The Future Work Economy

A topic I have been thinking about for a while now is what is the future of work, and of employment. There are a number of questions which come up, to which I must say I don’t have any answers.

One question I think about is the expected mismatch between the demand and availability of work in the future. Another is about the possible mismatch between skills requirement and availability.

Coming to the question of expected mismatch between work demand and availability, one dimension we need to consider, when building future scenarios is overall population. We are told repeatedly that technology is meant to make our lives easier, so we can spend more time with our loved ones. While thats a nice idea, what that means is that in the future, we are likely going to see much more work being automated at a global level, with people having to work less and less. This means lower demand for human resources, which could lead to a future this op-ed from Washington Post describes.

That said, however, there is another aspect which we need to consider. This is the fact that while a number of traditional occupations might not be around a few decades from now, there are likely going to be a number of new occupations, or even industries which could be generated over a period of time, as this piece from University of Kent tells us. While video games have been around for a while, no one could have anticipated the level of growth the gaming industry would see, for instance. New occupations and industries, of course, would require different skills, something we need to prepare our children for.

The other dimension is the mismatch between skills demand and availability. With Europe growing older, for instance, Europe will likely need to import workers, and with Africa growing younger, its quite simple to see where the additional workers required would come from.

This is an illustration of possible imbalances we could see in the future. The larger point here is this … the regions of the world which are well-off are likely to have fewer people in working age-groups in the future, while the regions which would have larger working-age populations would likely be unable to give access to the kind of education required to meet the needs of the job market.

Does this mean that it might be important for certain regions of the world to subsidise education and skill-building in other parts of the world? Should Japan, for instance, invest in education/skill-building in India? In other words, are we headed toward a far more integrated world as the viable solution to the problems of tomorrow?


Predictive Learning

In todays L&D landscape, the way businesses determine who should participate in what training isnt far away from some sort of conjuring act. More often than not, the result of this is a mixed bag, and many of the L&D professionals I speak to tell me that the L1 scores (based on the Kirkpatrick model) are more often than not tending towards the lower end of the spectrum.

There are typically two ways a business determines training participation. One is based on mandated training (usually related to promotion/growth), while the other is nomination by the business manager. Both of these are based on picking up from a ‘menu’ of available programs, and neither really takes into consideration the actual learning needs of the individual.

This is where the idea of predictive learning comes in. The idea here is simple … today, with the technology available to us, especially in the Big Data/Analytics domains, the data about what has worked in the past in what context is available to the organization in a large scale. This data is available based on training, HR, and operations/business data. This rich data can be leveraged to determine what is the best training solution which would likely work in a particular employee context. Like Big Data, this neednt look at the reason (or connection) between cause and effect, rather, look at the linkages as they have been seen in the past.

An important aspect of this picture is that this shifts the focus from training and learning, and from L&D to the individual learner, and makes the entire process people-centric.

One concern with this, though, could be that the outcome of the requirements could be way too granular, and too tailored to individual needs, so as to be unviable from the delivery perspective. More about this later …


HR Change Agenda

Over the last few days, two pieces have appeared in HBR, about the change agenda for HR. One is written by Ram Charan, which talks about splitting HR, while the other, written by Cathy Benko and Erica Volini, about what it will take to fix HR. At the most fundamental level, both these pieces acknowledge the fact that there is a problem with the HR function in the organization. And since they agree on that, they also agree that something needs to be done about it. And thats where, more or less, they move in different directions, as you would see from the blogs.

Lets step back, and take a look at some of the reasons why these problems are there, coming from the perspective of HR practitioners. The first aspect we need to understand is that in today’s world of business, with a steady level of complexity, and increasing levels of disruptive changes, HR managers need to understand details of the business, both internal and external to the organization. Only then can HR managers play a meaningful role in defining organization strategy. In other words, HR managers need to be at the confluence of business management, and people management. However, most of the HR practitioners I talk to are nowhere close to this point. Most HR practitioners are generalists, and not SMEs when it comes to business operations. This means that they need to take guidance from business managers, and formulate practices based on this guidance.

Because that might sound a bit abstract, let me take an example. Lets say a business manager decides that there are some skills lacking in his team. The manager would reach out to the L&D team, tell them what type of training is required, and the L&D team would search through a catalogue, identify the training, and execute the logistics to deliver the training. The L&D team, in this example, has no understanding of the reason for the training requirement, the objective that is to be met, or the outcomes that should come out of the training for participants. In this scenario, the team is essentially fulfilling requirements, rather than giving strategic inputs into the forecasting of medium- to long-term training needs, how these would help address business objectives, and address employee development.

To summarize, it is at the intersection of business and people management that there is a gap, and filling this gap is the need which needs to be addressed. To address this, we need people who have a sound understanding of the complexity and challenges of business, and how people practices can help to address those challenges and meeting that complexity. Whether this is to be achieved by splitting the HR function, I dont know, though the debate throws up more questions than just that. It raises the point that I am talking about here … that in stead of HR practitioners only taking guidance and fulfilling requirement, HR practitioners need to be in a place where they can add strategic value, and that this requires a change in the way HR managers look at the intersection of business management and people management.


TM/HR

Over a period of time, the concept of Talent Management has become a hot topic in HR circles, and many people are talking about the idea. However, I dont quite know any two sources which give the same definition of Talent Management. A number of things I have read include:

  • Talent Management is strategic while HR is transactional
  • Talent Management is about retaining high-flyers while HR is for lesser mortals
  • Talent Management is about managing skills while HR is about managing the policies related to people
  • Talent Management is old wine in new bottles
  • Its a term coined by clever management consultants to make a quick buck (no I havent read that but thats always a pet theory of quite a few people, isnt it?)

Are these true? I dont quite think so. To some extent, I feel Talent Management is the natural progression from the HR philosophy. Essentially, I feel the difference between HR and TM are more to do with how the organization looks at its main asset … people! In the earlier, HR world, people were one of the factors of production, and of creating value for the organization in a sort of undistinguished way, somewhat (though this is not exactly an accurate parallel, but just to create an illustration) like one machine is interchangeable with another machine, and none the wiser.

TM is based on the understanding that each individual is a distinct one, and each one has a distinct personality, a particular set of talents and skills, aspirations and potential which is unique to each one, and so, need to be treated iondividually. This means that the growth needs, based on their aspirations, would be different for different people, which means that development plans, both in terms of skills development and individual growth in the organization need to be tailored to the individual needs of the particular person. And this, I feel, is the primary difference between TM and HR.


Social Eminence

A discussion I was having the other day with colleagues about eminence and the role of social media in creating the persona of people who are experts at things brought out some rather interesting thoughts. One of the ideas that came out was that social reputation is based on one’s willingness to share knowledge. While I completely agree with that, this viewpoint confuses knowledge with the act of sharing. One can actually share things on social media without really knowing much about them. One of the things I see, for instance, on twitter, is that the rate at which people share links must mean they are reading like probably a thousand words per minute. Quite a few people I know just glance through an article or blog, and share it on social media. This is why I say hat sometime knowledge can be confused with the act of sharing.

Another important thing to understand is that it is very easy to manufacture things on social media. You might have seen a number of quotes from Albert Einstein on the web, and I don’t know how many of them are attributable to him. Taking an instance of a talk show I was watching, the analyst on the show was quoting a long-departed leader as having said something. This didn’t quite sound logical to me, so I started searching. After much searching, I found a blog which told how a lie was fabricated and why, and how it was circulated all over the world over social media. The “fact” may find it’s way twice around the world before folks start finding out. Also, there will be a number of folks on social media who will have spread the word, and very few who would take the effort to validate. What this means is that social eminence can be manufactured, and while there are self-correcting mechanisms which are there in the social ecosystem, these methods may not always be effective in a world with a very short memory. By the time you figure out something is wrong, nobody’s really interested, and setting the record straight is a moot point.

The point I am trying to make is that we need to be selective in the sources we subscribe to, and that we need to do our research before publishing something, a thing which is seldom done.


Big Data Analytics

For quite a while, I have been thinking that maybe I am the only one who doesnt understand what these words mean. I mean, with the buzz around these concepts (and here I mean the concepts, not the technology), these must be complex concepts to define, but the definitions that I was able to understand were all quite simple.

Big data is just that … BIG! There are essentially 3 things which define it:

1. Theres lots of it! Much more than we had imagined maybe even a couple of years ago.

2. The form of this data is too diverse. There text, images, videos, and what have you. Theres structured data and unstructured data, and data comes with its own context which makes it even more complex to handle.

3. Its being generated at a very fast pace. In fact, writing this blog is adding to this big data, as is your tweet, and those pictures you post on facebook, or those status updates that you like.

I was looking for whether this definition is correct or not, and I came across this video from Ericsson Research, which describes it quite simply with an example. If you want to get past the buzz and get to understand the concept, I would suggest you watch this.

So where does analytics come into the picture? Well, if theres so much of data, theres also the fact that its very difficult to build any coherent picture from this mass of data, and this problem is addressed by the analytics domain. Analytics helps us make sense of big data!

So what does Big Data Analytics need?

1. It requires infrastructure which is able to scale up or down based on the demands of the those who are generating this data, and those who are analyzing it. This means that the infrastructure needs to be flexible, and this can be handled much more easily with cloud solutions, and this is where cloud comes into the picture of big data and analytics.

2. It requires the applications which gather this data. A lot of this data is being generated by automated systems like sensors, and through mobile devices. With the scenario of equipment communicating with other equipment, the concept of the internet of things comes into the picture. Also, with the mobile device explosion, the importance of mobile applications and mobility solutions as an integral part of the picture also becomes apparent.

3. It requires the statistical and technology foundation which will help users or systems to make sense of this data. This is the analytics piece of the picture.

Heres a nice video about an IBM study on analytics.

This is how the picture gets a little clearer, and we can see how the cloud, internet of things, mobility, big data, and analytics are coming together to create a whole new technology paradigm.


Changing Education …

A few days ago, came across this article about the CS221 program offered by Stanford online. You can find more programs here. I found these quite fascinating. Somewhere, these present a changing face of education … or do they? I suppose this change started with MIT putting their courseware online. Then there was academicearth, which i thought was a sort of game-changer given that here, we didnt just have the courseware, but the entire lecture series video-recorded, and posted online. This meant anyone with an internet connection could be there, could learn from the some of the top universities, from anywhere in the world. Then there was Khan Academy … a game-changer in terms of the sheer scale Salman Khan has been created over the last 6 years (please dont look at these chronologically, am just trying to build the sort of continuum of changes which i feel have contributed to a possible new direction for education), and then there was classroom videos posted on youtube. Amazing, wouldnt you say?

These have a way of changing the way education is delivered going forward. If you look at the scenario today, teachers at a university deliver the same lectures year after year to a different audience. Instead of having to do this, teachers could video-record their lectures, and post them online, to be available to students. On their part, teachers need to be able to be available to guide research, mentor Ph. D. folks, and (probably the new aspect here), manage the learning process. When talking about managing the learning process, am talking about creating, managing, kindling conversations among students, guiding and mentoring students to enable them to learn more beyond the classroom lectures, and facilitate learning outside the classroom, in an ongoing way.

The next part, of course, is how this changing paradigm of education can be leveraged in the business scenario to redefine the training landscape. Any thoughts?