We provide information for better people decisions.
The ultimate formula: brain facts + analytics + management practices = People Intelligence!
It’s important to start from How people really work. Neuroscience permitted us to understand some fundamental notions about the brain and this body of knowledge could facilitate people, teams and organizations in achieving outstanding results. Data about competencies or behaviors may be evaluated through algorithms of people analytics in order to provide to leaders a decision support system to improve people management.
Below you can find some examples of realizations:
1. How to improve selection? In an italian private banking structure we found that there are certain skills that make the difference as regards results achieved and a factor that explains the cultural fit.
The selection process was revised by inserting a change model that would help the recruiter to manage the rational and emotional decision-making and the evaluation of the candidate focusing on the emerged skills, even with the support of an assessment tool and a set of structured questions for the interview. Furthermore, the evaluation form has been revised in order to get coherent, consistent and comparable feedback from different people.
2. How to reduce hiring times? A Fashion company had the need to reduce the time and costs dedicated to the selection of people who were not in target. From the analysis of excellent candidates, a ranking algorithm was created with a predictive value of 90%.
The algorithm can be integrated with the software used for online recruiting so as to provide the list of candidates directly in order of priority to the hiring manager. The system provides the possibility to calibrate the filters to different profiles or countries. The solution also makes it possible to provide an answer to the need of employer branding that can help the company bring out the people value proposition.
3. What are the drivers of performance? In a leading food processing company we found that there is a unique distinctive competence in sales that really makes the difference between the top and the low performers.
This awareness has led to rethink the old performance system which was based on a competency model that made the evaluation too long, not motivating and above all not-value added nor for the manager nor for the employee. The new system was based on a smart model with a strong focus on managerial actions and people development on what really made the difference with a user-friendly and short format.
4. What makes the difference in teams? An international consulting company asked us to analyze some of their team to understand why some were performing and others were not. Three features making the difference have been identified.
From this research a teamwork simulator has emerged which allows us to form groups in the best way, support the warm up at the beginning of a project with a group profile to be discussed among team members so as to raise awareness of the possible dynamics and construction of an accountability tool to keep the focus on people and detect potential signals of turnover.
The same methodology is applicable to Management Teams or established working groups.
5. How to personalize development? A company in the construction industry has asked us to give each individual person the training contents he/she really needed in a simple way so as not to waste time. The solution: a system of neural networks to be included in the e-learning platform.
An assessment was implemented, connected to the company’s competency model, where an expert predictive system pointed out, for each person, what were the competencies to be improved in order to have the greatest impact on performance. The system, linked to the performance management appraisal, could either provide information mediated by the direct boss or simply the opportunity for self development. The training contents could then be managed with an APP.
6. How to detect signals of turnover? An organization asked us to create a turnover early warning system to provide to the HR department and line managers real-time signs about people at risk of leaving the company to better manage critical situations. The model has a more than 70% predictability.
The application of people analytics to improve business retention is based on the identification of key variables that influence the abandonment, the construction of a predictive model and the continuous analysis of objective and people’s perceived data in order to allow the automatic emergence of warning signs to enable early intervention. The parameters are adjusted annually for a continuous improvement of the algorithm.
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