An organization’s career architecture is the foundation upon which human capital management (HCM) programs are built and serve as the framework to deploy talent management strategies and implement supportive technology. As economic shifts continue, companies are forced to adapt their business’ strategy to remain competitive and in turn require organizational transformation, reskilling and a career architecture that provides relevant data to support these changes. Without a human-centric and automated solution, companies struggle with the daunting, expensive and time-consuming process of maintaining dynamic job and skill data or risk trusting technology that compromises the validity of critical data informing workforce decisions. With these challenges in mind, TalentGuard introduced its AI-powered Intelligent Role Studio (IRS) – a solution that combines deep subject matter expertise with algorithmic intelligence.

Prior to the Intelligent Role Studio, an average engagement for a global organization to update thousands of job roles with competencies took 9-18 months and the data nearly became obsolete by the time an organization was ready to use it. TalentGuard’s newest software innovation uses artificial intelligence and machine learning to accelerate, automate and simplify key processes in job role and skills management across the enterprise at higher delivery speeds than ever before while also empowering organizational subject matter expertise. Organizations can quickly augment, develop and maintain a clear model of their company’s career architecture so they can match people with roles, design career paths, and assess performance consistently and continuously throughout the company.

In January 2020, Josh Bersin used a comparison of Google Maps to Waze to describe the technology approaches for solving this problem. Google Maps was compared to the traditional design of jobs and competency models whereas Waze was the new approach that is heavily reliant on employee feedback to make suggestions around job fit and career moves. TalentGuard introduced a hybrid approach where Intelligent Role Studio is the perfect combination of both. To continue the GPS navigation software analogy, if you don’t build and update the structured maps foundation you’ll end up with chaos on the roads. You can have incredible driving skills, but in the end, you’ll inevitably drive down a road that should’ve been marked closed and crash because of poor data and unreliable feedback.

A practical and efficient approach relies on both job structure and human intelligence, whereas the “old” and “new” approaches were polarized. One is structured while the other is unstructured. One requires preplanning whereas the other happens in “real-time’. One is human labor intensive, and the other adheres to technology working behind the scenes. TalentGuard remains true to the stance that you cannot take away the human element from human capital management and while applying intelligent methodologies to remain up to date you can’t also compromise the data and structure that we all know to be effective.

“Artificial and Machine are two words that talent management practitioners never use to describe best practices in human capital management. Yet, many firms that specialize in the development of AI and ML applications for HCM seem intent on removing humans from the workflow and critical decision making. TalentGuard’s approach is human-centric where AI and ML are applied at strategic high-risk, high-value points that complement and boost the performance of talent management practitioners,” said Chief Technology Officer, Frank Ginac.

Any career architecture project requires extensive involvement from HR, Organizational Development (OD) and managers acting as subject matter experts to aggregate the right data for job roles. Oftentimes an outside management consulting firm works with these groups as well, piling on the costs. Once complete, the end product is delivered across multiple spreadsheets. Technology implementations expose that managing job role data is very complex, manual and cause massive delays because the data can’t be used effectively in talent management software, often rendering the job data outdated. Meanwhile, more recent approaches rely heavily on a system to automatically figure out what skills you need without the proper human intervention which have customers weary of the results. But now human-centric and AI-powered Intelligent Role Studio automates key processes, maintains dynamic and verified data, and empowers organizational subject matter expertise.

“Our goal was to give employees an amazing talent mobility experience to help improve retention, but we didn’t want to spend significant amounts of time updating and evolving our job roles on an annual basis. TalentGuard gives us a way to significantly speed up this process by eliminating the painstaking manual effort while also keeping roles relevant. With Intelligent Role Studio, we can focus more on getting our employees what they need instead of being stuck in the role rationalization processes that is common without a product like this,” said Stacey Houston, Sr. Learning & Development Consultant at Accruent –the world’s leading provider of intelligent solutions for managing the built environment.

IRS delivers key benefits:

• Technology-enabled services to eliminate up to 75% of traditional manual service provider functions (e.g., competency mapping, job calibration, learning mapping, and building progressions).
• A single source of truth and centralized repository for job role data, skills data, capability data and employee talent profile data.
• A streamlined software implementation unifying competency, skills management and verification with talent management processes such as succession planning, internal mobility and performance all in one platform.

With IRS, companies can achieve the following:

• Align: Seed a company job roles data with TalentGuard’s industry leading job role ontologies and use AI to automatically align job roles with each client’s unique requirements by automatically rationalizing job role names, descriptions, grades, skills, and more from a variety of customer-provided data sources.
• Progress: Automatically and intelligently build career progressions based on job grades, job families, titles, similar skills and existing internal data reflecting career moves.
• Learn: Over time, job roles change both organically from within an organization and across its industry. TalentGuard’s AI continuously scouts for clues, from employees and internal data sources and from external data sources, that a role is changing and then calls on SMEs to review and train the AI with the goal to build trust in the AIs ability to act more autonomously.
• Evolve: As the system learns and human trust is established, TalentGuard’s AIs begin to evolve roles autonomously but always under the watchful eyes of SMEs. Transparency and explainability is essential. TalentGuard’s AIs provide both so that SMEs can make final decisions about how to shape a role and it helps the AI better nudge role changes in the future.

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