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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 TheRaven on Tuesday February 13 2018, @10:24AM

    by TheRaven (270) on Tuesday February 13 2018, @10:24AM (#637061) Journal

    Weather is a nice example. You can predict the weather with around 60% accuracy by saying today will be the same as yesterday. You can also predict it with around 60% accuracy by saying that it will be the same as precisely one year ago. Combining these two techniques doesn't get you more than about 65% accuracy. Doubling the amount of compute that you throw at the models gives you less than a linear increase in complexity.

    You see this kind of diminishing returns in a lot of things. You can get around 90% accuracy from a trivial 4-state branch predictor and around 95% accuracy from the kind that we make students implement as an exercise. With a modern pipeline, you need to predict about 25 branches into the future to keep the pipeline full, so a 95% accurate predictor gives you only a 35% probability of keeping the pipeline full. Going from 90% to 95% was quite easy, going from 95% to 97% is really hard and still gives you only around a 50% chance of keeping the pipeline full.

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