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The Future Workplace by Mike Walsh

By Mike Walsh | Jul 12, 2021 | Comments Off

"The pandemic has accelerated the forces of digital transformation, making it more critical than ever to embrace new ways of working and a data-driven approach to decision making."

Should we stay, or should we go? The post-pandemic return to work is fast becoming a controversial and complex issue for leaders to navigate. Everyone has an opinion on the issue. Some are desperate to escape months of Zoom fatigue, while others see little point in commuting for an hour to simply sit in front of another screen. If that seems like a tough choice, it is because it is a false one. The real issue is not remote vs. office work - it is how do we reinvent the workplace for a new era of AI-powered competition?

The real lesson of the pandemic was not that we could run meetings remotely, but rather that the key to our survival was embracing the hard science of digital transformation. When everything turned upside down in early 2020, demand spiked, supply chains splintered, and business processes shattered. The organizations that made it through the crisis did so because they rapidly deployed AI, algorithms, and automation to handle the harsh new operating environment. That worked then, but now, something more is required.

We face a new set of challenges. Implementing automation alone will not be enough to deliver the kind of creative solutions required to reshape industries. Nor will letting people continue working from home be enough to reboot conservative and traditional corporate cultures.

We are about to discover that remote work was just the beginning of a much bigger revolution that is set to reshape the future of all organizations. Rapid shifts in technology, customer needs, and competitor dynamics are a prescription for a more agile, adaptive, and resilient type of firm capable of integrating not only cutting-edge technologies but also embracing a new generation of talent as well.

The pandemic has accelerated the forces of digital transformation, making it more critical than ever to embrace new ways of working and a data-driven approach to decision making. Every workplace in the future will be powered by data. Whether it be how we engage and evaluate our talent, how we automate our processes, or even how we make decisions as leaders - the ability to effectively leverage AI, automation, and algorithms will be at the heart of any 21st-century business.

While many fear imminent change, a bigger opportunity awaits. The question is not whether AI will eliminate jobs, but rather: how will it change them? The leaders of the future need to embrace an entirely new set of skills, capabilities, and mindsets in order to be successful.
 

 

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Three Things Leaders Must Know about Automation by Mike Walsh

By Mike Walsh | Jun 14, 2021 | Comments Off

The real question is: how do we make sure the future of work fits the world we want to live in?

Futurist and best-selling author of The Algorithmic Leader, Mike Walsh explains that there are three things leaders need to know about automation:

1. Automation redefines the capabilities of your workforce
Rather than replacing people, automation offers the chance to reimagine work roles. When a lawyer uses AI to read trust documents and contracts, or a financial advisor leverages an algorithm to create a personalized financial plan - they haven't made themselves obsolete. Quite the contrary. They have merely shifted the boundary of what human-shaped work should be. Enhancing capabilities through better tools rather than squeezing more effort out of your workforce - is the most sustainable way of achieving productivity gains.

2. There is a difference between complexity and ambiguity
Organizations are decision-making machines, but not all decisions are born equal. Some decisions are complex but inherently suitable for automation because they follow well-defined rules. Other decisions may appear simple but involve a high degree of ambiguity that requires human judgment. In this video, I discuss the difference between 1st, 2nd, and 3rd order decisions - and the role that AI and automation can play in each.

3. Automation is the start, not the endpoint of your journey
Deterministic automation is a powerful tool in getting your digital transformation started. The exercise of mapping your processes, linking your enterprise systems, and unlocking more insights about your operations will not only increase your internal clock speed, it will provide contextual data for more sophisticated machine learning tools to optimize and enhance your business. By all means, go for the quick wins offered by automation, but don't stop short of the real prize that comes with reinventing yourself as an AI-powered organization.

READ FULL ARTICLE 

 

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10 New Rules For A New World by Mike Walsh

By Mike Walsh | May 04, 2021 | Comments Off

The Real Question is This: What is Possible in an Age of AI that was Not Possible Before?

The biggest danger in any crisis is anticipating a return to normal. As vaccine programs roll out worldwide, organizations and governments are preparing for economic recovery, a return to offices and corporate travel, and a resumption of business as usual.

The COVID-19 crisis, however, was not a pendulum now on the return swing to normal; it was a portal from the world we knew, to a radical new future that we are yet to fully understand.

While for many of us working from home has been a new and unexpected challenge - that is just the start of a much bigger transformation set to reshape the nature of business itself. In order to survive, every organization will have to virtualize.

Whether it be serving customers through digital channels or leveraging AI, algorithms and automation to ensure business continuity - we are likely to experience in the next twelve months, a decade's worth of change. Not every business will make it, but those that do will never be the same again. And for leaders, now more than ever, is a time to upgrade their capabilities, embrace new technologies, and reimagine what they do.

Becoming future-proof is more than just about getting through the current crisis - it is about being ready for the new world that awaits us on the other side.

Rule #1: Digital Disruption is Now Just Digital Delivery

We are all disruptors now. Being digital is nothing special, it is just the price of staying in business. The real question is this: what is possible in an age of AI that was not possible before?

Rule #2: There is No Remote Work, Only Work

Remote work is just the beginning of a much bigger transformation that is set to transform the nature of work itself. The true future of work will be shaped by five forces: mobility, autonomy, memory, objectivity and velocity.

Rule #3: Robots are Not Coming for Our Jobs, They are Here to Change Them

AI will not destroy jobs, but it will change them. A new world needs new kinds of capabilities - and that means that we need to evolve and upgrade, just as our machines do.

Rule #4: Experiences Matter more than Transactions

What did we learn about the future of retail, when the world’s stores had to close? Whether it be an app or a showroom, engaging experiential design is what really counts.

Rule #5: The Best Way to Lead is to be Data-led

Being a leader in the Algorithmic Age requires a very different approach. We all like to claim to be ‘data-driven’, but in truth, what we really need to be is ‘data-led’.

Rule #6: There is no New Normal

What if the new normal, is not normal at all? Thanks to COVID-19, we are now living in a radically different reality - robotics, VR, automation, protests, surveillance, fake news. The first step to survival is acknowledging that there is no going back from this.

Rule #7: XR is the New Reality

XR or virtual reality, augmented reality and mixed reality are all on the brink of becoming mainstream technologies that will transform how we live and work. Now is the time to reimagine the way we interact with our customers and create radically new experiences not possible before.

Rule #8: Social distancing is Here to Stay

Social distancing is more than a pandemic response, it is a preview of an AI-powered world in which we deliver products and services using automation and machines with minimal or no human contact.

Rule #9: The Future of AI is Personal

We are fast accelerating to a future in which we will interact with applications with our voices rather than screens, but before we get there, we need a new, more personal approach to AI - virtual assistants that are a digital extension of ourselves.

Rule #10: The Future Favors the Bold

This is no time to settle for survival as a second prize to success. After the chaos of 2020, we need bigger dreams than just recovery. What matters now is reinvention, nothing less.

 

 

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Mike Walsh - Technology and Culture

By Mike Walsh | Sep 30, 2020 | Comments Off

 

COVID-19 forced students and educators into the unknown world of virtual education. Futurist and keynote speaker Mike Walsh explains that there is no "remote learning." It's simply "learning."


Watch Mike ponder some of the fascinating things the current crisis has forced educators to recognize and see the cracks in how society thinks about remote learning.

One of the fascinating things about the current crisis is how much it forced us to realize the cracks in the way we thought about remote work and remote learning. And, you know, for some people working from home was actually… Well, it was working from hell. And the same thing applied to many parents who now had to deal with the realities of trying to deal with a blended learning model, technology and their kids being home permanently.

As we move into the future, though, it's increasingly clear that the video technology behind this, is not the hard part. I mean, zoom is nothing new. I mean, what you see here is that NSA video phone from 1960. I actually found prototypes of video phones going all the way back to AT&T in 1930. So if it took 90 years for us to get our act together with using live video technology, it probably wasn't the technology that was holding us back.

What was holding us back was essentially, culture. You see, technology can change the hardware of your school, or your educational facility. But true transformation, requires you to rethink culture, because culture is your operating system. When I say culture, I mean, the way your teachers interact with students. The way they interact with each other and faculty. The way that principals interact with you as leaders. In the end, it's the system of interactions that really drive success or failure of your transformation.

 

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Cyberpunk 2020: There is no new normal

By Mike Walsh | Jul 14, 2020 | Comments Off

There's no denying it - we are in a brand new world. COVID-19 has brought about massive change at a pace never seen before.

How are you going to survive Cyperpunk 2020?

Mike Walsh offers 3 solutions in this video below.

Mike offers a weekly prescription for your organization’s reinvention in his TO.MOR.ROW newsletter - subscribe here.

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Leadership in a time of crisis

By Mike Walsh | Apr 15, 2020 | Comments Off

What impact will the COVID-19 have on business and our economy, and what will this mean for leaders? Futurist Mike Walsh predicts that the pandemic will hasten the arrival of a radical new future of work, and a decade's worth of change in just 12 months. While for many of us working from home has already been a new and unexpected challenge, Mike believes that this is just the start of a much bigger transformation set to reshape the nature of business itself. Watch his video below to learn more - and subscribe to his new weekly video series, New Rules For A New World.

BRAND NEW Virtual Keynote from Mike Walsh: The Future-Proof Organization

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Retrain, re-equip, and re-energize

By Mike Walsh | Feb 26, 2020 | Comments Off

An excerpt from The Algorithmic Leader

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Automation might not entirely eliminate traditional jobs from your company, but it will absolutely change the nature of those jobs and the skills required to do them.

Imagine that you have a job as a retail merchandiser at Coca- Cola, and that you are responsible for visiting stores and kiosks, advising merchants on how to arrange their products, and checking compliance with the brand guidelines. Now, using a platform like Einstein by Salesforce, a customer can just take a picture of their store’s fridge and the algorithm will tell them what to do and where to place their product. What will the purpose of the retail merchandiser be now that their job has been changed by AI? Which of their skills are still relevant, and what might a career migration path look like?

The rise of mass automation brings with it unavoidable, but not unaddressable, political and social consequences. We have been here before. Economist David Autor argues that near the end of the nineteenth century, agricultural states in America faced the prospect of mass unemployment as more automation was introduced into the farming industry. Rather than waiting to see what might happen, those states drove the high school movement, which required everyone to stay in school until the age of sixteen and became the basis for the K–12 education system that is still in place today.

That education system, however, may not be up to the task that we now face. Andrew Ng, also a pioneer in online education and co-founder of Coursera, believes that our challenge is to find a way to teach people to do non-routine, non-repetitive work. To date, our education system has not been good at doing that either at scale or fast enough to keep pace with rapid industry change.

That leaves a lot of the responsibility for education in the hands of employers. Some have already stepped up to the challenge. United Technologies, for example, pays employees’ tuition bills up to $12,000 a year. Facebook offers free AI classes for all their employees, whether or not they work in IT, while Microsoft’s performance review system includes an appraisal of how employees have learned from others and how they have applied that knowledge. However, training is not enough, unless it helps employees migrate to a new way of working and thinking. A good example of a scaled-up migration initiative is AT&T’s Workforce Reskilling and Pivot Program. AT&T is one of the world’s largest employers. The average tenure at AT&T is twelve years, twenty-two if you don’t count the people working in call centers. Internal research com- pleted in 2013 found that 100,000 of AT&T’s 240,000 workers were in roles that the company probably wouldn’t need in a decade. Worse, when the company’s leadership began to analyze the kinds of roles that they would need, they realized there were serious skill gaps. The company would need a lot more coding skills, for example, and more leaders who could make smart decisions based on data and analytics.

To address this, the company kicked off a major reorganization. They streamlined the thousands of job titles that existed at AT&T into fewer and broader categories that clustered similar skills. This simpler classification allowed employees to start planning a more diverse career path through the company and to focus on the new skills they would need.

As part of this overhaul, AT&T created an online system called Career Intelligence that allowed their employees to identify alternative positions, see what skills were required, find out how many positions are available, investigate whether the segment was projected to grow or shrink, and explore what they might earn. However, there was a catch: while the training was free and some of the learning modules could be done at work, employees would have to do much of the work on their own time.

The challenge for companies building retraining programs is that AI is evolving so rapidly, it will be hard to pin down the skills and capabilities that people will need. Even worse than not training an employee for a future job is training them for a job that no longer exists by the time they are ready. Workers will need to constantly upgrade themselves as machines evolve. Algorithmic leaders will have a responsibility, and an incentive, to ensure that both they and the people around them are able to stay just a little further ahead on the curve of the AI revolution in order to remain relevant and valuable.

While lifelong learning is a standard cliché of large organizations, it takes on an entirely new meaning in an age of machine intelligence.

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Don't fear the rise of AI

By Mike Walsh | Feb 26, 2020 | Comments Off
We should not fear the rise of AI

Leverage your data and technology

In the industrial revolution, when they first brought automation to the cotton industry, the weavers got upset. They thought, this is our livelihoods here. But as it turns out, they didn't lose their jobs, their jobs changed. Rather than physical labor, their work now became keeping the machines running. As long as they did that, their productivity went up. In fact, 50 fold which meant the cost of cloth began to fall and people started buying more cloth. The total number of people employed in the cotton industry in America, between 1830 and 1900 didn't go down. It quadrupled.

Something similar as you may know, happened with ATMs. Everyone thought the ATM is going to destroy the job of the bank teller. Right? Yes, you didn't need as many tellers to open up a branch anymore, but this also meant it became cheaper to open up branches in many different formats. The job of the teller has changed. You need people who've got social skills, who can empathize, who can market and sell other products who can build relationships. 

That's really the question we now need to face. It's not will technology destroy jobs. The question is, how do jobs need to change and in particular, how does our jobs as leaders of the community need to change? I believe we need to become algorithmic leaders. What I mean by that is that we need to become leaders for an algorithmic age. We need to develop a deep understanding of human complexity. This is how to empathize.

What is a good experience for our members or customers, how do we motivate people on our team? These are very human qualities that machines will never replace. There's not enough. We also need to take on some of the qualities of machines too. So we need to develop a flair for what I call computational thinking. Don't worry, we don't have to learn how to program. What this means is in the future, we need to approach making decisions and solving problems in a structured way that allows us to leverage data and technology to augment our capabilities. So something to be frightened of. This is how we're going to give ourselves cognitive superpowers.

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What algorithmic leaders can learn from the United customer crisis

By Mike Walsh | Nov 13, 2019 | Comments Off

 

What can we learn from the famous United incident with David Dow? Mike Walsh clarifies why we need ethics in our digital AI world .

 

 

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Netflix's Algorithmic Leadership

By Mike Walsh | Aug 20, 2019 | Comments Off

 

As a futurist, I’m often asked what it takes to takes for a large, traditional organization to embrace AI or make digital transformation work. Algorithmic-leader

If only the challenge was just technology! Disruptive technology changes the hardware of your business; to truly become a successful 21st organization you first have to accept that culture is your operating system.

Take Netflix as an example. I have often wondered how an old-school media mogul like Rupert Murdoch, John Malone, or Ted Turner might have run that business. What made the CEO of Netflix, Reed Hastings, so effective? How was he able to achieve such rapid global growth at Netflix while navigating difficult transitions, such as when the company switched from sending physical DVDs in the mail to embracing broadband streaming? Is Netflix successful because it runs on algorithms, or because it is run by algorithmic leaders?

 

I had an interesting insight into that question when I met Andy Harries, the CEO and co-founder of Left Bank Pictures. Harries is one of the world’s top drama creators, including Cold Feet, Prime Suspect, Wallander, Outlander, and The Queen, which saw Helen Mirren win, among other awards, an Oscar for Best Performance by an Actress in a Leading Role.

Hear my take on it in this video below.

 

 

The Algorithmic Leader Behind Netflix’s Insights

Harries wanted to pitch a TV show about the British royal family, based on themes explored in The Queen. He met with all the major US TV networks, who liked the idea but, after lots of consideration and debate, couldn’t commit to moving forward. Finally, Harries decided to meet with Reed Hastings and Netflix’s chief content officer, Ted Sarandos.

It was the strangest meeting, Harries explained, as he handed me a cup of a coffee at his office in London. As soon as he walked into the conference room with Hastings and Sarandos, and before he had a chance to pitch the show, they told him that they were ready to move ahead. And not just with a pilot, but with a full season.

Unlike the other networks, the team at Netflix had already analyzed their audience data and had used algorithms to predict the show’s likely performance. They knew their audience and precisely the kinds of shows that would work. Furthermore, with an upcoming launch in the UK market, they believed that the proposed show would be a hit. And they were right. The Crown’s third season is now in production, and it has twice been nominated for an Emmy for Outstanding Drama Series.

Algorithmic leaders reveal themselves in the way they make decisions and solve problems. How Reed Hastings and his team think about content, its relationship to their audience and their platform, and even how it should be presented and released is radically different from the way traditional leaders in media companies act and behave.

When you are capable of knowing precisely what any of your millions of global customers are doing or desiring at any point in time, how can you not see the world differently? How can you not seek to leverage machine learning, algorithms, and automation to fulfill those needs in a highly personalized way?

How Algorithmic Leaders Are Made

Of course, leaders like Hastings didn’t always have that kind of perspective. Most of us who are currently in leadership positions started out as analogue leaders. We need to make a conscious decision to adapt and evolve and to recognize that the availability of data and algorithms should change our viewpoint.

Being an algorithmic leader means more than just being able to share a few rehearsed anecdotes about artificial intelligence and big data. It means learning to tamp down your own ego, willingly tearing down the corporate structures that support your status, letting go of the idea that you need to make all the decisions, letting your teams self-organize and self-manage, not worrying about being seen to be right all the time, being open to more open forms of partnerships and work arrangements, and embracing a new, uncertain future.

Mike Walsh is the author of ‘The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You’,from which this article is excerpted. Walsh is the CEO of Tomorrow, a global consultancy on designing companies for the 21st century.

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