Predictive analytics: hewlett packard's flight risk prediction

Hewlett-Packard (HP) has taken a step towards the future by leveraging the power of predictive analytics to predict employee behavior. With the use of a Flight Risk score, HP is able to determine the likelihood of an employee leaving their job. This practice may raise eyebrows among some staff members, but the company sees it as a profitable strategy to reduce turnover and associated costs.

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The Power of Predictive Analytics

Predictive analytics allows organizations to gain insights about individuals by analyzing existing data. This process creates new information by identifying patterns and predicting future outcomes. HP, along with other companies like retailer Target and law enforcement agencies, uses this technology to make informed decisions based on predictions about employee behavior, customer preferences, and criminal activity.

By predicting which employees are likely to leave, HP can take proactive measures to retain them. This approach helps reduce the high costs associated with finding and training replacements. Managers at HP rely on the Flight Risk score to guide their decisions and develop strategies to improve employee satisfaction and engagement.

Success and Savings

HP's Flight Risk prediction capability has already shown promising results. The company has successfully decreased the turnover rate of its specialized sales compensation team from 20% to 15% in some regions. This reduction in turnover translates to significant cost savings.

Overall, HP estimates that its Flight Risk prediction capability has the potential to save $300 million globally in staff replacement and productivity loss expenses. By identifying high-risk employees, HP can focus its efforts on retaining them and ensuring their satisfaction and loyalty.

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Factors Influencing Flight Risk

The Flight Risk score takes into account various factors that influence an employee's likelihood of leaving. HP's analysis has revealed that promotions, although generally beneficial, can increase Flight Risk within the sales compensation team. This finding suggests that promotions must be accompanied by significant pay hikes to ensure employee retention.

Other factors that contribute to Flight Risk include salary, raises, performance ratings, and job rotations. Higher salaries, more raises, and better performance ratings are associated with lower Flight Risk. Job rotations introduce change and help keep employees engaged, especially in roles that involve repetitive tasks.

Addressing Concerns and Maintaining Privacy

While the use of predictive analytics raises concerns among some employees, HP assures that the Flight Risk scores are confidential and only accessible to a select few high-level managers. The company emphasizes that the purpose of the model is not to penalize employees but to make necessary adjustments to reduce the probability of them leaving.

It is important to note that predictive analytics, although it analyzes individual data, does not invade privacy. The process focuses on discovering patterns and making predictions based on aggregated data, rather than inspecting individuals' personal information. However, the application of predictive analytics may reveal unvolunteered truths about individuals, which can be a source of concern for some.

The Dilemma of Predictive Analytics

Predictive analytics presents a dilemma for society as it balances the potential benefits with the risks to civil liberties. While predictive analytics can improve various aspects of life, such as healthcare, crime prevention, and personalized recommendations, it also raises questions about the ethical use of predictive technology.

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For example, the prediction of pregnancy by retailers like Target can have significant implications for individuals, such as job security and financial stability. Similarly, the prediction of criminal behavior by law enforcement agencies raises concerns about potential injustices and the reliability of predictions.

As we embrace the power of predictive analytics, it is crucial to establish ethical guidelines and safeguards to ensure that civil liberties are protected. The responsible use of predictive technology requires a balance between the benefits it provides and the potential risks it poses.

Hewlett Packard's Flight Risk prediction model showcases the potential of predictive analytics in the field of human resources. By leveraging data and predictive algorithms, HP is able to identify employees at risk of leaving and take proactive measures to retain them. While concerns about privacy and ethical implications exist, the responsible use of predictive analytics can lead to significant cost savings and improved employee satisfaction. As society navigates the information age, finding a balance between the power of predictive technology and safeguarding civil liberties is essential.

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