Tag Archive for human resources analytics

Two Key Benefits of HR Analytics

In my last article, I wrote about the definition of HR Analytics and the skills needed to be successful in this field. In this article, I want to discuss two key benefits of HR analytics to the HR function in an organization and to the business: Evidence Based Decisions and Reducing Human Bias.

HR professionals want to be strategic partners with business leaders, not simply a cost center designed to maintain policies and procedures. While these policies are important, analytics provides HR with a means to demonstrably improve the efficiency of a company’s people resources. It does this in several ways.

Evidence Based Management Decisions

Through its dependence upon data and facts, HR Analytics delivers evidence, and evidence trumps intuition. To support these benefits, I’ll ask two questions:

Is your interview process optimized to find the best candidate for a position?

If you have ever participated in an interview process from the hiring perspective, you may be aware that at many companies, interviewing candidates can be an informal, non-standardized process. At worst, interviewees are simply asked by HR “What did you think?” More sophisticated HR methodologies define a standardized process for who the candidate meets and what questions are asked. At each stage, feedback is collected and quantified, typically in the form of ratings. Are these ratings predictive of future performance in the job role to be filled? HR Analytics can tell you the factors that are predictive of high performers in certain job roles (or tell you that you don’t know and that you should either change your process or collect different data points).

Does internal employee training improve company performance?

Most HR professionals would say ”Yes, employee training is a good thing and we need to do it.“ Many top companies spend precious resources to train their sales staff or send aspiring leaders to leadership training. Does this training have a material impact on performance? On the company’s bottom line? HR Analytics aspires to quantify that benefit. To do this, we may need to pull together data from several systems, such as on-the-job performance data, financial data and data collected during the training process. We should define the performance metrics that are most important in that job role. We must also consider a baseline of performance (i.e., comparable employees who were not able to take the training). By taking a more scientific approach, we can quantify the benefit and produce evidence of impact. We may also demonstrate that certain training is ineffective.

Reducing Human Bias

If you have read Michael Lewis’s book The Undoing Project, then you know about the work done by psychologists in the last 50 years to explain how bias interrupts the human mind’s ability to perceive information. Literally, our personal bias leads us to see things that simply are not there. We all have expectations, and these expectations are based upon hard won human experience—most of which has served us very well in life. But in the case of making HR judgments, or indeed any judgement requiring us to process large amounts of information, bias is quite detrimental.

In the questions/examples provided above, we see the opportunity for human bias to creep into common HR processes and potentially undermine them. First, let’s examine the interviewing process. As people, we may have expectations about how a qualified candidate dresses, how they speak, and which personality traits are most prominent in a good candidate. These are likely informed by our own experience, and colleagues who may have made a deep impression on us. Just as likely, information contradicting the same bias is dismissed. This means that our human minds are not able to process large amounts of information in a uniform and objective manner. When applied correctly, HR analytics can do this much better.  For example, an HR analytics team would consider data collected during the evaluation phase and performance data for successful applicants; in other words, before and after hire. Hopefully, many applicants become very successful at your firm, but you also know that many do not. We can apply a label certain to each candidate profile, recognizing that the candidate either was or was not successful.  We can then train our analytics algorithms to learn what a successful employee will look like, mathematically, at hire time and reduce our human bias. Bear in mind that bias can still creep into the process, if interviewers fail to recognize the need for standardization and quantification.

Similarly, as it relates to evaluating training against performance, we see an opportunity for bias to lead to conclusions that are false, or at least for which there is no evidence. Business leaders can (and should) demand this evidence from HR, so that they know that capital is being deployed correctly in support of the firm’s financial well-being. To be clear, it can be very difficult to prove causation between training and financial ratios (i.e., that training causes an increase in Net Income). However, HR should be able to provide evidence demonstrating correlation between employees who perform well on the job (be that metric in sales figures or on-time delivery) and those who attend certain training activities. When HR provides evidence of this correlation, it becomes a strategic partner with business leaders, helping them see and understand the patterns in human behavior.

See Differently, Know the Facts

Analytics offers HR professionals an opportunity to approach decision making differently. Measurements and quantification of candidate and employee characteristics and performance can provide evidence of correlation between the policies HR is supporting and the outcomes the business seeks to drive. By thinking differently about HR, we can reduce our propensity to see things that are not there, replacing that vision with a clear eyed, scientific, data-driven approach.

Want to learn more about the world of HR Analytics? We are speaking at this year’s CBIA Human Resources Conference on the topic. We hope to see you there!

Berry_Brian-240About Brian: Brian Berry leads the Microsoft Business Intelligence and Data Analytics practice at BlumShapiro. He has over 15 years of experience with information technology (IT), software design and consulting. Brian specializes in identifying business intelligence (BI) and data management solutions for upper mid-market manufacturing, distribution and retail firms in New England. He focuses on technologies which drive value in analytics: data integration, self-service BI, cloud computing and predictive analytics

5 Critical Skillsets for HR Analytics

Increasingly, companies are applying analytics and data science procedures to new areas of their business. Human Resources (HR) management, with its central role in managing the People in a business, is one such area. HR Analytics is a fact-based approach to managing people. A fact-based approach helps organizations validate their assumptions about how best to manage their people. This makes good business sense: on average, companies spend 70% of their budget on personnel expenses.

Using data and statistical methods, HR may look to examine people-oriented questions, such as:

  • Can we better understand employee absenteeism rates at a labor-intensive business, such as retail, food service or industrial manufacturing? Can we predict it?
  • Do our compensation realities reflect fair and balanced job classification policies? Asked differently, which factors are most predictive of compensation: ones we want to reward (i.e. education level, on-the-job performance) or ones we need to ignore (i.e. gender, age or race)?
  • What is our real employee churn rate? Can we identify employees headed out the door and take preventive steps?
  • Are our service response times keeping pace with spikes in customer demand?

These questions, and many more, can be answered with datasets, data science and statistics.  But how?  Analytics involves skill sets that go beyond those considered “traditional.” Knowledge of recruitment, hiring, firing and compensation are key to understanding HR processes. However, HR professionals often struggle to answer these questions in a data-driven manner, because they lack the diverse skills required to perform advanced analytics. These skills include statistical and data analytical techniques, data aggregation, and mathematical modelling. Finding the right data can be another challenge. Data analytics requires data, and that data is likely to reside in several different systems. IT professionals play a critical role. Finally, communication to the business is a key skill. HR Analytics projects may produce analysis and models that contradict conventional wisdom.  Action on these insights requires the team to communicate the what, why and how’s of Data Science.

To be successful, HR Analytics projects require five distinct skillsets to be successful in creating value for an organization.

  • Without Business input, HR Analytics projects may answer questions with no value added to the organization.
  • Without Marketing input, insights from HR Analytics will fail to be adopted by the business.
  • Without HR input, the team will struggle to recognize relevant data and interpret the outcomes.
  • Without Data Analytics input, analysis will be “stuck in first gear” – producing basic descriptive statistics (i.e. Averages and Totals), but never advancing to diagnostic (i.e. root cause) or predictive (i.e. Machine Learning) models.
  • Without IT input, the team struggles to acquire relevant data in a usable format.

HR leaders must engage all the required perspectives and skillsets to be successful with analytics. Business, marketing, HR and IT are common perspectives found in most organizations. But Data Analytics professionals, able to cleanse data, identify candidate predictive models and evaluate model output, are typically lacking.  We encourage HR professionals, interested in learning more about The Power of Data, to reach out to our Data Analytics Advisory Services team. Our goal is to help you understand the data science process, identify business opportunities, and potentially offer analytics services that fill in the missing pieces for your puzzle.

Want to learn more about the world of HR Analytics?  We are speaking at this year’s CBIA Human Resources Conference on the topic. We hope to see you there!

Berry_Brian-240About Brian: Brian Berry leads the Microsoft Business Intelligence and Data Analytics practice at BlumShapiro. He has over 15 years of experience with information technology (IT), software design and consulting. Brian specializes in identifying business intelligence (BI) and data management solutions for upper mid-market manufacturing, distribution and retail firms in New England. He focuses on technologies which drive value in analytics: data integration, self-service BI, cloud computing and predictive analytics