Who moved my job? Long live my new Job - Part 1


Job's are a direct function of industry demand. Your salary depends on which segment of skill demand versus supply you represent. In this blog, we will try to get to the root cause of changing job demands in the industry beyond 2017 and try to base our blog on the 'ages of the industry'.

If you turn pages from Industrial history you would surely recognise three phases of dominance in the industry.

The first phase was the phase of manufacturing which started circa 1900 and ended 1960. This phase introduced the concept of fixed labour based jobs inside factories which engaged workers and supervisors in mass production of items.

The second age came in circa 1960 when the concept of distribution came into existence. Supply chain management, six sigma, Quality Assurance, Quality control, Kanban were born in this phase. This made items global and sourcing a big deal in business chain.

This IT age started in circa 1990 and ended by 2012. Although, very quite peaceful death.

Then came the age of Information. Most of us belong here - I belonged to this era when I joined the IT services industry 15 years ago. The age of information enabled IT which made connected PC's via client server and the internet along with in premise data center came into existence. It gave birth to the revolution of offshore which knocked huge opportunity, especially in India. This IT age started in circa 1990 and ended by 2012. Although, a small part is still alive as BAU (business as usual) support (legacy systems) and asset migration from in premise to cloud.

Industry regenerates itself by reinventing business models and this is what the current age is all about. This age is called as the age of the customer. The empowered business users and customer are calling the shots which decide the future of a company. In this age - an empowered customer is looking for a diverse business model, the vertical shift from cost centre to profit centre, digital based service offerings and continuous engagement via data-based decisions.

The shift between 2012 to 2017 has been very fast and has caught service providers in a fix and hence the job demand has not been anticipated very clearly.

In this age - an empowered customer is looking for a diverse business model, the vertical shift from cost centre to profit centre, digital based service offerings and continuous engagement via data-based decisions.

If we focus on the Indian job market - the demand from the traditional IT age to customer based digital age has caused a huge gap in demand and supply in the job market.

The previous skills of IT age included client-server programming, CRM, ERP, BI and web-based technology is the legacy in customer era. Clients are no longer interested in building their business strategy over these systems and would consider them as BAU (business as usual) system of records and build a totally new roadmap for the digital economy. Some will play safe and add the digital layer like analytics over the legacy investment as a hat.

But these are Enterprise architecture approaches. The fact still remains that skills of the yester age of IT are no longer in demand apart from the BAU production system needs.

Clients are no longer interested in building their business strategy over these systems and would consider them as BAU (business as usual) system of records and build a totally new roadmap for the digital economy.

So where does the cookie crumble in terms of the Digital era of empowered customers?

The answer lies in one primary area and this has propelled the empowered customer in current age to take data-driven decisions.

The answer is Data Science - This umbrella term has multiple skill demand in the role of data engineers, data architect, data analyst, data steward, data scientist (some see this as a team rather than a role) and Analytics manager. These skills are very different from the traditional IT services skill demands. These skills require a higher commitment to academics, greater programming skills, deeper understanding of the theory of computer engineering and statistics. Top skills needed here are: Higher education in computer science and statistics, Programming skills in R and Python, Data cycle concepts ,business domain skill along with strong interpersonal skills like problem solving, business analysis, end user interviewing skills, working in an agile mode and leadership.

Now, let us take a couple of profile from Indian context (leaving the few ivy leagues) and see if we may match them to this demand.

Mr X is a pass out from a Private engineering college in India. He has done some training and completed a mandated project as part of engineering course work. His coding is limited to C/C++ and Java if he is from CSE/IT. How can this profile be mapped? This profile lack business domain experience plus strong programming skill is generally missing considering multiple internet reports suggesting programming as a sub 10% available skill for Indian freshers. The only 'trainable' skill is data cleansing which will map to a data engineer. Rest of the roles will go unattended. Even the role of data engineer is not trained but trainable. Trainable would mean that a recruiting company would still need to invest in training of the employee post joining.

Miss Y is a PhD in Computer Science. Let us try to map this profile. Clearly here, we have the business domain and programming missing. Current PhD track is publication focussed in Journals where as the demand is to showcase programming algo and theories as codes in GitHub. The Hiring team needs to see quick demonstrated capability as GitHub codes and not publications. R and Python again are a missing link in most cases.The plus here is the background in statistics and computer engineering can go handy but goes way short to be mapped to a data architect role. Also, working in an agile environment which demands delivery every day of the work and status reported as a daily stand up meeting may go against the status quo of research for a longer duration often in years. Here business needs a solution in weeks and will not give you years to deliver a solution.

Media trends reports these demands upto 200,000 jobs in India by 2018

This creates a wide gap between demand and supply in the current job market as we saw in these two examples. Hence, this is also an opportunity for the right candidate.

Media trends reports these demands upto 200,000 jobs in India by 2018. But this present us with an 'unicorn' hunt from a scenario where a qualified candidate can demand very high salary in data areas with a starter demanding 9 lacks per annum and some seniors at 35 lacks per annum.

Conclusion: The jobs of the customer era will pay much more CTC than it paid in the IT age but the skills are not readily scalable in a factory model uplift. Hence, the overall employment % will drop if we look at net hiring rate. It would take a strong commitment from the learners to invest in learning to suit the customer era. The days of degree based jobs are gone and comes in skill profiling based employment.

In the next blog we would see how Machine Learning skill demand is related to the demand equation of the digital customer enpowered era.

About Author : Anirban has 15 years of experience in IT services industry working for various clients in utilities, telecom, automobile and chemical industry. Anirban holds a PMP from PMI, USA along with an engineering degree in Information Technology. Anirban has worked around the globe in UK, Singapore, Germany and India. His core skills apart from management are - SAP, Machine Learning, Deep Learning, OpenCV, ROS and data management. Anirban founded MieRobot blogs to motivate students in new areas of employment and skills around the world like robotics and machine learning.

References:

http://www.thehindubusinessline.com/info-tech/startups-forking-out-fat-pay-packets-to-attract-talented-data-scientists/article8276091.ece

https://en.wikipedia.org/wiki/Manufacturing

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