Monthly Archives: November 2021

Gamification in the Workplace

Using Game Elements to Boost Engagement and Creativity

Gamification in the Workplace: Using Game Elements to Boost Engagement and Creativity

GUEST POST from Chateau G Pato

In today’s fast-paced and competitive business environment, companies are constantly looking for innovative ways to engage and motivate their employees. One method that has gained popularity in recent years is gamification – the use of game elements and principles in non-game contexts to drive desired behaviors. By incorporating elements such as points, badges, leaderboards, and rewards into everyday tasks and processes, organizations can increase employee engagement, productivity, and creativity.

Case Study 1: Salesforce

One company that has successfully implemented gamification in the workplace is Salesforce. The global customer relationship management software company uses a gamified platform called “Trailhead” to train and motivate its employees. Trailhead allows employees to earn points, badges, and rewards for completing training modules and challenges, creating a sense of accomplishment and friendly competition among teams. As a result, employees are more invested in their learning and development, leading to increased productivity and retention.

Case Study 2: Microsoft

Another example of gamification in the workplace is Microsoft’s “The Ribbon Hero” game. Designed to help employees improve their skills in using Microsoft Office applications, the game challenges players to complete tasks and challenges within the programs, earning points and moving up levels as they progress. By making learning fun and interactive, Microsoft has seen a significant increase in employee engagement and proficiency with their software tools.

Conclusion

Incorporating gamification into the workplace can have numerous benefits for organizations, including increased employee engagement, motivation, and creativity. By tapping into employees’ natural desire for competition, recognition, and achievement, companies can create a more dynamic and fulfilling work environment. As technology continues to advance and the workforce becomes increasingly diverse and digital, gamification will play an essential role in driving innovation and success in the modern workplace.

SPECIAL BONUS: The very best change planners use a visual, collaborative approach to create their deliverables. A methodology and tools like those in Change Planning Toolkit™ can empower anyone to become great change planners themselves.

Image credit: Pixabay

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Big Data Analytics in Healthcare

Unlocking Insights for Better Patient Outcomes

Big Data Analytics in Healthcare: Unlocking Insights for Better Patient Outcomes

GUEST POST from Art Inteligencia

In today’s technologically driven world, data plays a crucial role in almost every sector, and healthcare is no exception. With the rise of electronic health records and wearable devices, the healthcare industry has access to a vast amount of patient data. Big data analytics in healthcare is revolutionizing the way patient care is delivered by unlocking valuable insights that can lead to better outcomes.

One of the key areas where big data analytics is making a significant impact is in personalized medicine. By analyzing large datasets of patient information, healthcare providers can tailor treatment plans to individual patients based on their unique characteristics and medical history. This allows for more targeted and effective treatments, ultimately leading to better outcomes for patients.

Case Study 1: Mayo Clinic

A notable case study showcasing the benefits of big data analytics in personalized medicine is the work being done by the Mayo Clinic. By leveraging advanced analytics tools, the Mayo Clinic has been able to identify patterns in patient data to predict disease progression and customize treatment plans. This approach has resulted in improved patient outcomes and reduced healthcare costs, highlighting the potential of big data analytics to transform the healthcare landscape.

Another area where big data analytics is making a difference in healthcare is in population health management. By analyzing data from large groups of patients, healthcare providers can identify trends and patterns that can help improve overall health outcomes for entire communities. This proactive approach allows for early intervention and targeted interventions to prevent the onset of chronic diseases and improve population health.

Case Study 2: Pittsburgh Medical Center (UPMC)

An excellent example of the success of population health management through big data analytics is the partnership between the University of Pittsburgh Medical Center (UPMC) and IBM Watson Health. By combining UPMC’s wealth of patient data with IBM’s advanced analytics capabilities, the organizations have been able to develop predictive models that identify patients at risk for various health conditions and tailor interventions to prevent or manage these conditions effectively. This partnership has led to better health outcomes for patients and reduced healthcare costs, demonstrating the power of big data analytics in improving population health.

Conclusion

Big data analytics in healthcare is transforming the way patient care is delivered by unlocking valuable insights that lead to better outcomes. By leveraging advanced analytics tools, healthcare providers can personalize treatment plans, improve population health, and ultimately enhance the overall quality of care. The success stories of organizations like the Mayo Clinic and UPMC demonstrate the potential of big data analytics to revolutionize healthcare and improve patient outcomes. By embracing this technology and incorporating it into everyday practice, healthcare providers can truly unlock the full potential of big data analytics and provide better care for patients.

Bottom line: 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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Understanding Customer Needs and Expectations

Key considerations for planning a customer-centric digital transformation

Understanding Customer Needs and Expectations

GUEST POST from Chateau G Pato

In today’s rapidly evolving business landscape, digital transformation has become a critical imperative for organizations looking to stay competitive and relevant. However, many companies often overlook one crucial aspect of this process – understanding and meeting the needs and expectations of their customers.

A customer-centric approach to digital transformation is essential in ensuring that the changes implemented align with what customers want and need. By putting the customer at the center of the transformation journey, businesses can drive greater customer satisfaction, loyalty, and ultimately, business growth.

To effectively plan a customer-centric digital transformation, organizations must first gain a deep understanding of their customers’ needs, preferences, and pain points. This can be done through a variety of methods, such as customer surveys, focus groups, and data analytics. By collecting and analyzing this information, businesses can identify key trends and insights that can inform their digital transformation strategy.

Case study 1: Amazon

Amazon is a prime example of a company that has successfully implemented a customer-centric digital transformation. By leveraging data analytics and machine learning, Amazon is able to personalize the online shopping experience for each customer, recommend products based on their browsing history, and offer fast and convenient delivery options. This customer-centric approach has helped Amazon cement its position as the largest online retailer in the world, with a loyal customer base and strong brand reputation.

Case study 2: Starbucks

Starbucks is another company that has prioritized customer needs and expectations in its digital transformation efforts. By investing in its mobile app and loyalty program, Starbucks has made it easier for customers to order and pay for their favorite drinks, earn rewards, and receive personalized offers. This has not only improved the customer experience but also increased customer engagement and loyalty. As a result, Starbucks has seen significant growth in its digital sales and overall revenue.

Conclusion

Understanding and meeting customer needs and expectations are essential considerations for planning a successful customer-centric digital transformation. By putting the customer at the center of the transformation journey and leveraging data and insights, businesses can drive greater customer satisfaction, loyalty, and business success. Through the examples of Amazon and Starbucks, we can see the tangible benefits of taking a customer-centric approach to digital transformation. By learning from these companies and incorporating their strategies into their own efforts, organizations can position themselves for long-term success in the digital age.

SPECIAL BONUS: The very best change planners use a visual, collaborative approach to create their deliverables. A methodology and tools like those in Change Planning Toolkit™ can empower anyone to become great change planners themselves.

Image credit: misterinnovation.com

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COVID-19 Presents an Opportunity to Create an Innovation Culture

GUEST POST from Pete Foley

I left P&G about eight years ago, and one of my last jobs involved working on innovation culture.  It was a passion project, and the topic of one of my first blogs published outside of P&G.  It’s also something I keep coming back to, as I believe it is one of, if not the most important components of a successful innovation organization. But I’m writing this because I believe Covid19, together with recent socio-political dynamics has created a once in a lifetime window to effect cultural change in our organizations.  It’s a huge opportunity, but one that comes with commensurate risk.

Changing culture is hard.  A leadership team can often make a strategic change almost on a dime, but culture has much deeper roots, and so takes longer to change. Strategy is more about what we are doing, culture is more about how we do it.  It’s comprised of a multitude of little everyday things that ultimately much of our time.   It’s how we make decisions, take risks, act or procrastinate, how much we share, how much we listen. In other words it’s deeply linked to fundamental behavior and values, and is heavily influenced by habits and the unconscious decisions frameworks that Daniel Kahneman calls System 1 thinking.  As such, it cannot be changed by management decree.  It can be nudged by changing reward or organizational structure, something we tried every few years at P&G.  But ultimately changing culture means either changing people’s deeply rooted behaviors, or changing the people themselves.

That’s hard to do, and also inefficient, at least in the short-term.  If an innovation team is thinking about process, it’s not thinking about innovations. But Covid19 created a once in a lifetime opportunity.  I’d not wish the last 18 months on anyone, but like it or not, our cultures have been disrupted, and that gives us a semblance of a fresh start, and hence an opportunity for change.  Habits have already been broken, ‘givens’ challenged and new skills learned. And if the great resignation actually occurs, we can expect an elevated level of personnel movement both between and within companies to go along with broken habits and new skills.  A perfect storm for cultural change.  .

But how do we take advantage of this rare opportunity? Culture is a big, hairy topic, with a lot of moving parts, so one option is to be a little reductionist, and break it down into it’s component parts. My personal culture model is a hybrid derived from many sources, and comprises Capability, Space, Psychological Safety, Designed Serendipity and Motivation.  Let’s look at them in turn:

Capability– Innovation needs people with knowledge and experience.  But it also needs fresh perspective. Too much experience locks us into isolated pillars of expertise that make it hard embrace new technology.   But too little experience risks the merry-go-round of constantly reinventing the wheel.  We need to balance between the two.  But we can hit that balance far more effectively if we retain the right kind of experience, experts who are also cognitively agile, open to new experience, and so able to integrate fresh ideas with their hard earned knowledge.  The conundrum is that these experts are often the most likely to seek out new challenges, or to relish the risk of career changes. In other words, those most likely to participate in a ‘great resignation’.  This makes it imperative to proactively  identify, recruit or retain experts with high mental agility, or T-Shaped innovators who can bridge between different groups.

But it’s not enough to get the right mix at the organizational level, we need it to drill down into individual teams. Humans have a habit of self selecting groups that they feel comfortable working with, which can mean diversity within an organization translates into diversity between, rather than within teams. Curating teams to ensure each fully team reflects organizational diversity reduces factions, spreads knowledge, enables cross mentoring and thus creates a stable but not stagnant culture more quickly after a period of change.  It also grows the next generation of innovation leaders who have learnt bridging skills ‘on the job’, by working in cognitively diverse teams.

  1. Space –Innovators need time and autonomy. Obviously this needs to be within some reasonable constraints, as businesses today cannot afford ivory towers.. But truly disruptive ideas take time, and some failure along the road to success. Build too much stage gate control into innovation, enforce unrealistic timelines, or talk about productive failure without actually embracing it, and the result will be mediocrity and increasingly smaller innovations.  Everything becomes disruptive in name, but not reality.  The good news is that this is perhaps the biggest opportunity to come out of Covid19, as for many, remote working has increased both time and autonomy.  Of course, remote working comes with downsides, some of which I discuss below, and not everybody has more time at home. But overall we’ve been given a gift of more time and more autonomy.  It’s critical that we take full advantage of this, and don’t lose it, or over-manage it in the name of efficiency.

2. Psychological Safety.  Failure is now widely acknowledged as part of the innovation process. But in reality, but when the rubber hits the road, it’s still often considered as a negative. After all, we build a culture that values capability and expertise so that we can anticipate ‘obvious’ pitfalls, and so avoid failure.  But if we’ve sufficient capability, that makes failures more valuable, as the unexpected is the single biggest source of disruptive and breakthrough innovation.  Furthermore, the scientific method, when employed correctly, designs tests to challenge our assumptions, not confirm them.  We run tests to uncover unexpected issues before we go to market. So as we rebuild innovation culture, it is critical that the psychology safety needed to fail productively is not just preserved, but enhanced. It really is the key to big ideas. But at the same time, it’s also critical not to confuse it with ‘safe spaces’.  Psychological safety has nothing to do with avoiding ideas we are uncomfortable with.  Instead it’s about creating an environment where people can safely challenge their own and others’ ideas, share unpopular opinions and failures, and be treated with respect when they do so.  That is fundamental to the scientific method, and hence to an effective innovation culture.

3. Designed Serendipity.  While this is a reductionist analysis, it’s impossible to avoid how interdependent these components are.  Capability needs space to operate, while space helps to create psychological safety.  That in turn makes it easier to fail, and share unexpected results.  And our most disruptive ideas typically come from those results experts weren’t expecting. Assuming that most competitors have similar pools of expertise, surprising results are the only way to break a close innovation race.  These can come from failures, as discussed above.  But they can also come from outside, either from someone viewing  our results through a different lens, and so seeing something we miss because of confirmation bias, or from somebody sharing information that they wouldn’t realize is relevant to us.  While we cannot force this type of cross- disciplinary interaction to occur per se, we can design organizations to facilitate it.  We can create spaces where people mix and communicate informally.  Or run training sessions that bring together mixed teams. A coffee bar in a work place, or an excellent cafeteria that encourages people to stay on site and mix all have benefits that are hard to quantify, but can also do an enormous amount to trigger an innovative culture.  But much of this requires people to be physically present.  Remote working provides time and convenience benefits, and works well for some tasks.  But we need to prevent the pendulum from swinging too far.  Whether it’s the serendipity of unexpected discussions at the water cooler, or the subtle body language that encourages someone to share a counter intuitive idea, or a failure, some personal interactions work better when people are physically in the same place.  We can certainly learn from our Covid experience, and reduce non productive time in the office.   But subtleties such as body language and microexpressions get lost on Facetime, making tough discussions tougher, sharing ‘bad’ results harder. And without physical presence, we’ll lose much of the serendipity of insight and information sharing in common physical spaces.  We don’t have to go back to where we were, but getting the balance right will drive competitive advantage by optimizing sharing, serendipity, and recruitment and retention.

4. Motivation. I’ve saved what I think is the hardest topic until last. Intrinsic motivation is absolutely key to an innovative culture.  If people love what they are doing  they will go the extra mile.   Passion means problems stay top of mind, increasing the chances of serendipitous innovation, or ‘Eureka moments’.  Money is important if you don’t have enough, but it’s intrinsic motivation that drives disruptive innovation. That motivation largely comes from one or all of three places; fascination with a problem, deep commitment to a team or authentic alignment between project and individual purpose.  The first two are fairly self-evident.  But the last one has always been tricky, and has become more difficult in our post Covid, more polarized world. Firstly, it must be authentic. For example, motivating a team to get behind a sustainability project that turns out to be largely greenwashing, or that evolves from authentic to greenwashing under timing or economic pressure can quickly turn motivation into indifference, or worse.  And the line between greenwashing and real environmental initiatives is often more fuzzy than we like to admit.  There are inevitably trade offs as we try and balance the needs of a business with the need to improve an environmental footprint, and often what starts as a major benefit gets trimmed en route to market.  And it’s not one size fit’s all, as one persons authentic is another persons greenwashing.   Furthermore, environmental is probably the easiest of the ‘purpose motivators’ to manage.

For more contentious social justice areas, it’s increasingly likely that not everyone in a team will be aligned with a project.  Even if they put aside their personal views, intrinsic motivation will inevitably fall in this situation.  Conversely, tap into a teams passions too well, and we risk  the core brand or product becoming secondary to the ‘cause’.  But even bigger risks as we look outward to the consumer.  Even if we have an organization that shares common values, taking a position on a contentious social justice issue is quite likely to alienate a significant segment of consumers.  Yet we know from Ehrenburg-Bass research that broad appeal and availability usually generates more volume than loyalty, and so even initiatives that enjoy short-term bumps in volume from socio-political positions can suffer long-term damage.  The short-term loyalty they create is often more short-lived than any emotional disconnection from a brand from consumers who disagree.   There are also additional issues with cognitive fluency, as while some brands are a good fit with environmental or social justice positions, many are not.  Consumers only associate about 1-3 attributes with a brand, and there is a significant risk of with subtraction by addition if a brand starts focusing on communications that are not a fluent fit with core equity.

None of this means we shouldn’t strive to create greener products, and indeed for many categories a healthy environmental profile is rapidly becoming price of entry.  The picture with social justice is more complex and more polarized, but again, all companies should strive to do the right thing, and be good corporate citizens.  But it’s important to do so carefully, ensure that we’re not alienating consumers, that initiatives are a fit with equity, and are sufficiently differentiated at a time when environmental and social justice communication is pervasive.  And there is always the question of source validity, and whether your brand has the perceived authority to  take a position on an issue.  And if our goal is to improve intrinsic motivation and employee satisfaction, it’s also worth considering that internal cultural benefits can often be achieved more effectively via inwardly facing initiatives that don’t risk  alienating consumers.

In conclusion, Covid19 has created opportunity for significant change in innovation culture, and in some cases, that change is already irreversible.  But it is sill important to step back, ask ourselves how much we want to change, and what parts of our culture we may want to protect.  If you are reading this, you are probably an innovator, and so change is in your blood.  But do keep in mind that the grass is always greener.  Whether we are innovating products, services or organizations, the new often looks better simply because we don’t know the issues we haven’t yet discovered.

I sometimes think innovation is like a giant game of wack-a-mole, where we innovate to improve one area, only to inadvertently create a new unexpected one along the way.  Sometimes these are minor, and just a part of the innovation process, sometimes they are much bigger, as in Boeings 737 Max.  This does not mean we should stagnate, or miss a once in a generation opportunity.  But just as culture is usually slow to change, it’s also slow to fix if we get it wrong.  So before messing too much with the DNA of an organization, it’s worth at least considering if the upside is worth the inevitable disruption, both anticipated and unanticipated. We have a once in a lifetime opportunity – don’t miss it, but don’t throw the baby out with the bathwater either!

Image credit: Pixabay

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Leveraging Technology in Change Planning

Tools and Platforms for Success

Leveraging Technology in Change Planning

GUEST POST from Art Inteligencia

In today’s rapidly evolving business landscape, change is inevitable. Whether it is a shift in market demands, a new competitor entering the scene, or a global crisis such as the COVID-19 pandemic, organizations are constantly faced with the need to adapt. However, implementing change within an organization can be a complex and challenging process, requiring strategic planning, effective communication, and strong leadership.

One key factor that can greatly facilitate the change planning process is the use of technology. Technology has become an integral part of modern business operations, offering tools and platforms that can streamline processes, improve communication, and facilitate collaboration. In this article, we will explore how organizations can leverage technology to drive successful change initiatives, using two case studies to illustrate best practices.

Case Study 1: Company A

Company A is a global technology company that specializes in developing innovative software solutions for businesses. When the COVID-19 pandemic hit, Company A was faced with the challenge of transitioning its workforce to remote work virtually overnight. To ensure a smooth transition, Company A utilized a project management platform that allowed employees to collaborate on projects, track progress, and communicate in real-time.

By leveraging this technology, Company A was able to create a seamless remote work environment, ensuring that employees were able to stay connected and productive despite the challenges posed by the pandemic. Additionally, the platform allowed for centralized communication, enabling leadership to provide updates and guidance to employees in a timely manner.

Case Study 2: Company B

Company B is a manufacturing company that was looking to implement a new ERP system to streamline its operations and improve efficiency. However, the implementation of a new ERP system presented a significant change for employees, who were accustomed to using legacy systems.

To ensure a successful transition, Company B implemented a change management platform that allowed employees to access training materials, communicate with project leads, and provide feedback on the new system. The platform also served as a repository for resources and information, ensuring that employees had access to the support they needed throughout the transition process.

By leveraging technology in their change planning efforts, Company B was able to minimize resistance to change, increase employee engagement, and ensure a smooth implementation of the new ERP system.

Conclusion

Technology can be a powerful tool for organizations looking to drive successful change initiatives. By leveraging tools and platforms that facilitate communication, collaboration, and information sharing, organizations can streamline the change planning process and ensure a smooth transition for employees. The case studies presented in this article demonstrate the impact that technology can have on change management, highlighting the importance of incorporating technological solutions into change planning strategies. By embracing technology, organizations can navigate change with confidence and achieve long-term success in today’s rapidly evolving business environment.

Bottom line: 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: Unsplash

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Anticipating Future Customer Needs

Techniques for understanding customer expectations and designing products and services that align with evolving needs

Anticipating Future Customer Needs

GUEST POST from Chateau G Pato

In today’s fast-paced and ever-changing market landscape, businesses must constantly adapt to meet the evolving needs and expectations of their customers. Anticipating future customer needs is essential for ensuring long-term success and staying ahead of the competition. By understanding customer expectations and designing products and services that align with these expectations, businesses can create a loyal customer base and drive growth.

One of the key techniques for anticipating future customer needs is the use of data analytics. By analyzing customer data, businesses can gain valuable insights into customer behaviors, preferences, and trends. This data can help businesses identify emerging patterns and anticipate future needs before they become mainstream. For example, a retail company may analyze purchasing data to identify trends in consumer preferences and tailor their product offerings accordingly.

Another technique for understanding customer expectations is to engage with customers directly through surveys, focus groups, and feedback mechanisms. By soliciting input from customers, businesses can gain a deeper understanding of their needs and preferences. For example, a software company may conduct focus groups to gather feedback on new features and functionalities, allowing them to tailor their product development efforts to meet customer expectations.

Case Study 1: Amazon

Amazon is a prime example of a company that excels at anticipating future customer needs. Through their extensive use of data analytics, Amazon is able to track customer behavior and preferences in real-time. This allows them to recommend products to customers based on their browsing and purchasing history, creating personalized shopping experiences that align with customer expectations. Additionally, Amazon continuously innovates and introduces new services, such as Amazon Prime and Alexa, to meet evolving customer needs.

Case Study 2: Netflix

Netflix is another company that effectively anticipates future customer needs. Through data analytics, Netflix analyzes viewing patterns and preferences to recommend personalized content to users. By understanding what their customers like to watch, Netflix can tailor their content library to meet evolving preferences and expectations. Additionally, Netflix invests in producing original content, such as Stranger Things and The Crown, to cater to niche audiences and stay ahead of competitors.

Conclusion

Anticipating future customer needs is essential for businesses looking to stay competitive in today’s rapidly changing market. By utilizing techniques such as data analytics and engaging with customers directly, businesses can gain valuable insights into customer expectations and design products and services that align with evolving needs. Case studies like Amazon and Netflix showcase how businesses can successfully anticipate future customer needs and drive growth through customer-centric strategies. By prioritizing customer expectations, businesses can create a loyal customer base and thrive in an increasingly competitive market.

SPECIAL BONUS: The very best change planners use a visual, collaborative approach to create their deliverables. A methodology and tools like those in Change Planning Toolkit™ can empower anyone to become great change planners themselves.

Image credit: Pexels

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Change Management Needs to Change

Change Management Needs to Change

GUEST POST from Greg Satell

In 1983, McKinsey consultant Julien Phillips published a paper in the journal, Human Resource Management, that described an ‘adoption penalty’ for firms that didn’t adapt to changes in the marketplace quickly enough. His ideas became McKinsey’s first change management model that it sold to clients.

But consider that research shows in 1975, during the period Phillips studied, 83% of the average US corporation’s assets were tangible assets, such as plant, machinery and buildings, while by 2015, 84% of corporate assets were intangible, such as licenses, patents and research. Clearly, that changes how we need to approach transformation.

When your assets are tangible, change is about making strategic decisions, such as building factories, buying new equipment and so on. Yet when your assets are intangible, change is connected to people—what they believe, how they think and how they act. That’s a very different matter and we need to reexamine how we approach transformation and change.

The Persuasion Model Of Change

Phillips’ point of reference for his paper on organizational change was a comparison of two companies, NCR and Burroughs, and how they adapted to changes in their industry between 1960 and 1975. Phillips was able to show that during that time, NCR paid a high price for its inability to adapt to change while it’s competitor, Burroughs prospered.

He then used that example to outline a general four-part model for change:

  • Creating a sense of concern
  • Developing a specific commitment to change
  • Pushing for major change
  • Reinforcing and consolidating the new course

Phillips’ work kicked off a number of similar approaches, the most famous of which is probably Kotter’s 8-step model. Yet despite the variations, the all follow a similar pattern. First you need to create a sense of urgency, then you devise a vision for change, communicate the need for it effectively and convince others to go along.

The fundamental assumption of these models, is that if people understand the change that you seek, they will happily go along. Yet my research indicates exactly the opposite. In fact, it turns out that people don’t like change and will often work actively to undermine it. Merely trying to be more persuasive is unlikely get you very far.

This is even more true when the target of the change is people themselves than when the change involves some sort of strategic asset. That’s probably why more recent research from McKinsey has found that only 26% of organizational transformations succeed.

Shifting From Hierarchies To Networks

Clearly, the types of assets that make up an enterprise aren’t the only thing that has changed over the past half-century. The structure of our organizations has also shifted considerably. The firms of Phillips’ and Kotter’s era were vlargely hierarchical. Strategic decisions were made at the top and carried out by others below.

Yet there is significant evidence that suggests that networks outperform hierarchies. For example, in Regional Advantage AnnaLee Saxenian explains that Boston-based technology firms, such as DEC and Data General, were vertically integrated and bound employees through non-compete contracts. Their Silicon Valley competitors such as Hewlett Packard and Sun Microsystems, on the other hand, embraced open technologies, built alliances and allowed their people to job hop.

The Boston-based companies, which dominated the microcomputer industry, were considered to be very well managed, highly efficient and innovative firms. However, when technology shifted away from microcomputers, their highly stable, vertical-integrated structure was completely cut off from the knowledge they would need to compete. The highly connected Silicon Valley firms, on the other hand, thrived.

Studies have found similar patterns in the German auto industry, among currency traders and even in Broadway plays. Wherever we see significant change today, it tends to happen side-to-side in networks rather than top-down in hierarchies.

Flipping The Model

When Barry Libenson first arrived at Experian as Global CIO in 2015, he knew that the job would be a challenge. As one of the world’s largest data companies, with leading positions in the credit, automotive and healthcare markets, the CIO’s role is especially crucial for driving the business. He was also new to the industry and needed to build a learning curve quickly.

So he devoted his first few months at the firm to looking around, talking to people and taking the measure of the place. “I especially wanted to see what our customers had on their roadmap for the next 12-24 months,” he told me and everywhere he went he heard the same thing. They wanted access to real-time data.

As an experienced CIO, Libenson knew a cloud computing architecture could solve that problem, but concerns that would need to be addressed. First, many insiders had concerns that moving from batched processed credit reports to real-time access would undermine Experian’s business model.. There were concerns about cybersecurity. The move would also necessitate a shift to agile product management, which would be controversial.

As CIO, Libenson had a lot of clout and could have, as traditional change management models suggest, created a “sense of urgency” among his fellow senior executives and then gotten a commitment to the change he sought. After the decision had been made, they then would have been able to design a communication campaign to persuade 16,000 employees that the change was a good one. The evidence suggests that effort would have failed.

Instead, he flipped the model and began working with a small team that was already enthusiastic about the move. He created an “API Center of Excellence” to help willing project managers to learn agile development and launch cloud-enabled products. After about a year, the program had gained significant traction and after three years the transformation to the cloud was complete.

Becoming The Change That You Want To See

The practice of change management got its start because businesses needed to adapt. The shift that Burroughs made to electronics was no small thing. Investments needed to be made in equipment, technology, training, marketing and so on. That required a multi-year commitment. Its competitor, NCR, was unable or unwilling to change and paid a dear price for it.

Yet change today looks much more like Experian’s shift to the cloud than it does Burroughs’ move into electronics. It’s hard, if not impossible, to persuade a product manager to make a shift if she’s convinced it will kill her business model, just it’s hard to get a project manager to adopt agile methodologies if she feels she’s been successful with more traditional methods. .

Libenson succeeded at Experian not because he was more persuasive, but because he had a better plan. Instead of trying to convince everyone at once, he focused his efforts on empowering those that were already enthusiastic. As their efforts became successful, others joined them and the program gathered steam. Those that couldn’t keep up got left behind.

The truth is that today we can’t transform organizations unless we transform the people in them and that’s why change management has got to change. It is no longer enough to simply communicate decisions made at the top. Rather, we need to put people at the center and empower them to succeed.

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

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Augmented Reality and Healthcare

Improving Patient Experiences

Augmented Reality and Healthcare: Improving Patient Experiences

GUEST POST from Art Inteligencia

In recent years, the use of augmented reality (AR) technology has been steadily gaining momentum across various industries. One field where AR has shown significant potential is healthcare, particularly in improving patient experiences. By overlaying digital information onto the physical world, AR has the power to revolutionize the way healthcare providers deliver care and interact with patients.

Case Study 1: Surgical Navigation

One of the most promising applications of AR technology in healthcare is surgical navigation. Traditional surgical procedures often require doctors to rely on 2D images to guide their actions, which can be imprecise and time-consuming. By using AR, surgeons can now visualize 3D representations of a patient’s anatomy in real-time during surgery, allowing for more accurate procedures and shorter recovery times.

For example, the Cleveland Clinic has successfully implemented AR technology in their neurosurgery department to assist with complex brain surgeries. By using AR headsets, surgeons are able to see virtual 3D models of a patient’s brain overlaid onto their field of view, allowing for more precise navigation and minimally invasive procedures. This has led to improved patient outcomes, reduced complications, and shorter hospital stays.

Case Study 2: Pain Management

Another area where AR is making a significant impact in healthcare is in pain management. Chronic pain is a widespread issue that affects millions of people worldwide, often leading to decreased quality of life and reliance on medications. AR technology offers a non-invasive and drug-free alternative for managing pain through distraction therapy.

For instance, Cedars-Sinai Medical Center in Los Angeles has implemented AR technology to help pediatric patients cope with painful procedures such as injections or blood draws. By immersing patients in interactive virtual environments through AR headsets, healthcare providers are able to distract patients from the pain and anxiety associated with medical procedures. This has not only reduced the need for sedation and pain medication but also improved patient satisfaction and compliance with treatments.

Conclusion

Augmented reality technology has the potential to transform the healthcare industry by enhancing patient experiences and outcomes. From surgical navigation to pain management, AR offers innovative solutions to some of the most pressing challenges in healthcare today. As the technology continues to evolve, we can expect to see even more groundbreaking applications that will revolutionize the way we deliver care and improve the lives of patients around the world.

Bottom line: 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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