Dr Kazuo Yano, Fellow at Hitachi Ltd
Dr Kazuo Yano describes why Hitachi measure the happiness of their employees and how their Happiness Monitor uses the sensors in mobile phones as one way of capturing data about worker happiness.
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Read the transcript of Dr Kazuo Yano’s interview on measuring employee happiness and why this is important.Show transcript
Can you tell us about the happiness monitor you have been working on?
We try to quantify the happiness of people as a kind of index of the productivity of the knowledge workers. And, of course, happiness itself is very important for each individual. But also as a team or as a company, happy people shows a better result in business.
With your smart phone, you have an accelerometer inside. That sensor allows us to capture the very tiny physical motion – a hidden signal in the [period between] start moving and stop moving. That duration, whether that duration is short or long, is highly correlated with the happiness of people. It’s a very unconscious motion, so it cannot be controlled. But it’s a very objective measure of your happiness.
And it is quite useful for the AI era, because with good purpose, AI can [help you] work better; it can advise better intervention for you to be happier. In a call centre, we provide daily advice for the supervisor how many people will you talk today, based on past data. And actually, it shows 27% better productivity [when people are happier].
In Hitachi, business-to-business sales employees utilised our technology for several months, and those teams who utilised that advice system better get happier. And the people who got happier have shown better sales performance by about 30% in the next quarter. So happiness matters for your business performance.
How does Artificial Intelligence (AI) change the way that organisations work
In the past, we standardised our work to make it more productive and predictive. That was quite good when we were delivering standardised products and services all over the country. But, now everybody has different needs and changing needs. So only having standardised things does not make value.
AI and data analysis allows us to be flexible depending on the situation. Conventionally, we rely on standardisation and uniform deployment. But now we need to experiment and learn. So we face uncertainty.
The things we have already done make up only a part of the total world. We need new unexplored parts of the world that are systematically explored with the assistance and help of the new technology we call AI and data. In that way, we can face uncertainty and increased opportunity in a very effective way.
That means that the workplace and company decisions will be much more creative and innovative – because we are basing them on this data. Whether you utilise this technology is totally up to you. But companies who do this are getting results.
What does the future hold for AI?
AI is not a replacement for human labour. It is a very systematic way of solving problems, especially complex problems. Simple problems we can standardised and address during small chunks of a process. Doing this manually, that was what we did in the last century. But now, to create more value and more creative solutions, we need to have a new weapon or a new tool. That is AI and data.
Everybody on this planet can be much more creative. And depending on the situation, depending on your strengths, we can be more diversified. Businesses can be diversified and create more value. Charles Darwin said, “Evolution is not progress. Evolution is diversification of the descendants.” With AI we can be much more flexible and diversified and much more creative.
What opportunities does AI offer?
We need to be able to depend on less data. Many AI applications right now depend on very heavy data, so only those problems which have massive amounts of data can be addressed.
But for many of the most important problems, the data is much more limited. But the future our reliance on the amount of data will be reduced. With AI we will be much smarter [even when we have less data]. We know more with less information. That’s what smart means.
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Image under licence from iStockPhoto.co.uk, credit Delmaine Donson