Peizhen Gu

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“Big Data” or “Big Brother”?
Peizhen Gu
Posted on April 16, 2022 at 5:06 pm
How should companies draw the line on ethics when embracing the era of people analytics?

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On April 19, 2022, Peizhen Gu commented on Tech Is Transforming People Analytics. Is That a Good Thing? :

Hi Hanne,

Great post, thanks for sharing! I totally agree with your arguments. You raised an interesting point that people analytics tools are enlarging the power disparity between organization and its employees. Especially under the upsurge of enterprises going “digital transformation”, enterprises have a tendency to focus on driving quantitative clarity as much as possible – try to analyze whatever data available to see if there is an “insight” behind. However, being aware on the potential negative influence analytics might have on other qualitative measures – like organization culture and individual sense of belongings – are equality important.

On April 19, 2022, Peizhen Gu commented on A rising market: People Analytics Software is leading a change in Human Management  :

Hi Wish,

Great post, thanks for sharing! The development of people analytics has brought HRs a lot of possibilities on “WHAT problem to address” – with the improving of data availability. But it also raises discussions on “HOW to address these problems”. As you mentioned in the post, although there are handy analytics tools available in the open market, concerns still exist on issues like privacy still keeps many startup platforms from touching/analyzing their clients’ core data. However, does client themselves has the capability to properly use the analytic tools and get the insights they want without intensive help?

This raises question on which is the better way to address client’s people analytic related problems, “product” (like tool/platform/app) or “service” (professional service firm like Mckinsey) ?

On April 19, 2022, Peizhen Gu commented on Is Amazon Planning on Using NLP to Control Employee Interaction? :

Hi Nico, thanks for sharing! Really like your post and I think it sets a prefect example on how a good intention heads south after bad execution – you simply cannot have a platform with 100% positive reviews on one hand, and a platform which is free from surveillance on the other. Amazon certainly chose to sacrifice the latter in order to build the former, and NLP became their handy tool to achieve this. My thinking is that they identified the right “WHAT need to be solved”, which is the need to promote culture of providing positive feedback. However, they chose the wrong “HOW to solve it”. Looking into their current feedback system and structure and insert some nudges may be a better choice than implementing such a big initiative.