Tag Archives: Robots

The Robots Aren’t Really Going to Take Over

The Robots Aren't Really Going to Take Over

GUEST POST from Greg Satell

In 2013, a study at Oxford University found that 47% of jobs in the United States are likely to be replaced by robots over the next two decades. As if that doesn’t seem bad enough, Yuval Noah Harari, in his bestselling book Homo Deus, writes that “humans might become militarily and economically useless.” Yeesh! That doesn’t sound good.

Yet today, ten years after the Oxford Study, we are experiencing a serious labor shortage. Even more puzzling is that the shortage is especially acute in manufacturing, where automation is most pervasive. If robots are truly taking over, then why are having trouble finding enough humans to do work that needs being done?

The truth is that automation doesn’t replace jobs, it replaces tasks and when tasks become automated, they largely become commoditized. So while there are significant causes for concern about automation, such as increasing returns to capital amid decreasing returns to labor, the real danger isn’t with automation itself, but what we choose to do with it.

Organisms Are Not Algorithms

Harari’s rationale for humans becoming useless is his assertion that “organisms are algorithms.” Much like a vending machine is programed to respond to buttons, humans and other animals are programed by genetics and evolution to respond to “sensations, emotions and thoughts.” When those particular buttons are pushed, we respond much like a vending machine does.

He gives various data points for this point of view. For example, he describes psychological experiments in which, by monitoring brainwaves, researchers are able to predict actions, such as whether a person will flip a switch, even before he or she is aware of it. He also points out that certain chemicals, such as Ritalin and Prozac, can modify behavior.

Therefore, he continues, free will is an illusion because we don’t choose our urges. Nobody makes a conscious choice to crave chocolate cake or cigarettes any more than we choose whether to be attracted to someone other than our spouse. Those things are a product of our biological programming.

Yet none of this is at all dispositive. While it is true that we don’t choose our urges, we do choose our actions. We can be aware of our urges and still resist them. In fact, we consider developing the ability to resist urges as an integral part of growing up. Mature adults are supposed to resist things like gluttony, adultery and greed.

Revealing And Building

If you believe that organisms are algorithms, it’s easy to see how humans become subservient to machines. As machine learning techniques combine with massive computing power, machines will be able to predict, with great accuracy, which buttons will lead to what actions. Here again, an incomplete picture leads to a spurious conclusion.

In his 1954 essay, The Question Concerning Technology the German philosopher Martin Heidegger sheds some light on these issues. He described technology as akin to art, in that it reveals truths about the nature of the world, brings them forth and puts them to some specific use. In the process, human nature and its capacity for good and evil is also revealed.

He gives the example of a hydroelectric dam, which reveals the energy of a river and puts it to use making electricity. In much the same sense, Mark Zuckerberg did not “build” a social network at Facebook, but took natural human tendencies and channeled them in a particular way. After all, we go online not for bits or electrons, but to connect with each other.

In another essay, Building Dwelling Thinking, Heidegger explains that building also plays an important role, because to build for the world, we first must understand what it means to live in it. Once we understand that Mark Zuckerberg, or anyone else for that matter, is working to manipulate us, we can work to prevent it. In fact, knowing that someone or something seeks to control us gives us an urge to resist. If we’re all algorithms, that’s part of the code.
Social Skills Will Trump Cognitive Skills

All of this is, of course, somewhat speculative. What is striking, however, is the extent to which the opposite of what Harari and other “experts” predict is happening. Not only have greater automation and more powerful machine learning algorithms not led to mass unemployment it has, as noted above, led to a labor shortage. What gives?

To understand what’s going on, consider the legal industry, which is rapidly being automated. Basic activities like legal discovery are now largely done by algorithms. Services like LegalZoom automate basic filings. There are even artificial intelligence systems that can predict the outcome of a court case better than a human can.

So it shouldn’t be surprising that many experts predict gloomy days ahead for lawyers. By now, you can probably predict the punchline. The number of lawyers in the US has increased by 15% since 2008 and it’s not hard to see why. People don’t hire lawyers for their ability to hire cheap associates to do discovery, file basic documents or even, for the most part, to go to trial. In large part, they want someone they can trust to advise them.

The true shift in the legal industry will be from cognitive to social skills. When much of the cognitive heavy lifting can be done by machines, attorneys who can show empathy and build trust will have an advantage over those who depend on their ability to retain large amounts of information and read through lots of documents.

Value Never Disappears, It Just Shifts To Another Place

In 1900, 30 million people in the United States worked as farmers, but by 1990 that number had fallen to under 3 million even as the population more than tripled. So, in a matter of speaking, 90% of American agriculture workers lost their jobs, mostly due to automation. Yet somehow, the twentieth century was seen as an era of unprecedented prosperity.

You can imagine anyone working in agriculture a hundred years ago would be horrified to find that their jobs would vanish over the next century. If you told them that everything would be okay because they could find work as computer scientists, geneticists or digital marketers, they would probably have thought that you were some kind of a nut.

But consider if you told them that instead of working in the fields all day, they could spend that time in a nice office that was cool and dry because of something called “air conditioning,” and that they would have machines that cook meals without needing wood to be chopped and hauled. To sweeten the pot you could tell them that ”work” would mostly consist largely of talking to other people. They may have imagined it as a paradise.

The truth is that value never disappears, it just shifts to another place. That’s why today we have less farmers, but more food and, for better or worse, more lawyers. It is also why it’s highly unlikely that the robots will take over, because we are not algorithms. We have the power to choose.

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

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4 Key Aspects of Robots Taking Our Jobs

4 Key Aspects of Robots Taking Our Jobs

GUEST POST from Greg Satell

A 2019 study by the Brookings Institution found that over 61% of jobs will be affected by automation. That comes on the heels of a 2017 report from the McKinsey Global Institute that found that 51% of total working hours and $2.7 trillion dollars in wages are highly susceptible to automation and a 2013 Oxford study that found 47% of jobs will be replaced.

The future looks pretty grim indeed until you start looking at jobs that have already been automated. Fly-by-wire was introduced in 1968, but today we’re facing a massive pilot shortage. The number of bank tellers has doubled since ATMs were introduced. Overall, the US is facing a massive labor shortage.

In fact, although the workforce has doubled since 1970, labor participation rates have risen by more than 10% since then. Everywhere you look, as automation increases, so does the demand for skilled humans. So the challenge ahead isn’t so much finding work for humans, but to prepare humans to do the types of work that will be in demand in the years to come.

1. Automation Doesn’t Replace Jobs, It Replaces Tasks

To understand the disconnect between all the studies that seem to be predicting the elimination of jobs and the increasingly dire labor shortage, it helps to look a little deeper at what those studies are actually measuring. The truth is that they don’t actually look at the rate of jobs being created or lost, but tasks that are being automated. That’s something very different.

To understand why, consider the legal industry, which is rapidly being automated. Basic activities like legal discovery are now largely done by algorithms. Services like LegalZoom automate basic filings. There are even artificial intelligence systems that can predict the outcome of a court case better than a human can.

So, it shouldn’t be surprising that many experts predict gloomy days ahead for lawyers. Yet the number of lawyers in the US has increased by 15% since 2008 and it’s not hard to see why. People don’t hire lawyers for their ability to hire cheap associates to do discovery, file basic documents or even, for the most part, to go to trial. In large part, they want someone they can trust to advise them.

In a similar way we don’t expect bank tellers to process transactions anymore, but to help us with things that we can’t do at an ATM. As the retail sector becomes more automated, demand for e-commerce workers is booming. Go to a highly automated Apple Store and you’ll find far more workers than at a traditional store, but we expect them to do more than just ring us up.

2. When Tasks Become Automated, The Become Commoditized

Let’s think back to what a traditional bank looked like before ATMs or the Internet. In a typical branch, you would see a long row of tellers there to process deposits and withdrawals. Often, especially on Fridays when workers typically got paid, you would expect to see long lines of people waiting to be served.

In those days, tellers needed to process transactions quickly or the people waiting in line would get annoyed. Good service was fast service. If a bank had slow tellers, people would leave and go to one where the lines moved faster. So training tellers to process transactions efficiently was a key competitive trait.

Today, however, nobody waits in line at the bank because processing transactions is highly automated. Our paychecks are usually sent electronically. We can pay bills online and get cash from an ATM. What’s more, these aren’t considered competitive traits, but commodity services. We expect them as a basic requisite of doing business.

In the same way, we don’t expect real estate agents to find us a house or travel agents to book us a flight or find us a hotel room. These are things that we used to happily pay for, but today we expect something more.

3. When Things Become Commodities, Value Shifts Elsewhere

In 1900, 30 million people in the United States were farmers, but by 1990 that number had fallen to under 3 million even as the population more than tripled. So, in a manner of speaking, 90% of American agriculture workers lost their jobs, mostly due to automation. Still, the twentieth century became an era of unprecedented prosperity.

We’re in the midst of a similar transformation today. Just as our ancestors toiled in the fields, many of us today spend much of our time doing rote, routine tasks. However, as two economists from MIT explain in a paper, the jobs of the future are not white collar or blue collar, but those focused on non-routine tasks, especially those that involve other humans.

Consider the case of bookstores. Clearly, by automating the book buying process, Amazon disrupted superstore book retailers like Barnes & Noble and Borders. Borders filed for bankruptcy in 2011 and was liquidated later that same year. Barnes & Noble managed to survive but has been declining for years.

Yet a study at Harvard Business School found that small independent bookstores are thriving by adding value elsewhere, such as providing community events, curating titles and offering personal recommendations to customers. These are things that are hard to do well at a big box retailer and virtually impossible to do online.

4. Value Is Shifting from Cognitive Skills to Social Skills

20 or 30 years ago, the world was very different. High value work generally involved retaining information and manipulating numbers. Perhaps not surprisingly, education and corporate training programs were focused on teaching those skills and people would build their careers on performing well on knowledge and quantitative tasks.

Today, however, an average teenager has more access to information and computing power than a typical large enterprise had a generation ago, so knowledge retention and quantitative ability have largely been automated and devalued. High value work has shifted from cognitive skills to social skills.

Consider that the journal Nature has found that the average scientific paper today has four times as many authors as one did in 1950, and the work they are doing is far more interdisciplinary and done at greater distances than in the past. So even in highly technical areas, the ability to communicate and collaborate effectively is becoming an important skill.

There are some things that a machine will never do. Machines will never strike out at a Little League game, have their hearts broken or see their children born. That makes it difficult, if not impossible, for machines to relate to humans as well as a human can. The future of work is humans collaborating with other humans to design work for machines.

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

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Robots and Automation

Redefining Industries and the Workforce

Robots and Automation

GUEST POST from Art Inteligencia

The world is undergoing a technological revolution, where robots and automation are increasingly prevalent in industries, altering the way we work and transforming entire sectors. This paradigm shift has given rise to a new era for the global workforce, with significant implications for the economy and society as a whole. In this thought leadership article, we will explore how robots and automation redefine industries and reshape the workforce by examining two compelling case study examples.

Case Study 1: The Automotive Industry

The automotive industry has witnessed a remarkable transformation due to the integration of robots and automation. Assembly lines that were once dominated by human labor have now become hubs of robotic efficiency. Manufacturing giants like Tesla and Toyota have turned to automation to enhance production speed, improve quality control, and ultimately increase profitability.

The deployment of robots and automation in the automotive sector has proven to be a game-changer. By automating repetitive and labor-intensive tasks, such as welding, painting, and assembly, manufacturers have achieved greater precision and consistency in their operations. This shift has also led to a reduction in workplace injuries, as robots effectively handle hazardous tasks and operate in environments inhospitable to humans.

Yet, the introduction of automation in the automotive industry has not come without its challenges. While overall productivity has surged, concerns about job displacement have mounted. However, it is important to note that automation has typically resulted in the creation of new jobs that are more cognitively demanding and require advanced technical skills. Moreover, the shift to automation allows human workers to be up-skilled in areas such as robot programming, maintenance, and supervision, leading to higher job satisfaction and improved career prospects.

Case Study 2: E-commerce and Warehousing

The rapid growth of e-commerce has revolutionized the retail industry, prompting a surge in demand for warehousing and fulfillment centers. Robots and automation have played a pivotal role in meeting this demand by redefining the warehousing landscape. Companies like Amazon have embraced robotics to optimize their logistics operations, enhance efficiency, and streamline processes.

Robots deployed in e-commerce warehouses are capable of picking, packing, and sorting products at remarkable speeds, far surpassing the capabilities of human workers. They navigate the warehouse floor with precision and utilize machine learning algorithms to continuously improve their performance. Automation allows for a much quicker order fulfillment process, leading to reduced delivery times and improved customer satisfaction.

While the use of robots in e-commerce warehouses has raised concerns about job displacement, it is vital to understand the broader picture. As demand for online shopping and rapid delivery increases, the need for more sophisticated logistics operations grows as well. This expansion necessitates a larger workforce to manage, program, and maintain the robotic systems. Furthermore, the integration of automation in e-commerce has opened up new opportunities for workers in areas such as inventory management, data analysis, and customer service, illustrating the transformative nature of this technology.


Robots and automation are undoubtedly redefining industries and transforming the global workforce. As exemplified by the automotive industry and e-commerce sector, the integration of this technology has led to increased productivity, improved quality control, and enhanced safety measures. While concerns about job displacement persist, historical evidence suggests that automation creates new roles that require advanced skills, benefiting workers in the long run. To adapt to this rapidly changing landscape, harnessing the potential of robots and automation will be crucial for individuals, companies, and policymakers alike. It is through proactive adaptation and up-skilling that we can embrace this technological revolution and shape a future where robots work alongside humans for the betterment of society.

Bottom line: Futurists are not fortune tellers. They use a formal approach to achieve their outcomes, but a methodology and tools like those in FutureHacking™ can empower anyone to be their own futurist.

Image credit: Wikimedia

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Exploring the Role of AI and Robotics in Futurology

Exploring the Role of AI and Robotics in Futurology

GUEST POST from Art Inteligencia

The field of futurology is constantly evolving and growing in complexity as technology advances. Artificial intelligence (AI) and robotics are two technologies that are playing an increasingly important role in futurology. As we move further into the 21st century, these two fields of technology are being used to create a new era of possibilities and potential. In this article, we will explore the role of AI and robotics in futurology and discuss the ways they are being used to shape the future of our world. Here are five ways AI and robotics will contribute to our future:

1. Smarter and More Efficient Systems

First and foremost, AI and robotics are being used to create smarter and more efficient systems. By using AI and robotics, futurologists are able to create smarter systems that can process more data in a shorter amount of time. This allows for faster decision-making and improved analysis of data. AI and robotics are also being used to create autonomous systems that can make decisions without human input. This allows for faster, more efficient decision-making and improved accuracy.

2. Advanced Methods of Communication

Second, AI and robotics are being used to develop more advanced and sophisticated methods of communication. This includes the development of voice recognition and natural language processing technologies that allow for better communication between humans and machines. AI and robotics are also being used to create more sophisticated forms of communication between humans and machines, such as facial recognition and gesture recognition.

3. Effective and Efficient Goods and Services

Third, AI and robotics are being used to develop more effective and efficient ways of producing goods and services. By using AI and robotics, futurologists are able to create machines that can produce goods faster and more efficiently. This enables companies to reduce production costs and increase their profits. AI and robotics are also being used to create smarter machines that can be used to automate certain tasks, such as packaging and shipping, which increases efficiency and decreases costs.

4. Secure and Reliable Systems

Fourth, AI and robotics are being used to develop more secure and reliable systems. By using AI and robotics, futurologists are able to create systems that are more secure and reliable. This includes systems that are less vulnerable to cyber-attacks and data breaches. AI and robotics are also being used to create systems that can detect threats and respond accordingly.

5. Intelligent and Advanced Transformation

Finally, AI and robotics are being used to develop more intelligent and advanced forms of transportation. This includes the development of self-driving cars and other autonomous vehicles that can navigate roads and other terrain with greater accuracy and safety. AI and robotics are also being used to create smarter forms of transportation that can transport goods and people more efficiently.


AI and robotics are playing an increasingly important role in futurology. By using AI and robotics, futurologists are able to create smarter and more efficient systems, develop more advanced and sophisticated methods of communication, produce goods and services more effectively and efficiently, create more secure and reliable systems, and develop more intelligent and advanced forms of transportation. As technology continues to advance, AI and robotics will continue to play an important role in shaping the future of our world.

Image credit: Pixabay

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Announcing the Crowd Computing Revolution

Designing Work for Man and Machine to Do Together

by Braden Kelley

Announcing the Crowd Computing RevolutionI am proud to bring you a downloadable PDF of a piece I created on The Crowd Computing Revolution and the redesign of work that is now possible thanks to new technology tools and business architecture thinking that will allow man and machine to work more efficiently together than ever before.

Anyone who has read even one or two science fiction books or watched one or two SciFi movies inevitably finds themselves dreaming of a day when machines will free of us of some of the mundane tasks in our lives. Companies dream of this too. Witness the eagerness of companies to outsource entire job functions (or even more recently whole business processes) to third parties either onshore or offshore. Hackers and spammers have become quite adept at programming their machines to send emails to people or attempt to break through security around the clock, around the globe. We have built automated factories, interactive voice response systems, and devised all kinds of ways to put machines to work for us.

Roger Martin, Dean of the Rotman School at the University of Toronto has a simple framework from his treatise on Design Thinking titled The Design of Business, that shows how as we learn more about a knowledge (or work) area, our understanding and abilities allow us to move the piece of knowledge (or work) from something that is mysterious and performed in an ad hoc way by experts, to a level of maturity where we start to observe the patterns (or heuristics) in the knowledge area (or piece of work), to a stage where the work or knowledge is well-understood and can be reduced to an algorithm (or set of best practices) performed by lower skilled employees, and possibly even implemented as a piece of code to be executed by a robot or computer.

Knowledge Funnel

Source: The Design of Business by Roger Martin

But, as alluded to earlier, companies have not only become more comfortable with designing work to be executed by machines instead of employees, but also more amenable to many different sizes and shapes of work being completed by people outside the organization, including:

  1. Entire job functions (Contractors or Outsourcing Firms – Global Outsourcing Market was $95 Billion in 2011)
  2. Whole business processes (Business Process Outsourcing (BPO) Firms – 2011 Market in excess of $11 Billion)
  3. Projects or initiatives (Outside Consultants)
  4. Discrete tasks (99Designs, Crowdspring, etc.)
  5. Micro tasks (Amazon Mechanical Turk, etc.)

Task and Micro-Task Division

Task and Micro-task Division

Over time the human race has moved from building simple machines that function as tools (like a forklift), allowing a man to do more with the help of the machine, to building machines and robots capable of completing a whole task (like painting a car or making an exact copy of a document). Has anyone seen a help wanted advertisement for a scribe lately? Meanwhile, our fully automated manufacturing and packaging plants use machines to complete an entire process. But machines aren’t suitable for every kind of work. They are appropriate for tasks that are well-defined and repeated continuously as part of a standardized process, but not a proper fit for tasks where judgment is required, particularly tasks with numerous exceptions, variability, or personalization.

As a result, typically machines and robots have been relegated most often to the production areas of a business, places where it has been easy to define specific tasks or even whole processes that can be designed for machines or robots to own and complete 24/7/365 if necessary.

Build a Common Language of Innovation

Rethinking Who (or What) Does the Work

Crowd Computing Part 2Rise of the Crowd

There is another growing trend that is now rivaling the growing power of robotics and automation – crowdsourcing. It all started with prizes like The Longitude Prize, but now thanks to the power of the Internet, companies and individuals all around the world are breaking down their projects and processes and tapping into the power of the crowd using loosely-organized, non-employee workforces like Amazon’s Mechanical Turk to execute micro-tasks, getting whole tasks completed through sites like Top Coder and Crowdspring, or calling upon the crowd to solve difficult challenges using sites like Innocentive, NineSigma, and Idea Connection. Sites like these enable organizations to access knowledge, expertise, perspectives, or capacity that they don’t currently have in their organization (or to possibly to get a task or challenge completed at a lower cost). Check out my white paper Harnessing the Global Talent Pool to Accelerate Innovation to learn more about this topic and some of the strategies for successfully leveraging external talent.

Rise of the Business Architect

Our organizations face an innovation imperative amidst intensifying competition that is forcing an increasing number of industries to become commoditized. This increasing need for a sustained level of innovation and a requirement for innovation to be a repeatable and sustainable activity, has led to an increasing number of organizations to consciously design their approaches to the new businesses that they enter. This has led to the growth of two new business disciplines – business architecture and social business architecture.

NIH Business Architecture

Source: National Institute of Health

Business Architecture, according to Wikipedia, is “a modern technology-oriented business occupation…. Working as a change agent with senior business stakeholders, the business architect plays a key part in shaping and fostering continuous improvement and business transformation initiatives. Business architects lead efforts aiming at building an effective architecture for the business process management (BPM) projects that make up the business change programme. The business architect implements business models that require business technology to work effectively.”

Social Business Intersections Social Business Connections

Social Business Architecture on the other hand, facilitates and optimizes the group dynamics and interactions inside the organization, and Social Business Architects specialize in identifying the different parts of an organization that need to interact with groups of people outside the organization, how those parts of the organization should work together to communicate with people outside the organization, and help to identify and implement communications solutions that connect the organization with the target groups so that a meaningful connection and conversation can be built, and then helps to manage the conversations and the information and learnings from their outcomes for the benefit of the organization.

Social Business Attraction Social Business Engagement

Few organizations employ or are even yet aware of the need for Social Business Architects, but there are an increasing number of help wanted postings for Business Architects. This is because not only do organizations recognize the need to architect their new lines of business for maximum efficiency and to , but also because there are so many different ways that work can be executed (employees, contractors, consultants, outsourcing, business process outsourcing (BPO), crowdsourcing, and micro-task execution, that for maximum efficiency it now increasingly requires someone to investigate all of the options, break down the work to be done into jobs, projects and processes, tasks and microtasks so that the right resources can be hired, contracted, briefed, or otherwise engaged to ensure that everything is completed as quickly and as cheaply as possible.

A Guide to Open Innovation and Crowdsourcing

Investigating Examples of Crowd Computing

The Crowd Computing Revolution - Part ThreeMoving from The Design of Business to Redesigning Work

Business Architects have the opportunity to plan for the organization how work can move from mystery to heuristics to algorithms to code. Business Architects (or people filling this role in an organization) have the opportunity to redesign work in the most efficient way possible to leverage both man and machine to get the work done at the lowest cost possible. Technology now exists to allow Business Architects and managers to move beyond allocating work on a job, project, or process basis, and instead design flexible workflows that combine the use of humans and machines to complete the tasks that they are best suited for, or even for humans to augment the work of machines.

For example, imagine that you work in the purchasing department at a large multinational and every month you receive hundreds or thousands of invoices from suppliers all over the world in all different kinds of formats – electronic, mailed paper invoices, PDFs, scanned paper invoices, and even faxed invoices. Your job as purchasing (or accounts payable) manager is to track all of the invoices that you receive, get them entered into your ERP system, and ultimately make sure that they get paid. You can hire or use an existing employee or contractor to manually key them all in, or sign a big dollar outsourcing deal sufficient to support the hiring, training, and management of offshore resources by the outsourcer, or you could try and use OCR software to do the job, but it would fail because of the great deal of variability in both the input sources and formatting of the documents and you’ll end up needing human resources to interpret the OCR output anyways.

Crowd Computing Invoice Processing Example

Or, you could examine the workflow of the process and identify which micro-tasks humans are best suited to perform and which micro-tasks machines are most efficient and cost-effective at performing. Then assign the right micro-task to the right resource. In the case of human resources, this could be an employee, a contractor, an external expert, or even a resource you don’t even know or control (via a crowd workforce like Amazon Mechanical Turk, Elance, etc.). And finally for each micro-task, assign a level of confidence in the quality of the assigned resource’s output and a define a process for grading it. In situations where you have a high level of confidence in the micro-task’s output quality, you can move directly on to the next micro-task in the workflow, but if you have a low level of confidence in a particular micro-task output performed by a machine, assign an alternate process to validate that output (such as using someone via Amazon Mechanical Turk to validate that “yes, this is a purchase order number”).

But that is not all that is possible these days. It is now possible for systems that facilitate the management of this kind of atomized work structure definition and workflow management and assignment, like those from Crowd Computing Systems, to also use artificial intelligence to both learn from the corrections that humans are making to a machine-driven, micro-task execution to get more accurate in the future, but also to learn how to do micro-tasks that humans are currently performing without machine assistance and to help identify the best performing crowd resources to inform work allocation decisions and to perform overall output quality optimization.


In much the same way that outsourcing felt awkward 20-25 years ago and Business Process Outsourcing (BPO) felt foreign a decade ago, the time has come for crowd computing to begin to be a tool that managers and Business Architects can keep in their toolbox to better allocate work across man and machine. The time is now for man and machine to work together in ways that they never have before, and to learn from each other. The time has come for businesses and work to not just be operated and executed, but designed for maximum efficiency. Should we be afraid as workers that the machines are going to take away our jobs and leave us with nothing to do?

No. In much the same way that tractors and steam shovels began freeing man and beast from back breaking work nearly two hundred years ago, there are many benefits for man to gain from the crowd computing revolution – the biggest being freedom from an increasing amount of mind numbing work. Organizations that embrace crowd computing stand to gain not only to potentially lower processing costs for many high volume processes, but also will benefit from acquiring the ability to reassign analysts and other highly-skilled and trained employees to higher value work – better leveraging their existing human resources while simultaneously increasing employee satisfaction, retention, and knowledge creation in the enterprise. Are you ready for the crowd computing revolution?

Click Here to Download The Crowd Computing Revolution PDF



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Showrooming vs. Retail Warehousing

Showrooming vs. Retail WarehousingOld School vs. Old School

As the saying goes, ‘what’s old is new again’. Only this time robots and hand-held computers (aka smartphones) are involved.

I was having a conversation recently with a colleague about the retail industry and I made the point that all retail stores are warehouses, only some are prettier than others.

Walk into the average Macy’s or other department store and you’ll see piles of inventory out on display in the store, of every size (from small to XXXL) and variety (white, black, brown, etc.) with even more in the back. Retail WarehousingAll of this inventory has been tagged for individual sale and is there every day, just in case the person who wants that size, color, style, whatever, walks into the store ready to take it home today.

Contrast this with Argos in the UK or the now-defunct Best and Service Merchandise in the United States whose business model was to have only certain items out on display in the retail store, with the rest of the inventory in the back ready to be picked (much like an eCommerce environment) once the product(s) were ordered.

Showrooming and Retail Warehousing HybridApple Stores are a hybrid between the two. Accessories are out on the floor boxed for individual sale, while iMac and iBook computers, iPad tablets, and iPod mp3 players are all out of the box and display in droves for customers to try out and hopefully purchase. Then if they do, the box appears from the warehouse in the back.

But there is a new wave of entrepreneurs trying to bring back the catalog retailing business model into the modern age. Version 1 was standard eCommerce where the catalog was available online instead of in the store and no physical retail stores had to be maintained, leading to a financial advantage for online retailers like Amazon. But eCommerce has a weakness, and that is in product categories need to know how something fits or feels or otherwise fits their style or life.

ShowroomingThis has led to the rise of what physical retailers rail against, the concept of showrooming. If you’re not familiar with what showrooming is, it is the pattern of behavior where potential customers come into a physical retail store, explore the product, try it on if necessary, and then leave the store and buy the product online from a competitor like Amazon.

Some entrepreneurs are beginning to recognize the collision of some of the mobile technologies that underlie the showrooming trend together with automated robotic picking technologies and the recognition of inefficiencies in the traditional retail warehousing model.

Hointer Founder

One example is a Seattle area entrepreneur who left Amazon to launch a business called Hointer that while they are talking about how they are revolutionizing the premium jean shopping experience for men, their real strategy is to use their store as a rapid prototyping and testing environment to develop a technology platform supporting the browsing, trying, and checkout process that they hope to sell to a number of different retailers all around the world. Their modernization of the catalog showroom business model is predicated on reducing the square footage and personnel required to operate a store, thus increasing (hopefully) the dollars per square foot ratio that most retailers use as their success metric. One side benefit of the approach is that salespeople will be able to spend less time folding clothes and more time helping customers. Imagine that.

Will this robotic retailing concept catch on with more than utilitarian shoppers?

Image Credits: Daily UW, Hointer

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