To date, DBS Bank's human capital analytics team has uncovered hidden insights into how the bank hires, retains and maximises performance, successfully articulating them to the bank's management in a way that disrupted the thinking in its workforce.
Over a year ago, business leader turned HR practitioner, Grace Yip, chief operating officer of group HR at DBS Bank, was tasked to set up and run the human capital analytics team for DBS. After a year on this challenging yet fulfilling journey, Yip shares the five things HR leaders should keep in mind when setting up their own human capital analytics team.I’ve always been a strong believer of human resources teams using data better.
Before I became a HR practitioner at DBS Bank, I was a business leader, running a business and managing people. Data-backed solutions to HR problems were always more effective than making decisions based on “gut feelings” in creating value and improving productivity for the organisation.
So when analytics first appeared in the world of people operations five years ago, I thought it was great. I had read much about it and found myself selling these solutions to clients. It was fascinating to see how big data transformed gut feel into deep insights and recommended actions in the hiring and retaining of talent.
But I didn't truly understand the power of human capital analytics until I had to set up and run the human capital analytics team for DBS a year ago when I joined the bank.
For starters, it’s ridiculously hard work. In that first year, we developed our target operating model, hired the team, built our employee analytical records (ours has more than 600 attributes) and completed modelling for two projects, which are being deployed this year. Phew!
Here are five things I’ve learnt since setting up the human capital analytics team at DBS HR just over a year ago. It may not be rocket science, but it’s a meaningful reflection of this challenging yet fulfilling journey:
1. Set a clear direction and an inspiring visionI’ve found that having a clear direction of how human capital analytics operates and why it’s important is key to attracting the right talent.
Data scientists aren’t satisfied with simply knowing what projects they’ll be working on. That’s not enough. Instead, they want to feel that they fit in and are part of a critical function in the organisation. They want to understand the larger plan and if the organisation is committed to it – or if it’s just a passing fad.
A clear direction helps align with the organisation’s overall people priorities. It lets you tackle the easy wins, especially at the start of the journey, by showing your stakeholders that the team knows what it is doing, and that analytics is a tool that helps them and delivers value to both HR and the Business.
Today we have summarised our overall vision for human capital analytics into a single phrase: Powering HR into the Future; Powering our People into the Future. Our approach, analytical process, capabilities and services are illustrated in a single infographic using the analogy of a race track. Putting the human capital analytics team at the heart of insight has led to more effective decision making.
2. The answer lies at the crossroads of small and big dataIt is so easy to get caught up in the big data, especially when you have a lot of it, that we often forget the context of the problem.
This was my most painful lesson, learnt on one of our two projects last year, but also the most powerful one. We lost our way even though we began with a solid hypothesis, which drove our data collection.
Often, getting answers from big data is like finding a needle in a haystack. But you also need to understand the context of how human behaviour manifests itself.
You need the “small data” to get meaningful insights. You need to speak to people on the ground and understand their behaviour, to be able to detect patterns and analyse how that behaviour changes over time.
It was only when we took a step back, spoke more with our colleagues and observed the subject matter – gathering the small data – did we truly understand what we were solving. We had to reframe and re-contextualise our analysis. But once we did, everything fell into place and made sense.
One of my favourite reads of 2016 is Martin Lindstrom’s book, Small Data. It cemented my perspective on using both big and small data into our analytical approach.
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3. Never forget the return on investmentWe are so busy with the day-to-day functions at work that we often do not make time to establish a closed-loop process on projects; that is, taking action and giving feedback on this action.
But embarking on the human capital analytics journey is pointless unless someone decides to use these insights and acts on them.
At DBS, we make sure this closed-loop process is set up and followed.
We explain to managers that they must use these insights to help their teams grow well in concrete and actionable ways. The return on investment on our time, energy and resources is how we measure our success.
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4. Storytelling is critical in getting buy-inIt’s no secret that data scientists have their own data speak. Yet few have mastered the art of distilling the essence of their findings and telling a compelling story to those who are not in analytics.
Our human capital analytics team spends much time thinking through our storyboard that delivers a salient message in a brief but powerful summary.
We have found the use of short animated videos to work incredibly well for us. In three minutes, we are able to take the audience from zero awareness to a level of amazement at the insights we have uncovered through analytics. For those who are interested, you can take a look at one of our videos here.
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5. The world of data scientists is ripe for disruptionIn the short year where I’ve immersed myself in the data analytics community, I’ve found that I often need to separate the wheat from the chaff. Many can speak analytics, but not all can execute.
Analytics tools are also evolving so quickly that, soon, the average business person will find it easy to wield the power of analytics. In the near future, developing and refining statistical models and algorithms may be as simple as fiddling with Microsoft Excel.
Today, data scientists must not only have deep technical skills but also start building the breadth of capabilities to become high performers.
David Green’s LinkedIn post, “What constitutes best practice in people analytics”, is a great read about developing your capabilities. The stronger your breadth of capabilities, the more irreplaceable you will be even when disruptive technology comes knocking at your door.
I have also become a complete data geek and now truly appreciate the value that data brings to HR. Human capital analytics is core to recruiting and retaining the best people. It lays the foundation for the business, but requires perseverance and grit to get there.
Our human capital analytics team has uncovered deep insights into how DBS hires, how we retain and maximise performance. The most satisfying part of the journey has been how we have been able to uncover hidden insights and articulate them to DBS management in a way that disrupted the thinking about our workforce.
And on this one-year journey, my team and I have experienced first-hand how we can #bethechange and #livefulfilled.