforming the way we think about plastic, the Ellen MacArthur Foundation is paving the way for sustainable innovation in material management.

The Future of Recycling in a Circular Economy

As we progress towards a more sustainable future, it is imperative that we continue to innovate and improve our recycling efforts. Technologies such as chemical recycling offer promising avenues to break down plastics into their molecular components, allowing them to be reused in a true circular fashion. Additionally, smart waste management systems and AI can optimize recycling processes, increasing efficiency and reducing contamination in recycling streams.

However, fostering a circular economy isn’t solely a technological challenge; it also requires a shift in mindset. Education and community engagement play vital roles in changing behaviors and encouraging recycling as a part of daily life. Governments, businesses, and citizens must collaborate to build an economy that prioritizes sustainability over wastefulness.

In conclusion, recycling is more than just a tool for waste management; it’s a cornerstone for building a resilient and sustainable circular economy. By viewing waste as a resource and embracing both technological innovation and systemic change, we can create a future where economic growth and environmental stewardship go hand in hand.

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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Incorporating User Feedback into Iterative Design

Incorporating User Feedback into Iterative Design

GUEST POST from Chateau G Pato

In the realm of human-centered design, the influence of user feedback cannot be overstated. User feedback offers a compass that guides designers through the iterative design process, ensuring that products not only meet but exceed the needs and expectations of users. This article delves into the principles of incorporating user feedback into iterative design and provides real-world case studies to illuminate these principles in action.

Understanding Iterative Design

Iterative design is a cyclic process involving the continual refinement of a product through repeated cycles of prototyping, testing, and evaluation. The goal is to progressively enhance design decisions with each iteration, informed directly by user insights. Integrating user feedback into this loop ensures that designs are grounded in real-world usability and relevance.

The Critical Role of User Feedback

User feedback is the lifeblood of iterative design. It transforms subjective opinions into objective data, enabling designers to make informed decisions. By actively listening to users, designers can uncover unmet needs, identify points of friction, and discover opportunities for innovation.

Best Practices for Gathering User Feedback

  • Engage Early and Often: Involve users from the conceptual stage and maintain this interaction throughout the design process.
  • Diverse User Base: Ensure feedback from a wide demographic to capture diverse perspectives and needs.
  • Utilize Multiple Channels: Collect feedback through surveys, interviews, usability testing, and analytics to gather a comprehensive understanding.
  • Iterative Testing: Conduct frequent testing on prototypes to gather timely insights and adapt quickly.

Case Study 1: Airbnb

Revolutionizing Booking with User Insights

Airbnb, an industry leader in hospitality, exemplifies the power of user feedback in iterative design. Initially, Airbnb faced challenges with user booking processes and trust issues among the community.

To address these challenges, Airbnb conducted extensive user interviews and testing sessions. Feedback highlighted confusion around the booking interface and skepticism regarding property legitimacy and safety.

Based on these insights, Airbnb iterated on their design. They simplified the booking process by implementing a straightforward and transparent user interface. User profiles and reviews were made more prominent, improving trustworthiness through verified reviews and host information.

The result was a significant increase in user engagement and bookings, showcasing how targeted iterative design enhancements rooted in user feedback can lead to substantial business growth.

Case Study 2: Dropbox

Streamlining File Sharing with Continuous Feedback

Dropbox, a pioneer in cloud storage, faced challenges in its early stages with its file synchronization features. Initial users reported difficulties with the interface and inconsistent synchronization.

Dropbox’s response was to adopt an iterative design process heavily reliant on user feedback. They invited a broad user group to engage with beta versions, encouraging honest feedback and suggestions.

Through this feedback, Dropbox identified specific areas for improvement, such as the need for clearer file status indicators and more reliable background synchronization. Iterative testing and design adjustments addressed these concerns, enhancing overall user satisfaction and experience.

This consistent feedback loop not only improved the functionality but also cemented Dropbox’s reputation for reliability and ease-of-use, leading to increased adoption and user retention.

Conclusion

Incorporating user feedback into iterative design is not merely an option but a necessity for creating products that truly resonate with users. As demonstrated through the success stories of Airbnb and Dropbox, continually engaging with users and adapting designs accordingly can unlock new levels of innovation and success.

By understanding user feedback’s critical role, adopting best practices for its integration, and learning from successful case studies, businesses can refine their design processes to cultivate products that deliver exceptional user experiences and sustainable growth.

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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Have Humans Evolved Beyond Nature and a Need for It?

Have Humans Evolved Beyond Nature and a Need for It?

GUEST POST from Manuel Berdoy, University of Oxford

Our society has evolved so much, can we still say that we are part of Nature? If not, should we worry – and what should we do about it? Poppy, 21, Warwick.

Such is the extent of our dominion on Earth, that the answer to questions around whether we are still part of nature – and whether we even need some of it – rely on an understanding of what we want as Homo sapiens. And to know what we want, we need to grasp what we are.

It is a huge question – but they are the best. And as a biologist, here is my humble suggestion to address it, and a personal conclusion. You may have a different one, but what matters is that we reflect on it.

Perhaps the best place to start is to consider what makes us human in the first place, which is not as obvious as it may seem.


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.


Many years ago, a novel written by Vercors called Les Animaux dénaturés (“Denatured Animals”) told the story of a group of primitive hominids, the Tropis, found in an unexplored jungle in New Guinea, who seem to constitute a missing link.

However, the prospect that this fictional group may be used as slave labour by an entrepreneurial businessman named Vancruysen forces society to decide whether the Tropis are simply sophisticated animals or whether they should be given human rights. And herein lies the difficulty.

Human status had hitherto seemed so obvious that the book describes how it is soon discovered that there is no definition of what a human actually is. Certainly, the string of experts consulted – anthropologists, primatologists, psychologists, lawyers and clergymen – could not agree. Perhaps prophetically, it is a layperson who suggested a possible way forward.

She asked whether some of the hominids’ habits could be described as the early signs of a spiritual or religious mind. In short, were there signs that, like us, the Tropis were no longer “at one” with nature, but had separated from it, and were now looking at it from the outside – with some fear.

It is a telling perspective. Our status as altered or “denatured” animals – creatures who have arguably separated from the natural world – is perhaps both the source of our humanity and the cause of many of our troubles. In the words of the book’s author:

All man’s troubles arise from the fact that we do not know what we are and do not agree on what we want to be.

We will probably never know the timing of our gradual separation from nature – although cave paintings perhaps contain some clues. But a key recent event in our relationship with the world around us is as well documented as it was abrupt. It happened on a sunny Monday morning, at 8.15am precisely.

A new age

The atomic bomb that rocked Hiroshima on August 6 1945, was a wake-up call so loud that it still resonates in our consciousness many decades later.

The day the “sun rose twice” was not only a forceful demonstration of the new era that we had entered, it was a reminder of how paradoxically primitive we remained: differential calculus, advanced electronics and almost godlike insights into the laws of the universe helped build, well … a very big stick. Modern Homo sapiens seemingly had developed the powers of gods, while keeping the psyche of a stereotypical Stone Age killer.

We were no longer fearful of nature, but of what we would do to it, and ourselves. In short, we still did not know where we came from, but began panicking about where we were going.

We now know a lot more about our origins but we remain unsure about what we want to be in the future – or, increasingly, as the climate crisis accelerates, whether we even have one.

Arguably, the greater choices granted by our technological advances make it even more difficult to decide which of the many paths to take. This is the cost of freedom.

I am not arguing against our dominion over nature nor, even as a biologist, do I feel a need to preserve the status quo. Big changes are part of our evolution. After all, oxygen was first a poison which threatened the very existence of early life, yet it is now the fuel vital to our existence.

Similarly, we may have to accept that what we do, even our unprecedented dominion, is a natural consequence of what we have evolved into, and by a process nothing less natural than natural selection itself. If artificial birth control is unnatural, so is reduced infant mortality.

I am also not convinced by the argument against genetic engineering on the basis that it is “unnatural”. By artificially selecting specific strains of wheat or dogs, we had been tinkering more or less blindly with genomes for centuries before the genetic revolution. Even our choice of romantic partner is a form of genetic engineering. Sex is nature’s way of producing new genetic combinations quickly.

Even nature, it seems, can be impatient with itself.

Our natural habitat? Shutterstock

Changing our world

Advances in genomics, however, have opened the door to another key turning point. Perhaps we can avoid blowing up the world, and instead change it – and ourselves – slowly, perhaps beyond recognition.

The development of genetically modified crops in the 1980s quickly moved from early aspirations to improve the taste of food to a more efficient way of destroying undesirable weeds or pests.

In what some saw as the genetic equivalent of the atomic bomb, our early forays into a new technology became once again largely about killing, coupled with worries about contamination. Not that everything was rosy before that. Artificial selection, intensive farming and our exploding population growth were long destroying species quicker than we could record them.

The increasing “silent springs” of the 1950s and 60s caused by the destruction of farmland birds – and, consequently, their song – was only the tip of a deeper and more sinister iceberg. There is, in principle, nothing unnatural about extinction, which has been a recurring pattern (of sometimes massive proportions) in the evolution of our planet long before we came on the scene. But is it really what we want?

The arguments for maintaining biodiversity are usually based on survival, economics or ethics. In addition to preserving obvious key environments essential to our ecosystem and global survival, the economic argument highlights the possibility that a hitherto insignificant lichen, bacteria or reptile might hold the key to the cure of a future disease. We simply cannot afford to destroy what we do not know.

Is it this crocodile’s economic, medical or inherent value which should be important to us? Shutterstock

But attaching an economic value to life makes it subject to the fluctuation of markets. It is reasonable to expect that, in time, most biological solutions will be able to be synthesised, and as the market worth of many lifeforms falls, we need to scrutinise the significance of the ethical argument. Do we need nature because of its inherent value?

Perhaps the answer may come from peering over the horizon. It is somewhat of an irony that as the third millennium coincided with decrypting the human genome, perhaps the start of the fourth may be about whether it has become redundant.

Just as genetic modification may one day lead to the end of “Homo sapiens naturalis” (that is, humans untouched by genetic engineering), we may one day wave goodbye to the last specimen of Homo sapiens genetica. That is the last fully genetically based human living in a world increasingly less burdened by our biological form – minds in a machine.

If the essence of a human, including our memories, desires and values, is somehow reflected in the pattern of the delicate neuronal connections of our brain (and why should it not?) our minds may also one day be changeable like never before.

And this brings us to the essential question that surely we must ask ourselves now: if, or rather when, we have the power to change anything, what would we not change?

After all, we may be able to transform ourselves into more rational, more efficient and stronger individuals. We may venture out further, have greater dominion over greater areas of space, and inject enough insight to bridge the gap between the issues brought about by our cultural evolution and the abilities of a brain evolved to deal with much simpler problems. We might even decide to move into a bodiless intelligence: in the end, even the pleasures of the body are located in the brain.

And then what? When the secrets of the universe are no longer hidden, what makes it worth being part of it? Where is the fun?

“Gossip and sex, of course!” some might say. And in effect, I would agree (although I might put it differently), as it conveys to me the fundamental need that we have to reach out and connect with others. I believe that the attributes that define our worth in this vast and changing universe are simple: empathy and love. Not power or technology, which occupy so many of our thoughts but which are merely (almost boringly) related to the age of a civilisation.

True gods

Like many a traveller, Homo sapiens may need a goal. But from the strengths that come with attaining it, one realises that one’s worth (whether as an individual or a species) ultimately lies elsewhere. So I believe that the extent of our ability for empathy and love will be the yardstick by which our civilisation is judged. It may well be an important benchmark by which we will judge other civilisations that we may encounter, or indeed be judged by them.

When we can change everything about ourselves, what will we keep? Shutterstock

There is something of true wonder at the basis of it all. The fact that chemicals can arise from the austere confines of an ancient molecular soup, and through the cold laws of evolution, combine into organisms that care for other lifeforms (that is, other bags of chemicals) is the true miracle.

Some ancients believed that God made us in “his image”. Perhaps they were right in a sense, as empathy and love are truly godlike features, at least among the benevolent gods.

Cherish those traits and use them now, Poppy, as they hold the solution to our ethical dilemma. It is those very attributes that should compel us to improve the wellbeing of our fellow humans without lowering the condition of what surrounds us.

Anything less will pervert (our) nature.

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

Image Credits: Pixabay, Shutterstock (via theconversation)

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What Latest Research Reveals About Innovation Management Software

What Latest Research Reveals About Innovation Management Software

GUEST POST from Jesse Nieminen

Our industry of innovation management software is quite an interesting one. It’s been around for a while, but it’s still not a mainstay that every organization would use, at least not in the same way as CRM and team communication software are.

Hence, there’s quite little independent research available out there to prove its efficacy, or even for determining which parts of it are the most valuable.

So, when I saw a new study, conducted jointly by a few German universities, come out on the topic, I was naturally curious to learn more.

In this article, I’ll share the key findings of the study with you, as well as some personal thoughts on the how and why behind these findings. We’ll also wrap up the discussion by considering how these findings relate to the wider trends within innovation management.

About the Study

Before we get to the results, let’s first briefly cover what the study was actually about and how it was conducted.

First, the focus of the study was to analyze the role of Innovation Management Software (IMS) adoption for New Product Development (NPD) effectiveness and efficiency, as well as the factors (software functionality and offered services) that actually led to successful adoption of said innovation management software.

The data was collected with an online questionnaire that was answered by innovation managers from 199 German firms of varying sizes, 45% of which used an Innovation Management Software, and 55% of which didn’t.

While this is the largest independent piece of research I’ve yet seen on innovation management software, we should remember that all research comes with certain limitations and caveats, and it’s important to understand and keep these in mind.

You can read the paper for a more detailed list, but in my opinion, this boils down to a few key things:

  • First, the study uses NPD performance as a proxy for innovation outcomes. This is an understandable choice to make the research practical, but in reality, innovation is much more than just NPD.
  • Second, while the sample size of companies is respectable, the demographic is quite homogenous as they are all German companies that employ an innovation manager, which obviously isn’t representative of every organization out there.
  • Third, the results are analyzed with regression analyses, which always brings up the age-old dilemma: correlation doesn’t imply causation. In other words, the study can tell us the “what”, not the “why” or “how”.
  • And finally, while the chosen variables are based on validated prior research, the questions still require subjective analysis from the respondent, which can introduce some bias to the results.

So, let’s keep these in mind and move on to the actual findings.

The Main Findings of the Study

The authors have done a great job in summarizing the hypothesis and respective results in a table, which you’ll also find reproduced below.

Innovation Management Software Research Results

Let’s break the results down by hypothesis and cover the main takeaways for each.

Innovation Management Software Adoption Leads to Better NPD Performance

The first hypothesis was that using an Innovation Management Software would lead to better New Product Development performance. This can further be broken down into two parts: efficiency and effectiveness.

The results show that IMS adoption does indeed improve NPD efficiency, but the impact on NPD effectiveness wasn’t significant.

Innovation Management Software improves New Product Development efficiency, but the impact on effectiveness isn’t significant.

Intuitively, this makes sense and is also well in line with our experience. Innovation, especially in terms of NPD, is hard and requires a lot of work and difficult decisions, usually in the face of significant uncertainty. No software can magically do that job for you, but a good tool can help keep track of the process and do some of the heavy lifting for you.

This naturally helps with efficiency which allows innovators to focus more of their efforts on things that will lead to better results, but those results still aren’t a given.

Functionality That Leads to Higher IMS Adoption

The second hypothesis is focused on the functionality provided by the innovation management software, and the impact of said functionality on overall IMS adoption.

To be more specific, the respondents were asked how important they considered each functionality to be for their firm.

Here, Idea Management was the only functionality that had an impact for these firms.

Idea Management was the only functionality that had a significant positive impact for the surveyed firms.

Again, that intuitively makes sense and is well in line with our experience. Idea management is the part that you embed in the organization’s daily processes and use across the organization to make ideation and innovation systematic. And as mentioned, it’s the part that does a lot of the heavy lifting, such as increasing transparency, communication and collecting and analyzing data, that would otherwise take up a lot of time from people running innovation, which naturally helps with efficiency.

So, while Strategy and Product Management capabilities do have their uses, they are not nearly as essential to IMS adoption, or innovation success for that matter.

In our experience, this primarily comes down to the fact that most companies can manage those capabilities just fine even without an IMS. The value-add provided by the software just isn’t nearly as high for most organizations there.

Services That Lead to Higher IMS Adoption

The third and final hypothesis focused on the importance of the services offered by IMS vendors for the respective firms.

Here the spectrum covered consulting, training, customer support, customizations, as well as software updates and upgrades.

Here, the only factor that made a positive difference for the respondents was software updated and upgrades. This category includes both minor improvements as well as new functionality for the software.

Interestingly enough, for consulting that relationship was negative. Or as the authors put it, adopters more alienate than appreciate such services.

Software updates and upgrades were the only service with a positive impact, whereas consulting actually had a negative one.

Let’s first cover the updates and upgrades as that is probably something everyone agrees on.

Good software obviously evolved quickly and as most companies have embraced the Software as a Service (SaaS) model, they’ve come to expect frequent bug fixes, usability and performance improvements, and even new features for free. Over the lifetime of the product, these make a huge difference.

Thus, most understand that you should choose a vendor that is committed and capable of delivering a frequent stream of updates and new capabilities.

Let’s then move on to consulting and discuss why it is detrimental to adoption.

While we’ve always kept professional services to a minimum at Viima, this still came as a bit of a surprise for me. As I’ve raised this point up in discussions with a couple of people in the industry, that do offer such services, they seem to respond with varying degrees of denial, dismissal, and perhaps even a hint of outrage. When such emotions are at play, it’s always a good time for an innovator to lean in and dig a bit deeper, so let’s do that!

Looking at this from the point of view of the customer, there are a few obvious problems:

  • Misaligned incentives
  • … which leads to focusing on the wrong issues
  • Lack of ownership

Each of these could be discussed in length, but let’s focus on covering the keys here.

First, it’s important to understand that every software company makes most of their profits from software licenses. Thus, while generally speaking modern SaaS models do incentivize the vendor to make you successful, that isn’t the whole picture. The focus is actually on keeping the customer using the software. With the right product, that will lead to good outcomes, but that isn’t necessarily always the case.

However, when you add consulting to the mix, it’s only natural that it focuses primarily on the usage of the software because that’s what they know best, and what’s also in their best interest.

And, while making the most out of the software is important, it’s usually not the biggest challenge organizations have with their innovation efforts. In our experience, these are usually in topics such as organizational structure, resource allocation, talent, culture, as well as leadership buy-in and understanding.

And, even if the vendor would focus more on some of these real challenges the customer has, they rarely are the best experts in these matters due to their experience coming from matters related to the product.

Advice on Innovation Management

Now, once you have a consultant come in, you of course want to listen to them. However, a consultant’s job is to give advice, it isn’t to get to the outcomes you want or need, and there’s a big difference there. That is one of the fundamental challenges in using consultants in general, and a big reason for why many don’t like to use them for long-term issues that are core to your future success, such as innovation.

Having said that, if you do use consultants, you can’t lose track of the fact you still need to take ownership for delivering those results. The consultant might be able to help you with that, or they might not. It’s still your job to make the decisions and execute on the chosen plan.

Put together, these reasons are also why we have been reluctant to do much consulting for our customers. We simply think the customer is best served by taking ownership of these matters themselves. We do, on the other hand, seek to provide them with the information, materials and advice they might need in navigating some of these decisions – with no additional cost through channels such as this blog and our online coaching program.

How do these findings relate to wider IMS trends?

Now that we’ve covered the key findings, let’s discuss how these are present in the wider trends within the Innovation Management Software industry.

In addition to what we hear in our discussions with customers and prospects, we’ve also discussed the topic quite extensively with industry analysts and would break these down into a few main trends.

Focus on enterprise-wide innovation

One of the big trends we see is that more and more companies are following in the footsteps of the giants like Tesla, Amazon, Apple and Google, and are moving innovation from separate silos to become more of a decentralized organization-wide effort.

This isn’t always necessary for pure NPD performance, which is what the study was focused on, but it is certainly key for scaling innovation in general, and one where efficient idea management can play a key role.

Once you embark on that journey, you’ll realize that your innovation team will initially be spread very thin. In that situation, it’s especially important to have easy-to-use tools that can empower people across the organization and improve efficiency.

Simultaneous need for ease of use and flexibility

That enterprise-wide innovation trend is also a big driver for the importance of intuitiveness, ease of use, and flexibility becoming more important.

In the past, you could have an innovation management software that is configured to match your stage-gate process for NPD. You might still need that, but it’s no longer enough. You probably want more agile processes for some of your innovation efforts, and more lightweight ones for some of the more incremental innovation many business units need to focus on.

If people across the organization don’t know how to use the software, or require extensive training to do so, you’ll face an uphill battle. What’s more, if you need to call the vendor whenever you need to make a change to the system, you’re in trouble. Top innovators often run dozens or even hundreds of different simultaneous innovation processes in different parts of the organization, so that quickly becomes very tedious and expensive.

Reducing operational complexity and costs

A big consideration for many is the operational complexity and running costs associated in running and managing their infrastructure and operations.

Extensive configuration work and on-premises installations significantly add to both of these, so even though they can be tempting for some organizations, the costs do pile up a lot over time, especially since it requires a lot more attention from your support functions like IT to manage.

What’s more, if you want to make changes or integrate these systems with new ones you may introduce, typically you only have one option: you need to turn to your IMS vendor.

As IMS tools have matured and off-the-shelf SaaS services have become much more capable, the compromises in increased rigidity, complexity and running costs, as well as less frequent updates are no longer worth it and off-the-shelf SaaS is now the way to go for almost everyone. With SaaS, you benefit immensely from economies of scale, and you are no longer held captive by the sunk cost fallacy of up-front license payments and extensive configuration and training work.

Commoditization in Idea Management

As the study pointed out, idea management is at the core of most innovation management software. However, in the last decade, the competition in the space has increased a lot.

There are now native SaaS platforms, like Viima, that are able to offer extremely competitive pricing due to efficient operations and a lean organizational structure. This has put a lot of pressure on many vendors to try to differentiate themselves and justify their higher price tags with additional professional services, as well as adjacent products and capabilities.

In our experience, while these might sound good on paper, they aren’t often leading to more value in real life, and the respondents of this study would seem to concur.

Conclusion

So, to conclude, what did we learn from the research?

In a nutshell, no innovation management software or vendor will miraculously turn you into a successful innovator. A good software, however, will help you become more efficient with your innovation efforts, as well as lead to softer benefits such as improvements in communication, knowledge transfer and culture. Put together, these can make your life a lot easier so that you can focus on actually driving results with innovation.

What then should you consider when choosing your innovation management vendor?

Well, the evidence shows that you should focus on idea management, as that’s where the biggest impact on the factors mentioned above come from. And therein, you should focus on vendors that continuously update and evolve their software with the help of modern technology and that has made all the above so easy and intuitive that they don’t need to sell you consulting.

And of course, ask them the tough questions. Ask to test the software in real life. If you can’t, that is a red flag in and of itself. See how flexible and easy-to-use their software really is. Does it require consulting or configuration by the vendor?

This article was originally published in Viima’s blog.

Image credits: Unsplash, Viima

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AI-Powered Tools for Creative Industries

AI-Powered Tools for Creative Industries

GUEST POST from Chateau G Pato

The creative industries are experiencing a transformation, thanks to artificial intelligence (AI) tools that enhance productivity, spark innovation, and expand creative possibilities. From content creation to design, AI-powered tools are reshaping the way artists, designers, and thinkers work. This article explores these advancements, featuring real-world case studies that illustrate the impact of AI on creative processes.

The Rise of AI in Creative Processes

AI is equipped to handle tasks that traditionally required significant human effort, such as pattern recognition and data analysis. However, its influence on creativity isn’t about replacing human artistry—it’s about augmenting it. AI can handle repetitive tasks, allowing creatives to focus on what they do best: innovating and ideating.

Case Study 1: AI in Music Composition

AI Platform: AIVA (Artificial Intelligence Virtual Artist)

AIVA is an AI-based composer that’s been used by artists and musicians around the world to enhance and inspire music production. Trained on a wide range of classical compositions, AIVA can create original scores and suggest enhancements to existing compositions. By iterating with composers, AIVA helps create music that resonates emotionally with audiences.

Outcome: AIVA was employed in film scoring, leading to a fusion of human creativity and AI precision. Composers reported a 30% reduction in time spent on initial drafts, allowing more time to focus on intricacy and expression.

Tools Transforming the Industry

Beyond music, AI tools are influencing numerous sectors within creative industries. They provide everything from generative design and content curation to audience engagement analytics. Let’s explore another example where AI tools have significantly impacted creativity.

Case Study 2: AI in Graphic Design

AI Platform: Adobe Sensei

Adobe Sensei uses AI to boost productivity and creativity for graphic designers by automating mundane tasks such as object detection and layering. Designers can create more complex visuals in less time with AI assistance. Tools like Adobe’s “Content-Aware Fill” leverage AI algorithms to enhance or alter images seamlessly.

Outcome: A marketing agency integrated Adobe Sensei into their workflow, reducing their design time for digital advertising campaigns by 40%. Designers reported feeling less creatively fatigued, leading to a rise in innovative concepts and overall client satisfaction.

Conclusion

Artificial intelligence has carved out an invaluable role within the creative industries, not as a replacement, but as a powerful ally. The potential for AI to enhance creative output lies in its ability to handle intensive tasks, providing creatives with the freedom to push boundaries. As AI continues to evolve, so too will the possibilities for innovation, ensuring that the marriage between human creativity and machine precision leads to exciting new frontiers.

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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We Must Rethink the Future of Technology

We Must Rethink the Future of Technology

GUEST POST from Greg Satell

The industrial revolution of the 18th century was a major turning point. Steam power, along with other advances in areas like machine tools and chemistry transformed industry from the work of craftsmen and physical labor to that of managing machines. For the first time in world history, living standards grew consistently.

Yet during the 20th century, all of that technology needed to be rethought. Steam engines gave way to electric motors and internal combustion engines. The green revolution and antibiotics transformed agriculture and medicine. In the latter part of the century digital technology created a new economy based on information.

Today, we are on the brink of a new era of innovation in which we will need to rethink technology once again. Much like a century ago, we are developing new, far more powerful technologies that will change how we organize work, identify problems and collaborate to solve them. We will have to change how we compete and even redefine prosperity itself.

The End of the Digital Revolution

Over the past few decades, digital technology has become almost synonymous with innovation. Every few years, a new generation of chips would come out that was better, faster and cheaper than the previous one. This opened up new possibilities that engineers and entrepreneurs could exploit to create new products that would disrupt entire industries.

Yet there are only so many transistors you can cram onto a silicon wafer and digital computing is nearing its theoretical limits. We have just a few generations of advancements left before the digital revolution grinds to a halt. There will be some clever workarounds to stretch the technology a bit further, but we’re basically at the end of the digital era.

That’s not necessarily a bad thing. In many ways, the digital revolution has been a huge disappointment. Except for a relatively brief period in the late nineties and early aughts, the rise of digital technology has been marked by diminished productivity growth and rising inequality. Studies have also shown that some technologies, such as social media, worsen mental health.

Perhaps even more importantly, the end of the digital era will usher in a new age of heterogeneous computing in which we apply different computing architectures to specific tasks. Some of these architectures will be digital, but others, such as quantum and neuromorphic computing, will not be.

The New Convergence

In the 90s, media convergence seemed like a futuristic concept. We consumed information through separate and distinct channels, such as print, radio and TV. The idea that all media would merge into one digital channel just felt unnatural. Many informed analysts at the time doubted that it would ever actually happen.

Yet today, we can use a single device to listen to music, watch videos, read articles and even publish our own documents. In fact, we do these things so naturally we rarely stop to think how strange the concept once seemed. The Millennial generation doesn’t even remember the earlier era of fragmented media.

Today, we’re entering a new age of convergence in which computation powers the physical, as well as the virtual world. We’re beginning to see massive revolutions in areas like materials science and synthetic biology that will reshape massive industries such as energy, healthcare and manufacturing.

The impact of this new convergence is likely to far surpass anything that happened during the digital revolution. The truth is that we still eat, wear and live in the physical world, so innovating with atoms is far more valuable than doing so with bits.

Rethinking Prosperity

It’s a strange anachronism that we still evaluate prosperity in terms of GDP. The measure, developed by Simon Kuznets in 1934, became widely adopted after the Bretton Woods Conference a decade later. It is basically a remnant of the industrial economy, but even back then Kuznets commented, “the welfare of a nation can scarcely be inferred from a measure of national income.”

To understand why GDP is problematic, think about a smartphone, which incorporates many technologies, such as a camera, a video player, a web browser a GPS navigator and more. Peter Diamandis has estimated that a typical smartphone today incorporates applications that were worth $900,000 when they were first introduced.

So, you can see the potential for smartphones to massively deflate GDP. First of all, the price of the smartphone itself, which is just a small fraction of what the technology in it would have once cost. Then there is the fact that we save fuel by not getting lost, rarely pay to get pictures developed and often watch media for free. All of this reduces GDP, but makes us better off.

There are better ways to measure prosperity. The UN has proposed a measure that incorporates 9 indicators, the OECD has developed an alternative approach that aggregates 11 metrics, UK Prime Minister David Cameron has promoted a well-being index and even the small city of Somerville, MA has a happiness project.

Yet still, we seem to prefer GDP because it’s simple, not because its accurate. If we continue to increase GDP, but our air and water are more polluted, our children less educated and less healthy and we face heightened levels of anxiety and depression, then what have we really gained?

Empowering Humans to Design Work for Machines

Today, we face enormous challenges. Climate change threatens to pose enormous costs on our children and grandchildren. Hyperpartisanship, in many ways driven by social media, has created social strife, legislative inertia and has helped fuel the rise of authoritarian populism. Income inequality, at its highest levels since the 1920s, threatens to rip shreds in the social fabric.

Research shows that there is an increasing divide between workers who perform routine tasks and those who perform non-routine tasks. Routine tasks are easily automated. Non-routine tasks are not, but can be greatly augmented by intelligent systems. It is through this augmentation that we can best create value in the new century.

The future will be built by humans collaborating with other humans to design work for machines. That is how we will create the advanced materials, the miracle cures and new sources of clean energy that will save the planet. Yet if we remain mired in an industrial mindset, we will find it difficult to harness the new technological convergence to solve the problems we need to.

To succeed in the 21st century, we need to rethink our economy and our technology and begin to ask better questions. How does a particular technology empower people to solve problems? How does it improve lives? In what ways does it need to be constrained to limit adverse effects through economic externalities?

As our technology becomes almost unimaginably powerful, these questions will only become more important. We have the power to shape the world we want to live in. Whether we have the will remains to be seen.

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

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Measuring Success in Agile Transformations

Measuring Success in Agile Transformations

GUEST POST from Art Inteligencia

Agile transformations are sweeping through organizations worldwide, promising enhanced flexibility, faster time to market, and greater responsiveness to change. However, while many companies embark on this journey, the measure of success can often seem elusive. To truly gauge the effectiveness of an agile transformation, one must look beyond surface-level metrics and delve into deeper, more meaningful indicators.

In this exploration, we’ll delve into what it means to measure success in agile transformations, enriched by real-world case studies that illustrate successful implementations.

Understanding Agile Success

Agile transformation is not a destination but a journey. Success isn’t simply about adopting Scrum or any other agile framework. It’s about fostering a culture of continuous improvement, collaboration, and responsive adaptation to change.

To assess success, consider the following dimensions:

  • Customer Satisfaction: Are customers happier and are their feedback loops tighter?
  • Employee Engagement: Are team members more engaged and empowered to innovate?
  • Quality Improvement: Are defects reduced and is quality improving?
  • Time to Market: Are products and services hitting the market faster?
  • Value Delivery: Is there a clear, measurable increase in value delivered to stakeholders?

Case Study 1: TechCorp’s Agile Journey

Background

TechCorp, a mid-sized software company, embarked on an agile transformation to improve product development speed and enhance customer satisfaction.

Approach

The company started by forming cross-functional teams and implementing Scrum. Leaders invested in training and coaching, emphasizing a shift in mindset toward customer-centricity and collaboration.

Outcomes

Within a year, TechCorp saw a 30% reduction in time to market, with customer satisfaction scores increasing by 20%. Employee engagement surveys revealed a 25% boost in morale, and the defect rate in software releases dropped by 15%.

Continual retrospectives and adaptations became part of the culture, allowing TechCorp to sustain and build upon these gains.

Case Study 2: HealthFirst’s Transformation

Background

HealthFirst, a healthcare provider, sought to transform its operations to improve patient outcomes and operational efficiency.

Approach

The transformation began with the integration of agile methodologies across various departments, from IT to patient care management. A focus was placed on iterative improvement and adopting a data-driven decision-making process.

Outcomes

After two years, HealthFirst reported a 40% reduction in patient wait times and a substantial increase in patient satisfaction scores. Operational costs decreased by 15%, and employee turnover rates dropped by 10%.

The organization’s commitment to measuring patient-centric outcomes allowed for a more rounded view of success, blending agile practices with core healthcare principles.

Key Takeaways

Agile transformations can yield impressive results when approached with a comprehensive understanding of success metrics. Organizations should focus on aligning agile processes with broader strategic goals to ensure meaningful change.

By closely monitoring both qualitative and quantitative outcomes — from customer feedback to engagement levels — companies can create a consistent feedback loop to guide ongoing improvement. The true measure of success lies not only in adhering to agile principles, but in fostering a dynamic, responsive culture that can thrive in a rapidly changing world.

Are you ready to embark on your agile journey? Remember, success is measured not just in numbers, but in transformed lives and lasting impact.

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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Sickcare AI Field Notes

Sickcare AI Field Notes

I recently participated in a conference on Artificial Intelligence (AI) in healthcare. It was the first onsite meeting after 900 days of the pandemic.

Here is a report from the front:

  1. AI has a way to go before it can substitute for physician judgment, intuition, creativity and empathy
  2. There seems to be an inherent conflict between using AI to standardize decisions compared to using it for mass customization. Efforts to develop customized care must be designed around a deep understanding of what happens at the ground level along the patient pathway and must incorporate patient engagement by focusing on such things as shared decision-making, definition of appointments, and self-management, all of which are elements of a “build-to-order” approach.
  3. When it comes to dissemination and implementation, culture eats strategy for lunch.
  4. The majority of the conversations had to do with the technical aspects and use cases for AI. A small amount was about how to get people in your organization to understand and use it.
  5. The goal is to empower clinical teams to collaborate with patient teams and that will take some work. Moving sick care to healthcare also requires changing a sprint mindset to a marathon relay race mindset with all the hazards and risks of dropped handoffs and referral and information management leaks.
  6. AI is a facilitating technology that cuts across many applications, use cases and intended uses in sick care. Some day we might be recruiting medical students, residents and other sick care workers using AI instead of those silly resumes.
  7. The value proposition of AI includes improving workflow and improving productivity
  8. AI requires large, clean data sets regardless of applications
  9. It will take a while to create trust in technology
  10. There needs to be transparency in data models
  11. There is a large repository of data from non-traditional sources that needs to be mined e.g social media sites, community based sites providing tests, like health clubs and health fairs, as well as post acute care facilities
  12. AI is enabling both the clinical and business models of value based care
  13. Cloud based AI is changing diagnostic imaging and pattern recognition which will change manpower dynamics
  14. There are potential opportunities in AI for quality outcome stratification, cost accounting and pricing of episodes of care, determining risk premiums and optimizing margins for a bundled priced procedure given geographic disparities in quality and cost.
  15. We are in the second era of AI that is based on deep learning v rules based algorithms
  16. Value based care requires care coordination, risk stratification, patient centricity and managing risk
  17. Machine learning is being used, like Moneyball, to pick startup winners and losers, with a dose of high touch.
  18. It is encouraging to see more and more doctors attending and speaking at these kinds of meetings and lending a much needed perspective and reality check to technologists and non-sick care entrepreneurs. There were few healthcare executives besides those who were invited to be on panels.
  19. Overcoming the barriers to AI in sick care have mostly to do with changing behavior and not dwelling on the technicalities, but, rather, focusing on the jobs that doctors need to get done.
  20. The costs of AI , particularly for small, independent practitioners, are often not affordable, particularly when bundled with crippling EMR expenses . Moore’s law has not yet impacted medicine
  21. The promise of using AI to get more done with less conflicts with the paradox of productivity
  22. Top of mind problems to be solved were how to increase revenuces, cut costs , fill the workforce pipelines and address burnout and behavioral health employee and patient problems with scarce resouces.
  23. Nurses, pharmacists, public health professionals and veterinarians were under represented
  24. Payers were scarce
  25. Patients were scarce
  26. Students, residents and clinicians were looking for ways to get side gigs, non-clinical careers and exit ramps if need be.
  27. 70% of AI applications are in radiology
  28. AI is migrating from shiny to standard, running in the background to power diverse remote care modalities
  29. Chronic disease management and behavioral health have replace infectious disease as the global care management challenges
  30. AI education and training in sickcare professional schools is still woefully absent but international sickcare professional schools are filling the gaps
  31. Process and workflow improvements are a necessary part of digital and AI transformation

At its core, AI is part of a sick care eco-nervous system “brain” that is designed to change how doctors and patients think, feel and act as part of continuous behavioral improvement. Outcomes are irrelevant without impact.

AI is another facilitating technology that is part and parcel of almost every aspect of sick care. Like other shiny new objects, it remains to be seen how much value it actually delivers on its promise. I look forward to future conferences where we will be discussing how, not if to use AI and comparing best practices and results, not fairy tales and comparing mine with yours.

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