Today at the UNLEASH America conference, Reejig, the global leader in workforce intelligence, announced its new Work Ontology™, which unbundles traditional job architectures to atomized components such as skills required, tasks and task adjacency, requirements, and time allocated. Reejig customers can now achieve their workforce optimization goals with personalized, actionable, real-time insights that support the redistribution of work to the most efficient and innovative resources, embrace emerging work technologies and automation, and match their employees, candidates and contractors to meaningful careers.
"The world is going through an enormous paradigm shift in the way that we traditionally have organized around jobs and employees. Not only are employers having to respond and adjust to new ways of working since the pandemic, but they also must consider how to integrate rapidly-evolving technologies like artificial intelligence into their workforce strategies. Siobhan Savage, Reejig Chief Executive Officer and Co-Founder
As work evolves into a combination of jobs, projects, and gigs, companies must have the tools to unbundle work and optimize the allocation of tasks to workers, including full-time, part-time, gig, internal and external talent, and bots powered by generative AI.
In a new report, Goldman Sachs’ economists estimate that roughly two-thirds of U.S. occupations are exposed to some degree of automation by AI. Of those occupations that are exposed, roughly a quarter to as much as half of their workload could be replaced. But not all that automated work will translate into layoffs. According to the report, “Although the impact of AI on the labor market is likely to be significant, most jobs and industries are only partially exposed to automation and are thus more likely to be complemented rather than substituted by AI.”
The Reejig Work Ontology addresses the limitations of traditional workforce operating systems, which have long been based on job titles and jobholders, lacking visibility into the true skills and potential of their employees. It is responsive and dynamic by nature, continuously extracting and inferring from the most comprehensive set of data in the industry to create highly intelligent common language and insights around each unique organization’s work.
"The power of a dynamic, three-dimensional skills ontology has empowered our customers to do some amazing things. But now that we can support organizations to break down and decode jobs into atom-like tasks and molecule-like projects, matched with a similar understanding of their peoples’ skills we have closed a cumbersome gap on the journey to organizational agility. Mike Reed, Reejig Chief Customer Officer and Co-Founder
The Reejig Work Ontology, when used alongside the Reejig Skills Ontology, enables organizations to:
By understanding the relationships between detailed job components and people’s competences, experience, education, passions and preferences, Reejig’s central nervous system empowers organizations to achieve groundbreaking business results, including:
The Reejig central nervous system is powered by the world’s first independently audited Ethical AI. Its algorithms and models are compliant with global regulations on equal opportunity, anti-discrimination, anti-bias, and human rights — meaning all recommendations are based solely on skills and potential — not personal characteristics. Each customer's unique workforce intelligence delivers gender-balanced shortlists, diversity signals on candidates so you can hire and mobilize talent inclusively and fairly.
“We really saw a need from business leaders to have a actionable and achievable pathway into this future way of thinking — one that not only reduced administrative burden for their operations and people teams, but also one that they can trust will help make the most ethically sound decisions and build a world-class experience for their people.” Savage said.
To learn more about Reejig's workforce intelligence platform check out our platform pages, or follow us on LinkedIn and Twitter.