The recent IBM Smarter Workforce Summit in London provided essential practical guidance on launching a successful HR analytics project and resourcing an ideal team. Michael Carty reports.
“HR has the chance to thrust itself to the forefront of the business agenda by mastering analytics.” This is according to Jonathan Ferrar, who leads the analytics practice for IBM Smarter Workforce, speaking at this summer’s IBM summit. The event provided detailed practical guidance on getting HR analytics projects off the ground – and ensuring they are successful.
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Three key learning points emerged on how to launch a successful HR analytics project.
1. Focus on specific, achievable goals
“Start with why.” This is Ferrar’s succinct advice on the best way to kick off an HR analytics project. It is essential to identify the problem that needs to be solved, the data and resources available to you, and to know what success looks like.
Ferrar says: “Think small projects. Think projects closest to business needs. Think of today. Don’t spend too long on it. Working to identify the perfect solution and the perfect piece of work can mean it falls off the business agenda by the time you’re ready to report.”
Darren Philpott, vice president of organisational insight at Barclays, agrees that scale is a critical consideration for successful HR analytics projects. “Don’t go too big,” he says. “Don’t collect all the data that exists straight off. If you start small you can have a big impact. Don’t think you have to think big because the problem sounds big.”
2. Go after quick wins
Once your project is up and running, work on building its visibility and impact to ensure its survival and success. The shrewdest way to do this is by identifying and going after a “quick win” within the first 30 days, advises Kieran Colville, a consultant at IBM.
The ideal situation is one in which HR data can make an immediate difference while also delivering long-term cost or time savings.
“Focus on identifying and cleaning HR data relating to critical job families that are disproportionately impacting your chief executive’s key performance indicators (KPIs),” says Colville. “This shrinks the effort needed and fast-tracks your analytics project by showing immediate benefits for the boardroom.”
3. Be confident with HR analytics
Successful analytics projects can have a powerful positive impact on the organisation, and can increase the influence of the HR department. But for this to happen, HR must be able to communicate the project persuasively.
“It’s a question of being confident,” says Ferrar. “You don’t see finance or marketing trying to claim they have perfect data. They just report it. No one’s data will ever be perfect. Every time you have a new joiner, your data becomes imperfect.”
Storytelling skills, and the ability to create and land a persuasive message using HR data, are also “a huge part of how analytics can help empower HR,” says Colville. “HR analytics team leaders must go beyond pure dashboarding to being able to tell a story with data. You have to be able to tell a story so that your execs will get it intuitively and emotionally.”
Resourcing the ideal HR analytics team
“Are HR and analytics mutually exclusive?” This audience question from one delegate at the event pinpoints a key concern for HR. Analytics offers HR major opportunities to revolutionise its work and exert influence on the organisation, but the profession has not traditionally been seen as the place to find data specialists.
HR analytics careers
An effective HR analytics teams requires a diverse range of skills, says Colville. It should ideally include mathematicians, data scientists, statisticians and psychologists alongside HR business partners.
Dr Nigel Guenole, of IBM’s Smarter Workforce Institute, says that “HR is on the precipice” when it comes to making high-impact use of analytics and that “the profession is moving forward toward more data-focused decision-making”.
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He argues that HR is following a path already taken by finance and marketing when it comes to data. This path starts with intuition, then moves through the scientific use of data, towards a point at which data use is automated. As the importance of HR analytics grows, the HR profession will become increasingly attractive to candidates from more “numeric” backgrounds, he says.
HR should not fear analytics, Colville concludes: “Use analytics as your friend. Don’t view it as your enemy. It’s about building HR credibility, using evidence and insight to become more credible and influential.”
