As mentioned in my first blog about why early attempts at skills-based organizations failed, creating a skills-first job architecture is the foundational step to becoming a skills-based organization.
Let me explain why.
For several years, large companies have seen shorter tenures among their employee bases. To help retain and engage talent, leaders went out to the market and bought various solutions, such as talent marketplaces and Learning Experience Platforms, that were using skills (rather than jobs) for the first time.
Unfortunately, before moving on to some of these higher-value tasks that would positively impact the employee experience and help address business challenges, the talent architecture element was overlooked.
How can employees or candidates match themselves to exciting new jobs if you have not accurately and comprehensively defined the skills for those jobs? How can employees close skill gaps through learning if the gap hasn’t been adequately understood?
The Challenge and the Solution
One of the reasons that creating and unifying a skills-based talent architecture was overlooked: it's challenging to get right.
A leading North American Bank I spoke to recently with more than 50,000 employees spent just under two years creating a skill-first job architecture. This was a vast, expensive, and manual process including internal HR leaders and managers, support from a large consultancy, and one-to-one interviews across the business with SMEs.
This level of effort, which cannot be underestimated, is a major reason why some organizations have chosen to focus on other strategic priorities. The lemon didn’t appear to be worth the squeeze, especially when there appeared to be more immediate challenges such as lower-than-expected employee engagement with whatever shiny new tool had just been purchased.
Thankfully, there are now solutions that can support in the process, SkyHive being one of them.
Over the last six years, SkyHive has spent a significant amount of time and resources building the world’s largest labor market data set. This has supported the creation of a Knowledge Graph, where billions of nodes and edges compromising skills, contextual relationships, job titles, companies, and geographic locations are updated fluidly on a daily basis.
It is this “brain,” encapsulating all the available labor market data, that enables SkyHive to automate much of the process of mapping skills to jobs (see image). Our patented technology enables us to take as little as a job title and:
- Immediately detect relevance of the job title to the labor market
- Fully automate the identification of skills
- Generate new job descriptions
- Easily and continuously refresh each role with new and emerging skills
A fantastic example of this is our work with Merck, where SkyHive ingested and then attached skills to 5,000 jobs and pieces of learning content in just a few weeks. We then integrated directly with Merck’s HCM system to create a sustainable foundation for the business to launch its transition to skills-based practices, saving millions of dollars in the process.
It is this “sustainability” element that is crucial to ensure that the relevancy and integrity of job, learning, mentorship, and gig recommendations is preserved over time.
How can you understand, and then address, a skill gap if you are not continually updating/refining/adjusting the skills required for your roles?
There are two key reasons why this is so important:
- Modern HR systems (and talent marketplaces) recommend jobs & experiences (learning, gigs, projects, etc.) based on the skill gap between a job and an employee. If you haven’t defined the skill for your jobs and gathered an accurate view of skills for your workforce, the recommendations won't be very good.
- Skills evolve over time. Jobs change, and the skills associated with your job architecture must reflect current labor market trends to ensure relevant matching of jobs, learning, gigs, and projects in your HR system or talent marketplace over time.
A good example of this is a recent conversation with two VPs at a global payments company who, after investing millions of dollars in a market-leading talent marketplace for its 30,000 employees, said that the “AI recommendations for jobs don't work.”
Like many large organizations who are forward-thinking and keen to adopt new technology, they will need to take one step back to take two steps forward and address their foundation first to improve results.
This finally brings us on to what we call Horizons.
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Skills First, Then Internal Mobility
Horizons at SkyHive is our interpretation of our customers’ actions on the route to becoming skills-based organizations. Most clients are starting with Job Architecture before progressing onto things like workforce planning and ultimately end-to-end reskilling. Job Architecture is critical to enable skills-based job matching; you cannot improve internal mobility through job matching until you have the skills for both your jobs and your employees.
In my next posts, I’ll talk about how to tackle multiple skills taxonomies, and why an operating system (rather than another platform for employees), is required.
Paul Scott is a Senior Enterprise Account Executive at SkyHive. Contact him at Paul.Scott (at) SkyHive.io.
