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PowerCurve for Beginners: A Comprehensive Guide

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PowerCurve is a complete suite of decision-making solutions that help businesses make efficient, data-driven decisions. Whether you're new to PowerCurve or want to understand its core concepts, this guide will introduce you to chief features, applications, and benefits. What is PowerCurve? PowerCurve is a decision management software developed by Experian that allows organizations to automate and optimize decision-making processes. It leverages data analytics, machine learning, and business rules to provide actionable insights for risk assessment, customer management, fraud detection, and more. Key Features of PowerCurve Data Integration – PowerCurve integrates with multiple data sources, including internal databases, third-party data providers, and cloud-based platforms. Automated Decisioning – The platform automates decision-making processes based on predefined rules and predictive models. Machine Learning & AI – PowerCurve utilizes advanced analytics and AI-driven models ...
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7 top initial steps you need before you start HR predictive analytics

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Top criteria you need before you start analytics in the Human Resource department. I am sure you need many approvals to start analytics in HR.
hr analytics

The risks involved to start analytics in the Human Resource department

  1. You must comply with the legal requirements in which you operate as it relates to the use of people data. The reason is the analytical insights should reflect the cultural and social marks of your organization.
  2. You need to get involved all stakeholders involved and what the cost of what you're doing is relative to the benefit of doing it.
  3. Use analytics through accountable processes, one of which should be acknowledging that using predictive analytics with the workforce has the potential for negative impact, not just positive impact, Walzer said.
  4. Engage the legal department to make sure you understand any implications before you've done something, not after the fact.
  5. Assess whether the use of analytics involves sensitive areas, which it often will, Walzer said. But, she added, these are often accommodated by using reasonable safeguards.
  6. Know what data you just shouldn't collect. 
  7. One example is prescription drug use of employees. "Many employers have access to it through third-party health care providers, but the idea that you're going to bring it in poses a lot of liability to the organization

References

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