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posted by janrinok on Tuesday February 13 2018, @03:17AM   Printer-friendly
from the I-guess-so dept.

An increasing number of businesses invest in advanced technologies that can help them forecast the future of their workforce and gain a competitive advantage. Many analysts and professional practitioners believe that, with enough data, algorithms embedded in People Analytics (PA) applications can predict all aspects of employee behavior: from productivity, to engagement, to interactions and emotional states.

Predictive analytics powered by algorithms are designed to help managers make decisions that favourably impact the bottom line. The global market for this technology is expected to grow from US$3.9 billion in 2016 to US$14.9 billion by 2023.

Despite the promise, predictive algorithms are as mythical as the crystal ball of ancient times.

[...] To manage effectively and develop their knowledge of current and likely organisational events, managers need to learn to build and trust their instinctual awareness of emerging processes rather than rely on algorithmic promises that cannot be realised. The key to effective decision-making is not algorithmic calculations but intuition.

https://theconversation.com/predictive-algorithms-are-no-better-at-telling-the-future-than-a-crystal-ball-91329

What do you people think about predictive algorithms ? Mumbo jumbo or ??


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  • (Score: 2) by acid andy on Tuesday February 13 2018, @12:34PM

    by acid andy (1683) on Tuesday February 13 2018, @12:34PM (#637075) Homepage Journal

    My rant was typo-ridden - I know. Just to put it in context, my post was illustrating that most of the problems involving human beings often can't be solved with lazy, simplistic algorithms or flow charts. It's pseudo-science trying to find shortcuts to solve problems when typically there will already be a real, optimal solution staring somebody in the face. The trouble for the management overlords is they can't tell who to ask or who to believe for that optimal solution. It will be one of their subordinates. And the information they need probably won't appear on some crappy feedback form. I can't see how a prediction algorithm can approach anything like that optimal solution without actually acquiring the data that involves it. For example, say employees are stressed an less productive due to unrealistic deadlines. If the magic employee behavior prediction algorithm isn't fed data about deadlines being perceived as unrealistic, how can it possibly come out with the right result?

    It's total bullshit for unscientific idiots.

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