HR Analytics: A Tool for Workplace Transformation

Published by MBA Skool Team, Published on October 09, 2014

Moneyball- The Film and HR Analytics

“The problem we're trying to solve is that there are rich teams and there are poor teams. Then there's fifty feet of crap, and then there's us. It's an unfair game,” this is how Brad Pitt summarises the problems that his team faced in the movie Moneyball. Moneyball is a classic case of using analytics for recruiting a bunch of misfit baseball players who went on to win 20 consecutive games. In this article we will try to understand HR analytics process and try to deal with its implementation part, how to make a business case for HR analytics by linking it with business outcomes and lastly we will briefly discuss how HR analytics can be used in succession planning.

Image Courtesy:, jscreationzs

HR Analytics Process

Before we begin with the detailed process of implementing HR analytics in the organisation, let us first understand the process itself including the major components of the process and the way they impact the designing and implementation:

• Reporting: For some HR professionals, HR analytics have come down to tracking more and more metrics around HR activities. There is nothing wrong with measuring cost to hire, but it unlikely to excite top management unless you have shown the direct connection between it and the quality of people that are hired. We are not saying tracking such metrics is a useless exercise but it doesn’t make business sense to report metrics that do not show business value and do not mean much outside of HR.

• Dashboards: It is important to keep dashboard precise and user friendly as it will help the decision making authority to make sense out of it as they are always hard pressed for time.

• Benchmarking: One thing must be kept in mind that not all the best practices can be replicated as it is your organisation because of differences in structure, culture and strategy.

• Data Mining: HR needs to come up with all the relevant data for the metrics to see the trends which will help them predictive analysis which forms the next step.

• Predictive Analyses: Developing of such models is not a one of task as it is an iterative process and needs to be perfected.

• Operational Experiments: it involves designing operational experiments for developing models and evidences which helps in managerial decisions.

• Workforce Modelling: lastly, workforce modelling involves understanding the relationship between HR capital needs and change introduced in the organisation’s environment.

Implementation of HR Analytics

Now will discuss the things one must bear in mind while implementing HR analytics:

• Getting Started: Managers before starting on the journey of HR analytics must understand the problems currently faced by the organisation and the opportunities that exist in the external environment to increase effectiveness of the organisation. Organisation must be clear about the outcomes that it wants to achieve by using HR analytics. As will we explore later in the article the managers must try to link up the HR analytics with the business outcomes desired by the organisation. At the end of the end HR analytics should be a fancy thing HR pulls out of the cupboard when questioned about HR effectiveness but rather it needs to be aligned with the desired business outcomes on the onset.

• Align HR Analytics with Company Strategy: To achieve substantial and sustainable outcomes using analytics tools, it must be aligned with the long term strategy of the organisation. Senior management’s support is important to secure a buy-in from different stakeholder in the organisation. Otherwise HR analytics as an initiative will start with much fanfare only to fizzle out in the end without achieving any significant results.

• Identify Data Requirements & Ensure Consistency: After organisation identifies key challenges & aligns the HR analytics with the strategy, it must identify the data requirement and ensure that data is consistent.

• Define a Common Workforce Analytics Platform: Over complicated systems tend to decrease motivation to use and hence soon become obsolete.

• Putting HR Metrics and Analytics Data in Context: The data collated using platform can becomes useful when the managers attach some meaning to it. Different ways of doing it are reporting trend information of the HR metrics, benchmarking etc.

• Reporting What We Find: It is important to keep in mind the needs and capabilities of the targeted audience. The managers must be able to understand the data reported to them.

• Enhance HR Analytic Capacity: To sustain the fruits of HR analytics the organizations must focus on increasing the analytics capabilities of the organisation. Ways to do it includes training, recruiting right people, incorporating analytics in the KRAs, job rotations of the HR employees, providing support to the analyst.

• Self-Education- Key for Building Analytical Skills: Much more can be done especially when it comes to learning analytical competencies which are discussed later.

Ownership of the Process


Linking HR analytics to Business Outcomes

As already seen HR collects a good deal of data be it on employee turnover, cost-per-hire and even the ROI of their programs. What HR needs to do is to simply link their number with the numbers of finance department to come up link between HR analytics and business performance. HR needs to start using this data to ask and answer some hard questions such as how a particular employee is contributing to the business. The entire idea of reducing the cost of HR using HR analytics is fallacious as HR costs company mere 3% of the entire selling, general and administrative costs. But one must not overlook the effectiveness or strategic impact of HR activities. For example, inefficiency in recruitment process may impact the business in the long run as it will saddle the organisation with deadwood which in India is pretty difficult to get rid of. HR department in many organisation tend to focus only on the input such as cost for hire, time to fill but not on the outputs for example productivity/employee, improvement suggestions & savings per employee.

In our view the HR must focus on developing talent supply chain similar to the idea of supply chain as seen in operations. It must try to reduce the waste (in the form of non-performing employees and man hours lost because of them). We also acknowledge it is very difficult to directly establish the linkages between the business outcomes and HR interventions. For example in sales one can easily establish the link between sales numbers and financial performance of the organisation. What HR can do is it to focus on the people aspect of the balanced scorecard & development of key talent in the organisation. What HR can do is to begin with basic data and gradually develop a talent supply chain, components of which are illustrated below.

Some Approaches to Establish the Link

• Correlations: Correlating people data and business data can be a step in establishing the link between HR analytics & business outcomes. But one must remember the correlation doesn’t always mean causation. Superlative business performance can be caused by the conducive market conditions etc. HR must discount the effect of such factors while measuring the correlation.

• Cause-Effect Analysis: Structural equations modelling (SEM) is a statistical analysis approach that econometricians and market researchers have used for quite some time. This approach allows you the opportunity to:

1. Consider multiple independent & dependent factors concurrently;

2. Imply cause-effect relationships;

3. Calculate a more robust ROI; and

4. Correct for measurement errors.

• Regression Analysis: It helps HR to measure the impact of multiple pieces of data (independent variables) on a dependent variables. For example it can be used to connect employee satisfaction survey items to turnover intentions.

Competencies needed for Implementation of HR Analytics

HR personnel must possess the analytical competency to make sense out of the data. Above mentioned three approaches make use of these competencies.

• Identify the data for analysis & Data access

• Root cause analysis

• Basic univariate statistics

• Advanced univariate statistics (Correlation, Differences, etc.)

• Basic multivariate statistics (ANOVA, Regression, etc.)

• Advanced multivariate statistics (Structural Equations, etc.)

Case Study: Making use of HR Analytics in Succession Planning

HR analytics can be used to:

1. Discovering the aspects of employee performance which drive business outcomes.

2. Assessing the talent pool.

3. Creating succession planning tool based which involves talent pool development.

Overall Talent/ Succession Pool Health = x%

By incorporating the data from all the employees in the talent pool, the above scoreboard will help in identifying key talent in the organisation. It is one of the simplest scorecard but at the same time metrics to be included above are selected after much deliberation as correlations and impact has to be established before they are included. This tool will help the organisation in developing talent.

This article has been authored by Margesh Wavhal & Shruti Joshi from XLRI


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