Technology today is evolving at the most rapid pace ever. It is no wonder that the demand for skills pertaining to the latest technologies are at an all-time high, too. Forbes recently listed machine learning (ML) and artificial intelligence (AI) cloud amongst the top 10 digital skills. Additionally, according to a McKinsey report, 25-50 million emerging tech jobs are going to be created within the next 12-15 years. Of these, India alone needs to produce six million to 12 million jobs.

The existing demand-supply gap for these skills, however, affected the industry's performance in 2018. According to NASSCOM, this was due to the shortage of 140,000 skilled techies for 500,000 jobs available in the industry across verticals. This unmet demand has consequently led to an increase in the salaries of fresh and experienced talent in the field by as much as 60-80 percent. Talent is the biggest emerging theme that will define the next battleground.

According to a Wipro report, several large conglomerates, including TCS and Capgemini offer packages of up to 6-7 lacs to freshers if they are equipped with the relevant digital skills. Therefore, while in totality there is a huge demand and fat paychecks are up for grabs, it is increasingly becoming difficult to get more of this scarce resource. But unlike the U.S., where there are only two percent engineers available and hence only one in four job positions being filled, India has the largest pool of software engineers in the world. India also has the largest number of engineers graduating per year.

The area India needs to improve is investing in the upskilling of available talent pool. And, rightly so, this area is getting the maximum focus, both from the industry and the government. The Indian Government, through the National Skill Development Corporation (NSDC), is working hard to improve the current skill gap.

There is, however, the need for a deeper understanding of the problem, so as to approach the solution more effectively. According to the All India Council for Technical Education (AICTE), out of a million people who graduate in engineering and other technical courses, 80 percent are unemployed and 45 percent are unemployable. This problem of unemployable graduates is most prevalent in Tier II cities.

A study by analytics firm Aspiring Minds showed only 4.8 percent candidates could write correct logic for a program, and only 1.4 percent could write correct and ethical code. The study further revealed that only 20 percent engineers are employable to IT services, four percent to IT products, 45 percent to BPO industry, 15 percent to KPO industry, 20 percent to software tech and 45 percent to hardware networking. So, the majority of these engineers end-up taking non-IT jobs. Yet, it makes sense that most graduating engineers would want jobs in software engineering or core engineering. Therefore there is a need for this employability trend to be reversed, as an additional 2-4 lakh engineers need to be made employable.

If we were to pin-down the reason for this gap, it would simply be the lack of experience in the relevant skills that are required for emerging tech jobs. According to the Developer Skills report of an online learning platform,

there is a strong mismatch between the framework and skills required in the corporate world and the ones being taught to students. In an internal study conducted with more than 1000 fresh engineers, it was found that the most significant reason for not being able to find a tech job was low confidence in the ability to code. Close to 80 percent of the engineers blamed lack of focus and hands-on coding experience for this situation.

Within our education system, as well as the multitude of up-skilling and re-skilling options available, this unique requirement of ensuring deep and strong experiential learning is missing. Additionally, today, with the increasing requirements of the tech industry, the tech talent requirements are also wide and varied. The needs, more often than not, are a mixture of multiple coding languages and frameworks required to make the product usable.

Every professional program out there has an inbuilt deep experiential learning component without which the program is incomplete. In Medicine, every doctor has to undergo a compulsory extended duration of ‘hands-on’ learning where the young doctor learns under the guidance and mentorship of the experienced doctors - this is called ‘Residency’. Similarly in Chartered Accountancy has an ‘Article-ship’, and in Law there is an ‘Apprenticeship’. While the periods of learning are different, in each profession the understudy learns while working at it by themselves. This experiential learning that is inherently expected in, and hence built into, these professional programs ensures quality and relevant skill application of the talent.

There is a strong mismatch between the framework and skills required in the corporate world and the ones being taught to students

What can we infer from these models of learning? We learn that in order to develop a truly professional and deep-impact tech talent pool, the candidate has to first be skilled using the elements of deep experiential learning in live or live simulated environments with real deliverables which matter. Second, they need a hands-on and Do-it-Yourself approach. Finally, they need industry experts as mentors. It is important, for the technology space too, that we learn and evolve a solution in a similar manner.

Engineering does have an industry project built into the curriculum. However, for various reasons, this does not give the student enough exposure and hands-on experience to make them confident coders. Also engineers may be in non-computational fields to start with, hence their projects may not be relevant to a coding job. The second problem of variable and mixed requirements can, therefore, be solved by having a program which has the three elements mentioned above, and is further based on the exact requirements of the specific industry or product.

Tailoring each program to specific job requirements will ensure that we are able to increase an employable base of engineers and also maximize job opportunities. This kind of customization has been seen in many similar fields where big data and AI/ ML have made it a possibility with minimum effort. The simplicity of this solution is easily evident when we apply this to re-skilling of experienced engineers. This will allow engineers to have fruitful careers in their respective domains and revive the prospects of the domain as an integral part of the future business ecosphere.