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Embedded Learning: Integrating Skill Acquisition Into Day-to-Day Activities

Steven Hunt

Economies around the world are challenged with a chronic lack of skilled employees.  Despite high unemployment levels, many companies struggle to find people who have the technical qualifications and experiences needed to fill critical roles.

Traditional educational structures are failing to produce the numbers and kinds of skilled candidates companies need.  While there are many ways we can and should improve our educational systems to address the skills crisis, we should also be doing more to rethink the methods we use to develop skilled employees.

Rather than telling workers they must go to school to acquire new skills, its time to give people tools that help them learn from their current lives without requiring formal education.

To fully understand why, let’s look at the following:

  • Methods people use to acquire skills in the absence of formal training programs and why technology is enabling us to go “back to the future” when it comes to learning.
  • Barriers that prevent unskilled workers from acquiring more advanced job skills.
  • How we might leverage people’s day-to-day life activities as an under-utilized resource for acquiring skills.

How do people acquire skills organically? 

Going to school is not the natural way for people to learn.  Don’t get me wrong – I believe in the power of a good formal school system.  But if we look at the history of humans we did not develop schools until pretty late in our evolution.

For centuries we managed to learn without classrooms and courses.  So how did we do it?  The answer is learning from experience and observation.  People acquired skills by working alongside people who knew more than them and engaging in tasks that challenged them to think differently.  In other words, the most natural way for people to learn is through formal and informal mentoring and apprenticeship relationships.

The problem with the apprenticeship approach is it doesn’t scale well.  There simply aren’t enough apprenticeship opportunities available to produce the number of skilled employees we need.

In addition, not all experts make good mentors and coaches.  But technology is starting to change this.   YouTube is probably the best widespread example of how cloud based technology is allowing skilled mentors to share their expertise with people around the world.

Want to learn how to play guitar like Brian Setzer from the Stray Cats?   There’s a video where you can virtually “sit down” with him for an hour while he shows you various tips and tricks.  Want to learn how to cook like Emeril?   Check out videos where he’ll walk you through what he does to create unique flavors.  Public access video technologies like YouTube and private access social learning technologies like Jam are addressing the historic challenge of scaling expertise through mentorships.

We now have technology that allows us to manage many issues that historically limited the value of apprenticeship based training.   This technology makes things possible around learning that weren’t possible 10 years ago.

But technology by itself does not solve problems.   You have to use it correctly.  So what is required if we are to use this technology to develop underskilled workers?

What prevents under-employed people from acquiring the skills needed to advance their careers? 

There are three major barriers that make it difficult for under-skilled workers to acquire advanced job skills:  lack of on-the-job learning opportunities, lack of time and resources for formal training, and limited awareness of what kind of skills will provide the greatest career opportunities.   I will discuss each of these in turn.

One of the myths about technology is that it eliminates jobs.  People have visions of robots replacing workers.   But the reality is a bit more complex.  Technology actually creates jobs because it fuels efficiency and economic growth.  But the jobs technology creates tend to fall into two very distinct categories:

Highly-skilled positions associated with developing and maintaining complex technological systems

Low or unskilled positions associated with performing basic service tasks that are impacted by technology but that do not require an understanding of how the technology works.

There is also a third category of jobs that technology does tend to eliminate:  semi-skilled positions that people historically used to move from unskilled work to skilled work.

Consider the example of auto mechanic.  People used to become auto-mechanics by starting out in entry-level service station jobs that involved simple tasks like pumping gas and changing oil.

Over time they would perform increasingly complex automotive tasks such as fixing brakes or replacing spark plugs that allowed them to acquire the skills needed to become a master mechanic.

Contrast that to the modern career path to becoming a mechanic.   Thanks to technology, you could pump gas for years and never learn anything about what goes on under the hood of a car.  When you do look under the hood you are confronted with technology complex machines that are for more complicated then the V-8 engines of the 1960s.

It is now very difficult to acquire the skills needed to be a mechanic simply by working in a gas station.  Most mechanics had to go to school just to learn to use the technology necessary to diagnose engine problems, let alone fix them.

The increasing gap between skilled and unskilled positions makes it hard for people to work their way into skilled jobs through on-the-job learning.  This has severely constrained what traditionally was one of the main ways people advanced their careers through skill acquisition.

The economic difference between being a skilled vs. an unskilled employee also places additional constraints on the ability of people to acquire job skills through formal education.

Unskilled jobs by definition can be filled by people with very little training or experience.  Because the labor supply for these jobs is relatively high the wages for these jobs tends to be quite low.

Many unskilled workers have to work multiple jobs to meet their basic economic needs.   They do not have the time or money to enroll in formal training programs.   This means the people that need skills the most often have the most difficulty enrolling in structured classes that teach them.

Last, unskilled workers may struggle to determine what sort of skills they should acquire because they are frequently isolated working long hours in jobs that provide little exposure or opportunity to learn skills that will help them advance their careers.

They do not have access to mentors or other advisors who can provide suggestions on what sorts of leaning opportunities will have the greatest benefit for their long-term job prospects.

A possible answer:  embed learning into life. 

One potential answer to this dilemma is to build tools that will help unskilled workers to acquire valuable career skills through normal life activities.   In the 1980s a series of studies were conducted showing that people who performed presumably mundane tasks at a very high level had found ways to use these supposedly simple tasks to develop relatively complex skills (e.g., Lave et al., 1984, Scribner, 1984).

For example, shopping for groceries can involve the use of complex mathematical formulas when people truly challenge themselves to buy the most groceries with the least money.

Similarly, people who excel at packing odd shaped objects in way that maximizes the use of storage space are able to do this because they have developed complex spatial reasoning skills. The phenomenon of acquiring complex skills through seemingly non-work related tasks goes beyond analytical reasoning.

Years ago I was interviewing a woman who had not worked in many years because she had been focused on raising her children.  When I asked her what sort of managerial skills she possessed she provided examples from her activities coordinating youth athletic activities that involved a level of organizational, relationship building, and financial skills that vastly exceed those of many people who have years of formal managerial experience.

What these examples illustrate is that the “everyday life” is rich with opportunities to acquire highly complex and valuable job skills.   The challenge is getting people to recognize and capitalize on these learning opportunities.   Social learning technology holds the potential to change this.

Imagine online videos that teach people how to perform day to day tasks in a way that is more efficient and economical and that also helps them develop valuable work-related skills.   This would allow people to use tasks such as scheduling children’s activities, performing home maintenance, or participating in volunteer programs as opportunities to develop skills and capabilities that make them more valuable employees.

People could be also be shown how to leverage public online computer programs to build technology skills while simultaneously increasing their efficiency performing routine tasks such as household budgeting.   To be fully effective, this online training would include advice on what skills are most in demand for different jobs and how to leverage skills learned outside of work to open up new career opportunities.

I am not suggesting this approach will be easy or that it will ever replace the need for formal educational programs and on-the-job learning.  But embedding learning into life does provide an alternative way to acquire skills that is cheaper, easier to access, and in many ways complementary to existing education and job-based skill acquisition methods.

And the upside is considerable. Instead of telling people they need to go to school or get a job to acquire critical career skills, we can encourage them to take advantage of the learning opportunities that are all around them.  Perhaps in the future the key to getting a better job will be to simply focus on living a more effective and efficient life in general.

Contact Steven at: shunt@successfactors.com

This article was written as part of The Future of Education research initiative.

References

Lave J.,  Murtaugh M., & de la Rocha, O. (1984).   The dialectic of Arithmetic in Grocery Shopping, in Rogoff, B.

and Lave, J. eds, Everyday Cognition, Cambridge, MA, Harvard University Press, 67–94.

Scribner, S. (1984). Studying working intelligence. In B. Rogoff and J. Lave, Eds., Everyday Cognition: Its Development in Social Context. Cambridge, MA: Harvard University Press, pp. 9-40.

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Steven Hunt

About Steven Hunt

Steven Hunt is the Senior Vice President of Customer Value at SAP. He is responsible for guiding the strategy and deployment of knowledge, tools and process improvements that increase the value customers receive from SuccessFactors & SAP Cloud software as a service solutions.

Data Analysts And Scientists More Important Than Ever For The Enterprise

Daniel Newman

The business world is now firmly in the age of data. Not that data wasn’t relevant before; it was just nowhere close to the speed and volume that’s available to us today. Businesses are buckling under the deluge of petabytes, exabytes, and zettabytes. Within these bytes lie valuable information on customer behavior, key business insights, and revenue generation. However, all that data is practically useless for businesses without the ability to identify the right data. Plus, if they don’t have the talent and resources to capture the right data, organize it, dissect it, draw actionable insights from it and, finally, deliver those insights in a meaningful way, their data initiatives will fail.

Rise of the CDO

Companies of all sizes can easily find themselves drowning in data generated from websites, landing pages, social streams, emails, text messages, and many other sources. Additionally, there is data in their own repositories. With so much data at their disposal, companies are under mounting pressure to utilize it to generate insights. These insights are critical because they can (and should) drive the overall business strategy and help companies make better business decisions. To leverage the power of data analytics, businesses need more “top-management muscle” specialized in the field of data science. This specialized field has lead to the creation of roles like Chief Data Officer (CDO).

In addition, with more companies undertaking digital transformations, there’s greater impetus for the C-suite to make data-driven decisions. The CDO helps make data-driven decisions and also develops a digital business strategy around those decisions. As data grows at an unstoppable rate, becoming an inseparable part of key business functions, we will see the CDO act as a bridge between other C-suite execs.

Data skills an emerging business necessity

So far, only large enterprises with bigger data mining and management needs maintain in-house solutions. These in-house teams and technologies handle the growing sets of diverse and dispersed data. Others work with third-party service providers to develop and execute their big data strategies.

As the amount of data grows, the need to mine it for insights becomes a key business requirement. For both large and small businesses, data-centric roles will experience endless upward mobility. These roles include data anlysts and scientists. There is going to be a huge opportunity for critical thinkers to turn their analytical skills into rapidly growing roles in the field of data science. In fact, data skills are now a prized qualification for titles like IT project managers and computer systems analysts.

Forbes cited the McKinsey Global Institute’s prediction that by 2018 there could be a massive shortage of data-skilled professionals. This indicates a disruption at the demand-supply level with the needs for data skills at an all-time high. With an increasing number of companies adopting big data strategies, salaries for data jobs are going through the roof. This is turning the position into a highly coveted one.

According to Harvard Professor Gary King, “There is a big data revolution. The big data revolution is that now we can do something with the data.” The big problem is that most enterprises don’t know what to do with data. Data professionals are helping businesses figure that out. So if you’re casting about for where to apply your skills and want to take advantage of one of the best career paths in the job market today, focus on data science.

I’m compensated by University of Phoenix for this blog. As always, all thoughts and opinions are my own.

For more insight on our increasingly connected future, see The $19 Trillion Question: Are You Undervaluing The Internet Of Things?

The post Data Analysts and Scientists More Important Than Ever For the Enterprise appeared first on Millennial CEO.

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Daniel Newman

About Daniel Newman

Daniel Newman serves as the Co-Founder and CEO of EC3, a quickly growing hosted IT and Communication service provider. Prior to this role Daniel has held several prominent leadership roles including serving as CEO of United Visual. Parent company to United Visual Systems, United Visual Productions, and United GlobalComm; a family of companies focused on Visual Communications and Audio Visual Technologies. Daniel is also widely published and active in the Social Media Community. He is the Author of Amazon Best Selling Business Book "The Millennial CEO." Daniel also Co-Founded the Global online Community 12 Most and was recognized by the Huffington Post as one of the 100 Business and Leadership Accounts to Follow on Twitter. Newman is an Adjunct Professor of Management at North Central College. He attained his undergraduate degree in Marketing at Northern Illinois University and an Executive MBA from North Central College in Naperville, IL. Newman currently resides in Aurora, Illinois with his wife (Lisa) and his two daughters (Hailey 9, Avery 5). A Chicago native all of his life, Newman is an avid golfer, a fitness fan, and a classically trained pianist

When Good Is Good Enough: Guiding Business Users On BI Practices

Ina Felsheim

Image_part2-300x200In Part One of this blog series, I talked about changing your IT culture to better support self-service BI and data discovery. Absolutely essential. However, your work is not done!

Self-service BI and data discovery will drive the number of users using the BI solutions to rapidly expand. Yet all of these more casual users will not be well versed in BI and visualization best practices.

When your user base rapidly expands to more casual users, you need to help educate them on what is important. For example, one IT manager told me that his casual BI users were making visualizations with very difficult-to-read charts and customizing color palettes to incredible degrees.

I had a similar experience when I was a technical writer. One of our lead writers was so concerned with readability of every sentence that he was going through the 300+ page manuals (yes, they were printed then) and manually adjusting all of the line breaks and page breaks. (!) Yes, readability was incrementally improved. But now any number of changes–technical capabilities, edits, inserting larger graphics—required re-adjusting all of those manual “optimizations.” The time it took just to do the additional optimization was incredible, much less the maintenance of these optimizations! Meanwhile, the technical writing team was falling behind on new deliverables.

The same scenario applies to your new casual BI users. This new group needs guidance to help them focus on the highest value practices:

  • Customization of color and appearance of visualizations: When is this customization necessary for a management deliverable, versus indulging an OCD tendency? I too have to stop myself from obsessing about the font, line spacing, and that a certain blue is just a bit different than another shade of blue. Yes, these options do matter. But help these casual users determine when that time is well spent.
  • Proper visualizations: When is a spinning 3D pie chart necessary to grab someone’s attention? BI professionals would firmly say “NEVER!” But these casual users do not have a lot of depth on BI best practices. Give them a few simple guidelines as to when “flash” needs to subsume understanding. Consider offering a monthly one-hour Lunch and Learn that shows them how to create impactful, polished visuals. Understanding if their visualizations are going to be viewed casually on the way to a meeting, or dissected at a laptop, also helps determine how much time to spend optimizing a visualization. No, you can’t just mandate that they all read Tufte.
  • Predictive: Provide advanced analytics capabilities like forecasting and regression directly in their casual BI tools. Using these capabilities will really help them wow their audience with substance instead of flash.
  • Feature requests: Make sure you understand the motivation and business value behind some of the casual users’ requests. These casual users are less likely to understand the implications of supporting specific requests across an enterprise, so make sure you are collaborating on use cases and priorities for substantive requests.

By working with your casual BI users on the above points, you will be able to collectively understand when the absolute exact request is critical (and supports good visualization practices), and when it is an “optimization” that may impact productivity. In many cases, “good” is good enough for the fast turnaround of data discovery.

Next week, I’ll wrap this series up with hints on getting your casual users to embrace the “we” not “me” mentality.

Read Part One of this series: Changing The IT Culture For Self-Service BI Success.

Follow me on Twitter: @InaSAP

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Running Future Cities on Blockchain

Dan Wellers , Raimund Gross and Ulrich Scholl

Building on the Blockchain Framework

Some experts say these seemingly far-future speculations about the possibilities of combining technologies using blockchain are actually both inevitable and imminent:


Democratizing design and manufacturing by enabling individuals and small businesses to buy, sell, share, and digitally remix products affordably while protecting intellectual property rights.
Decentralizing warehousing and logistics by combining autonomous vehicles, 3D printers, and smart contracts to optimize delivery of products and materials, and even to create them on site as needed.
Distributing commerce by mixing virtual reality, 3D scanning and printing, self-driving vehicles, and artificial intelligence into immersive, personalized, on-demand shopping experiences that still protect buyers’ personal and proprietary data.

The City of the Future

Imagine that every agency, building, office, residence, and piece of infrastructure has an entry on a blockchain used as a city’s digital ledger. This “digital twin” could transform the delivery of city services.

For example:

  • Property owners could easily monetize assets by renting rooms, selling solar power back to the grid, and more.
  • Utilities could use customer data and AIs to make energy-saving recommendations, and smart contracts to automatically adjust power usage for greater efficiency.
  • Embedded sensors could sense problems (like a water main break) and alert an AI to send a technician with the right parts, tools, and training.
  • Autonomous vehicles could route themselves to open parking spaces or charging stations, and pay for services safely and automatically.
  • Cities could improve traffic monitoring and routing, saving commuters’ time and fuel while increasing productivity.

Every interaction would be transparent and verifiable, providing more data to analyze for future improvements.


Welcome to the Next Industrial Revolution

When exponential technologies intersect and combine, transformation happens on a massive scale. It’s time to start thinking through outcomes in a disciplined, proactive way to prepare for a future we’re only just beginning to imagine.

Download the executive brief Running Future Cities on Blockchain.


Read the full article Pulling Cities Into The Future With Blockchain

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Dan Wellers

About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

Raimund Gross

About Raimund Gross

Raimund Gross is a solution architect and futurist at SAP Innovation Center Network, where he evaluates emerging technologies and trends to address the challenges of businesses arising from digitization. He is currently evaluating the impact of blockchain for SAP and our enterprise customers.

Ulrich Scholl

About Ulrich Scholl

Ulrich Scholl is Vice President of Industry Cloud and Custom Development at SAP. In this role, Ulrich discovers and implements best practices to help further the understanding and adoption of the SAP portfolio of industry cloud innovations.

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4 Traits Set Digital Leaders Apart From 97% Of The Competition

Vivek Bapat

Like the classic parable of the blind man and the elephant, it seems everyone has a unique take on digital transformation. Some equate digital transformation with emerging technologies, placing their bets on as the Internet of Things, machine learning, and artificial intelligence. Others see it as a way to increase efficiencies and change business processes to accelerate product to market. Some others think of it is a means of strategic differentiation, innovating new business models for serving and engaging their customers. Despite the range of viewpoints, many businesses are still challenged with pragmatically evolving digital in ways that are meaningful, industry-disruptive, and market-leading.

According to a recent study of more than 3,000 senior executives across 17 countries and regions, only a paltry three percent of businesses worldwide have successfully completed enterprise-wide digital transformation initiatives, even though 84% of C-level executives ranks such efforts as “critically important” to the fundamental sustenance of their business.

The most comprehensive global study of its kind, the SAP Center for Business Insight report “SAP Digital Transformation Executive Study: 4 Ways Leaders Set Themselves Apart,” in collaboration with Oxford Economics, identified the challenges, opportunities, value, and key technologies driving digital transformation. The findings specifically analyzed the performance of “digital leaders” – those who are connecting people, things, and businesses more intelligently, more effectively, and creating punctuated change faster than their less advanced rivals.

After analyzing the data, it was eye-opening to see that only three percent of companies (top 100) are successfully realizing their full potential through digital transformation. However, even more remarkable was that these leaders have four fundamental traits in common, regardless of their region of operation, their size, their organizational structure, or their industry.

We distilled these traits in the hope that others in the early stages of transformation or that are still struggling to find their bearings can embrace these principles in order to succeed. Ultimately I see these leaders as true ambidextrous organizations, managing evolutionary and revolutionary change simultaneously, willing to embrace innovation – not just on the edges of their business, but firmly into their core.

Here are the four traits that set these leaders apart from the rest:

Trait #1: They see digital transformation as truly transformational

An overwhelming majority (96%) of digital leaders view digital transformation as a core business goal that requires a unified digital mindset across the entire enterprise. But instead of allowing individual functions to change at their own pace, digital leaders prefer to evolve the organization to help ensure the success of their digital strategies.

The study found that 56% of these businesses regularly shift their organizational structure, which includes processes, partners, suppliers, and customers, compared to 10% of remaining companies. Plus, 70% actively bring lines of business together through cross-functional processes and technologies.

By creating a firm foundation for transformation, digital leaders are further widening the gap between themselves and their less advanced competitors as they innovate business models that can mitigate emerging risks and seize new opportunities quickly.

Trait #2: They focus on transforming customer-facing functions first

Although most companies believe technology, the pace of change, and growing global competition are the key global trends that will affect everything for years to come, digital leaders are expanding their frame of mind to consider the influence of customer empowerment. Executives who build a momentum of breakthrough innovation and industry transformation are the ones that are moving beyond the high stakes of the market to the activation of complete, end-to-end customer experiences.

In fact, 92% of digital leaders have established sophisticated digital transformation strategies and processes to drive transformational change in customer satisfaction and engagement, compared to 22% of their less mature counterparts. As a result, 70% have realized significant or transformational value from these efforts.

Trait #3: They create a virtuous cycle of digital talent

There’s little doubt that the competition for qualified talent is fierce. But for nearly three-quarters of companies that demonstrate digital-transformation leadership, it is easier to attract and retain talent because they are five times more likely to leverage digitization to change their talent management efforts.

The impact of their efforts goes beyond empowering recruiters to identify best-fit candidates, highlight risk factors and hiring errors, and predict long-term talent needs. Nearly half (48%) of digital leaders understand that they must invest heavily in the development of digital skills and technology to drive revenue, retain productive employees, and create new roles to keep up with their digital maturity over the next two years, compared to 30% of all surveyed executives.

Trait #4: They invest in next-generation technology using a bimodal architecture

A couple years ago, Peter Sondergaard, senior vice president at Gartner and global head of research, observed that “CIOs can’t transform their old IT organization into a digital startup, but they can turn it into a bi-modal IT organization. Forty-five percent of CIOs state they currently have a fast mode of operation, and we predict that 75% of IT organizations will be bimodal in some way by 2017.”

Based on the results of the SAP Center for Business Insight study, Sondergaard’s prediction was spot on. As digital leaders dive into advanced technologies, 72% are using a digital twin of the conventional IT organization to operate efficiently without disruption while refining innovative scenarios to resolve business challenges and integrate them to stay ahead of the competition. Unfortunately, only 30% of less advanced businesses embrace this view.

Working within this bimodal architecture is emboldening digital leaders to take on incredibly progressive technology. For example, the study found that 50% of these firms are using artificial intelligence and machine learning, compared to seven percent of all respondents. They are also leading the adoption curve of Big Data solutions and analytics (94% vs. 60%) and the Internet of Things (76% vs. 52%).

Digital leadership is a practice of balance, not pure digitization

Most executives understand that digital transformation is a critical driver of revenue growth, profitability, and business expansion. However, as digital leaders are proving, digital strategies must deliver a balance of organizational flexibility, forward-looking technology adoption, and bold change. And clearly, this approach is paying dividends for them. They are growing market share, increasing customer satisfaction, improving employee engagement, and, perhaps more important, achieving more profitability than ever before.

For any company looking to catch up to digital leaders, the conversation around digital transformation needs to change immediately to combat three deadly sins: Stop investing in one-off, isolated projects hidden in a single organization. Stop viewing IT as an enabler instead of a strategic partner. Stop walling off the rest of the business from siloed digital successes.

As our study shows, companies that treat their digital transformation as an all-encompassing, all-sharing, and all-knowing business imperative will be the ones that disrupt the competitive landscape and stay ahead of a constantly evolving economy.

Follow me on twitter @vivek_bapat 

For more insight on digital leaders, check out the SAP Center for Business Insight report, conducted in collaboration with Oxford Economics,SAP Digital Transformation Executive Study: 4 Ways Leaders Set Themselves Apart.”

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Vivek Bapat

About Vivek Bapat

Vivek Bapat is the Senior Vice President, Global Head of Marketing Strategy and Thought Leadership, at SAP. He leads SAP's Global Marketing Strategy, Messaging, Positioning and related Thought Leadership initiatives.