Organizations today, have complex and customized human resource requirements. While these requirements vary across industries, location and size, certain common patterns related to HR tasks emerge within organizations. Leveraging such patterns across the HR functions and employee lifecycle can not only help in identifying success mantras and what works but also helps in building predictability and prescriptiveness going forward. Hence, building insights based on these patterns and translating them into actions has the power to transform a traditional instinct based HR function to a smart data-driven arm of the organizations.

As the business continuously become smarter, leaner and faster, leveraging this power of talent analytics must be extremely relevant and useful for organizations, one would imagine. But the statistics tell a different story. People Matters conducted a survey on the usage trends of Talent Analytics, across a wide spectrum of organizations. 

We asked critical stakeholders from organizations about the existence and the scale of talent analytics capabilities in their organization. We also asked them about their plans and intentions to leverage talent analytics in the future. In total, 502 companies participated in the survey, and on the basis of their responses, derived the trends and findings that could be extrapolated to represent a major chunk of the business community. The figures suggest that organizations haven’t yet harnessed the power of talent analytics.

As businesses become more demanding in the wake of constantly disrupting ecosystem, the need of the hour for the HR leaders is to not only to partner with the business leaders to achieve results but have readily available data to be able to make impactful decisions. In this context, talent analytics is pivotal in setting the HR function for success. 

The research reveals that the key objectives for those leveraging talent analytics revolve around talent attraction and retention, improving HR process efficiency and measuring impact of metrics on business outcomes. Following are the some findings of the research:

Talent Analytics capability continues to be incipient

In line with a similar research last year, this year also the results suggest that talent analytics is a relatively unexplored territory in organizations in India.

Only 27 percent respondents stated that they have a dedicated talent analytics capability centers in their organization, and 23 percent aim to build one in the coming year. 

Looking at the analytics maturity curve, we observed that more than 35 percent of the participants still find themselves to be in the ‘Simple Reporting’ stage, and around 50 percent of them are either at the simple or the advanced reporting stages with their Analytics Programs.  Just over 1 percent of the participants are at the Prescriptive Analytics stage, which is the most relevant and desirable stage, and a key area of business analytics today. Also, among the organizations with Descriptive, Predictive or Prescriptive Analytics capabilities, 54 percent are MNCs, underlining the point that MNCs have been faster off the blocks, with integrating analytics into talent management.  

To put the maturity stages in perspective, the survey asked the participants about analytics tools and technology that they use. 75 percent of the organizations still use spreadsheets. A substantial number (57 percent) of the participants use HRIS reports or dashboards for managing their talent analytics functions. Only 14 percent of the organizations use online or cloud-based analytics software, and in total, 26 percent use a dedicated analytics software, be it on-premise or online.  Going forward, organizations would increasingly need to shift to cloud-based or dedicated offline analytics software for HR, just like they are doing for their core business functions. 

There exists a gap between the importance that organizations place on talent analytics and the plan in action

Upon asking organizations about their motivations for employing the Talent Analytics programs, it emerged that talent attraction and retention, improving HR process efficiency and measuring impact of metrics on business outcomes are the top 3 objectives of talent analytics programs, with 69 percent, 68 percent and 66 percent votes respectively.

96 percent of the HR leaders believe that talent analytics enables them to support their leaders in business execution, and 83 percent also agree with the assertion that it is an important competitive strength for their organization. In fact, over 71 percent of them say that their business heads and CXOs regularly request for actionable insights derived from talent analytics. Yet, only 40 percent of them have a designated budget for their talent analytics initiatives, and 48 percent have a defined team for performing it. 

To support the actions, only 8 percent of all the organizations have a separately allocated budget for talent analytics. Speaking of the amounts, 78 percent of the companies have an annual budget of less than INR 50 lakhs for it, while another 17 percent of them have a budget ranging between INR 50 lakhs and 2 crores. 

In majority of the organizations, the talent analytics teams are a part of HR function reporting to the CHROs/HR functional Head

For 21 percent of the organizations, talent analytics strategy is being handled by a single business unit, while for another 21 percent, multiple business units are together managing it. In terms of the structure, 57 percent respondents state that the people handling talent analytics are a part of the HR function, whereas for another 25 percent of the respondents, there is no dedicated team for it. 

In 38 percent of the companies, the talent analytics team reports to the CHRO, and for another 34 percent, they report to the HR functional head. For the rest of the companies (who do have a team), they either report to the CXOs (20 percent of total), or to the Business Analytics Head (6 percent of total). 

The budgets also relay a similar story with 50 percent of respondents revealing that their talent analytics budget is a part of total HR budget only.

Organizations are leveraging a hybrid approach of in-house capabilities partnered with external sources

46 percent of the organizations are the ones that have developed their talent analytics capability centers in-house, and do not plan to bring in external partners for the next twelve months. Another 31 percent have mostly developed their capability in-house, but they do plan to bring in external service providers in the coming twelve months. 6 percent of the organizations have majorly outsourced the function, but also intend to enhance their in-house capabilities in the next one year. 

40 percent of the respondents were equivocal about the capability of their talent analytics team, while 33 percent said that their team needs improvement, and the remaining 27 percent found their team to be capable enough.       

Out of the organizations that employ the services of an external partner, a majority of them (54 percent) do it for the technology and talent analytics tools that are provided to them by their service provider. Data mining and analysis (42 percent), and strategy and consulting (38 percent) are the other key areas, where the external partners are involved. 

Evidently, the HR function has not really leveraged the power of talent analytics when compared to other matured functions in businesses, but there exist multiple challenges that need to be overcome to emerge as a completely data-based function. The research has revealed inconsistencies in collecting and capturing data (53 percent), inconsistent HR metrics (50 percent) and lack of integration between HR and other functions (50 percent) which constitute as the top three challenges faced by organizations in implementing successful analytics programs. While there is a long way to go for the HR function, the constant disruptions to the businesses and the sweeping tides of HR technology are sure going to be the biggest drivers of helping the function in taking the leap of faith and ultimately emerging as truly a prescriptive function.