The Learning Animals: How Training Your Staff Retains Them

I’ve recently been reading the New York Times Bestseller from Google, ‘How Google Works’. The purpose of the book is to give the business world a real insight into how Google operates. Amongst the different chapters within the book, from planning to culture and innovation, I was particularly interested in Google’s approach to talent.

It’s clear from the book that Google aims to employ those who are ‘independent thinkers’, by this I think they are really relating to smart people. This doesn’t necessarily mean earning a degree from Harvard or Cambridge, it’s more to do with those who can solve problems.

Within the ‘Talent’ chapter there’s a section about ‘Learning Animals.’ For me, this was especially interesting as one of our values at Webanywhere is ‘Always Learning’. Google comments how the age of the internet and technology is in constant change. So, they value people not only on how smart they are now, but also on their ability and hunger to learn into the future. This is valuable to Google as they develop new markets, such as the ‘self driving car’, ‘Google Glass’ and ‘Google Fibre’. The starting point for the ability to learn, they say, is an individual’s brain power, but this is not the only ingredient required. One other ingredient which Google looks for is those who ‘love a rollercoaster’.

We’ve seen a similar approach from similar companies in their culture and talent hiring process, notably Netflix, where there are constantly looking out for the smartest people to hire in their business; something which has been commented as the best piece of business advice to come out of Silicon Valley in recent years.

The book also talks about the traditional approach to recruitment, and how Google differs. For example, the traditional approach to recruitment is if the candidate has excelled previously in a similar role. Google mentions that hiring on specialism over intelligence is wrong. Take the internet industry, with the dynamic rate of change, a specialist can be dangerous as they focus too much on ‘what they know today, and, in a previous life’. You need what’s going to happen tomorrow.

Google says it’s difficult to hire learning animals. Jonathan Rosenberg uses a certain technique to find them out during the interview process. He asks, ‘’What big trend did you miss about the Internet in 1996?’’ This question forces the candidate to think about what went well, and what they missed. They then admit to what they did wrong, this question is impossible to fake, according to Google.

Once you’ve hired your ‘Learning Animals’, it’s important you keep them! High performance individuals need interesting and engaging work. One method Google have adopted is to create board level projects around business issues whereby all employees can apply to work on the specific opportunity for a change. For example, Larry Page posted a project which a junior employee at Google was able to work directly with Larry.

One of the major components to ensure your learning animals remain within your business is to start using talent analytics. This is something Bersin by Deloitte have recently written a report based on the organisations they surveyed, known as the ‘Talent Maturity Model.’ Organisations are assessed based on their use of Talent Analytics, for example, low level one talent analytics focuses on tactical decisions based on data, whereas, level 4 is based on a predictive model looking at where the data is used to link with strategic planning and specific scenarios.

In the report more than half organisations who were surveyed said they were ‘Level One’. At levels two and three, 40% of organisations used talent analytics for activities such as benchmarking and ‘people planning’. Only 4% are seen as those at level four, these organisations are really linking their strategic plans into their talent pools known as ‘Predictive Analytics.’

In Google’s case, Talent retention is key, they do this by keeping the talent pool busy, engaged and challenged. As the research by Bersin suggests, talent management can be better understood with the use of data. Clearly, the 4% of organisations using ‘Predictive Analytics’ are set apart in their thinking from the rest. They are using talent analytics to link in with their long term strategic goals. Take for example a leadership blended learning programme. As your leaders go through this programme you can use analytics to quickly see the level of engagement in workshops. You will also be able to view this from their level of interaction within the elearning environment. For those who are within your talent pool aren’t engaged, you could use ‘Level Three’ analytics to create talent development programmes specifically for those people, or, as Bersin put it ‘People Models.’

Level four in Bersin’s Talent Maturity model is really trying to predict this people however and therefore allowing data to inform specific circumstances that might arise and for the organisation to then plan for these changes, should they arise. In doing so the organisation can plan to mitigate those risks.

Like what you read? Give Conor Gilligan a round of applause.

From a quick cheer to a standing ovation, clap to show how much you enjoyed this story.