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Predictive analytics: forecast knowledge

Past results do not guarantee future performance. If this is true, how come we only look at past performance during a job interview? Managers also tend to focus on past performance and achievements during the yearly appraisal meetings. The objective of a job interview or appraisal meeting is to shape future performance.  So why should we still evaluate what the employee has done in the past? 
Knowledge and skills decline if they are not maintained. In 1890 Hermann Ebbinghaus found scientific evidence for the forgetting curve. If we stop maintaining our knowledge, it will fade away over time. So what is the value of a certificate or diploma after a couple of years if no maintenance has been done on what has been learnt? 
Learning, forgetting and Google
Knowledge is needed to develop skills. And our brain specifically struggles when it has to retain the knowledge that we have acquired. If we see, hear or read something today, we will forget up to 80% within one week if we do not actively process what we have read, seen or heard. 
All this is reinforced by the Google effect on the brain: if our brain knows that it can search for information, it will no longer store the information itself, but just store how and where the information can be searched for.  Very useful, but very inconvenient when you are a doctor or a pilot and need to memorize essential information within a split second.
Past performance is normally the central theme during a job interview or appraisal meeting. However, this past performance cannot be changed any more. The past remains a status quo. 
What can we do to get more control over future knowledge and skills? Which means do we have to put the emphasis on the future rather than on the past during a job interview or appraisal?
Predictive analytics
Big data is hot. Can big data also play a role in determining future competences?
Yes it can. Predictive analytics can be used to calculate on a personal level how and when knowledge declines if it not maintained. Analysis of the learning history enables us to calculate how and when knowledge fades away over time. 
So the combination of scientific research and new technology enables us to determine a person’s proficiency on a specific subject for any given moment in the future. Will the right person have the right knowledge at the right time? 
Is the employee ready to perform specific tasks in the future or is additional training required? And how do we value the feedback of managers, colleagues or customers when assessing the quality of current competences? Can we use all this data to determine whether or not the employee will be qualified for a specific job in two or three months? 
Learning technology becomes now part of the job interview or appraisal meeting. Not to take decisions on a candidate’s qualifications, but to provide useful input that enables managers to make better evaluations. Training acts as a bridge towards future performance.  
Permanent education
Predictive analytics can also be used to continuously maintain knowledge and skills. What is the right time to refresh a specific training? 
By smartly using predictive analytics you can guarantee a higher knowledge level of your employees, while reducing costs. After all, training sessions are now only scheduled when the probability is highest that the employee really needs it at the day and hour of the training session. Not earlier, not later. 
Future competences
Evaluating new or existing employees should always be a human action. Technology and science can help us improving the quality of our evaluations and decisions. The right training for the right employee at the right time will increase the performance standard of our employees. And this reflects positively on the manager. 
Food for thought for your next job interview of appraisal meeting? 
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