Having A Clear Objective Is Essential As it prevents the company

Especially for those starting out. As it prevents the company from getting lost in HR Directors Email Lists without knowing what it should be used for. 2. Definition of metrics Let’s say you hope to increase employee engagement. How will this factor be evaluated? You can investigate actual hours worked. Number of projects completed. Suggestions offered. Participation in projects. And so on. Want to know which performance metrics to monitor with your salespeople? Check out the main ones: Performance indicators for salespeople 3.

Collect The Data Your First Initiatives

Collect the data Your first initiatives may be focused on what is relevant to the objective outlined. With time and experience in People Analytics. It is possible to expand the scope and collect more and more data. Which will point out new risks or opportunities. Helping to define new goals. 4. Analysis and correlations The team responsible for using People Analytics should investigate the data. Seeking to recognize patterns. Identify problems and so on. The analysis must correlate the information and its possible causes : find out if sales productivity has increased after training. For example. It is important to try to isolate variables to know
when they really influenced the result.

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Analysts Should Ask Whether

Analysts should ask whether increased productivity is common at this time of year; new employees were hired; the company’s leadership has changed… 5. Anticipate scenarios As data analysis shows certain patterns. We must use them to anticipate what might happen . Looking at what has already happened will not make us predict the future. Of course. But it allows us to know the chances of each possibility occurring. Defining priorities for the next steps. Over time – and the new data it will bring – it will be possible to create increasingly secure models and protect the organization by reducing the number of unforeseen events in your path. 6. Decide on new directions Information is critical. But it does not create new results until action is taken. The data should guide strategic actions that allow evaluating the hypotheses raised.

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