Six Reasons Norway is a Leader in High-Performance Teamwork

Six Reasons Norway is a Leader in High-Performance Teamwork

GUEST POST from Stefan Lindegaard

If you research why certain countries are leaders and others are laggards in high performance teamwork, you quickly see that Norway and thus the Norwegian society has several notable characteristics that contribute to the success of high-performance teams in business and organizations.

Note: Thank you to those who joined me in Oslo to discuss high-performance teams and explore my new and developing concept of High Performance Zones for Teams: Trust, Empowerment, and Collaboration.

Here are a few key factors for Norway in the context of high-performance:

  1. High Levels of Trust: Norwegian society is characterized by high trust both in institutions and among individuals. This trust extends into the workplace, where there is a strong belief in the reliability and integrity of colleagues. High trust environments can enhance collaboration and the sharing of ideas, which are crucial for high-performance teams.
  2. Flat Organizational Structures: Norwegian companies often favor flat organizational structures over hierarchical ones. This promotes open communication and a sense of equality among team members, enabling quicker decision-making and greater flexibility – important attributes for high-performance teams.
  3. Work-Life Balance: Norway places a strong emphasis on work-life balance, which helps maintain high levels of job satisfaction and motivation among employees. Well-rested and well-rounded employees are more likely to contribute positively to their teams.
  4. Focus on Consensus-Building: In Norwegian business culture, there is a tendency towards consensus-building rather than top-down decision-making. This approach ensures that various perspectives are considered and that team members are committed to the agreed-upon course of action, leading to more sustainable and effective team performance.
  5. Investment in Employee Development: There is a significant investment in training and development within Norwegian organizations. A well-trained workforce with opportunities for continuous learning and improvement can adapt and perform better in dynamic business environments.
  6. Innovation and Technological Adaptation: Norway is well-known for its adaptation of new technologies and innovation. High-performance teams often leverage cutting-edge technologies and new practices to maintain competitive advantages.

These aspects of Norwegian society and organizational culture provide a supportive environment for cultivating high-performance teams, which are essential for achieving exceptional outcomes in business and other fields.

How does your country compare on these six factors? Please share, and let’s discuss.

Image Credits: Pixabay

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How to Design Offsites That Generate Revenue

How to Design Offsites That Generate Revenue

GUEST POST from Robyn Bolton

Corporate offsites – the phrase conjures images of everything from “mandatory fun” with colleagues to long and exhausting days debating strategy with peers.  Rarely are the images something that entice people to sit up and shout, “YEA!” But what if the reality could be something YEA! worthy?

That’s exactly what the authors of the recent Harvard Business Review (HBR) article, “Why Offsites Work – and How to Get the Most Out of Them,” describe and offer a guide to accomplish.

Offsites May Be the Answer to the WFH vs. RTO Debate

Offsites aren’t new but they’ve taken on a new role and new significance as companies grapple with how to manage Work from Home (WFH) and Return To Office (RTO) policies. 

As with most things in life, the pendulum swings from one extreme to another until eventually, finally, landing in a stable and neutral midpoint.  When the pandemic hit, we swung from every day in the office to every day at home.  Then society opened back up and corporate landlords came calling for rent, whether or not people were in the offices, so we swung back to Return to Office mandates.

Offsites, the authors suggest, may be the happy medium between the two extremes because offsites:

“give people opportunities for interactions that otherwise might not happen. Offsites create unique opportunities for employees to connect in person, forming new relationships and strengthening existing ones. As a result, offsites help people learn about others’ knowledge and build interpersonal trust, which are both critical ingredients for effective collaboration.”

Offsite Connections Lead to Collaborations that Generate ROI

After analyzing eight years of data from a global firm’s offsites and 350,000 “instances of formal working relationships”  for 750 employees, the authors found that intentionally designed offsites (more on that in a moment) yield surprisingly measurable and lasting results:

  • 24% more incoming requests for collaboration amongst attendees post vs. pre-offsite (silos busted!)
  • 17% of new connections were still active two years after the offsite (lasting change!)
  • $180,000 in net new revenue from collaborations within the first two months post offsite (real results!)

The benefits event extended to non-attendees because they “seemed to get the message that collaboration is important and wanted to demonstrate their commitment to being collaborative team players” and “likely identified new collaborators after the offsite through referrals.”

How to Design Offsites That Get Results

Four key strategies emerged from the authors’ research and work with over 100 other organizations:

  1. Design for the people in the audience, not the people on stage.  Poll attendees to understand their specific needs and goals, then design collaborative activities, not management monologues.
  2. Design for the new hires, not the tenured execs.  Create opportunities for new hires to meet, connect with, and work alongside more experienced colleagues.
  3. Set and communicate clear goals and expectations.  Once the offsite is designed and before it happens, tell people what to expect (the agenda) and why to expect it (your design intentions and goals).  Also, tell them how to make the most of the offsite opportunities by thinking about the skill and network gaps they want to fill.
  4. Track activities to measure ROI.  The connections, collaborations, and commitments that start at the offsite need to continue after it in the form of ongoing communication, greater collaboration, and talent engagement.  Yes, conduct a post-event survey immediately after the event but keep measuring every 2-3 months until the next offsite.  The data will reveal how well you performed against your goals and how to do even better the next time.

Offsites can be a powerful tool to build an organization’s culture and revenue, but only if they are thoughtfully designed to go beyond swanky settings, sermons from the stage, and dust-collecting swag and build the connections and collaborations that only start when people are together, in-person, outside of the office.

Image credit: Unsplash

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Surviving Change

Surviving Change

GUEST POST from Greg Satell

The Greek philosopher Heraclitus observed that “There is nothing permanent except change” and events over the past few thousand years would seem to prove him right. Yet while change may endure, the rate of change fluctuates over time. Throughout history, forces tend to cascade and converge on particular points.

By all indications, we are in such a period now. We are undergoing four major shifts in technology, resources, migration and demography that will be transformative. Clearly, these shifts will create significant opportunities, but also great peril. The last time we saw this much change afoot was during the 1920s and that didn’t end well.

Yet history is not destiny. We’re entering a new era of innovation in which our ability to solve problems will be unprecedented and can shape our path by making wise choices. Still, as we have seen with the Covid pandemic, the toughest challenges we will face will have had less to do with devising solutions than with changing behaviors and conquering ourselves.

Building A Shared Understanding Of The Problems We Need To Solve

The first step toward solving a problem is acknowledging that there is one. Even before Covid skeptics came into vogue, there was no shortage of pundits who denied climate change. For years, many considered Alan Greenspan to possess sage-like wisdom when he asserted that markets would self-correct. In the end, even he would admit that he was gravely mistaken.

The truth is that we live in a world of the visceral abstract, where strange theories govern much of our existence. People can debate the “big bang,” deny Darwin’s theory of natural selection or even deride these ideas as “lies straight from the pit of hell.” Many agreed when Senator Marco Rubio asserted that these things have nothing to do with our everyday lives.

Still, the reality is that modern existence depends on abstract theories almost every second of the day. Einstein’s theories may seem strange, but if GPS satellites aren’t calibrated to take them into account, we’re going to have a hard time getting where we want to go. In much the same way the coronavirus doesn’t care what we think about Darwin, if it is allowed to replicate it will mutate and new, more deadly variants are likely to arise.

History shows that building a consensus to confront shared challenges is something that is firmly within our capability. The non-proliferation agenda of the 1950s led to concrete achievements such as the Partial Test Ban Treaty. When advances in gene therapy made the potential for danger clear, the Berg Letter called for a moratorium on the riskiest experiments until the dangers were better understood. These norms have been respected for decades.

Discovering Novel Solutions

Identifying and defining our challenges is just a first step. As Bill Gates pointed out, we still don’t know how to solve the climate crisis. Despite all the happy talk about technological advancement, productivity growth remains depressed. We’ve seen a global rise in populist authoritarianism and our inability to solve problems has surely contributed.

Put simply, we do not know how to overcome all of the challenges we face today. We need to innovate. However, innovation is never a single event, but a process of discovery, engineering and transformation. We can’t simply hope to adapt and overcome when a crisis hits, we need to innovate for the long-term.

Consider our response to the Covid crisis. Yes, the pandemic caught us off-guard and we should have been better prepared. But our most effective response wasn’t any of the emergency measures, but a three-decade effort that resulted in the development of mRNA vaccines. Even that was nearly killed in its cradle and surely would have been if it had not been for the dedication and perseverance of a young researcher named Katalin Karikó.

An emerging model taking hold is collaboration between government, academia and private industry. For example, JCESR is helping to create next generation technologies in energy storage, the Partnership on AI is helping to map the future for cognitive technologies and the Manufacturing USA Institutes, bring together diverse stakeholders to drive advancement.

Perhaps most of all, we need to start taking a more biological view of technology. We can no longer expect advancement to progress in an organized, linear way. We need to think less like engineers building a machine and more like gardeners who grow ecosystems to nurture new possibilities that we can’t yet imagine, but are lying beneath the surface.

Driving Adoption And Scaling Change

If there’s anything we’ve learned during the Covid pandemic is that developing a viable solution isn’t enough. Early measures, such as masking and social distancing, were met with disdain. The development of effective vaccines in record time was something of a miracle. Still, it was met with derision rather than gratitude in many communities.

This is not a new phenomenon. Good ideas fail all the time. From famous cases like that of Ignaz Semmelweis and William Coley to the great multitudes whose names are lost to history, any time a new idea threatens the status quo there will always be some that will seek to undermine it and they will do it in ways that are dishonest, underhanded and deceptive. If change is ever to prevail, we need to learn to anticipate and overcome resistance.

The good news is that it only takes a minority to embrace change in order for it to prevail. Everett Rogers found that it took only 10%-20% of system members to adopt an innovation for rapid adoption to follow. An analysis of over 300 political revolutions estimated that 3.5% active participation was enough. Other research suggests that the tipping point is 25% in an organization.

What we need is not more catchy slogans, divisive rhetoric or even charismatic leaders, but to empower movements made up of small groups, loosely connected but united by a shared purpose. My friend Srdja Popović provides great guides for social and political revolutionaries in both his book and his organization’s website. I have adapted many of these ideas for corporate and organizational contexts in Cascades.

Perhaps most importantly, as I recently pointed out in Harvard Business Review, is that transformation is fundamentally distinct from other stages of innovation. Coming up with a new idea or solution takes very different skills—and often different people—than driving adoption and scale.

Building A Bridge Through Shared Identity

Marshal McLuhan, one of the most influential thinkers of the 20th century, described media as “extensions of man” and predicted that electronic media would eventually lead to a global village. Communities, he predicted, would no longer be tied to a single, isolated physical space but connect and interact with others on a world stage.

What often goes untold is that McLuhan did not see the global village as a peaceful place. In fact, he predicted it would lead to a new form of tribalism and result in a “release of human power and aggressive violence” greater than ever in human history, as long separated —and emotionally charged— cultural norms would constantly intermingle, clash and explode.

Today, what we most need to grapple with is the dystopia that McLuhan foresaw and described so eloquently and accurately. People do not vehemently refute science, trash Darwin, deny climate change or oppose life-saving vaccines because they have undergone some rational deductive process, but because it offends their identity and sense of self. That, more than anything else, is why change fails.

Yet as Francis Fukuyama pointed out in his recent book, our identities are not fixed, but develop and change over time. We can seek to create a larger sense of self through building communities rooted in shared values. What’s missing in our public discourse today isn’t more or better information. What we lack is a shared sense of mission and purpose.

That is the challenge before us. It is not enough to devise solutions to the problems we face, although that in itself will require us to apply the best of our energies and skills. We will also have to learn to survive victory by overcoming the inevitable strife that change leaves in its wake.

— Article courtesy of the Digital Tonto blog
— Image credits: Pexels

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Artificial Innovation

Artificial Innovation

by Braden Kelley

Recently several people have asked me whether or not artificial intelligence (AI) has a role to play innovation. One of the ways I’ve answered this question is by speaking about how artificial intelligence can be used to help test/disprove assumptions. Innovation always makes assumptions and often the success or failure of any innovation effort is determined by how well the team identifies the critical assumptions to test, those that if incorrectly assumed to be true could later derail the pursuit of innovation or waste limited innovation investment dollars.

But I thought it could be interesting to use AI to answer this question in more detail, leveraging my Eight I’s of Infinite Innovation framework to highlight how artificial intelligence could be used at each step of the continuous innovation journey.

Below you will find a detailed explanation of the Eight I’s of Infinite Innovation framework along with clearly called out contextual responses generated by Microsoft CoPilot detailing how AI could be used productively during that specific phase of the continuous innovation journey from prompts generated by me after uploading a PDF version of the original Eight I’s of Infinite Innovation article (see the link at the bottom).

Eight I's of Infinite Innovation

Creating a Continuous Innovation Capability

To achieve sustainable success at innovation, you must work to embed a repeatable process and way of thinking within your organization, and this is why it is important to have a simple common language and guiding framework of infinite innovation that all employees can easily grasp. If innovation becomes too complex, or seems too difficult then people will stop pursuing it, or supporting it.

Some organizations try to achieve this simplicity, or to make the pursuit of innovation seem more attainable, by viewing innovation as a project-driven activity. But, a project approach to innovation will prevent it from ever becoming a way of life in your organization. Instead you must work to position innovation as something infinite, a pillar of the organization, something with its own quest for excellence – a professional practice to be committed to.

So, if we take a lot of the best practices of innovation excellence and mix them together with a few new ingredients, the result is a simple framework organizations can use to guide their pursuit of continuous innovation – the Eight I’s of Infinite Innovation. This framework anchors what is a very collaborative process. Here is the framework and some of the many points organizations must consider during each stage of the continuous process:

1. Inspiration

  • Employees are constantly navigating an ever changing world both in their home context, and as they travel the world for business or pleasure, or even across various web pages in the browser of their PC, tablet, or smartphone.
  • What do they see as they move through the world that inspires them and possibly the innovation efforts of the company?
  • What do they see technology making possible soon that wasn’t possible before?
  • The first time through we are looking for inspiration around what to do, the second time through we are looking to be inspired around how to do it.
  • What inspiration do we find in the ideas that are selected for their implementation, illumination and/or installation?

How to leverage artificial innovation during the Inspiration phase (according to AI):

  • AI can help employees find inspiration by analyzing vast amounts of data from various sources, such as social media, news articles, and industry reports. By identifying emerging trends and patterns, AI can provide insights into what is possible and inspire new ideas for innovation. Additionally, AI-powered tools can help employees visualize potential solutions and explore creative possibilities.

2. Investigation

  • What can we learn from the various pieces of inspiration that employees come across?
  • How do the isolated elements of inspiration collect and connect? Or do they?
  • What customer insights are hidden in these pieces of inspiration?
  • What jobs-to-be-done are most underserved and are worth digging deeper on?
  • Which unmet customer needs that we see are worth trying to address?
  • Which are the most promising opportunities, and which might be the most profitable?

How to leverage artificial innovation during the Inspiration phase (according to AI):

  • AI can assist in the investigation phase by processing and analyzing large datasets to uncover hidden insights and customer needs. Machine learning algorithms can identify patterns and correlations that may not be immediately apparent to humans, helping organizations understand which opportunities are most promising and worth pursuing. AI can also automate the process of gathering and organizing information, making it easier for employees to focus on deeper analysis.

3. Ideation

  • We don’t want to just get lots of ideas, we want to get lots of good ideas
  • Insights and inspiration from first two stages increase relevance and depth of the ideas
  • We must give people a way of sharing their ideas in a way that feels safe for them
  • How can we best integrate online and offline ideation methods?
  • How well have we communicated the kinds of innovation we seek?
  • Have we trained our employees in a variety of creativity methods?

How to leverage artificial innovation during the Inspiration phase (according to AI):

  • AI can enhance the ideation process by generating a wide range of ideas based on input from employees and external sources. Natural language processing (NLP) algorithms can analyze and categorize ideas, making it easier to identify the most relevant and promising ones. AI-powered collaboration tools can also facilitate brainstorming sessions, allowing employees to share and build on each other’s ideas in real-time, regardless of their physical location.

4. Iteration

  • No idea emerges fully formed, so we must give people a tool that allows them to contribute ideas in a way that others can build on them and help uncover the potential fatal flaws of ideas so that they can be overcome
  • We must prototype ideas and conduct experiments to validate assumptions and test potential stumbling blocks or unknowns to get learnings that we can use to make the idea and its prototype stronger
  • Are we instrumenting for learning as we conduct each experiment?

How to leverage artificial innovation during the Inspiration phase (according to AI):

  • AI can support the iteration phase by providing tools for rapid prototyping and experimentation. Machine learning models can simulate different scenarios and predict potential outcomes, helping teams identify and address potential flaws in their ideas. AI can also automate the process of collecting and analyzing feedback from experiments, enabling continuous improvement and refinement of prototypes.

Eight I's of Infinite Innovation

5. Identification

  • In what ways do we make it difficult for customers to unlock the potential value from this potentially innovative solution?
  • What are the biggest potential barriers to adoption?
  • What changes do we need to make from a financing, marketing, design, or sales perspective to make it easier for customers to access the value of this new solution?
  • Which ideas are we best positioned to develop and bring to market?
  • What resources do we lack to realize the promise of each idea?
  • Based on all of the experiments, data, and markets, which ideas should we select?

How to leverage artificial innovation during the Inspiration phase (according to AI):

  • AI can help organizations identify the most viable ideas by analyzing data from experiments, market research, and customer feedback. Predictive analytics can assess the potential success of different ideas and prioritize those with the highest likelihood of success. AI can also identify potential barriers to adoption and suggest strategies to overcome them, ensuring that innovative solutions are accessible and valuable to customers.

You’ll see in the framework that things loop back through inspiration again before proceeding to implementation. There are two main reasons why. First, if employees aren’t inspired by the ideas that you’ve selected to commercialize and some of the potential implementation issues you’ve identified, then you either have selected the wrong ideas or you’ve got the wrong employees. Second, at this intersection you might want to loop back through the first five stages though an implementation lens before actually starting to implement your ideas OR you may unlock a lot of inspiration and input from a wider internal audience to bring into the implementation stage.

6. Implementation

  • What are the most effective and efficient ways to make, market, and sell this new solution?
  • How long will it take us to develop the solution?
  • Do we have access to the resources we will need to produce the solution?
  • Are we strong in the channels of distribution that are most suitable for delivering this solution?

How to leverage artificial innovation during the Inspiration phase (according to AI):

  • AI can streamline the implementation process by optimizing production, marketing, and sales strategies. AI-powered project management tools can help teams plan and execute tasks more efficiently, while machine learning algorithms can optimize supply chain and distribution processes. AI can also personalize marketing campaigns and sales approaches, ensuring that new solutions reach the right customers at the right time.

7. Illumination

  • Is the need for the solution obvious to potential customers?
  • Are we launching a new solution into an existing product or service category or are we creating a new category?
  • Does this new solution fit under our existing brand umbrella and represent something that potential customers will trust us to sell to them?
  • How much value translation do we need to do for potential customers to help them understand how this new solution fits into their lives and is a must-have?
  • Do we need to merely explain this potential innovation to customers because it anchors to something that they already understand, or do we need to educate them on the value that it will add to their lives?

How to leverage artificial innovation during the Inspiration phase (according to AI):

  • AI can enhance the illumination phase by helping organizations communicate the value of their innovations to potential customers. NLP algorithms can generate compelling marketing content and product descriptions, while sentiment analysis can gauge customer reactions and adjust messaging accordingly. AI can also identify key influencers and target them with personalized messages to amplify the reach of new solutions.

8. Installation

  • How do we best make this new solution an accepted part of everyday life for a large number of people?
  • How do we remove access barriers to make it easy as possible for people to adopt this new solution, and even tell their friends about it?
  • How do we instrument for learning during the installation process to feedback new customer learnings back into the process for potential updates to the solution?

How to leverage artificial innovation during the Inspiration phase (according to AI):

  • AI can facilitate the installation of new solutions by removing barriers to adoption and ensuring a seamless customer experience. AI-powered customer support tools can provide instant assistance and troubleshooting, while machine learning algorithms can personalize onboarding processes to meet individual customer needs. AI can also monitor usage patterns and gather feedback, enabling continuous improvement and updates to the solution.

Conclusion

The Eight I’s of Infinite Innovation framework is designed to be a continuous learning process, one without end as the outputs of one round become inputs for the next round. It’s also a relatively new guiding framework for organizations to use, so if you have thoughts on how to make it even better, please let me know in the comments. The framework is also ideally suited to power a wave of new organizational transformations that are coming as an increasing number of organizations (including Hallmark) begin to move from a product-centered organizational structure to a customer needs-centered organizational structure. The power of this new approach is that it focuses the organization on delivering the solutions that customers need as their needs continue to change, instead of focusing only on how to make a particular product (or set of products) better.

By leveraging AI at each stage of the innovation process, organizations can enhance their ability to generate, develop, and implement successful innovations.

So, as you move from the project approach that is preventing innovation from ever becoming a way of life in your organization, consider using the Eight I’s of Infinite Innovation to influence your organization’s mindset and to anchor your common language of innovation. The framework is great for guiding conversations, making your innovation outputs that much stronger, and will contribute to your quest for innovation excellence – it is even more powerful when you combine it with my Value Innovation Framework (found here). The two are like chocolate and peanut butter. They’re powerful tools when used separately, but even more powerful when used together.

Click to access this framework as a FREE scalable 11″x17″ PDF download

Click to download the PDF version of this article

People who upgrade to the Bronze Version of the Change Planning Toolkit™ will get access to my Innovation Planning Canvas™ which combines the Value Innovation Framework together with the Eight I’s of Infinite Innovation, allowing you to track the progress of each potential innovation on the three value innovation measures as you evolve any individual idea through this eight step process.

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Don’t ‘Follow the Science’, Follow the Scientific Method

Don't 'Follow the Science', Follow the Scientific Method

GUEST POST from Pete Foley

The scientific method is probably the most useful thing I’ve learnt in my life. It is a near universal tool that can be used in so many ways and so many places.  It unleashes a whole world of assisted critical thinking that is invaluable to innovators, but also in our personal lives.  Teaching it to individuals or teams who are not trained as scientists is one of the most powerful and enabling things we can do for them.  And teaching it to kids, as opposed to endless facts and data that they can easily access from the web is something we should do far more of.  

Recruiting Skills not Expertise:  When I was involved in recruiting, I always valued PhD’s and engineers.  Sometimes that was for their unique, specialized knowledge.  But more often than not it was more for the critical thinking skills they had acquired while gaining that specialized knowledge. In today’s rapidly evolving world, specific knowledge typically has a relatively short shelf-life.  But the cognitive framework embodied by the scientific method is a tool for life, and one that can be reapplied in so many ways.  .

Don’t Follow the Science, Follow the Process:  All too often today the scientific method gets confused with ‘following the science’.  The scientific process is almost infinitely useful, but blindly ‘following the science’ is often far less so, and can be counter productive.  The scientific method is a process that helps us to evaluate information, challenge assumptions, and in so doing, get us closer to truth.  Sometimes it confirms our existing ideas, sometimes it improves them, and sometimes it completely replaces them.  But it is grounded in productive and informed skepticism, and this is at the heart of why science is constantly evolving.

‘Follow the Science’ in many ways the opposite.  It assumes someone in a position of power already has the right answer.  At it’s best it means blindly follow the consensus of today’s experts.  All too often it really means ‘do as you are told’.   Frequently the people saying this are not the experts themselves, but are instead evoking third party expertise to support their viewpoint.  That of course is the opposite of science.  It’s often well intended, but not always good advice.

Science is not a Religion:  At the heart of this is a fundamental misunderstanding of science, and scientists. In today’s media and social media, all too often science and scientists are presented with a quasi-religious reverence, and challenging the current view is framed as heretical.  How often do you here the framing ‘scientists tell us… ‘ as a way of validating a position?   

This is understandable.  The sheer quantity and complexity of information we are faced with in our everyday lives is increasingly unmanageable, while big challenges like climate unimaginably complex.  I find it almost impossible to keep up with my own interests, let alone everything that is happening.  And some topics are so technical that they simply require translation by experts.  When someone announces they’ve discovered the Higgs boson particle, it’s not really practical for any of us to pop over to the local particle accelerator and check for ourselves.  So expertise is clearly an important part of any decision chain. But experts come with their own biases. An engineer naturally tends to see problems and through, an engineering lens, a chemist through a chemical one.

Science in Support of an Agenda:  One danger with the ‘follow the science’ mantra is that it is often used to reinforce a belief, opinion, or even agenda.  I’ve seen this all too often in my work life, with the question, ‘can you find me a paper that supports ‘x’.  This is often benign, in that someone passionately believes something, and wants to find evidence to support it.   But this is fundamentally the wrong question, and of course, completely ‘unscientific’.

The scientific literature is filled with competing theories, disproven or outdated ideas, and bad science.   If you look for literature to support an idea you can usually find it, even if it’s wrong.   Scientists are not gods.  They make mistakes, they run poor experiments, and they are subject to confirmation biases, ego, and other human frailties. There is a good reason for the phrase that science evolves one death at a time. Science, like virtually every human organization is hierarchical, and a prestigious scientist can advance a discipline, but can also slow it down by holding onto a deeply held belief. And mea culpa, I know from personal experience that it’s all too easy to fall in love with a theory, and resist evidence to the contrary. 

Of course, some theories are more robust than others.   Both consensus and longevity are therefore important considerations.  Some science is so well established, and supported by so much observation that it’s unlikely that it will fundamentally change.  For example, we may still have a great deal to learn about gravity, but for practical purposes, apples will still drop from trees.    

Peer Review:  Policing the literature is hard.  Consensus is right until its not. Another phrase I often hear is ‘peer reviewed’, in the context that this makes the paper ‘right’.  Of course, peer review is valuable, part of the scientific process, and helps ensure that content has quality, and has been subject to a high level of rigor.   If one person says it, it can be a breakthrough or utter nonsense.  If a lot of smart people agree, it’s more likely to be ‘right’.  But that is far from guaranteed, especially if they share the same ingoing assumptions. Scientific consensus has historically embraced many poor theories; a flat earth, or the sun revolving around the earth are early examples. More tragically, I grew up with the thalidomide generation in Europe.  On an even bigger scale, the industrial revolution gave us so much, but also precipitated climate change.  And on a personal level, I’ve just been told by my physician to take a statin, and I am in the process of fighting my way through rapidly growing and evolving literature in order to decide if that is the right decision.  So next time you see a scientist, or worse, a politician, journalist, or a random poster on Twitter claim they own scientific truth, enjoin you to ‘follow the science’, or accuse someone else of being a science denier, treat it with a grain of sodium chloride.

They may of course be right, but the more strident they are, or the less qualified, the less likely they are to really understand science, and hence what they are asking you to follow.  And the science they pick is quite possibly influenced by their own goals, biases or experience. Of course, practically we cannot challenge everything. We need to be selective, and the amount of personal effort we put into challenging an idea will depend upon how important it is to us as individuals.      

Owning your Health:  Take physicians as an example.  At some time or other, we’ve all looked to a physician for expert advise.  And there is a good reason to do so.  They work very hard to secure deep knowledge of their chosen field, and the daily practice of medicine gives then a wealth of practical as well as well as theoretical knowledge.  But physicians are not gods either.  The human body is a very complex system, physicians have very little time with an individual patient (over the last 10 years, the average time a physician spends with a patient has shrunk to a little over 15 minutes), the field is vast and expanding, and our theories around how to diagnose and treat disease are constantly evolving.  In that way, medicine is a great example of the scientific method in action, but also how transient ‘scientific truths’ can be.  

I already mentioned my current dilemma with statins.   But to give an even more deeply personal example, neither my wife or I would be alive today if we’d blindly followed a physicians diagnosis.

I had two compounding and comparatively rare conditions that combined to appear like a more common one.  The physician went with the high probability answer.  I took time to dig deeper and incorporate more details.  Together we got to the right answer, and I’m still around!

This is a personal and pragmatic example of how valuable the scientific process can be.  My health is important, so I chose to invest considerable time in the diagnosis I was given, and challenge it productively, instead of blindly accepting an expert opinion. My physicians had far more expertise than I did, but I had far more time and motivation.  We ultimately complemented each other by partnering, and using the scientific method both as a process, and as a way to communicate.   

The Challenge of Science Communication:  To be fair, science communication is hard.   It requires communicating an often complex concept with sufficient simplicity for it to be understandable, often requires giving guidance, while also embracing appropriate uncertainty. Nowhere was this more evident than in the case of Covid 19, where a lot of ‘follow the science’, and ‘science denier’ language came from.  At the beginning of the pandemic, the science was understandably poorly developed, but we still had to make important decisions on often limited data.  At first we simply didn’t understand even the basics like the transmission vectors (was it airborne or surface, how long did it survive outside of the body, etc).  I find it almost surreal to think back to those early months, how little we knew, the now bizarre clean room protocols we used on our weekly shopping, and some of the fear that has now faded into the past.  

But because we understood so little, we made a lot of mistakes.  The over enthusiastic use of ventilators may have killed some patients, although that is still a hotly debated topic. Early in the pandemic masks, later to become a controversial and oddly politically charged topic, masks were specifically not recommended by the US government for the general public. Who knows how many people contracted the disease by following this advice?   It was well intentioned, as authorities were trying to prevent a mask shortage for health workers. But it was also mechanistically completely wrong.

At the time I used simple scientific reasoning, and realized this made little sense.  If the virus was transmitted via an airborne vector, a mask would help.  If it wasn’t, it would do no harm, at least as long as I didn’t subtract from someone with greater need. By that time the government had complete control of the mask supply chain anyway, so that was largely a moot point. Instead I dug out a few old N95 masks that had been used for spray painting and DIY, and used them outside of the house (hospitals would not accept donations of used masks). I was lambasted with ‘follow the science’ by at least one friend for doing so, but followed an approach with high potential reward and virtually zero downside. I’ll never know if that specifically worked, but I didn’t get Covid, at least not until much later when it was far less dangerous.

Science doesn’t own truth: Unlike a religion, good science doesn’t pretend to own ultimate truths.  But unfortunately it can get used that way.  Journalists, politicians, technocrats and others sometimes weaponize (selective) science to support an opinion. Even s few scientists who have become frustrated with ‘science deniers’ can slip into this trap.

Science is a Journey: I should clarify that the scientific method is more of a journey, not so much a single process. To suggest is is a single ‘thing’ so is probably an unscientific simplification in its own right. It’s more a way of thinking that embraces empiricism, observation, description, productive skepticism, and the use of experimentation to test and challenge hypothesis. It also helps us to collaborate and communicate with experts in different areas, creating a common framework for collaboration, rather than blindly following directions or other expert opinions.    

It can be taught, and is incredibly useful.  But like any tool, it requires time and effort to become a skilled user.   But if we invest in it, it can be extraordinarily valuable, both in innovation and life. It’s perhaps not for every situation, as that would mire us in unmanageable procrastination.  But if something is important, it’s an invaluable tool. 

Image credits: Pixabay

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Dynamic Thinking

Dynamic Thinking

GUEST POST from Mike Shipulski

If you’re asked to do cost reduction, before doing that work, ask for objective evidence that the work to grow the top line is adequately staffed. You can’t secure your company’s future through cost reduction, so before you spend time and effort to grow the bottom line, make sure the work to grow the top line is more than fully staffed. Without top-line growth, cost reduction is nothing more than a race to the bottom.

If you’re asked to do more of what was done last time, before doing that work, look back and plot how that line of goodness has improved over time. If the goodness over time is flat (it hasn’t increased), the technology is mature, there’s nothing left, and you should improve something else (a new line of goodness). If the goodness continues to increase over time, ask customers if it’s already good enough. Do this by asking if they’d pay more for more goodness. If they won’t pay more, it’s already good enough. Stop work on that tired, old line of goodness and work on a new one. If goodness over time is still increasing and customers will pay more, teach someone else how to improve that line of goodness so you can establish the next line of goodness which will be needed when the old one gets tired.

If you’re asked to make your product do more, before doing that work, figure out if the planet will be better off if your product does more. If the planet will frown if your product does more, make your product do less with far less. In that way, your customers will get a bit less, but they’ll use far fewer resources and the planet will smile. And when the planet smiles, so will the stockholders of the company that provides less with far less.

If you’re asked to improve a specific line of goodness, before doing that work, look to see if competitive technologies are also improving on that same line of goodness. If their improvement slope is steeper than yours, you will be overtaken. Find a new line of goodness to improve, or buy the dominant company in that’s making progress with the competitive technology. Don’t wait, or sooner rather than later, they’ll buy you.

If you’re asked to make your product do more, before doing that work, look at the byproducts that will increase and how that relates to the regulatory standards. If those nasty byproducts are (or will be) regulated, future improvements will be blocked by regulatory limits. You can argue about when those limits will be a problem, but you can’t argue that those regulatory limits will ultimately take you out by the knees. It’s a tough pill to swallow, but it’s time to look to a new technology because your existing one will soon be outlawed.

Everything changes. Nothing is static. Technologies get better, then it’s difficult to make the next improvement. Competitors get better, then it’s difficult to be better than them. Environmental constraints get tighter, then you’re legally blocked from improvements that violate those constraints. Last year’s solutions become obsolete. Last year’s analysis tools become obsolete. Last year’s best materials are no longer best. And last year’s manufacturing best processes are no longer best. That’s just how it works.

Before you allocate precious resources to do what you did last time, spend a little time to analyze the situation in a dynamic sense. What changed since last time? Has the regulatory environment changed? Have competitors made improvements? Have new competitors emerged with new technologies? Has your legacy technology run out of gas or does it still have legs? Have new tools come of age and who is using them?

Everything has a half-life – technologies, products, services, tools, processes, business models, and people. When new things are come to be, the only thing you can guarantee is that time will run out and they will run their course. Even if your business model has been successful, it has a half-life and it will die.

Success causes us to think statically, but the universe behaves dynamically. The trick is to use the resources created by our success to sow the seeds that must grow into the solutions of an uncertain future. The best time to plant a tree was fifteen years ago, and the next best time to plant one is today.

Image credit: Pexels

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The State of Customer Experience and the Contact Center

The State of Customer Experience and the Contact Center

GUEST POST from Shep Hyken

Oh, what a difference a year makes. A few months ago I traveled to Las Vegas to attend the Customer Contact Week (CCW), the largest conference and trade show in the contact center industry. For the past several years, the big discussion has centered on artificial intelligence (AI), and that continues, but Customer Experience (CX) is also moving into the spotlight. AI and natural language models can give customers an almost human-like experience when they have a question or complaint. However, no surprise, some companies do it better than others.

First, all the hype around AI is not new. AI has been in our lives for decades, just at a much simpler level. How do you think Outlook and other email companies recognize that an email is spam and belongs in the junk/spam folder? Of course, it’s not 100% perfect, and neither are today’s best AI programs.

Many of us use Siri and Alexa. That’s AI. And as simple as that is, it’s obviously more sophisticated when you apply it to customer support and CX.

Let’s go back 10 years ago when I attended the IBM Watson conference in Las Vegas. The big hype then was around AI. There were some incredible cases of AI changing customer service, sales and marketing, not to mention automated processes. One of the demonstrations during the general session showcased AI’s stunning capability. Here’s what I saw:

A customer called the contact center. While the customer service agent listened to the customer, the computer (fueled by AI) listened to the conversation and fed the agent answers without the agent typing the questions. In addition, the computer informed the agent how long the customer had been doing business with the company, how often they made purchases, what products they had bought and more. The computer also compared this customer to others who had the same questions and suggested the agent answer those questions. Even though the customer didn’t yet know to ask them, at some point in the future, they would surely be calling back to do so.

That demonstration was a preview of what we have today. One big difference is that implementing that type of solution back then could have cost hundreds of thousands of dollars, if not more than a million. Today, that technology is affordable to almost any company, costing a fraction of what it cost back then (as in just a few thousand dollars).

Voice Technology Gets Better

Less than two years ago, ChatGPT was introduced to the world. Similar technologies have been developed. The capability continues to improve at an incredibly rapid pace. The response from an AI-fueled chatbot is lightning fast. Now, the technology is moving to voice. Rather than type a question for the chatbot, you talk, and it responds in a human-like voice. While voice technology has existed for years, it’s never been this good. Google introduced voice technology that seemed almost human-like. The operative word here is almost. As good as it was, people could still sense they weren’t talking to a human. Today, the best systems are human-like, not almost human-like. Think Alexa and Siri on steroids.

Foreign Accents Are Disappearing

We’ve all experienced calling customer support, and an offshore customer service agent with a heavy accent answers the call. Sometimes, it’s nearly impossible to understand the agent. New technologies are neutralizing accents. A year ago, the software sounded a little “digital.” Today, it sounds almost perfect.

Why Customers Struggle with AI and Other Self-Service Solutions

As far as these technologies have come, customers still struggle to accept them. Our customer service research (sponsored by RingCentral) found that 63% of customers are frustrated by self-service options, such as ChatGPT and similar technologies. Furthermore, 56% of customers admit to being scared of these technologies. Even though 32% of the customers surveyed said they had successfully resolved a customer service issue using AI or ChatGPT-type technologies, it’s not their top preference as 70% still choose the phone as their first level of support. Inconsistency is part of the problem. Some companies still use old technology. The result is that the customer experience varies from company to company. In other words, customers don’t know whether the next time they experience an AI solution if it will be good or not. Inconsistency destroys trust and confidence.

Companies Are Investing in Creating a Better CX

I’ve never been more excited about customer service, CX and the contact center. The main reason is that almost everything about this conference was focused on creating a better experience for the customer. The above examples are just the tip of the iceberg. Companies and brands know what customers want and expect. They know the only way to keep customers is to give them a product that works with an experience they can count on. Price is no longer a barrier as the cost of some of these technologies has dropped to a level that even small companies can afford.

Customer Service Goes Beyond Technology: We Still Need People!

This article focused on the digital experience rather than the traditional human experience. But to nail it for customers, a company can’t invest in just tech. It must also invest in its employees. Even the best technology doesn’t always get the customer what they need, which means the customer will be transferred to a live agent. That agent must be properly trained to deliver the experience that gets customers to say, “I’ll be back.”

Image Credits: Pexels, Shep Hyken

This article originally appeared on Forbes.com

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Best Team Building Exercise Around

Best Team Building Exercise Around

GUEST POST from David Burkus

Team building is a crucial element of creating a strong team culture. Understanding each other’s differences and preferences is a vital step in becoming a high-performing team. But many leaders struggle to find and deliver effective team building exercises. There are many too choose from, and many fall short. So many exercises focus solely on getting teammates to understand each other’s differences—often expressed as personality, identity, or experiences.

But for team building exercises to work, teams can’t just understand each other. They need to understand each other’s behavior.

And that’s what makes the “manual of me” activity the single best team building exercise. Instead of assigning different letters or numbers to different team members based on personality. It focuses on having teammates share their different work preferences. This tool allows team members to gain a deeper understanding of each other’s strengths, weaknesses, preferred environments, and working preferences. And over time, teams become be able to coordinate and even predict each other’s behavior.

In this article, we will delve into the concept of a Manual of Me, how to construct one, and the benefits of sharing and collecting these manuals within the team.

The “Manual of Me”

The Manual of Me is a powerful tool that enables team members to gain insights into each other’s behavior and preferences. It consists of a core of four, fill-in-the-blank questions: “I’m at my best when _____,” “I’m at my worst when _____,” “You can count on me to _____,” and “What I need from you is _____.”

By discussing these questions, team members can understand each other’s strengths and weaknesses, preferred environments, and working preferences. This understanding is crucial for creating a harmonious and productive team culture.

Constructing a Manual of Me

Constructing a Manual of Me involves a conversation within the team where each member shares their answers to the four core questions. Before starting the activity, it is important to inform the team about the purpose and provide them with the template and questions ahead of time.

The first question, “I’m at my best when _____,” focuses on identifying individual strengths, preferred activities, and environments for optimal performance. This question allows team members to understand how they can bring their best selves to the team.

The second question, “I’m at my worst when _____,” helps identify tasks and environments where individuals may struggle or under-perform. By understanding these limitations, team members can provide support and create an environment that minimizes challenges.

The third question, “You can count on me to _____,” highlights each person’s contributions and areas where they can provide help to the team. This question promotes collaboration and allows team members to leverage each other’s strengths.

The fourth question, “What I need from you is _____,” identifies areas where individuals need support or assistance from others. This question fosters open communication and helps team members understand how they can best support each other.

Additional questions can be added to the Manual of Me based on the team’s industry and level of familiarity with each other. These questions can delve deeper into specific aspects of work or personal preferences that are relevant to the team’s dynamics.

Sharing and Collecting Manuals of Me

Once each team member has shared their answers, there should be time for discussion and clarification. This allows team members to gain a deeper understanding of each other’s perspectives and preferences.

The completed Manuals of Me can be in various formats such as PDFs, Word documents, PowerPoints, or videos. It is important to choose a format that is easily accessible and can be stored in a shared folder or platform where the team can easily access them.

The ongoing conversation and understanding fostered by the Manuals of Me can lead to improved collaboration and performance within the team. By referring back to these manuals, team members can ensure that they are effectively supporting each other and leveraging their strengths.

When new team members join, they can be introduced to the Manuals of Me and encouraged to share their own once they feel comfortable. This helps integrate new members into the team and ensures that everyone is on the same page.

The Manual of Me is a powerful team building exercise that promotes understanding and collaboration within a team. By discussing strengths, weaknesses, preferred environments, and working preferences, team members can create a strong team culture and enhance their performance. The ongoing conversation and understanding fostered by the Manuals of Me can lead to improved collaboration and performance within the team.

Image credit: Pexels

Originally published on DavidBurkus.com on October 2, 2023

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Top 10 Human-Centered Change & Innovation Articles of November 2024

Top 10 Human-Centered Change & Innovation Articles of November 2024Drum roll please…

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

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

  1. A Shared Language for Radical Change — by Greg Satell
  2. Leadership Best Quacktices from Oregon’s Dan Lanning — by Braden Kelley
  3. Navigating Uncertainty Requires a Map — by John Bessant
  4. The Most Successful Innovation Approach is … — by Howard Tiersky
  5. Don’t Listen to These Three Change Consultant Recommendations — by Greg Satell
  6. What We Can Learn from MrBeast’s Onboarding — by Robyn Bolton
  7. Does Diversity Increase Team Performance? — by David Burkus
  8. Customer Experience Audit 101 — by Braden Kelley and Art Inteligencia
  9. Daily Practices of Great Managers — by David Burkus
  10. An Innovation Leadership Fable – Wisdom from the Waters — by Robyn Bolton

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

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

SPECIAL BONUS: While supplies last, you can get the hardcover version of my first bestselling book Stoking Your Innovation Bonfire for 51% OFF until Amazon runs out of stock or changes the price. This deal won’t last long, so grab your copy while it lasts!

Build a Common Language of Innovation on your team

Have something to contribute?

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

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

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Why Annual Employee Experience Audits Are Important

Why Annual Employee Experience Audits Are Important

by Braden Kelley and Art Inteligencia

In today’s rapidly evolving business landscape, organizations are recognizing the importance of not just their customers’ experience, but also their employees’. The concept of employee experience encompasses every touchpoint a worker encounters from recruitment to retirement. However, what often remains underappreciated is the systematic examination of this experience through regular audits. Today, we’ll explore why annual employee experience audits are critical for any forward-thinking organization.

Understanding Employee Experience

The employee experience can be defined as the sum total of all interactions an employee has with their employer. This includes the culture, the physical workspace, tools and technology provided, leadership behavior, and organizational practices. Together, these elements shape how employees perceive their organization and directly influence engagement, productivity, and retention.

The Need for Regular Audits

Conducting regular audits of the employee experience is crucial for several reasons:

  • Identifying Pain Points: Just as businesses conduct customer journey mapping to understand customer pain points, employee experience audits help uncover hidden obstacles impacting employee satisfaction and performance.
  • Measuring Impact of Changes: Organizations implement initiatives to improve the work environment regularly. Audits provide a structured approach to assess the impact of these initiatives, offering insights into what’s working and what isn’t.
  • Aligning with Strategic Goals: As companies evolve, ensuring that the employee experience aligns with the organization’s strategic goals becomes imperative. Audits help in recalibrating experiences to support these objectives.

The Benefits of Annual Audits

Moving from sporadic reviews to a structured annual audit brings several benefits:

  • Enhanced Engagement: Regular audits demonstrate a commitment to employee well-being, fostering a culture of trust and transparency which enhances overall engagement.
  • Improved Retention: By identifying factors that contribute to dissatisfaction or turnover, organizations can proactively address issues, making it easier to retain top talent.
  • Informed Decision Making: Comprehensive data from audits enable leaders to make informed decisions about policies, benefits, and strategic initiatives that can enhance the employee experience.

What a Complete Employee Experience Audit Looks Like

A thorough employee experience audit should include several key components:

  • Comprehensive Surveys: Distribute surveys that cover a wide range of topics including workplace culture, management effectiveness, communication, work-life balance, career development, and employee satisfaction.
  • Focus Groups and Interviews: Conduct focus groups and one-on-one interviews that allow employees to provide detailed feedback and personal insights that might not surface through surveys alone.
  • Observation: Observe working conditions, team dynamics, and workflow interactions to gain an understanding of the daily employee experience.
  • Data Analysis: Analyze HR data, turnover rates, and performance metrics to identify trends and areas needing improvement.
  • Technology and Tool Assessment: Evaluate the tools and technologies available to employees for their effectiveness in enhancing productivity and satisfaction.
  • Leadership and Management Review: Assess leadership styles and their alignment with employee needs and organizational values.
  • Feedback Loop: Establish a mechanism for continuous feedback and updates to the audit process to ensure it evolves with organizational changes.

What An Employee Experience Audit IS NOT

An employee experience audit is not an employee experience survey. Like a financial audit, it should also typically be conducted by a small group from outside the organization to maintain objectivity and honesty in the observations, devoid of assumptions and rationalizations of design tradeoffs. Employee experience auditors are trying as much as possible to walk in the shoes of employees across channels for key activities and so they must not be isolated from key systems or key employee groups to determine the most important activities and systems to dive the deepest into the experience of.

An employee experience audit is not a solution but research with recommendations. It is worthless without a commitment to act on the findings found. The leadership commitment and plans for how deficiencies will be addressed is EVEN MORE IMPORTANT than how the employee experience audit is conducted.

Implementing Effective Audits

For an audit to be effective, it should be thorough and inclusive. Consider the following steps:

  1. Define Objectives: Clearly outline what you aim to achieve with the audit.
  2. Utilize Surveys and Interviews: Gather quantitative and qualitative data through employee surveys and interviews.
  3. Analyze Data: Use data analytics to identify trends and patterns. Pay attention to anomalies and outliers.
  4. Actionable Recommendations: Transform insights into actionable steps that can be implemented to drive positive change.
  5. Leadership Commitment: Secure commitment from leadership to fund and implement the greatest improvement opportunities identified during the audit.

Conclusion

The workplace is fundamentally changing, and so too must our approach to understanding it. Annual employee experience audits provide a robust framework for consistently enhancing the environments we create for our workforces. In doing so, we not only improve the lives of our employees but also drive innovation, loyalty, and performance that propels our organizations forward. But an employee experience audit is not the same thing as an employee survey. It is instead an outside-in evaluation of the experience employees have while executing key activities across key systems. By embedding an annual employee experience audit practice into our routine, we fortify the human connection at the heart of every successful enterprise.

If you would like to team up to conduct an Employee Experience Audit at your company, please contact me and we can get you on the calendar to meet with our team.

Image credits: Pixabay

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Content Authenticity Statement: The core premise and structure for this article was created by Braden Kelley. The OpenAI Playground, taking on the role of human-centered change and innovation thought leader Braden Kelley has helped to flesh out the content of the article with supplementary content added by Braden Kelley, including the section on What An Employee Experience Audit IS NOT.