If you've started to look at all the possible SaaS solutions for internal mobility, some of the language can be perplexing. Here's a short run down of several of the common terms you'll come across, what they mean and why you should consider them in deciding on an internal mobility solution.
This is one of the most common terms you'll find associated with internal mobility platforms. A taxonomy is a hierarchical classification system - like the filing system on your computer. A skills taxonomy specifies the way you'll categorise and organise all the skills you need within your workforce.
It's usually ordered according to what's most important to the business and it helps HR and employees understand which skills they have, how they relate to organisational needs and what gaps there are. You can design your own, or work from an existing taxonomy that someone else has compiled.
If you're about to embark on some kind of skills audit, you'll need to figure out your taxonomy first. If you're then going to use it to manage workforce capabilities, one of the challenges is deciding on how and when the taxonomy is updated. For example, if a new programming language is developed, who decides if you need it in your taxonomy and how and when do you insert it?
A skills ontology differs from a taxonomy because it shows relationships between the skills. An ontology might show that someone skilled in programming also has problem solving skills or is good at logical thinking.
An ontology looks more like a mind map, whereas a taxonomy looks like a family tree. There's a nice visual representation of the two here. A family tree is a hierarchical representation, but if you drew lines across it to show relationships like brother, sister, aunt, uncle, cousin, etc - it would look more like an ontology. You can also then group people or objects by these relationships - for example, 'all the cousins' (which you can't do in a taxonomy).
A skills ontology is useful in understanding skills across different dimensions, and it gives you a common language when trying to understand or simplify all the skills data across a skills taxonomy. This can then be used to help you define the aspects of a particular job, which can help employees identify if that role is a good fit for them.
Some internal mobility solutions come with ontology builders, which can analyse your workforce skill set and create an ontology specific to your organisation that you can use to maintain all your skills data.
A skills cloud is an inventory of all known skills - usually compiled from multiple organisations or looking at large numbers of people, like all LinkedIn profiles. Some skill clouds available today contain tens of millions of skills. But the skills cloud doesn't organise or categorise them. It is the data set that taxonomies and ontologies can be built from.
Skill clouds currently analyse millions of job postings, company job descriptions or individual profiles and can identify new and emerging skills in real-time.
More sophisticated AI engines don't just look at the terms in the data they have. They can infer skills an individual might have by comparing their data with other similar profiles, looking at the social content they post or courses they've completed. Some systems can also infer skills strength by recognising how long it's been since you used a skill and applying some criteria that cause skills strength to decline over time.
why all this matters
All these concepts are important today because the conventional approach to defining a job - with a competency model and job description - just cannot keep pace with how quickly the world of work is changing.
Project based work and the need for agility mean that identifying all the skills that an organisation needs to achieve its business objectives just cannot be managed manually. Fortunately, AI is clever enough to do this for us.
Big data sets combined with machine learning allow internal mobility tools to crunch the numbers and more accurately match people to roles in a talent marketplace, or recommend learning that will help them develop the skills to advance their career.
We could be moving towards the 'Google of skills', where you type in what you need or where you want to go and the internal mobility platform finds you the perfect match.
At Randstad RiseSmart, our career development and skilling solutions use Burning Glass for skills data. Burning Glass is considered to be one of the leaders in this field. Their system extracts skills data from millions of global job postings on a daily basis to determine what’s in demand, what’s new and how it’s being described.
It would be reasonable to think that people with skills similar to the ones you require for a particular role - skills adjacencies — are likely to be the candidates who can most easily move into that role. However, LinkedIn's 2021 Workplace Learning Report found that's not necessarily the case. Many employees have moved into highly technical, in-demand roles from entirely different occupations.
For example, half of the employees who moved into data science and artificial intelligence (AI) roles came from unrelated industries. That proportion is even higher in other disciplines: engineering roles - 67%, content roles - 72%, and sales - 75%. More interestingly, the people who moved into data science and AI had the largest variation in their skill profiles - half of them had skills with low similarity.
While skills adjacencies are an important consideration in job matching, what's inspiring about this finding is that it confirms people are much more capable of making a career leap or radical pivot than traditionally thought.
Our career coaches have known this for years. They've coached tens of thousands of people through every kind of career move you can imagine. Often, they give people the tools and the confidence to make a career shift that previously they didn't think was possible.
Given the pace of technological change and the demand for people with skills in these areas, this data should give HR practitioners confidence in plans to reskill or redeploy people into digital fields - and drive greater diversity in these areas.
learning experience platform (LXP)
If you need to upskill or reskill people to take on more work in these high-demand areas, an LXP could help.
Firstly, let's define the difference between an LXP and the more common LMS. An LMS is usually deployed to manage in-person training or formal learning that the organisation makes available to employees. It's ideal for keeping track of who's completed what, when employees must undertake learning for compliance or regulatory reasons.
An LXP is typically a richer and more engaging environment for learners and, in addition to the formal learning available through an LMS, also includes learning content (in all its forms) created by employees. Users can rate and review content and receive recommendations based on their interests and goals.
LXPs tap into the know-how that employees have and let them post instructions, videos or comments that their colleagues can find 'in the moment' when they need to know something to perform their job better.
This term is emerging as a way to describe the use of one or more AI-powered talent management tools. Having a tool or a platform to provide talent intelligence means deriving insights about your workforce from data about their skills, experience, career goals, performance, demographics and learning needs, etc.
These insights can then be used to better match people to the right opportunities - not just permanent roles; but gigs, projects, secondments or anything that develops them in a way that furthers their ambitions and supports company growth.
making sense of internal mobility tools
The world of internal mobility platforms is moving fast and new terms are being coined all the time. Some tools work best when combined with others, some operate as standalone solutions. Our team is here to guide you through what's right for your organisation.
We believe our approach is different to all the other providers, as we offer the only internal mobility and skilling platform that combines user-friendly smart matching and learning recommendations with a human element - 1:1 coaching and guidance from certified, professional career coaches and learning advisers.
To find out more, or to request a demo of our platform, please contact us.