As an executive coach I am a qualified professional that works with individuals (usually executives, but often high-potential employees) to help them gain self-awareness, clarify goals, achieve their development objectives, unlock their potential, and act as a sounding board. The later as a consequence,  often expose my awareness to a vast amount of subjects,  one in particular drew my attention,  the challenge senior leaders face with the “DIGITAL TRANSFORMATION OF THE WORKFORCE” this topic push me to delve into the  workforce  transformation our  society is currently  experiencing.

One of the reasons this topic is sensitive  to me is that  it touches  the begin of my working life, in the 90’s I’ve started coding at very young age, my first computer program using Basic, Dbase and Clipper was at the age of 17. After few years I’ve been able to provide automation to payroll, accounting, school reports, credit control, chamber of commerce,  retail automation and you name it. I had 60% of the city business as my clients while finishing secondary school.  Coding came as a natural ability spending sleepless nights reading books and engaged on logic challenges, trails and tests with processing speed and data storage capacity limitations

We are in a state of revolutionary transformation as companies begin to apply artificial intelligence on a massive scale. Within intelligent automation enabled by AI old jobs will die, and new jobs are born at an accelerating pace. Digitalization affects both business processes and work culture,  in order to thrive in the technology revolution, corporations need to ensure that their employees are ready to face the new challenges and opportunities. Yet, according to the KPMG 2018 Global CEO Outlook report, CEO’s are not investing in the experts that enable change in their culture, or experts in learning and development1.
When skill gaps are ignored, or when leadership perpetuates antiquated training programs, the only way to fill those skill gaps is through firing and rehiring large segments of the workforce. This is neither economically, nor socially sustainable, and retraining programs are needed to help companies take advantage of the new technologies. I wrote this article to provide insights into the benefits of proactive retraining and reskilling, and to help better understand the economics of learning. Whether you are a CEO, executive, HR expert or L&D specialist, this insight will give you ideas of how to enable both socially and economically sustainable learning programs in your business. I hope this insight  will raise some questions: how would your business benefit from better learning? How could you make better investments in development? Could you retrain your employees rather than replacing them with workers possessing different skills? If it does, I am happy to talk with you to find out what your business can gain from a proper learning strategy.

The Fourth Industrial Revolution 
We are living in the era of the fourth industrial revolution (4IR). In contrast to past industrial revolutions, this one is driven by  the  adoption  of  new  technologies  at  an  exponential  rate.  Analytics,  artificial  intelligence  (AI),  cognitive  technologies,  and the internet of things (IoT) enable a new fusion between the digital and the physical worlds, creating a more holistic, interconnected digital enterprise. Data is collected from physical systems, processed, and then analyzed to drive intelligent actions. These feedback loops generate opportunities for new products and services, create new jobs and allow us to make changes to how we operate our businesses. The change is global, and not only technological, but also social and economic. (Deloitte, 2018)2.
Many companies face the challenge of implementing AI-based solutions in their business. Artificial intelligence solutions are so powerful that they will transform every industry. AI increases productivity and quality of services so much so that companies will be forced to adopt AI in order to remain competitive. Intelligent Automation applications set new standards of quality, efficiency, speed, and functionality. The companies that successfully employ intelligent automation may surpass competitors that do not employ intelligent automation. If companies take full advantage of intelligent automation, the overall impact on business could rival that of the enterprise resource planning wave of the 19903 Enterprise resource planning (ERP).

Currently, AI is being implemented to automate administrative, routine tasks.  We can already see vast implications of AI in the banking industry, where thousands of people are being laid-off. In any field, hundreds of thousands will face the same fate in the very near future. AI is impacting other industries like insurance, public administrative organizations, complex manufacturing, and professional services, and as a result of this transformational impact, we can also expect change on a societal level. McKinsey Global Institute estimates that 14 percent of the global workforce will need to switch occupational categories by 2030 as the world of work is disrupted (McKinsey, 2018)4. 50 percent of current work activities are technically automatable by adapting currently demonstrated technologies. In its 20th CEO survey, PwC found that 77 percent of the CEOs interviewed see the availability of key skills as the biggest threat to their business7. Even  with  the  emergence  of  robots  and  AI,  our  human  workforce  remains  integral  to  the  success  of  our  business.  It  is  important to consider the impact that digitization, automation and AI will have, not only on day to day tasks, but on work culture as a whole.


The Employee Revolution
The pressure for transformation in our society is caused by two factors: longevity and the accelerated rate of change in our environment. These prevailing megatrends are illustrated in the figure below by McGowan & Shipley. Gone are the days when formal education was the only education anyone needed to succeed. Now and in the future, most learning will take place within organizations and the ecosystems surrounding them. McGowan claims that all of the successful enterprises today are in the learning business8, including e.g  Apple, Amazon and Facebook. Lifelong learning is no longer an option, it is a necessity. The transformation illustrated in Figure 1 will hit many industries. The first industries that will be impacted are those that have predictable environments, like operating machinery or preparing fast food. Machines can work more efficiently than humans by collecting and processing data5. Software automation and even more sophisticated forms of AI-based implementations, like Intelligent Automation, will inevitably alter many administrative jobs in the public sector, banking and finance, advanced manufacturing and expertise-based services

In a recent interview Mr. Reijo Karhinen, CEO of OP Financial Group, expressed his vision of the future. Based on a lifetime of experience in the Finnish banking sector, he predicted that 1/4 of the jobs in banking will disappear in the next few years.9 McKinsey Global Institute estimates that between 400 million and 800 million individuals could be displaced by automation and need to find new jobs by 2030 around the world5


Meet Your New Co-Workers
Employees that retain their jobs will face a new world of working side-by-side with robots and AI. In addition to autonomous vehicles, self service point of sale systems, and fully automated manufacturing robots, we see AI sneaking into jobs that typically require human intelligence. Here are a few examples:


Artificial Intelligence

AI applications today are made to help humans think better10. AI solutions are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages11

 
Intelligent Automation

Intelligent automation is a combination of AI and automation. Intelligent automation systems sense and synthesize vast amounts of information and can automate entire processes or workflows, learning and adapting as they go3.


Process Automation Robots

Robotic  Process  Automation  (RPA),  the  first  stage  of  Intelligent  Automation,  is  a  way  to  automate  repetitive and often rules-based processes. RPA robots undertake transaction processing just like their human counterparts and can work on multiple processes, across multiple functions (e.g finance cash postings in the morning, work on HR processes in the afternoon)12.  


Personal Assistants 

AI-powered personal assistants blend into other technologies, making it possible to easily search for information and automate routine tasks, such as calendar booking. Apple’s Siri, Microsoft’s Cortana and Google Assistant are already well known personal assistants.


Customer Service Bots

In customer service, chatbots are used to answer questions in a friendly and familiar chat interface. A chatbot can be trained to understand and answer predefined set of frequently asked questions. As a fallback if a bot can’t serve the customer’s request, the bot can forward the question to a real person.

 Digital Learning Assistants

Chatbots can be very efficient in mimicking human interaction. This was proven by a Georgia Tech professor, who used chatbot to answer students’ questions throughout the semester13. A chatbot, also known as a digital learning assistant, can be used in corporate environments to help employees learn at their own pace, at any hour of the day, and also has the power to make the learning experience highly personalized.


Not all jobs can be automated. Jobs involved in managing people, applying expertise or creativity, and social interactions will remain in human hands5. The demand for talent and the right skills is high. Quite often “CEOs wish to find unicorns; the fully-formed employees with the precise skills that the organization needs not only today, but for whatever the future may bring”7. But as technology continues to change the environments in which we work, the definition of the ‘perfect employee’ will continue to change as well


The Most Wanted Skills

Soft skills are becoming more valuable for both the employee and the employer, as CEOs see the value in marrying technology with exclusively human capabilities7. The modern employees have good social and emotional skills, making them good communicators5

The  most  in-demand  skill  set  includes  adaptabilityproblem-solving,  logical  reasoning,  creativity  and leadership7.

The most desirable employees should be the learners – those with curiosity and the ability to innovate. 

Adaptability – Problem-solving – Creativity – innovation Leadership


“Cultivate  the  workforce’s  creativity  and  digital  dexterity.  Humans’  contributions  should focus on developing new ideas and revising workflows to exploit the latest technological advances.14Gartner, Future of Work Scenarios 2035: ‘I’d Rather Have a Bot Do It’ Van L. Baker, Tom Austin, 4 April 2018

The Two-Sided Challenge

In the chart above, McGowan illustrates how in the future more skilled employees are needed to complete complex tasks side-by-side with Artificial Intelligence solutions. On the other end, the work tasks that are routine and predictable can be replaced with automation and those jobs that can’t be automated are split into smaller tasks (atomisation) and given to those who are willing to complete a task at the lowest cost15


Digital enterprises are facing a two-sided challenge: they are forced by competitors into automating their processes and yet they have to keep their reputation as a responsible and respected employer in order to attract and retain talent7. The conclusion in the IMF Working Paper was that “automation is good for growth and bad for equality”16. How can companies find the balance between remaining competitive through automation and being socially responsible? It seems that while society is using technology more than ever, companies must become more humane than ever. 
History has shown us that with new technologies come new jobs5. As new technologies emerge, new jobs are born. Dr. Ashkan Fardost reminds us that this industrial revolution, also known as industrial 4.0, is nothing alien; we’ve had machine takeovers in industries many times in the past. Emerging technologies have always led to an increase in the value chain that resulted in new demands in terms of skill and intellect in people.17 Companies will have to find the right combination of digital assets and human skills in order to realize the advantages of AI18. There’s a need for a whole new generation of technology specialists. But who’s going to train them?


Intelligent Automation experts are currently in very high demand, and the gap in the job market is expected to grow over the next ten years. Salaries for Data Scientists, Machine Learning experts and Intelligent Automation experts are already growing quickly. There is a fixed cost associated with hiring and firing, and this creates an economic reason for reskilling part of the workforce. 
The skills that companies require of their workforce are already changing. As the rate of change increases, companies will continue to struggle with identifying skill gaps and how job functions must subsequently evolve.6
Well-organized knowledge capture and management is crucial in the digital enterprise. How aware are you of the talent that exists within your company and what skill-sets will your company require over the next five to ten years? How can you map and predict the future of your company’s current talent pool and processes? Should you train your existing employees to master the skills, or hire a new generation?

A Sustainable Learning Strategy

The dream of finding unicorns, the fully-formed employees ready to take on any given work task, will always be  there.  But  even  the  unicorn’s  skills  will  become  outdated.  It  is  impossible  to  know  what  kind  of  new  job  roles we will have in a few years. Or as Gartner puts it: “Nearly 80% of business and IT executives expect skills and knowledge in 10 years to have little resemblance to those their organizations have today.”21 In order to stay competitive, corporations must act. This is where enterprise performance management and employee development merge together. According to the World Economic Forum’s report: “Once we know the knowledge and skills requirements of a  job,  we  can  assume  that  employees  transitioning  out  of  that  job  will  be  able  to  bring  those  capacities  into  any new roles”22. Even though job roles change, the skills should transformed to serve new positions. Existing employees always possess knowledge about the company and the work context, that has been built over time. This knowledge offers a solid foundation for successful retraining and development programs

.
The Best Employees Are Made, Not Found

The solution in finding (and keeping) the right skills is to develop them from existing internal talent. In a recent paper about IT roles and talent profiles, Gartner recommends CEO’s to “Devise a strategic plan to take bold steps to source and develop talent.”21  The World Economic Forum emphasizes that it is crucial that businesses support their current workforces by training23.


Construct a Learning Strategy

Building a corporate academy and a successful learning strategy starts with understanding the business goals, and the skills needed to achieve them. A strong learning and training strategy will make sure that employees’ skills are kept up to date, while jobs continue to evolve with technology.

 
What new skills are needed?

What new job roles need to be created?

What old job roles are no longer necessary? 

When new skills are achieved, how could they be applied to future job roles?


The next step is to map the existing skills and knowledge in the company. Once the skills are recorded, the skill gaps can be found and personal learning goals set. Knowing your employees’ skills throughout the process will help you decide which new skills can be trained, and which skills need to be acquired by hiring. McKinsey Global Institute reports that a traditional approach to training and retraining often stresses theory too much, when in fact practical skills should be the focus6. In building the learning strategy, it is important to keep in mind how the learning should actually happen. Should learning be social, digital, practical, formal or informal? Should you offer theory or practical challenges? According to the 70:20:10 learning model it should be all of this, but in the right proportion24. Learning should be up to 90% informal, learning by doing or learning from co-workers.


If a corporate academy built correctly, learning is integrated in the flow of day to day work. Using a sophisticated digital learning solution makes learning new skills more relevant to actual work tasks, and the learning materials are available when they are needed the most, to support the work assignments. Once constructed, the new learning strategy should be piloted to test these new practices and enable the use of predictive models. Predictive analytics will make it possible to create high quality learning material, as they help in predicting what will happen and recognize the bottlenecks in the processes and areas to improve the content.


Invest in Learning Content

A great learning strategy and a solid technological learning solution are useless without carefully produced learning material. Different types of topics and objectives require different kinds of materials. The right kind of content is optimized for the purpose, personalized for the individual needs, and serves the company objectives. The learning solution in use should bend to meet the requirements of the content and strategy.
When designing learning content, we should ask ourselves these four questions:


What needs to be learned?

Who needs to learn it?

How should the learning materials be constructed and delivered?

How do we measure the impact of learning on our business?


When the learning objectives are clear, it becomes very easy to not only monitor and review learning activities and behaviours, but also to link learning activities to business outcomes. Once learning materials are produced, they need to be constantly reviewed. Adjusting the materials with the help of learning analytics makes it possible to increase the production value of the learning program, leading to higher retention and shorter time to competence.


Choose the Right Tools

The learning development market offers a variety of different learning  solutions.  Out-of-the-box-solutions  promise  fast  success, and highly customizable learning experience platforms (LXP) promise precise results.  A corporate academy can be built on both. However, according to Deloitte, the latter offers more tools in personalizing, curating, searching and analyzing the content28.
A  modern  corporate  academy  harnesses  the  powers  of  Artificial Intelligence and Intelligent Automation, and molds these technologies into a system that seamlessly supports the development of the workforce. With a learning experience platform also comes integration capabilities, enabling access to multiple technologies via a single touchpoint28

Conclusions 
Get started with an economical learning strategy. Businesses need to be aware of the possibilities that learning can bring to them. Optimal investments  in  L&D  can  create  massive  savings, especially when  the  alternative is hiring and firing. 
Know what your employees are capable of. What skills and knowledge do you have in your organization? When you have a better idea of what skills your employees collectively possess, it is much easier to identify areas for improvement and provide training accordingly.
A good training program is an investment in the future – better customer experience and scalability. Digital training is scalable and when done well, the same materials can be used to train thousands of people.
Analytics help you in making better decisions with predictable outcomes. By tracking all of the learning data available to you, and leveraging predictive analytics, you can begin to understand how the learning impacts business and predict the future training needs. 
Not only have AI and intelligent automation become part of the daily work  tasks  for  many,  but  they  are  also  used  to  support  corporate  learning. It is crucial to find the right tools to measure the learning impact and offer the learning in a timely and personalized fashion. Investing in a learning platform that supports intelligent technologies will help you in creating the most efficient learning program for your employees.

Renato Moreira – Executive Coach

References:
1 – Growing pains – 2018 Global CEO Outlook. KPMG.  http://bit.ly/kpmg-growing-pains

2 – Renjen, Punit. The Industry 4.0 manufacturing revolution. Deloitte Insights.  http://bit.ly/deloitte-insights-1

3 – Schatsky, David; Mahidhar, Vikram. Intelligent automation: A new era of innovation. Deloitte Insights. http://bit.ly/deloitte-insights-2

4 – Kauppalehti. “Nordeassa tuhat tehtävää siirtyy roboteille yksin tänä vuonna …”  http://bit.ly/kauppalehti-nordea

5 – Manyika,James; Lund, Susan; Chui, Michael; Bughin, Jacques; Woetzel, Jonathan; Batra, Parul; Ko, Ryan; Sanghvi, Saurabh. Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages. McKinsley Global Institute.  http://bit.ly/mck-future-of-jobs  

6 – Illanes, Pablo; Lund, Susan; Mourshed, Mona; Rutherford, Scott; Tyreman, Magnus. Retraining and reskilling workers in the age of automation. McKinsey Global Institute. https://mck.co/2BBJNgm

7 –  CEO Survey Global Talent. PwC.  http://bit.ly/pwc-ceo-survey

8  Heather McGowan. OEB Berlin: Learning Uncertainty. YouTube. http://bit.ly/heather-mcgowan-1

9  Helsingin Sanomat. OP-ryhmästä häviää tuhansia työtehtäviä jo lähivuosina, varoittaa eläkkeelle jäävä pääjohtaja Reijo Karhinen HS:n haastattelussa. http://bit.ly/hs-op  

10  Guszcza, Jim. Smarter together: Why artificial intelligence needs human, Deloitte. http://bit.ly/deloitte-insights-3

11  Oxford Dictionaries. https://en.oxforddictionaries.com

12  Deloitte: The robots are here – Meet your digital workforce. http://bit.ly/deloitte-rpa

13  McFarland, Matt. What happened when a professor built a chatbot to be his teaching assistant. The Washington Post.  http://bit.ly/wapo-teaching-assistant

14  Gartner: Future of Work Scenarios 2035: ‘I’d Rather Have a Bot Do It’. https://gtnr.it/2OSt622

15  McGowan, Heather; Shipley, Chris. Debate Prep: When Trump Says “Jobs” Think Algorithms, Not Immigrants. Medium. http://bit.ly/-medium-heather-mcgowan  

16  Berg, Andrew; Buffie, Edward F; Zanna, Luis-Felipe. Should We Fear the Robot Revolution? (The Correct Answer is Yes). International Monetary Fund. http://bit.ly/imf-robot-revolution  

17  Fardost, Ashkan. The most valuable lesson on digitalization according to Dr. Ashkan Fardost. Valamis. http://bit.ly/valamis-ashkan-fardost  

18  Bughin, Jacques; Hazan, Eric; Ramaswamy, Sree; Chui, Michael; Allas, Tera; Dahlström, Peter; Henke, Nicolaus; Trench, Monica. How artificial intelligence can deliver real value to companies. McKinsey Global Institute. https://mck.co/2BveKTB

19  Rittenberg, Libby; Tregarthen, Tim. Principles of Microeconomics. MIT Open Coursware. http://bit.ly/mit-microeconomics-1

20  IBM. Predictive Analytics. http://bit.ly/ibm-predictive-analytics

21  Gartner: CIOs Must Evolve IT Roles and Talent Profiles to Adopt and Scale Bimodal. https://gtnr.it/2Pog5hU  

22  World Economic Forum. Towards a Reskilling Revolution – A Future of Jobs for All. http://bit.ly/world-economic-forum-1  

23  World Economic Forum. The Future of Jobs. http://bit.ly/world-economic-forum-2

24  Center for Creative Leadership. The 70-20-10 Rule for Leadership Development. http://bit.ly/ccl-70-20-10

25  Gartner: Market Guide for Corporate Learning Suites. https://gtnr.it/2N8a7jx

26  Valamis Listed as a Representative Vendor in Gartner’s 2018 Market Guide for Corporate Learning. Valamis.  http://bit.ly/valamis-gartner-market-guide  

27  Valamis Shortlisted in Deloitte’s Learning Experience Platform Market Overview. Valamis. http://bit.ly/valamis-deloitte-shortlist  

28  Clarey, Janet. Learning Experience Platforms: Solution Provider Capabilities. Deloitte Development LLC. 

29  Machine Learning Engineer Salaries in the United States. Ineed.com https://indeedhi.re/2Qnvek0

International experience in organisational and leadership development, consultant for business leaders to build and implement a comprehensive global approach to excellence, personal development, moderator for meetings, facilitator, motivational, cultural change management, NLP trainer and Executive Coach; Drive accountability and sustainability of development with a focus on creating a strong development culture.

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