How to get up to predictive analytics speed in 3 key steps

Predictive analytics can help to address critical business issues including optimising costs and managing risk, transforming business models and increasing innovation, through to enhancing the customer experience and accelerating sales

Less than 20 percent of organisations are able to apply predictive analytics to address important people issues, according to research from IBM.

This is primarily due to a lack of understanding of how to use analytics to improve the business bandwidth due to competing priorities internally or a lack of relevant skills within the function to address these issues, said Leslie Breackell, IBM smarter workforce client engagement leader, A/NZ.

“The majority of HR as a whole is still focused on basic HR reporting and statistical analysis of employee data, such as historic reporting and dashboards,” she said.

But for those organisations which are making headway in this area, Breackell said the important trends seem to be:

  1. Making better decisions rapidly. This is no longer a goal; it’s an imperative. “We have to shrink the time to informed action, which requires us to deliver more than just faster answers; it demands that we identify the right questions to ask,” she said.
  2. Treating employees as individuals. Employees increasingly want to be treated by their organisations as an individual; they want to work with leaders who tailor their approach and work environment for everyone.
    “They have the expectation that the company knows them at an individual level and can tailor their work environment for them,” said Breackell. “The insights from predictive analytics give leaders the opportunity to do this more effectively than ever before.”
  3. Ensuring HR relevancy within the business. Predictive analytics gives HR another avenue to be business relevant; providing a data-driven connection to how an organisation should fully capitalise on its human capital.
    “It’s about time HR professionals were more ROI driven and ‘fiscally responsible’ – because they can now point to real insights that link to real business benefits,” she said.

By identifying these trends, the IBM research showed that predictive analytics in a HR context can help to address critical business issues including optimising costs and managing risk, transforming business models and increasing innovation, through to enhancing the customer experience and accelerating sales.

How data is impacting talent decisions
Breackell explained that the intent of analytics is threefold: to create better, smarter decisions; it enables one to move from guesswork and assumptions to actionable business intelligence; which ultimately leads to clarity and insights. 

“’Insights’ is the key word here and from a HR perspective, means an organisation can link people metrics to business outcomes,” said Breackell, who said this can help business to respond to issues such as:

  • The propensity for top performers to leave the business
  • How to improve high performer retention within critical locations
  • Which candidates will likely succeed in a new leadership role (and why) as well as safeguarding the leadership talent pool for critical roles
  • Improving customer loyalty through workforce drivers and quickly finding the right experts

“In addition, analytics helps us to better leverage workforce and behavioural science so that we better understand talent and predict the likelihood of their success – even before they join an organisation,” said Breackell.

“It’s about fearlessness – which we know is not a trait bred into HR

“A huge advantage of applying analytics to talent management is being able to understand what makes people great at what they do and accurately match that to a culture they will thrive in with the skills they have developed and connecting those people to the right job both internally and when recruiting externally.”

By using analytics linked to behavioural science, she said organisations can hire and develop employees that mirror their very best.

Predictive analytics and HR leaders
There are a number of factors that need to be considered for a successful application of predictive analytics in the HR function, said Breackell.

Business priorities must be a central component of analytics, and she said the HR team has to understand the business and can use analytics to reinforce and drive activity to support it now and into the future.

HR can also leverage analytics to focus on storytelling, and HR analytics in this capacity is about how to influence other people to make better decisions.

“Through predictive analytics, HR can actually change the way that information is presented to others by outlining what the data is saying and using that to provide recommended outcomes and next steps,” she said.

“That’s where HR adds value and remains relevant.

“Today’s smarter workforce calls upon HR leaders to be bolder; that’s about being prepared to think differently and take some calculated risks.

“It’s about fearlessness – which we know is not a trait bred into HR. But to use analytics well, you have to be more fearless – at least in the right context and in the right way.

“This means HR leaders need to have a greater level of comfort with statistics and numbers. They don’t have to know the detail of how to run regressions, but it’s about working in a data driven way.”

“The majority of HR as a whole is still focused on basic HR reporting and statistical analysis of employee data”

While perfect data isn’t required for a successful analysis, Breackell said it is important that HR leaders find people in their teams who can revolutionise the way that they think about analytics inside of HR.

Applying this approach to leadership will not only help the function to understand the past, but also optimises the present, and attempts to predict the future, all the while linking back to business objectives, she added

Geting up to speed with predictive analytics: 3 key steps
Breackell said there are a number of key steps HR leaders can take to help improve their predictive analytics skills and capability:

  1. Set your direction: It’s important to establish a clear vision and agree on the scope of responsibility for any talent analytics function. Define a governance model so that the analytics activities are clearly contributing to business objectives. Aim for quick win projects – this is important as it will uncover some important insight and generate executive discussion.
  2. Define your approach: One aspect here is about knowing your data – Is the organisation’s data reliable and accurate? Perfect data across all data sets is unrealistic, but there may be many views on what is an acceptable level of completeness. Another aspect is around data management.
    A challenge often concerns the need to bring together disparate data sources. Or a common problem is that HR typically owns the data, but does not manage it. Then there’s the need to know and decide on technology solution options, such as cloud technologies for efficiencies, convenience and cost effectiveness. New technologies on the market can make use of cognitive and visualisation technologies to aid storytelling and presentation of results.
  3. Grow your capability: Finally, there’s the matter of identifying and defining the roles and skills required for an effective analytics team, as well as the numbers of people required. Identify an HR analytics leader with strong commercial and operational business experience.
    Ensure the HR analytics team has a balance of skills including HR knowledge, analysis expertise, and consulting. The required size of the team will often depend on the nature of the business problems being addressed by analytics, the overall complexity of HR, and the size of the workforce. Once the team is in place and has grown in capability, the analytics work should begin to gather traction in the business. Identifying analytics projects that go beyond traditional HR boundaries to impact the business and the wider operating environment will be more impactful.

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