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4 Steps to Develop Data-Driven HR and People Teams

Source | | Caroline Styr

70% of HR executives say that HR is ripe for reinvention, according to Gartner’s recent research ‘Accelerating the journey to HR 3.0’. HR is evolving into a more data-driven, digital function, driven not by intuition, but by evidence and actionable insights from AI and internal/ external data. Forward-thinking HR professionals understand the subsequent need to upskill.

Trends like automation and AI in HR might lead you to believe that the future of HR requires HR professionals to become technical above all else. But this isn’t the case. Research from myHRfuture in 2019 looking at the HR skills of the future showcased that the most in demand skills amongst HR professionals are not just technical skills, like people analytics and strategic workforce planning. Skills to manage relationships with key stakeholders, influence change and build credibility are also critical for data-driven HR. This year, Insight222 published research looking at how roles are developing within the people analytics function. The fastest growing roles are data scientist and business consultant – once again showing that even within the HR analytics function itself, it’s not all about technical roles.

We’ve looked back on the most popular skills that HR professionals have been learning in myHRfuture in 2020. The same pattern is emerging, that it’s not just technical skills that HR is focused on, but consulting and influencing skills as well. We’ve grouped the most in demand training into four themes. As talent executives plan to double their efforts in the next two years to upskill their HR teams in new capabilities, let this list be a guide to what’s trending in HR upskilling:

  1. Building a solid foundation in People Analytics

  2. How to have effective conversations with the business

  3. Storytelling with data

  4. Ensuring you’re creating value with People Analytics

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As an individual HR practitioner, it is increasingly important to be able to accurately interpret people data and make recommendations or take actions based on this insight. When taking on a challenge your organisation is trying to solve, for example a high attrition rate, statistics can help HR professionals to understand and validate what’s going on from a people perspective. Statistical analyses can form the basis of an evidence-based recommendation (not just relying on gut feel), which can be made to business stakeholders. This approach helps to position HR as a data-driven strategic partner for the business.

The first port of call for any HR professional is building basic statistics and data analysis skills. Our course, Understanding and Applying Statistics in HR is one of the most popular for this very reason.

From an organisational perspective, the people analytics function needs to build a robust foundation, including strong governance, effective prioritisation of business challenges and delivering tangible business outcomes. One way to consider the elements you need for a successful people analytics team is with Insight222’s Nine Dimensions for Excellence in People Analytics® model:

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The first step to successful data-driven HR comes before any number crunching and analysis is done at all. Instead of launching straight in with a “hot topic” or something that you personally, or the HR function more broadly, might think is interesting, it’s critical to start with a burning business challenge. Uncovering these challenges depends on effective conversations with the business.

Understanding business needs requires excellent communication and relationships with business stakeholders and is often a task undertaken by the HRBP. The next step is to translate findings from these conversations into hypotheses for your people analytics function to tackle. The popular course, Framing Business Questions and Developing Hypotheses for People Analytics, teaches you:

  1. How to make sure that your People Analytics project adds value

  2. How to get to the heart of the problem the business is trying to solve, before starting your analysis

  3. How to understand and translate those problems into a clear hypothesis

  4. How to ensure that the analysis you do is business relevant and has the right context

  5. How to prepare to conduct the analysis yourself, or hand it over to the People Analytics team

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