One expert shares an insight into how HR can ensure that the data it collects will add value to business
Every HR professional knows that collecting data is becoming increasingly prominent within the industry – but what is less clear is working out what to do with it.
According to Adam Hall, head of employee surveys and insights at Towers Watson, there are two main types of analytics:
1. Descriptive analytics
These allow you to look at facts, answering questions – such as: ‘What has happened?’, ‘What was turnover?’, or ‘Who is eligible to retire?’ Descriptive analytics also incorporate the ability to better ‘describe’ those facts through trending, filtering, cascading and benchmarking. Most importantly, descriptive analytics lead to ‘hypotheses discovery’ and help to lay down the platform for predictive solutions.
2. Predictive analytics
This method does not describe ‘facts’, but outlines the probability that something will happen in the future. This can be anything from whether an employee will leave the company to whether a new hire will succeed. By understanding characteristics that lead to a high probability of a given outcome – whether through individually oriented action plans or through programmatic and policy changes – HR can hope to influence and/or prepare for the outcome.
“The challenge is to know what questions to ask,” Hall said. “These will be the questions that are crucial to the organisation’s success. Then it’s about analysing them and being able to tell a compelling story to the business leaders.
“Without the right question, the answer gained is not likely to have any strategic benefit or solve a business issue. The questions HR should be asking are those that uncover the roles and conditions that deliver most value to the business.”
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Impact the C-suite with your HR analytics
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According to Adam Hall, head of employee surveys and insights at Towers Watson, there are two main types of analytics:
1. Descriptive analytics
These allow you to look at facts, answering questions – such as: ‘What has happened?’, ‘What was turnover?’, or ‘Who is eligible to retire?’ Descriptive analytics also incorporate the ability to better ‘describe’ those facts through trending, filtering, cascading and benchmarking. Most importantly, descriptive analytics lead to ‘hypotheses discovery’ and help to lay down the platform for predictive solutions.
2. Predictive analytics
This method does not describe ‘facts’, but outlines the probability that something will happen in the future. This can be anything from whether an employee will leave the company to whether a new hire will succeed. By understanding characteristics that lead to a high probability of a given outcome – whether through individually oriented action plans or through programmatic and policy changes – HR can hope to influence and/or prepare for the outcome.
“The challenge is to know what questions to ask,” Hall said. “These will be the questions that are crucial to the organisation’s success. Then it’s about analysing them and being able to tell a compelling story to the business leaders.
“Without the right question, the answer gained is not likely to have any strategic benefit or solve a business issue. The questions HR should be asking are those that uncover the roles and conditions that deliver most value to the business.”
Related stories:
It's the small things: Little data before big
Impact the C-suite with your HR analytics
Interest high, uptake low with HR big data
