HR analytics: what your HRMS can do for you

The modern world is built on data and the workplace is no exception.

When it comes to making your people data work for you, an HRMS analytics module is the way forward. Most come with a set of pre-programmed ‘readymade’ metrics and reports, poised to offer you fresh organizational insights. Indeed, the 2017 Sierra-Cedar HR Systems Survey placed metrics in leading companies top five priorities for the year.

The following article looks at the key issues associated with HR analytics, including:

• What is HR analytics?
• Why an HRMS is the way forward
• The business case for HRMS analytics
• A guide to common HR analytics reports
• Selecting HR analytics tools
• The potential impact of HR analytics

What is HR analytics?

Put simply, HR analytics are sophisticated reports using your stored people data. By combining different data sets, your HRMS can provide strategic, and even predictive, insights that can be used to better guide your business strategy. In a sense, they are a more sophisticated version of HR KPIs (KPIs 2.0, if you will) only whereas KPIs tend to be backward-looking, HR analytics are peering into the future.

Get more info on how you can use HRMS analytics with this guide to managing HR data with HRMS

Why an HRMS is the best way to get more out of HR analytics 

Volume and variety of data is key to useful (and accurate) analytics and although most organization’s people information doesn’t yet approach the volumes needed for true Big Data, it’s getting there and your HRMS is the primary store of such information.

Analytics and reports can be categorized four ways:

• Basic operational quantitative reports: these tell you 'how many' and 'how much' – nice to know but limited in application.
• Wider operational reports: these tap into broader sources of information – good for benchmarking performance.
• Strategic outputs: using statistical analysis and segmentation to create ‘human resource analytics models’ – more applicable to longer-term decision-making.
• Predictive analytics: scenario planning and detailed analysis derived from multiple data sources – offering strategic insights.

In the past, HR has been limited to the first two categories but with more advanced HRMS functionality, and greater integration between different databases and sources, current software can now offer the user higher level insights.

The business case for HRMS analytics

The key stakeholders for HR analytics tools are an organization’s managers and leadership – whether it’s operational managers using real-time reporting features, or C-suite leaders using recruitment and performance models to predict future skills needs and shape recruitment strategies.

Learn more about getting senior management onboard with your HRMS project with this guide to selling HRMS to C-level

The key potential benefits of HR analytics features are as follows:

• Way better than using Excel: this may seem obvious but plenty of HR professionals remember when HR data was all spreadsheets with very limited number-crunching possibilities. Any analysis was effectively done ‘by hand’ whereas most HRMS reporting and analytics modules have sufficient automation to make dealing with HR data a less time-consuming and more responsive proposition.
• More efficient planning: historical data-mining and real-time analysis can enhance planning at all levels of management, from better daily deployment of your workforce, to estimating how many new hires you’ll need in the next fiscal year, to your high-flyers’ flight risk.
• Data visualization: more and more HRMS reporting modules are offering visualization capabilities, combining your chosen data and presenting it in pictorial or chart format for more immediate understanding and impact.
• Embedded analytics: HR analytics are not a stand-apart function, increasingly they are part and parcel of manager’s daily interactions with the HRMS. For example, when reviewing a promotion prospect’s record, the manager may have instant access to salary ranges, benchmarked performance, absence rates compared to the average, and so on. All information that in the past would have required a formal request to an HR administrator.
• Easier succession planning: building on the previous point, insights into your workforce demographics and performance can make succession planning both easier and more accurate, allowing you to anticipate retirements, turnover, and establish levels of relevant skills, knowledge and future potential within your current employee population – thus anticipating future hiring needs.
• Identification of the best candidate sources: using HR analytics and reporting, you can review historical sources and costs of new employees, combining that data with details such as career path and turnover. Perhaps also cross-referencing with comparisons of internal and external job candidates. From data like this you can see which sources have proven most valuable and target them in future.
• Improving employee engagement: staff polls and engagement surveys generate large quantities of data that can be used to identify the policies, incentives and types of work that different types of employees appreciate best, leading to strategies that will boost engagement and improve retention of valued personnel.
• A more credible HR function: let’s face it, HR is still often perceived as focused on people rather than the business and bottom line. Hard data and the outputs of HR analytics builds HR’s credibility by helping express people strategies in terms of business impact.

A list of common HR analytics reports

Different management roles have different information needs. Customized HR metrics dashboards allows them to focus on the metrics and reports they need in an easily understood format. The following examples or report types are listed according to which roles may find them most useful.

Selecting HR analytics tools

Specific HR analytics requirements will be unique to each organization, so the following are presented as examples rather than recommendations, with the intention of giving a glimpse of the current market state.

Find out more about the HRMS selection process with our comprehensive HRMS selection survival guide

1. SAP SuccessFactors

SAP's SuccessFactors system draws on a variety of talent data sources (including core HRMS data, talent records, engagement information, financials, etc.) to produce analytics and insights concerning employee engagement, diversity, performance, and turnover. Self-service gives tailored access managers and leaders, supported by on-screen guidance and explanations which assist in interpretation and practical application. Built-in benchmarking allows comparison with relevant peers and competitors.

2. Visier

Visier’s Continuous Machine Learning technology claims to be, “up to 10x more accurate at predicting who will resign over the next 3 months than guesswork or intuition.” The offered predictive analytics relate to resignations, recruitment decisions, compensation & benefits, and workforce planning.

3. TalentSoft

TalentSoft’s talent management analytics include both a range of ready-to-use analytics templates focused on common HR challenges plus the option of creating customized dashboards for individual user’s needs. Reports can be run for individuals as well as whole teams. Such micro level analysis should be treated with caution but it does offer a very focused approach.

4. Vista

Vista (by PDS) taps directly into the data stored in the company’s HRMS package, offering a full set of predefined analytics templates, all fully customizable. Similarly, user dashboards are configurable and easy to use. The company offers full HR analytics training in systems tools, statistics, and data modeling in general.

5. IBM Watson Analytics

IBM’s Watson cites the use of artificial intelligence and machine learning principles to create accurate business insights, including areas such as recruitment, workforce utilization, employee satisfaction, attrition, and training and career development. The system incorporates a system of prompts and guidance, calibrated so as to cater for those new to analytics the more experienced user.

The potential impact of HR analytics on your organization

The critical test of any HRMS analytics module is the impact it has on your business and strategy. To conclude, the following is a list of potential impacts that you should expect.

• More accurate prediction of future trends: starting with the obvious, real-time data and in-depth insights should allow you to strategize based on an accurate model of the future based on past information and current benchmarked data, allowing more proactive decision-making and a sharper competitive edge.
• More focused hiring: currently, recruitment and hiring is one of the most data-rich areas of the HR function and so you should expect to see the biggest impact of HR analytics in this area; from prediction of which candidates have a higher risk of leaving or underperforming, to identification of  the most effective recruitment channels, to  streamlining your next batch of high-performing future leaders.
• More strategic and business-focused HR: HR’s role as a key contributor of strategic insight and its impact on the organization’s bottom line should be enhanced by the use of HR analytics. This is due to analytics' strengths in linking linking people data with business data to show clear interrelationships.

However, in order to reap these benefits, the HR function’s own skill set will need to evolve. HR must feel at home in this new world of Big Data, algorithms, and ‘competitive intelligence’, etc. with the skills and understanding to ask the right questions, interpret the right data, and produce the right insights. Data scientists are the newest addition to the HR team.