Skills - from HR, for HR, in HR
This is the second in a series of articles. You can read the first article to learn more.
Skills mapping paves the way to the future.
As we have laid out in our introductory article of this series, many businesses are working hard toward becoming a truly skills-based organization (SBO). The appeal of this compellingly simple strategy is easy to see - as an organization continues to evolve to stay competitive and grow, rigid teams, job roles, and titles are simply too static. Despite the deployment of agile methodologies, traditional titles and roles become a hindrance, both internally and externally, to continuous innovation of products and services, to continuous re-alignment with current priorities, as well as reacting to markets and clients.
While the strategy of transforming into a skills-based organization presents a compelling vision for agility and growth, it brings with it a set of complexities that are often underestimated. This transition is not just about embracing new ideas but also about tackling the practical challenges that arise in their implementation.
The Importance of Skills Data
The organization that seeks to maximize innovative evolution therefore needs to look beyond the agile methodologies and seek to sunset these rigid systems. However, to align with a more project-based approach, to be able to quickly shift focus and efforts in line with the latest priorities, the inevitable challenge comes down to the following: How can people identify the right talent, within the organization, to put together the right project team, at the moment of need? And keep doing so, iteratively?
The potential for an organization to unlock new levels of performance through skill mapping is immense. However, realizing this potential hinges on one critical factor: the collection and maintenance of accurate and up-to-date skills data.
HR professionals can only imagine the increased potential an organization would have access to if it mapped the skills that each employee possesses, to then identify the right skills and/or the right talent for specific projects and developments? This would also allow a much more strategic identification of those within the organization as prime candidates for specific upskilling and reskilling efforts - while increasing employee satisfaction through career progression and personal development, and reducing costly churn.
READ: How the Workforce Learns
Being Strategic
As a result, upskilling and reskilling could also be approached much more strategically, benefitting the organization in two ways. First, as a whole, this could increase capability, agility, and potential. Second, learning and development efforts of this kind also benefit individuals seeking to expand and develop skillsets in line with their own career aspirations..
However, as HR and L&D functions started to implement this powerful and practical model of the SBO, an unsolved challenge remains: where will the reliable, up-to-date data come from to fill in the framework and do so continuously? Despite skills matrices and frameworks being developed, they are an arduous and time-consuming task to try and fill, especially when some of these frameworks can include up to 50,000 "skills."
Challenges with Skills Data
Vendors entered this market quickly, with so-called talent marketplaces promising to map out the organization and fill in the skills data. However, the challenge here is that talent marketplaces, as well as similar products in the HR and L&D space, struggle or simply fail because they depend heavily on manual input of skill data, and in particular when turning to self-declarative data input.
Not only can self-declaration of skills be utterly flawed, a lesson learned from the research is learners’ inability to judge their own level of competence correctly. Also, they are an utterly time-consuming and highly inefficient process. On top of all of that, self-reporting is ethically questionable, to say the least, especially in a competitive work environment with employees aiming for promotions and recognition. Another challenge is that, in our experience and that of the practitioners and leaders with whom we speak, typically only one in five of those employees within the scope of a skills-based project will have completed their profiles and updated them regularly in the first place.
Given the sheer size of these frameworks and the number of skills within them, too much data is simply missing to make this a useful approach for any kind of strategy and planning. More importantly, what is missing is the subset of data on highly specific and practical skills, which is the data HR and L&D would need most to make skill data relevant and actionable today, rather than in theoretical exercises over the long term. In our experience, many talent marketplaces now claim their AI "solves" this problem, but we are yet to see a compelling example of such deployment of AI, rather than the mere use of a buzzword.
Aligning Talent Strategy with Business Objectives
However, a significant barrier often encountered in the journey to becoming an SBO is the disconnect between HR and the wider organizational strategy. This disconnect is epitomized by our title – Skills - from HR, for HR, in HR. Too often, HR initiatives, including skills-based strategies, are developed and implemented in a vacuum, focusing solely on HR's internal processes and goals, rather than aligning with broader business objectives. This approach limits the potential impact of these initiatives because they fail to leverage and integrate the diverse insights and needs of different business units.
To address this, we need to bridge the gap between HR and the rest of the organization. The implementation of an SBO model should be a collaborative effort that involves input and alignment with various business functions. This integration not only enriches the skills framework with diverse perspectives but also ensures that the strategy is attuned to the actual needs and goals of the organization.
This synergy is crucial because keeping the skills-based initiative confined within the walls of HR for an extended period can lead to “analysis paralysis.” Striving for a flawless system from the outset sets unrealistic expectations. Instead, achieving a 7/10 or 8/10 level of insight into skills should be viewed as a significant progress point, worthy of celebration. The journey from a blind spot in skills management to a substantially clear view is a commendable leap, and it's important to acknowledge this progress without being hindered by the pursuit of an unattainable perfection.
The key is to apply the skills-based approach in areas where it can turn previously unsolvable problems into solvable ones, leveraging the available data effectively. It’s not necessary to have a perfect or complete solution from the beginning. Rather, starting with targeted applications, where the skills data makes a tangible difference, can set the stage for broader, more refined implementation over time. This approach not only fosters a culture of continuous improvement but also aligns HR's strategies more closely with the practical, evolving needs of the business.
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Beyond HR
As we navigate the complexities of skills-based initiatives, it becomes clear that the approach should extend beyond HR's domain. For it to be truly effective, the skills framework must be integrated with the wider business strategy. This integration is not just beneficial; it's a foundational requirement for the SBO model to function effectively. The connection between HR, L&D, and the broader business is established through specific use cases and data-driven insights.
As the world is changing in regard to accessible, live data, its analysis and strategic value, almost in real-time, this picture will continue to change. Especially with the progress in AI, organizations can now seek to utilize both structured as well as unstructured skills data in better ways than ever before, and with ever-growing capability expected in the near future. Heaps of internal data that would have taken weeks or months to try to analyze can now be utilized in much shorter time frames.
AI is also delivering opportunities in terms of further data collection on skills and performance metrics. Look, for instance, at Microsoft’s launch of co-pilot. Not only will AI drastically change how we work on a day-to-day basis, but especially in the knowledge economy, AI now also has direct access to a wide range of performance data. Think of all the contributions and completion of tasks on specific projects for each team member! These can now be collected and documented easily with AI. And this isn’t limited to completion data alone. It can include the quality of the work (measured via a range of sources, including AI), but also the time it took to deliver each. Clearly, while this sounds a step forward from a data and skills perspective, potential ethical challenges around data and privacy would also need to be taken into account and addressed appropriately.
As we continue to explore the dynamic landscape of skills-based organizations, the role of data becomes increasingly central to our understanding and implementation of these models. The next installment in our series will delve into the intricate world of data, examining how it drives the SBO model and the nuanced decisions it informs.
WHAT’S NEXT?
In this forthcoming article, we will also introduce the transformative impact of Large Language Models (LLMs) on skills management. We will explore how LLMs are redefining our approach to skill data analysis and utilization, offering unprecedented insights and efficiencies. This discussion will not only build upon the foundations laid in our previous articles but will also open new avenues for understanding how AI and advanced technologies are shaping the future of HR and organizational development.
Join us as we venture further into the intersection of data, AI, and skills, uncovering how these elements collectively forge a path toward more agile, informed, and effective organizational strategies.
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