Top Tips from #PeopleAnalytics15


If you’ve looked at my blog and/or Twitter feed this week you can’t have failed to notice how inspired I was by #PeopleAnalytics15. With such a focussed agenda it was inevitable that things got a little repetitive as the conference progressed, but I found reassurance in the realisation that an effective people analytics function can be developed when adhering to a few key points. I realise there’s already quite a few posts of this type around, but I always find it helpful to crystallise your own thoughts and translate your learning to your own context. Therefore here are my top tips from the event.

1. The Perfect Data Misnomer
We heard lots of warnings against being paralysed by obsessing over perfect data. Of course good data is important, but responsibility for it’s quality needs to be pushed out to front line data entry. If perfect data is used as an excuse, people analytics is never going to happen. As was pointed out, a little bit of dirty data is unlikely to affect the conclusions you draw from the overall data set.

2. Pull yourself together
And your data of course. How many of us are guilty of having multiple spreadsheets in various locations? How many of us gather data only to store it away where it never sees the light of day? Data in silos creates just that mindset. Bring it together and our insights become much more powerful. Yes this can be hard, but so worth it.

3. Context, context, context.
Without context, data is merely reporting numbers. It only becomes meaningful when we connect all data to what the business is trying to achieve.

4. Focus on the Outliers
Stop reporting data based on the workforce as a whole. Drill down. Find the meaning. Take performance for example – an overall view of effectiveness is useless. Focus on the best performers and how to emulate their success, as well as the worst performers and how to improve or resolve their situation.

5. Data Transparency
When data is the preserve of a privileged few it becomes powerless. If those on the front line don’t see how useful the data they gather can be, it will not be a priority. Transparency can be a little scary but if access to meaningful data is restricted it is unable to drive change.

6. Start small
When something new emerges into the field, we can be quickly left feeling excluded. If your preferred learning style is through experience you’ll be relieved to hear that this is the recommended approach for developing your analytics function. Start small with the simple wins that will give analytics the credibility to grow.

7. Ask the right questions
Some of the speakers emphasised the importance of giving your leaders what they want via analytics, but of course this relies on them knowing what analytics can do and therefore asking for the right information. Reporting headline statistics unrelated to the business aims isn’t going solve any problems. By framing analytics as providing the interpretation and insight to get to the heart of issues you can start to encourage the right questions being asked of the organisation’s data.

8. Storytelling and presentation
It’s difficult for me to convey via words the difference the simple, targeted presentation of data can make. Once again it’s about focus and questioning the established presentation methods to ensure they drive the right outcome. Data that tells a clear story is much more compelling.

One of the most powerful messages I took away from the event was that people analytics is the difference between making decisions based on “I think” and “I know”. If a single focussed reason is required to drive support for analytics then that is it.

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