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Eduardo Valencia
403 followers -
Director of Master in People Analytics
Director of Master in People Analytics

403 followers
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1. Three subjective and three objective methods to measure performance.
2. An actual performance evaluation case based on the 180° feedback survey methodology.
3. A proposal to evaluate performance more frequently, using objective measures.
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Data deceit is a subject that I find very dear to my heart. I often rant against the countless deceptions that often slip into what appears to be data-validated talk.

Alberto Cairo has embarked on an inspiring campaign to equip the citizenry with a solid visual literacy as an antidote for a poison that runs rampant in our world. His call to action is: "join me in the fight!". Well, I am in!
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In this post:

1) It is important to understand the actual causes of a problem

2) How can we anticipate the consequences of the actions that you plan to take in HR

3) Clearly explain the reasons for an intervention

4) There are black box algorithms (like neural networks) and glass box algorithms (also called "white box"), opposites obviously. These are the heroes of this post.
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"Engagement is profitable.” That sentence sounds good, doesn't it? Truly motivated employees are an important factor in the success of an organization. Unmotivated workers won't contribute as much.

WATCH OUT!

Fact: Many studies on engagement and the bottom line unanimously agree on engagement's correlation with profit:
But: I think you need to be especially skeptical when reading statistics that talk about correlations between engagement, and profit.
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The deal: I want your feedback! Read People Analytics. Data and Text Analytics for Human Resources. It is free now.
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Many users who want to incorporate text analytics into their Voice of the Employee (VoE) analysis are not sure how to translate their business requirements into something compatible with their current processes.
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If today we call it ”people analytics” instead of ”HR Analytics, ”talent analytics,” or ”workforce analytics,” it’s Google’s fault.
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To overcome evil and lies, you must be well trained, like the students of Hogwarts, in defending against these statistical dark arts.
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Data privacy is going to be an increasingly important topic of debate within companies.
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But is this really big data? When can we say we've arrived at "Big?"
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