Since 2019, SAP SuccessFactors has been evolving from a pure Human Capital Management Software towards a Human Experience Management Platform. The use of a Human Experience Platform is to place the organization strongly in the War of Talents and to meet current needs. Companies must answer the question, "How do I get the right people in the right roles?" At the same time, the needs of employees cannot be ignored. This is where the Whole Self Approach comes in. It should no longer be just about questioning what an employee can do for a company, but much more about optimizing the conditions of employees and their development opportunities so that they feel valued for their whole self.
Fig. 1 - Wholeselfmodel*
Studies have shown that employees achieve increased motivation, resilience, and creativity when their job is aligned with their values, and they feel valued as a person. Amy Wilson put it this way: it's about empowering employees to ask themselves, "What is important to me?" Long-term career planning should be regularly scrutinized and adjusted, as everyone changes over time and therefore their goals can change as well. The focus of consideration is the central questions; what do I want now? What motivates me today? Who do I want to become?
Career development and learning are essential components of self-actualization. Once employees have decided where they want to go, they can develop in a targeted manner. How does SAP SuccessFactors support this? The Career Development Planning and Mentoring module is at the heart of this. The system forms the basis for employees to independently identify goals and possible future job roles. The new 2H2022 release expands this function. SAP is introducing the use of machine learning with the new Career Explorer. The goal of the Career Explorer is to show relevant career options such as the career development of similar employees in the company, roles outside of one's own hierarchy and job roles that one would not have thought oneself capable of. But what exactly is changing? Previously, Career Paths could be created by HR staff and employees could look at existing paths and decide which roles were right for them. The new Career Explorer, on the other hand, recommends career opportunities based on the careers of other employees from the company. In the process, recommendations are updated every two weeks. The recommended roles are displayed in a lineage chart, just like in the previous Career Paths feature. The position cards contain the option to call up further information (click on the three dots).
Fig 2 - Career Path in Career Explorer*
Users can look at the corresponding job profiles, where further information such as job descriptions etc. are stored. There they have the option to mark the role as a target role or to remove it from the recommendations. By removing roles, the personalization of the recommendations is improved. In the future, these roles or child roles will no longer be recommended. If a user marks the suggested role as a target role, it will be added to the Career Worksheet. The user can then use functions such as gap analysis in the familiar CDP environment.
Fig. 3 - View further Information*
The system also provides the option to view why the role is being suggested. This information can become especially important when it comes to job roles that one has not considered before. In this way, the company actively supports the employees' own development and creates a growth environment - what could be more motivating?
Fig. 4 - Recommendation Reasons*
The advantages of the new Career Explorer over the classic Career Path can be seen in a nutshell:
Often classic, predefined career paths. Recommendations associated with very high administrative costs.
Recommendations individually for each employee, based on personal data such as educational data, skills, job history including department and position.
HR needs to check and adjust paths regularly.
Every 2 weeks, the system automatically generates new recommendations. No effort on the part of HR.
You might wonder, thatthere has already been the “suggested roles” tool within career worksheet. The Career Explorer greatly improves and extends this function. The new Career Explorer is able to analyze a higher amount of data and make the recommendations more individual. To analyze such a large amount of data, People Connection Integration must be activated in SAP SuccessFactors. This enables the system to transfer the data to SAP AI Business Services.
Fig. 5 - Dataflow*
As with any AI, the same applies here - it is only as good as the data it is fed. Contact your partner to check your readiness. The recommendation is primarily generated based on the following information:
Users’ background information, including school and degree
Users’ job history, including job classification, department, and position
Users’ competency rating
You can find a detailed overview here. It is important to ensure that the relevant data is available in appropriate quality and quantity. Basically, the SAP SuccessFactors instance used must meet the following technical requirements:
The use of Employee Central
The use of the Job Profile Builder where Job Code & Classification are mandatory, while the creation of competencies is recommended to generate better recommendations.
Succession&Development is enabled
At least 1,000 employee-job role pairs in the system (including current and historical data)
The Career Explorer is a further step in the design of the new Human Experience Management platform. Other functions that are being established in line with the Whole-Self model are the Opportunity Marketplace, the Center of Capabilities and the Talent Intelligence Hub.
With the wholeself approach, two goals can be achieved in one. First, companies can position themselves strongly in the war of talents, and at the same time, the approach helps employees find fulfillment in their jobs. People who find fulfillment and meaning in their jobs are healthier, more productive, more creative, and more motivated, which benefits everyone involved. At the same time, the use of modern AI technology emphasizes the software's ability to innovate. The ability to adapt new developments and integrate them into the software is crucial and points to its forward-looking character. Be curious about the further developments of the Whole-Self Model and follow my channel to not miss any updates.
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