FAQs

Managing the integration of talent and AI (Talent+AI™) where resources are allocated to achieve a measurable and predictable return on Talent +AI capital.

The process starts with the problem, Talent+AI integration, and reinvents the existing job, hierarchy, headcount model, replacing it with a services model that allows Talent+AI and AI to co-exist in problem solving and workflows that optimize value. Resource allocation is based on value less cost, not just cost. The organization of resources is based on a supply-demand model featuring customer value chains of processes and deliverables. The organization design is a service marketplace of Human and AI resources transparent to source with a mission of delivering customer value. Adaptability is critical to consume rapidly developing AI and meet innovative competitive forces. Org design structures minimize decisions and control - fostering the fewest number of management layers, thus, reducing overhead. The change process is highly configurable depending on the market segment and the organization’s culture.

The value of a service is initially based on attributes that distinguish value and the customer(s) who defines or confirms the attributes and the degree the value achieved. An algorithm reduces the attribute assumptions per service into a metric called “service-value™”. A feedback loop is created to improve the assumptions based on the customer feedback regarding the value received. In addition, the service-value represents the margin contribution of the service – service-value less cost. An additional feedback loop is represented by financial modeling of service value by individual, group, function, rolled up to the P/L level.

The first step in the process is to transform from a job to a service model. We use a custom AI tool for converting job data into an initial version of services by job role. Individuals who perform a job role participate in an exercise that begins by describing in their own words the services they provide and the customers(s) who benefit. The final step of the exercise is to review their service descriptions with those provided by AI and modify the AI services to align with the actual services and customer(s) performed. This provides a continuous feedback that improved the AI generated process.

The current job structure is completely outdated. Lots of waste occurs as layers of managers make decisions on getting the “right” work done. The process of understanding value is unclear and inconsistent. Jobs constrain talent, especially top performers. The service model allows for a flow of distributing the right talent to provide the most valuable service. The organization grows flatter and far more adaptable. This kind of model provides a language of services where talent and AI can co-exist and be optimized by a new “3D operating model™”.

Hierarchical models rely on management to focus, lead, and control the work. They are wasteful, slow, and not efficient for a hybrid workforce of Talent+AI. AI solutions are not efficient in a job structure. A service model provides the opportunity for exchanging Human and AI services and providing a method of estimating value. The new org design provides a supply-demand model of service distribution – far more efficient in reducing cost and increasing productivity to meet service demand.

The services model provides the same language and interchangeability of services by sources of talent and AI. Human Equivalence™ allows applying of Human services as percent FTE, service-value, and performance attributes. While AI could be measured differently – translating those differences in Human equivalence allows the use of a financial planning model. The equivalence is not 1-1, but the assumptions will improve in time as the assumptions are continually tested to improve the alignment of assumptions and actual financial results.

Traditional 2D operating model consists of jobs, headcount, cost, overhead, and revenue/labor cost. It is a crude process full of lots of assumptions and waist in computing return on Human capital. AI can also be measured in cost but how are talent and AI optimized? The 3D operating model consists of services, service profiles of 100% FTE per individual and service-value, cost, and service margin contribution. Via Human equivalence Talent and AI can be integrated into Talent+AI return on capital.

In the 3D operating model talent is measured by value or margin contribution. A focus on efficiency is often focused on cost. A common goal is to get “rid” of headcount. This may create a measurable cost return. However, the non-measure impact of people, their emotions, motivation, and engagement can easily create a real cost instead of efficiency gains. The 3D model is focus on value creation which requires motivation, innovation, and initiative. The service model allows for more freedom for individuals to grow, distribute value, and customize their work-life.

Market forces will ultimately shape the future of Talent+AI organizations. Ask yourself, in 5-10 years will the current hierarchical structure survive? They are too slow, too wasteful, and too inefficient. The early adopters of 3D will gain the “unfair competitive advantage™”.