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timelines, performance management and more. The CEO wants to know the headlines: What is it going to cost? How long before we’re fully productive again? Who do we need to keep and for how long? Which top performers are at risk? Is there a talent pool in the area we can tap into - and how will we track, measure and monitor the project through to completion? Ouch! Not only a difficult project from a people and logistical perspective, but complex in terms of variables and data. However, a lot of the baseline information should be in your HR and Payroll systems. A modern analytics platform will allow you to layer in some basic variables to build a describable financial hypothesis based on your people data.
In the new data culture, ideas, proposals, solutions, reports and suggestions must come with a data-backed justification - this is the new rule - and the key question from HR leaders, the part that ignites curiosity and unearths insight is, ‘so what’? What does it tell us about this process’ relation to our business objectives, our bottom line? Human brains aren’t wired to react to metrics and spreadsheets. So, if you need to provoke action, or you require busy people to pay attention, it’s best to use an ancient, proven medium… stories. The best data stories distil the ‘so what’, to make data actionable, helping busy decision-makers quickly understand the meaning, appreciate the ramifications of the proposed actions and the consequences of inaction. As a HR data journalist, your job is to package the information, provide the headline statement in context, then back it up with visualisations that demonstrate the exact insight you want them to pull from your data. Busy C-suite leaders, who may not have a technical grasp of metrics, will more easily grasp the meaning and value of your data when presented in a narrative, where key insights clearly demonstrate cause and effect relationships as part of an overall story.
A transition to data-based practices can be a difficult mindshift for HR staff who have traditionally been trusted to make educated gut decisions. Complex data sets are intimidating, but it doesn’t even have to be that complex. Take one of the most famous examples of data analysis - Billy Bean, the subject of the book Moneyball, fundamentally changed Major League baseball, by using decades of data about successful baseball players. He formulated his question; ‘which factors indicate likely player success?’. Then he looked at the past, extrapolated a trend and used it to plan a talent strategy so effective, that he’s now basically immortal in the world of baseball. For HR teams coming to grips with data and analytics, it’s important to emphasise that you can make a huge impact with comparatively simple analysis. In fact, a thrifty approach to data practice is precisely the mindset you want to adopt. This stinginess, a familiar trait among data scientists, is what motivates the creative approaches that typify some of the very best work. Because there’s plenty of room for creativity and innovation in analytics, good data scientists focus
primarily on the question and look at the real world, before they identify the datasets required to yield an answer. For instance, here’s a great question; ‘who are the key facilitators across our organisation’? Facilitators, thought leaders, problem-solvers, skull-crackers - the go-to people, without which efficiency and productivity would slow to a crawl. How do we use data to identify them? You might expect a complex analysis of CPD scores and performance metrics, adjusted for region, seniority and department. That would give you your go-to set. Possibly, yes; but is that a real-world answer? And is there an easier solution? In the real world, ‘go-to’ people spend a lot of time answering questions and solving problems, that’s why they’re go-to people. Therefore, communications data, email and internal phone calls, might paint a detailed picture of how knowledge-flows within an organisation. Your ‘go-to’ people are the hubs in this web, and communications data identifies them independently of location, grade or access to training. Answers to people analytics questions don’t always come solely from HR data, which is why integration is so important in modern organisations. Analytics technology has advanced to the point where incorporating disparate sources, even third-party data - like gender pay gap benchmarking - should no longer be a hurdle. People analytics isn’t about focusing on people data, it’s about posing people questions, to find the appropriate answers.
•
IN THE NEW DATA CULTURE, IDEAS, PROPOSALS,
SOLUTIONS, REPORTS AND SUGGESTIONS MUST COME WITH A DATA-BACKED JUSTIFICATION - THIS IS THE NEW
RULE - AND THE KEY QUESTION FROM HR LEADERS, THE
PART THAT IGNITES CURIOSITY AND UNEARTHS INSIGHT IS, ‘SO WHAT’?
FOR FURTHER INFO
www.peoplexcd.com
DECEMBER 2019 | thehrdirector | 51
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