Following the post on the future of work, was thinking about what implications this would have for education, and the most obvious connection between work and education is about credentials. These are the signposts that tell (current or future) employers that a person has a certain set of characteristics. The most obvious example of credentials is the degree which your college/university has given you, telling the world that you meet a certain set of criteria. Often, this criteria is somewhat obscure, and may mean all things to all people, as we can see from the fact that the same credential from different universities mean different things, as seen from the value that people assign to them.
Today, a college degree has immense value for an employer, because the college degree tells the employer that the student has gone through a certain set of courses, and therefore is the right person to meet the requirements of the employers. From the employer’s perspective, the degree tells them that the prospective employee has the skills to be able to build a career. What employers look for is the assurance that the prospective employee has what it takes to fit into the grand scheme of things, to become a part of the larger picture that their organisation represents.
However, as the nature of work changes, as I said before, would such a credential of an ability to learn all things be as important? I believe that in such a scenario, where an individual would be contributing their specific quantum of work in a larger value chain as a ‘freelancer’ the skills of the individual in that particular space would become much more important than their generic ability. This means that organisations would naturally be more interesting in evidence of achievement in that specific area.
Such a shift in focus from organisations would necessarily mean that the ability to demonstrate ability in a particular area would become more valuable than the ability to demonstrate overall/generic ability. Hence, I feel, artefacts generated by individuals in the course of their learning, whether in the form of project reports, or papers authored, or creative work, would probably have a far greater impact than the degree. So, for instance, a paper written by a student on a particular topic, related to the work sphere of the student would likely have far more interest for employers than the degree or the grade would.
In other words, the evidence of achievement, in the form of artefacts, or in the form of eminence would become a far more valuable resource by which to evaluate prospective employees than simply the degree.
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?
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 …
I am these days reading a book about Big Data, and going through some of the applications of the technology, I was thinking about some of the ways Big Data can be applied in people matters. I tried to google about usage of Big Data for Performance Management, and didnt quite find much (or maybe thats because the search terms show results for application performance management). One aspect of using technology in HR, I feel, is in the realm of Performance Management.
Today, appraisals are done in an objective manner, with ratings which try to capture achivements and performance. However, as we know, these are a sort of force-fit. What does a rating of “Exceeds Expectation” mean? Does this mean, for instance, that performance is high, or does this mean that expectations are low? Somehow, this seems to be like fitting a square peg in a round hole, or a round peg in a square hole, if you prefer it that way.
An alternative to this could be the usage of technologies like Big Data to handle this. To begin with, managers could have the option of writing their observations, along with specific examples or scenarios as part of the appraisal process. This kind of input gives us rich information about people performance. Instead of trying to fit performance into a quantitative scale, this has the possibility of giving us qualitative inputs into performance.
Add to this the fact that plenty of business-related data is available from finance, sales, and operations, and we have immense data, both quantitative and qualitative, with which to work. Using this data as the starting point, Big Data technologies could be used to build correlation between manager comments and business performance, and deriving employee performance based on this correlation. This has the benefit of giving a descriptive picture of performance, one which describes achievements in a more meaningful way which can be used to drive talent processes.
Theres much more that Big Data can be used for, as this post by @josh_bersin describes.
Continuing from this post, I was thinking about more details about this parallel between Talent Management and Supply Chain Management. The first principle, from which I am trying to derive things here is that in both cases, there is a demand (in one case for talent, and in the other case for products), which needs to be met, and frameworks or processes put into place to match supply with demand. With products, the source of demand is simple to visualize. Not so with talent. So lets begin by taking a look at that.
The need of strategies, processes, and practices in the organization is to meet the business vision of the organization. To meet this vision, some work needs to be done by some people, and therefore, there is a need for people, equipped with the talent to do this work. So, the demand for talent arises from the work to be done to meet the strategic goals of the organization. Add to this the fact that there is specific talent available within the organization, and from there, its a question of trying to match available talent to the demand for talent, and based on this, determine what talent is required (in which area) to meet this demand. The supply of demand comes from employees, contractors, applicants, and L&D. I say L&D because learning is one way for creating talent supply to meet the talent needs of the organization.
Having said this, the basic concept which is the core for SCM is the concept of the part number. This is the unique identifier which tells anyone across the supply chain which specific material or product is being talked about. There needs to be a concept similar to this, something which uniquely identifies the attributes of the talent required (somewhat like part number which uniquely identifies the specifications of the material being spoken about). Different organizations meet this requirement in different ways. As you will read here, IBM solved this with the concept of JRSS, the Job Role Skill-Set, which is a composite of the job role, the role that an individual performs, and the skill sets that the individual has. This is the common identifier which can uniquely define what talent is being spoken of in the talent planning process.
A discussion I was having the other day got me to think about how Talent Management is based on principles which are analogous to other functions. And this brought me to the idea of the similarity between Talent Management and Supply Chain Management, in terms of principles. If we look at the essence of Talent Management to be about bringing the right people to the right roles at the right time, then we can, from there, start looking at the essence being to match the demand for talent with available supply, and building supply pipelines where there is a shortfall.
To begin with, one of the major conconers for organizations is uncertainty. If things were fairly certain, then there wouldnt be much to be gained by trying to manage talent, because things would be running pretty much the way they are running. The sources of uncertainty are many, but thats for another time. This uncertainty results in the need to identify, based on the organization strategy, and operating plans for the coming years, what the organization’s talent requirement is going to be. Given uncertainty, there is also the need to identify how good this estimate is. This is analogous to demand planning, where the need is to estimate how much demand the organization would need for which products, and the amount of uncertainty (sometimes measured in terms of probability) associated with that demand. Based on this estimate, one can arrive at the talent required to meet the strategic and operational plans.
With this forecast as the baseline, one can then look at the talent existing in the system. This may be the talent pool which is ready for the roles for which they are required. This is akin to the gross-to-net calculation which is common in all material planning (MRP) systems. At the same time, one also needs to try to identify how many people the organization wants to, or can, develop from within, to meet these talent requirements, and from here, derive what the hiring plan looks like. This is quite akin to make-or-buy decisions material planners regularly have to make, keeping in mind available resources to make. At the same time, this serves as the input to defining Development Plans, which is akin to creating Work Orders to meet the build requirements.
Traditional succession planning is about identifying which individual should be doing what role some period down the line, but this is problematic, given that after that period of time, either the person may not be with the organization, or the role envisaged may not be part of the role directory of the organization. So, instead of looking at an individual job and a particular person, one can look at a job family to be fulfilled by a talent pool. This is analogous to product-family or product-category level planning, because forecasting, and therefore planning at the aggregate level is more accurate.