The Game of Why’s?


Untitled design

Every great leader I’ve ever spoken with or read about, when looking at the way their company works, or confronting a business challenge, does the same thing: They ask “Why?” at least three times to really find an answer. Try it.

Using the the Rule of Three 

Playing The Game of Why’s is simple. Deceptively simple. On the surface it seems like “What’s the big deal?” If you honestly play it, it becomes a very BIG deal. For every answer you have to whatever statement you’re making, simply ask “Why?” and do it again and again, three times.

WHY Number 1 will feel right, and skipping right past it will drive you crazy since we love to jump to conclusions.

WHY Number 2 will usually annoy you since it’s further away from the answer you initially wanted, and often seems counterintuitive. Keep going. You’re almost there …

WHY Number 3 will always amaze you since you’re finally getting to some really interesting place you never imagined.

The Science Behind the Game

The Rule of Three Why’s is valuable because of what we learned from the neurosciences. They discovered that the past and the future are in the exact same region of the brain. Whether we are remembering the past,  or envisioning the future,  we use the same part of our brain.

The current idea is that we use past experiences to scaffold the future; we base the future on what we experienced from the past. That makes sense since we need to have a sense of security as we go through our day so we can safely (and somewhat mindlessly) get from point A to B, not fear death when eating a Big Mac, look forward to being warmly greeted upon returning home, and so on.

We need predictability which is why change is so hard for us – we are simply not wired for it. Once we get our safe and sane existence under control, chaos is not something to which we desire. Occasionally, we sometimes long for something new, different, or novel. But for the most part we like to measure out our lives in coffee spoons.

This means that the brain apparently predicts the course of future events by imagining them taking place much like similar past ones.

The Pace and Complexity of Change

There’s something inherently problematic in thinking this way in today’s world.

At a 2017 Learning Conference, a panel of CLOs from four major corporations were asked the following question “What is keeping you up at night?” All four had a similar answer: “The pace and complexity of change.”

Change has become so common and ubiquitous that we need to start thinking in new ways all the time. That means that we cannot default to the brain’s habit of using the past to predict and determine the future. We need to constantly invoke our imagination and be continuous learners.

To do that, we need to realize three things:

  1. The past and the future are exactly the same. They are both an illusion created in the same part of our mind. Makes sense to collocate the past and future since it’s an economical, energy efficient way to use neurons and synapses.
  2. Change is difficult because there is a failure of the imagination. Magical thinking is defined as imagining if I do the same thing tomorrow that did not work today, it will magically happen. Magical thinking is a good way to define the way we usually use our brains and for the most part it’s an okay system when what we’re doing is working. The dilemma in today’s world is that we need to change a few old ideas. For instance “Knowledge is power” needs to become “Sharing knowledge is power” and “If it ain’t broke, don’t fix it” needs to be flipped to be “If it ain’t broke, break it and make a better one.” Sleeping dogs are also in trouble …
  3. The past is not a great predictor of the future. If you ever bought a mutual fund the marketing materials always needs to legally state “Past performance is not an indicator of future outcomes.” I think that needs to become a mantra for everything we do. That’s not to say that sometimes past performance does not have the same outcome in the future. Even dice rolled twice will come up with the same number.

We simply need to be conscious of the past we imagine. stop thinking of it as real when it is really our imagination at work, and let go of it. Then we can build the future on a new vision of something never before imagined.

That act of the mind – letting go of the past and imagining a new and different future –  is at the heart of all invention, exploration, creativity, disruption, innovation, and revolution. And as I said at the beginning of this post, one good way to get there is to play The Game of Why’s and use The Rule of Three.

My new book, “Minds at Work: Managing for Success in the Knowledge Economy”, is available in print and ebook versions on Amazon and all the other book seller’s websites.

 

 

Exciting News From Me


FYI – Just heard that the book is starting to ship!

On December 1st my book, Minds at Work, co-authored with my friend Stephen J. Gill, will launch. The book is being published by ATD Press and there will be an exciting ATD webinar – MANAGEMENT & LEARNING WILL CHANGE FOREVER (AND YOU NEED TO KNOW HOW AND WHY)  – https://lnkd.in/gJHEXeN. 

Thanks for reading KnowledgeStar and I hope to see many of you there!

book and heasdshot

Imagining the Future of Work


We have been talking about the rapid inevitable change from labor-intensive managing hands type of work, to the mind-intensive managing minds work most of us perform. We too often imagine it happening in offices or manufacturing environments. Truth is it’s happening in places we would never imagine, from pizza parlors to coal mines to … take a look.

Originally produced by Quartz Media

Learning Culture & Human Capital: The Reality, the Myth and the Vision


new-paradigm-ahead (2)

Sally Ann Moore is the Director General iLearning Forum at Closer Still Media. iLearning Forum is the most important learning meeting in Europe. Sally Ann wrote this as part of her preparation for the conference that I am honored to be speaking at in Paris on 22nd & 23rd January, 2018 at the iLearning Technologies France.

While preparing the Learning technologies France 2018 conference programme, I have been doing research and reading, and in particular looking at L&D trends, Talent Management and Human capital management. I unearthed a real shock and a paradox about the value of people to organizations.

Business Leaders don’t really Value People

In November 2016 The Korn Ferry Institute published their grim findings of a global study:  In August and September, 2016, Korn Ferry interviewed 800 business leaders in multimillion-dollar global organizations on their views on the value of people in the future of work. These leaders were in the United Kingdom, China, the United States, Brazil, France, Australia, India, and South Africa.

  • 63% of the CEOs said that in 5 years, technology will be the firm’s greatest source of competitive advantage.
  • 67% said that technology will create greater value in the future than people will. (and 64% believed people are a cost, not a driver of value)
  • 44% said the prevalence of robotics, automation and artificial intelligence (AI) will make people “largely irrelevant” in the future of work.

Worse still, the study found that when asked to rank what their organization’s top five assets will be 5 years from now, the company’s human resources  did not make the list. The top five assets were:

  1. Technology (product, customer channels);
  2. R&D / Innovation;
  3. Product / Service;
  4. Brand; and
  5. Real Estate (offices, factories, land).

So much for Human Capital Management and Learning Culture! I can even affirm that some of the companies in the survey also like to say people are their greatest asset. Ha! (They just don’t tell shareholders that – 40% of respondents in the Korn Ferry survey said they have experienced shareholder pressure to direct investment toward tangible assets like technology). This known as a “tangibility bias”.

As someone deeply involved in Learning and people development, I had to follow my strong belief that it is people that make THE difference, its people that add value and people are the best investment we can make. So I dug deeper. Eureka!

But the Tangibility biased are wrong!

In December 2016, in an economic analysis also commissioned by Korn Ferry, they report that human capital represents to the global economy a potential value of $1,215 trillion – more than DOUBLE the value of tangible assets such as technology and real estate (valued at $521 trillion today).

So, while large organizations put technology in the spotlight in the future of work, it is, in fact, human capital that holds the greatest value for organizations now and in future.

Human capital is also the greatest value creator available to organizations: For every $1 invested in human capital, $11.39 is added to GDP, (the Korn Ferry economic analysis finds). The CEO’s should note that the return on human capital—value versus cost—is the by far the best investment over time.

The problem is “Leaders may be facing what experts call a tangibility bias,” said Jean-Marc Laouchez, at Korn Ferry. “Facing uncertainty, they are putting priority in their thinking, planning and execution on the tangible – what they can see, touch and measure, such as technology investments. Putting an exact value on people is much more difficult, even though people directly influence the value of technology, innovation and products.”

How can we, the L&D specialists address this issue?

We are faced with a constant threat of budget cuts and lukewarm commitment from the executive.  I have always said that if you can’t measure it, you can’t manage it. Also what you measure is what you get…..

What are you measuring? My casual research suggests that most training managers measure learner satisfaction with their training, and there are plenty of tools for measuring knowledge and skills attainment. Sadly this doesn’t lead us to a tangible ROI. We can only measure that if we measure outcomes of the L&D investment. That is to say the change in work performed and the increased value of that work.  In this respect, I am glad to say that we are now making big strides implementing the Kirkpatrick model over here and addressing the 70:20:10 rule in our L&D projects. (More on this in my next article)

Managing Minds, not Hands

Additionally I came across some new thinking published this year by David Grebow and Stephen J. Gill in the USA. They have been researching for a book to be published early 2018 by the ATD press, entitled:  “Minds at Work: Managing for Success in the Knowledge Economy”

They began the research by looking for examples of companies that said they were learning cultures, where learning was continuous and supported in every aspect of organizational life. They never found one. They found some examples of learning cultures within companies, in various departments and units, but never consistently across the whole enterprise. They eventually realized why:  A company can tell the world it has a learning culture, provide lots of learning opportunities, and supply eLearning for everyone. But if management support for learning is not apparent and not constantly on display by managers every day, the original culture that supported and rewarded “not learning” will dominate over any attempt to be a learning culture.

They realized that a culture focused on learning needs leaders and managers focused on learning. So they looked at the critical relationship between managers and learning. Managers are expected to direct people’s daily work and performance. They are not usually expected to develop employees. In the research the authors (Grebow and Gill) identify two basic categories of business organization:

  • 19th style Century “Managing hands” older companies, an endangered species
  • 21st century knowledge economy, new companies “Managing minds”

The business results of the latter group are far more spectacular than the former. The authors go on to look at several case studies, in order to identify best practice of managing minds. David Grebow will present their results (and the book) at Learning Technologies France, international conference stream,  on 22nd & 23rd January 2018.

Minds at Work will be published this December 2017 by ATD Press and is available now for preorder on Amazon.

Coming Soon to a Workplace Near You


In my most recent book Minds at Work, co-authored with Stephen J. Gill, we imagined a new way of learning anytime and anyplace we called Interactive Performance Support:

“The most up-to-date version is what we call Interactive Performance Support (IPS). Here is an example of how an IPS program could be employed in a manufacturing environment.

You’re walking over to your industrial-grade, high-precision CNC lathe, and your cellphone buzzes to get your attention. The lathe has been equipped with a near-field communication beacon, which sent you a text: “The lathe needs a compliance check today. Here is the checklist. Please complete the checklist and send it back to Susan before noon.” Susan is back at corporate in the compliance department. As you approach the machine, the checklist pops up on your smartphone waiting to be completed.

At the fourth item on the list, you’re not sure you remember what exactly needs to be done—you have fallen off the Forgetting Curve.

So you go to the lathe’s instructions and operations page on your phone and watch a short video—taken from your push training class—on how to make sure the vector control spindle drive is correctly calibrated. You watch the video as it plays on your smartphone, pausing at each step, and follow the instructions. The exact procedure must be done right, and so you want to make sure you understand how to do it correctly. You then use your phone to locate another employee who has been tagged as an expert on doing this job. She answers your call and explains exactly what you need to watch out for when you do the calibration, and stays on the phone until you are finished with that part of the process.

Once the calibration is done, you snap a photo, finish checking the boxes on the list, and send the photo and the completed list back to Susan.

mach

An IPS program can:

  • Reduce downtime
  • Increase time to performance
  • Increase return on investment for machine manufacturers
  • Increase productivity
  • Reduce injuries and accidents
  • Provide better compliance
  • Deliver more up-to-date information
  • Improve communication and collaboration

You cold replace the Smartphone or tablet with Google Glass EE and the result would be the same. This is one example of the way technology can support the work of people who are being asked to use their minds.

This is the Internet of Smart Things™. Imagine if the equipment you used in the workplace could:

  • show you what you need to know about how they operate
  • tell you how to use them correctly and efficiently
  • help you be safer working with or around them
  • offer you details to complete and submit regulatory forms and checklists
  • show you how to fix them if they are broken
  • provide you with the schematics and diagrams you need
  • help you contact a mentor or emergency assistance
  • and more, lots more.

What if all of this information was delivered automatically whenever you were within a short distance of the machine?  Imagine if it was instantly and securely viewable from any nearby internet-connected device.

Think of the enormous impact that could have: eliminating errors, boosting employee productivity.  It could dramatically reduce errors and injuries and associated workman’s comp and insurance costs —  all of which would obviously have a positive effect on the bottom line.

We’ve all heard and read about how The Internet of Things in the home will utterly transform the ways in which we live. We’ve heard for years how your refrigerator is going to send a shopping list to your grocery store, your car will make an appointment for an oil change, and the blinds on your windows will automatically close as dusk falls.

What about the Internet of Things in the workplace? It seems to me that far more people need the machines they work with on the job to supply them with specific information.

While I can appreciate that having a dishwasher that will automatically turn itself on when its full might be nice, having a piece of machinery that can provide me with safety warnings or with a checklist before I operate it could prevent me from being seriously injured.

You have now crossed over into the Internet of Smart Things.

The opportunities are vast and diverse, across industries ranging from mining, logging oil exploration and refining, to manufacturing, pharmaceutical and medical, construction and engineering, food production and agriculture.

According to a recent Gartner study the size of the market for the Internet of Things (IoT) by 2020 is estimated to be $1.9 Trillion.

And here’s a breakdown by Industry according to another Gartner study:

gart

Putting people back into the IoT. Worth doing? You tell us …

Addendum:

I’ve been getting a lot of readers responses to this post and here’s a summary of some of the best.

Q: Is there any IPS program on the market for me to look at?

None yet. We are in development of an app that can do everything we described and are at the early build stages.

Q: Will training be replaced by the IosT?

Our prediction is that when the Internet of Smart Things becomes widespread in a few years, and machines and equipment can ‘talk’ with you through your internet-connected device, hard skills training will go away. That means no more time or money wasted on defining, designing, developing, delivering, managing, and measuring hard skills training. No more worries about people quickly falling off the learning curve. It will be performance support just-in-time, where you need it,  to get the job done, instead of just-in-case training by appointment just in case you need to know it someday.

This is from a whitepaper we’re writing: “If the things we work with could only tell us how to safely operate them, let us know what they need to run at peak efficiency, show us how to fix them and replace their parts, the result would be dramatic. Increases in performance and compliance, reductions in costly errors and downtime, and the avoidance of expensive and even deadly accidents. It would change everything by making every thing smarter.” So if training is still focusing on hard skills, we predict it will soon disappear and be replaced by the Internet of Smart Things.

Q; What about measuring the impact of what people know and need to learn?

One of the most important elements: measurement. Right now it’s iffy at best to measure the relationship of training for hard skills and performance. With a product like KnowledgeStar and the Internet of Smart Things, the measurement is automatic.

The smart device and the smart thing in the smart workplace all feed back to whoever needs to see if the work is done correctly, safety forms are filled out, compliance reports completed, break-fix or replacement done in a timely manner and more. Measurement is built into the smart workplace.

It automates Kirkpatrick Level 5 and gathers data and reports it back to people responsible for improving the IPS program. It can also identify top performers and people who are working as mentors and coaches and reward them.

Minds at Work will be published this December 2017 by ATD Press and is available for preorder on Amazon.

The Pizza Story


81pabuk6

 

 

The Pizza Story

In our new book Minds at Work, we talk about the older labor-intensive economy in which we made things and needed to manage hands, and the newer mind-intensive economy in which we produce work with our minds and need to manage minds.

Automation creates a future in which there ar no hands left to manage.

To bring that point  home, we have the pizza story. In a kitchen in Silicon Valley, the team at Zume Pizza is hard at work. Pepe and Giorgio squirt on the sauce, and Marta and Bruno spread it in concentric circles, just like they do in Italy. Then Vincenzo puts the pizza in the oven to bake to perfection. And they do not even stop for a moment to catch their breaths.  That’s because Pepe, Giorgio, Marta, Bruno and Vincenzo are co-bots (robots). And while human employees still apply the toppings according to the customer’s wishes, it’s only a matter of time before they cede that role, too. Made-to-order, ready-to-go, fully automated pizza in as little as seven minutes: As the owners are proud of saying, it’s “artisanal robotic pizza.”

When there are no hands to manage, what’s left.

Postscript: When we originally came across this story and added it to the book Minds at Work, there were only 4 co-bots working at Zume. Since then they’ve added Vincenzo. That means that the unemployment rate for robots is zero.

The Short Definition of “Real Learning”


Real learning is the ability to adopt what you know and know-how to do and adapt it under an everchanging variety of circumstances.

 

No point beating around the pedagogical bush. I’ve been asked by a number of readers “How would you define real learning?” Real learning is the ability to adopt what you know and know-how to do and adapt it under an everchanging variety of circumstances. Learning is an ongoing process. That’s my definition and I’m sticking to it.

Real Learning Versus Rote Learning

Learning in a classroom, actual or online, involves the use of short-term memory. It is all about remembering – regurgitating – then forgetting. It is rote learning, the encumbered and inhibited kind we are mostly used to doing. You remember the lesson, and show that you remember through a variety of tests and then move on. Moving on is all about forgetting. With two interesting and notable exceptions. Art. Science. The reason is simple. Art and Science require an evolving degree of knowledge from basic to advanced. Think learning to play the tuba or building a car. It’s the kind of subject matter that was always learned by apprenticing or being tutored by a master. You need basic math to get to algebraic equations and then onto experimental astrophysics. If you don’t master the fingering you cannot play a decent scale let alone get to a Bach sonata.

By contrast, real learning is somewhat like sleeping. (Not the sleeping you do when a sage-on-the- stage drones on in that sonorous monotone and lulls you into dreamland.) You do not “fall” to sleep, you go through a process of sleeping, through stages. If you’re constantly interrupted you wake up the next morning feeling like you had a bad night sleep. Real learning requires stages as well, and you cannot skip over any of them.

Playing Golf: Spaghetti on the Putting Green

Even though I do not play the game, I use golf as an example to explain the process of real learning. Interestingly a recent number of neuroscience researchers have been doing the same. They talk about reaching a point during the adoption phase where you peak at the physical learning part of the game, and you move on to the strategic or mental part. Your body has practiced so much it has really learned what to do, and now it’s on to the rest of you to learn to find the spot where you want the ball to go. Feel the wind. Sense the way the green curves. Before you get to that stage you spend a lot of time looking all over the place. They followed the eye patterns of novice golfers on a green, lining up a putt, and when they illustrated their eye movements it looked like someone had thrown a plate of spaghetti on the green. Lines and loops going every which way. With the top golfers, the eye patterns were a only few lines, most of them moving directly towards the cup.

When you have learned to play well enough, the body part of the learning to play golf is done, and your mind is free to focus focus focus. You reached the point where you are in the zone. It’s like sleep where you managed to avoid being interrupted until you reach Phase 5 – dreaming.

Why Do We Continue to Fake It?

Rote learning is an incredible waste of time and money. So much of what we learn in school, and in companies that have copied the schoolplace model into the workplace, is forgotten. It does not build on itself from experience. Not just experience in the sense of doing but even experience of knowing more. Even though history, for example, should take you from the Year One up until Today, and then deeper into every era, most of what you learn about history you quickly test and rapidly excrete. That’s just the way the system measures and rewards the student. It has nothing to do with really learning about history. Or any other subject as well. And it certainly fails miserably at providing the 21st century skills we need for the emerging Knowledge Economy.

My Story About History and Herstory

Side note: An alternative example of real learning. I had the advantage of going to a school – at the time it was called “experimental” – where we spent two years moving through time. Going to school was like being in a time machine. For example, when we were learning about the period called the 16th century, we did not have just one short history lesson,  but learned everything 16th century. We were taught about their language, words, maps, arts, crafts, clothes, sciences, cultures, politics, music, poetry, literature, plays, travels, trade, religions, wars, weapons, you name it. We were immersed in the 16th century. It felt like we were in the 16th century. It’s just another model that while not perfect, teaches you more about history than the 3 weeks you get in most schools before jumping ahead from the 16th to the 17th century.

Back to real learning versus rote learning. There are two very surprising elements to real, uninhibited learning that the fake pale excuse of rote learning excludes, disables, and even prohibits.

The Critical Importance of Forgetting

The first is that real learning starts with forgetting – making room for the new. If you have a hard time forgetting the old you will have a difficult time starting to learn the new. If you had a hard time learning what you know, then you will also try and hold on to the old and not learn the new. And be honest we’ve all experienced it. That moment when they upgrade or change a process or procedure or tool you know how to use and you exclaim “Hey, I just learned how to use it, and they’re already changing it!” So, you need to be able to clear the mental cache to use a materialistic model of the brain.

It’s Not Failure if You Learn Something

The second big part – the really big part – of real learning is failure. Failure happens. When you are adapting what you learned from the last time you did it or thought it or spoke it or argued it or whatever, you will experience failure. Smart people who are real learners go “Oh I failed, okay what did I do wrong and how can I fix it so next time I do it right?” Einstein. Edison. Dyson. My Uncle Karl. Long list. So you need to accept and enable failure for the process of real learning to work. And if “failure is not an option” then you will fail and not learn anything.

If you are involved in any kind of learning, and forgetting and failure are not emphasized as part of the learning … leave. You will not really learn a thing. If forgetting what you know at the start (I love those movie scenes where the Sargent – Captain – Leader says “Okay you idiots for starters I want you to forget everything you ever learned!”) then real learning will not happen. By the way forgetting is a brain function as studied by neuroscience as remembering. Imagine what your life would be like if you could not forget what you learned the first (and last) time you learned it …

The “High Wire Training” Exception

Now there is what I call “High Wire Training” where failure leads to your or someone else’s death. Walking across the Grand Canyon. Going into battle in Afghanistan. Responding to a 911 emergency involving a mass shooting or horrible car accident. Let’s be honest. Most of what we learn is not in the High Wire Training category. If it was, this would be a very different blog with a focus on practice, practice and more practice. Repetition. Simulation. VR headsets and more … hmmm … maybe next time.

To sum it up. Learning is a natural brain process that occurs in stages. Real learning enables all the stages. Rote learning disables the stages and focuses on a small part of the process. I’m not sure what value rote learning has in today’s world. Then again, I’m not sure it ever had any real value. What’s the point of spending time and energy learning something only to forget it almost immediately after the test?

To review: Real learning is the ability to adopt what you know and know-how to do and adapt it under an everchanging variety of circumstances. It is one of the reasons my new book Minds at Work harps on the need for continuous learning in the Knowledge Economy where every day – using what you know and know-how to do – is more than ever under the pressure of constantly changing circumstances.

Minds at Work will be published this December 2017 by ATD Press and is available for preorder on Amazon.

 

CFO to CEO: “What happens if we invest all this money into managing minds and they leave us?” CEO to CFO: “What happens if we don’t and they stay?”


new-paradigm-ahead (2)

This is the first in a three-part series. The goal is simple: Completely change the way we manage and learn. Forever. Looking forward to your reactions.

Companies worldwide today seem to be suffering from the same challenges: finding and hiring talent, time-to-performance, employee engagement and retention, innovation, decision-making, and more. They all seem to be fighting off the symptoms of the common disease that has infected them. This series of posts is part of a carefully-researched and groundbreaking book “Minds at Work”, co-authored by Stephen J. Gill and I, that traces the astonishing root cause behind the malaise that’s gripping corporations, and how it can be cured.

Part One: The Wisdom in the Maps from the Age of Exploration

20914600_1423967234346287_743164956207227959_n

Old maps are brilliant. The great mapmakers of the 16th and 17th centuries not only captured the places that were known, but gathered information from as all available sources in their efforts to map uncharted territory. The 1502 Hunt-Lenox Globe is a great example: when its creators reached a place in unknown maritime waters, they would add the warning “here there be dragons” and illustrate that area with pictures of sea monsters.

Corporate managers are now sailing into uncharted territory. It seems as if we all went to bed one night, and when we awakened the next day, everything had changed. Yet many of us are still operating as if it were yesterday. Most of the management practices and principles we use today were devel­oped in the 19th and 20th centuries, when managers were managing hands and workers were learning at a different pace. Digital technology, automation, and globalization have changed everything forever, and we all know that it’s not changing back.  In our 21st-centu­ry knowledge economy, employees produce knowledge and know-how. In order to remain competitive, corporations have a critical need to ensure that employees are continuously learning, and need to find ways to ensure that can — and will — happen.

Stuck in a Timewarp

In actuality, most manag­ers are continuing to rely on management principles and practices that were developed to meet the needs of prior centuries. Yet we have discovered that there has been a trend — growing almost undetected — among corporations located around the globe, to manage employees in radically new ways that are a better way to meet the needs and challenges of today’s knowledge economy.

The greatest mapmakers of old were not the ones who made better maps of places that were already known, but the ones who were able to imagine where the places that were still unexplored and uncharted might be, and how they might be reached.

A similar approach is needed now. Managers are in uncharted territory. They are struggling to imagine what to do and how to manage employees hired for what their minds can create, rather than what their hands can produce. Managers suddenly find themselves in a company that desperately needs employees to be responsible for their own learning, since no L&D or HR department can keep up with the rapid pace of change.

­

The forces driving the new world economic order has placed companies at an inflec­tion point in the history of managing people and the way they learn.  Managers continue to sit at the exact center of the curve, which has been shaped by three sweeping and dramatic shifts in the economy in the last 200 years, each of which created its own management approach and educa­tional system to teach people how to do their jobs.

The Agricultural Economy: Managing Backs

The first great economic era focused on land: land for wealth, land for status, land for food. Private property was legally defined for the first time. Learning was hands on, and on the farm. Education was limited to a few, and was delivered in the home by tutors or in small private schools and colleges to the chil­dren of wealthy landowners and landed gentry.

Bodies were originally the major tool of production; over time, people learned to harness the power of oxen and horses. At the most extreme, people were enslaved or indentured to do the most backbreaking work. In the early 1800s, picking cotton was one of the most important jobs in the U.S. economy. We managed backs, and even in 1900, almost 90 percent of the population in the America and Europe worked on farms and in the fields.

The 20th-Century Industrial Economy: Managing Hands

The second great economic era focused in things. Harnessing steam power, discovering the uses for electricity and making their power universally available to mass-pro­duce cars, clothing, food, and more on our assembly lines and in factories. Machines revolutionized farm work and the number of farm­ers dropped to below six percent by the end of the century. Backbreaking household chores were utterly transformed. Clothes no longer had to be washed by hand — a machine could do it.  Huge blocks of ice no longer had to be hauled up stairs once the refrigerator was invented. Electric vacuum cleaners saved hours previously spent hanging up rugs and hitting them with rug-beaters.

Education was also transformed by the industrial economy. Public education was meant for everyone, and through a series of legislative decisions, it reached the rich and poor, urban and rural, male and female. Classroom instruction emphasized preparation for careers that were more about using hands than backs. Schools emphasized efficiency over individualization, and focused on educating the masses by using a curriculum designed centrally by experts that was consistent year after year. Companies taught managers and employees to do their jobs by exactly copying the classroom setting in which, as children, everyone had learned to learn.

The work­place became the school-place. The goal was mass training for mass production so that employees would be able to perform the same task or set of tasks the same way for as long as those skills remained useful.

Change was slow, and learning a skill or how to complete a task often took months, even years. People reported to the same site—office or factory—day after day. The predominant method of learning was classroom-based and instructor-led. It was high­ly structured training that followed a model developed during WW1. Corporations or training companies developed programs or courses and pushed them out to people the corporation had determined needed them.

Frederick Winslow Taylor, one of the first management consultants, wrote The Principles of Scientific Management in 1911. He developed what he called the “scientific management theory,” by studying the way hands were used at work, and using a stopwatch to time these movements to the hundredth of a minute.  The goal of these time-motion studies was to scientifically determine the most efficient way to reduce the time needed for a worker to complete each task. If that could be done, Taylor believed he would have come up with the best way to optimize and manage work on the assembly line.

For the rest of the 20th century — some 90 years — Taylor’s research would be the standard used for managing hands. It formed the basis for a branch of study called “manage­ment science” and other influential theories, including Max Weber’s Bureaucratic Management, Abraham Maslow’s Hierarchy of Needs (1943), and Douglas McGregor’s Theory X & Theory Y (1960). Today’s MBA degree traces its lineage directly back to Taylor and his studies and work that are inextricably linked addressing the needs of industrial age businesses and managers, who hired employees to work with their hands.

The 21st-Century Knowledge Economy: Managing Minds

mind

In this third and most recent economic era, the focus is on something intangible: data. Data that help create information that is turned into knowledge. In 1982, nearly 40 years ago, Peter Drucker was prescient enough to realize that a major change in the needs of corporations and labor force. name He realized that increasingly, people were working to produce information rather than things or goods and he referred to them as “knowledge workers.”   These were employees who mass produced know-how and ideas. They spent their days fluidly moving between thinking and talking, meet­ing and deciding, researching and writing. They transformed data into information and then into knowledge. Increasingly, large corporations and our economy was quickly evolving, depending less on the work of backs or hands and more on brainpower. And yet the way corporations were managing, training and educating people did not evolve in parallel. Essentially, it remained static.

The way corporations train employees today is fundamentally the same as it was 100 years ago. Training is still pushed out as an event and primarily presented by a “sage-on-the-stage” even if that stage is online. The same schoolplace-in-the-workplace approach used during the previous industrial economy is widely used today. Employee management practices are still based on strategies that were created to manage hands – “command-and-control”, “knowledge is power,” siloed organizational structures with minimal collaboration across the enterprise, lack of transparency, “cube farms,” a limited use of communication technology. That’s the rule and not the exception.

We Crossed the Rubicon of Work, and it Was Deep … Really Deep

The agricultural economy and the industrial economy were more evolutionary than revolutionary.

For thousands of years people used their hands to produce everything from food to tractors, and work was labor-intensive. During this period, especially through both industrial revolutions, the way people structured organizations, and approached management and learning, was a result of the need to manage hands to maximize performance and expenditures.

The changes that have come in less than 50 years are a true revolution.

For the first time in history, we have an economy in which the majority of employees use their minds to produce the work they are paid for.  These profound changes mean corporations now have no choice but to restructure our organizations, management models, and learning practices to align with and support this historic change. The new mind-intensive knowledge economy means corporations must embrace new ideas and models to ensure they are getting the smartest, most agile, innovative, creative, and collaborative workers.

Part Two: The Impact of the Great Divide and the Inflection Point