Too few organisations are actively implementing talent analytics capabilities to address complex business and talent needs.

Google uses analytics to gain insights into the impact of every interview and source of hire. Companies such as Pfizer, AOL, and Facebook, now analyse the factors that correlate with high-performer retention. BP uses analytics to evaluate its training. SAB Miller uses analytics to drive high quality standards across a variety of programmes worldwide.

Despite these and other high-profile uses of analytics, Deloitte’s 2015 Human Capital Trends survey confirms that most organisations have been slow to implement such capabilities. Three in four surveyed companies (75 per cent) believe that using people analytics is “important,” but just 8 per cent believe their organisation is “strong” in this area — almost exactly the same percentage as in 2014.

Organisations are still new to this discipline, and many suffer from poor data quality, lack of skills, and a weak business case for change. While people analytics programmes can deliver a high return on investment (ROI), HR leaders have difficulty building an integrated plan. And more than 80 per cent of HR professionals score themselves low in their ability to analyse — a troubling fact in an increasingly data-driven field.

As HR analytics teams struggle to build this capability, vendors are starting to fill the gap. Today, nearly every HR software vendor is eager to sell packaged predictive analytics tools, often built right into their talent and HR management software.

But buying more data-driven HR and talent management software is just the first step — it will take several years for businesses to fully absorb this technology. Companies with leading capabilities in HR and people analytics have been building these capabilities for three years or more.

Where can an organisation best apply analytics to improve talent management? Some possible areas include:

• Understanding and predicting retention: With retention and engagement now becoming a CEO-level issue, understanding why people leave a company has become a top priority. One vendor we know of has become so sophisticated at this analysis that it can predict retention within weeks, simply based on data available from an individual’s behaviour on social media. This type of data-driven insight has become a hot commodity in Silicon Valley’s new race to attract and retain top software engineers.

• Boosting employee engagement: While changing behaviour among managers often proves harder than simply uncovering facts, many companies are using analytics to identify ways to increase engagement and/or boost retention. One company, for instance, found that its compensation was too evenly distributed, pleasing mid-level performers but leading high achievers to depart for greener pastures.

• Expanding the sources of talent and improving the quality of hires: After years of forcing job candidates to endure endless rounds of interviews and tests, Google used data to discover that, after the fourth interview, every following interview is largely a waste of time. Not only did this discovery streamline recruiting, it also helped the company understand what management factors led to the best job performance. Based on insights from its “people science” work, Google wrote its manifesto on leadership.

• Profiling high performers in sales and customer service: Companies such as Oracle and ADP analyse sales performance based on talent characteristics. They can now better decide who to hire, how to set quotas, and who should become a sales leader.

Beyond those more common applications, people analytics are beginning to be used in more advanced ways. Many financial services firms, for instance, have turned to analytics to understand and predict ethics and compliance problems. As new government regulations place greater burdens on financial institutions to prevent misconduct, a tool that accurately forecasts which employees are most at risk of committing ethical transgressions offers a critical insight.

Analytics reaches into other exciting areas as well, such as how people learn and progress in their career. Learning management systems vendors now offer new tools that use data to “recommend learning” in the same way as Amazon and Netflix recommend books and movies.

The common theme connecting all these applications is simple: They address business issues, not merely HR issues. Connecting these tools to business needs helps build the case for investment in and deployment of analytics. Companies can move faster on analytics by considering a cross-disciplinary approach. One company created a cross-functional team called “HR Intralytics” to model ways in which the efficiency and effectiveness of its people services could be improved. This team worked with finance and business operations to visualise data across processes, defining the business benefits of improvements to various parts of HR. The output was so compelling to the board of directors that it approved funding for a major transformation — including a dedicated people analytics centre of excellence. As people analytics takes hold, data-driven decisions will become a common theme across all parts of HR. Organisations should invest aggressively in this new discipline, link it to the rest of the business, and reskill their teams to bring data to work in every major people related decision.

Where companies can start:

• Build the right team and show the return on investment: An analytics team should be multidisciplinary, combining employees with business knowledge and those with technical skills. Employees with physics and engineering backgrounds and industrial-organisational psychologists are often good candidates for the team. Pair them with a talent expert who understands the people dimension. Add team members with skills in communication, visualisation, and consulting to help drive value, and remember to quantify the value that better decision making is bringing to the organisation.

• Start with the tools you have: Organisations do not need to purchase new software to start the transformation. Using the analytics tools built into spreadsheets is a good place to start, allowing organisations to put existing capabilities to work to analyse data that are too often underused. Do not let the perfect be the enemy of the good; it is better to do analytics based on less-than-perfect data than to do no analytics whatsoever.

• Partner with IT: Data quality is often a problem when it comes to the people side of the business. HR teams must enlist the support of IT early to help build a programme to clean up, rationalise, and continuously monitor data quality

• Use analytics on the HR organisation to show analytics’ potential: Assimilate data on the demand and supply profile of HR services, and apply the principles of modelling, forecasting, and visualisation to illustrate the dynamics of the function itself. Look for areas in the HR operating model that can be improved, quantify the potential impact, and then design embedded analytics as part of the new landscape.

• Focus on immediate business needs: Analytics is a business priority, not merely an HR tool. When analytics connects directly to business issues, the argument for investment becomes more powerful to the organisation as a whole. Start with a well-known problem — be it turnover, sales productivity, or customer service quality — and start studying the people factors that drive outcomes. Sophistication comes with time and investment, and showing early results will help sell the programme to business leaders. More integrated tools are now available, and if early results drive value, companies can justify major investments.

• Leverage embedded analytics by upgrading technology platforms: More than 70 per cent of our respondents are upgrading or have recently upgraded their core HR systems with new cloud platforms. The business case for these systems should include a hard look at the potential benefits from robust people analytics. Because reducing turnover, improving sales productivity, and increasing the quality of hires all have a tremendously high ROI, analytics often represents a strong business case to justify modernising the HR infrastructure.

BOTTOM LINE

Data and analytics are key to solving many of the problems we identify in this report: engagement, leadership, learning, and recruitment. Companies that excel in talent and HR analytics can be positioned to out-compete and outperform their peers in the coming years.

Without early, substantial investments, however, it is difficult to get traction. Companies should therefore make a serious commitment to this discipline, search for robust solutions from their core system vendors, and hire people into HR who have an interest and background in analytics and statistics.

For more information about Human Capital Services at Deloitte, contact Jessica Mello, director of consulting at Deloitte, on 295-1500 or at jessica.mello@deloitte.bm