This week we worked on various aspects of Future of Work.  At the center of this work is the Job Architecture.  This topic has gained so much attention in the last 18 months.  Rather than being a purely strategic initiative, Job Architecture must be well understood by both Strategic Workforce Planners and as well as Recruiters. This week’s email is an attempt to explain what is Job Architecture and why we need to pay attention to the same

Last week in Texas is almost back to normal weather, and I witnessed several lawns getting fertilized and getting ready for Spring.  As I was in the midst of Job Architecture design, I realized that the days of calling for a Drone Service to do the fertilizing is not far away.  As I observed the micro-tasks of fertilizing the lawn, there is a lot more strength in the argument that this task will be automated in the near future and can be ordered through an app very soon

While the tasks can be automated, interacting with the customers and providing suggestions will not be automated.  There is a reason for that.  The first wave of AI-led by the mathematical genius Alan Turing, started approximately in the year 1945.  Alan Turing’s famous work towards a simple question he proposed.  I propose to consider the question, ‘Can machines think?

The next 50 years went away in trying to make machines like humans.  This wave is considered a failure in academic circles.  The second wave of AI started post the internet era.  Here Machines were taught with some rules and a set of algorithms.  Rather than attempting to think like Humans, that focus was on how to perform the tasks at hand better.  This is a foundational shift in AI.  A flood of innovation happened with this thinking.  Factory automation, Agricultural crops management, Advanced formulations in medicines, Supply Chain Automation, Transportation, and in multiple areas, Machines entered smartly.  At this juncture, the boundaries and capabilities of machines are constantly expanding.

Let us look at the patent filed by Amazon on airborne fulfillment centers.  This is entirely designed with Drones doing the delivery.  (A concept called Drone Nests). “The AFC (airborne fulfillment center) may be an airship that remains at a high altitude (e.g., 45,000 feet), and UAVs with ordered items may be deployed from the AFC to deliver ordered items to user designated delivery locations,” the patent reads.

The rate and the way AI is evolving, there is a significant role for Humans.  This is where the story gets very interesting for Workforce Planners and Recruiters to focus on.  Let us look at the Education sector as an example.  Massive online courses, YouTube-driven lectures, study aids, global professors’ reach, and other technological advancements have not minimized professors and lecturers’ roles.  Before the pandemic, I attended one of Harvard’s free lectures, and it was packed full with people standing and taking notes.  This is because any job we design (across any function), the current state is the least advanced state it will ever be and will continually evolve.

Less than three years ago, financial analysts waited three days to get data feeds from IT to be uploaded in SAP-like platforms.  Today, they have grown so much to be able to leverage SQL and pull many reports themselves.  In this context, the whole Low Code/No Code movement needs to be understood by Workforce planners.

A low–code/no–code development platform is a visual software development environment that allows citizen developers (meaning any employee in an enterprise) to drag and drop application components, connect them together and create a mobile or web app.  Modules can be rearranged and repeatedly tested until the app works as expected.

This is perhaps the most fascinating trend that is happening.  So development may not be developer-constrained.  Appian is one such platform that is gaining a lot of attention. There are many platforms, and in some ways, the RPA tools are also in this category though low code/no code is a bit more cognitive.  The whole idea is how can the end users gain ML and AI capabilities without having to do development.

Everyone has some innovative ideas, and often the IT and Development requirements shut down such projects.  This may change.  Let us now look through the lens of why SWP and Recruitment should take this into account.  To demonstrate this, I have given the Emerging skills for few critical job families

• SWP Planners should have these skills in their Job Architecture and incorporate them across families.  (there is also a set of behavioral skills that is changing).  If we do not include these skills, the design of job Architecture becomes like the never-ending paint job at Forth Rail Bridge (a bridge so long that when you get to the end, you start painting the other end. Some say the paint job at the Golden Gate Bridge in California is also like that)
• For Recruiters, this gives a very wide range of keywords and algorithms on how to search.  Even a very surface understanding of these technologies will make a huge difference in your searches and interviews. 
• I am sharing a sample, and if you need more details about a particular job family, please let us know