The subject of analytics is often discussed but rarely executed well, even in the most well-established talent management functions.
While most organizations collect data, manipulate it, and produce reports from it, few could honestly state they are leveraging HR data to drive business performance by making better decisions about how the organization’s largest variable expense is managed.
Instead of powering decision science, the majority of established talent management analytics do a great job at telling us what has happened and how much administration has been completed. When reported, the verbal response to such analytics is often “that’s interesting,” but little to no action is triggered.
A lot of factors have contributed to the sad current state of analytics in the human resource function; luckily, most are remediable today.
Drivers of Weak Analytics
- Skill deficiency. Until recently, many of the tools that enable robust analytics required intermediate- to expert-level understanding of statistics, a skill rarely held by the average HR professional. As a result, talent management functions lacking the budget to hire a dedicated analyst often went without. While many organizations could still benefit greatly from hiring a statistician or true business analyst, many of the tools used to power advanced analytics have become significantly easier to use in recent years.
- Lack of business knowledge. The second most pervasive barrier to developing world-class analytics is one the HR profession gets chastised for on a regular basis. While more and more HR professionals are learning more about their organization’s business than ever before, a majority lack a deep understanding of the business to figure out all of the talent management system touch-points and interactions capable of demonstrating a causal tie to business performance. The increased visibility of talent management issues in recent years is helping to rectify this, as many organizations are moving more professionals with line-management experience into human resource management roles.
- Expensive tools. While a lot can be done with modern spreadsheet applications, true business intelligence platforms have been relatively expensive up until recently. The growth in availability of enterprise-class opensource applications has exerted significant cost pressure on commercial business intelligence providers, making such applications much more affordable.
- Lack of quality data. Even with deep business knowledge, analytical skills in place, and access to leading-edge tools, a majority of organizations struggle to enable world-class analytics in large part because the quality of the data they have to work with is beyond poor. Because many HR professionals are overly burdened with task-oriented work, capturing data in a valid, consistent way is not a work habit that has been well-honed. While workloads are not likely to decrease anytime soon, a growing number of tools in the “text analytics” market are enabling organizations to analyze trends using data in a form most talent management organizations have in abundance, unstructured text.
- Complicated nature of talent management. It is easy for those outside the HR function to criticize HR, but ask any functional executive who has transferred into HR from another function and they will confirm that managing the systems that govern talent is inherently more complex than originally perceived. In many respects, the HR function is a full-fledged business within the enterprise, one that requires in-depth access to cross-functional expertise to execute well. A growing number of organizations are starting to realize that employment opportunities truly are products. As such, they must be designed, packaged, marketed, sold, supported, and serviced. This new mindset is bringing new professionals honed in such skills to the HR function following the realization that it is a lot easier for other professionals to learn HR than it is for HR professionals to learn marketing, sales, or finance.
As talent management increases in perceived importance among members of the executive committee, the pressures on HR leaders to be more scientific will only become more prevalent. Luckily, several emerging tools are coming online that will help HR professionals accomplish significantly more.
Emerging Tool/Approach: Text Analytics
The first promising tool, just emerging from infancy stage and still relatively complex in nature, is enterprise class software to enable “text analytics.”
The HR function is full of data residing in blocks of text that historically was difficult to derive trend data from, including verbatim responses in learning development plans, performance evaluations, applicant/candidate/employee/manager surveys, online forums, emails, etc.
To make use of such data in the past required that human readers comb through all of the related documents, manually extracting comments in context and categorizing them according to some predetermined categorization schema, an activity capable of consuming an enormous amount of labor in even the most basic of scenarios.
Text analytics software is making such analysis feasible to the masses by automating the contextual comment parsing and categorization processes. The software can complete overnight analysis that would take teams of humans manually executing the process months to complete.
The power of this emerging capability within HR is simply astounding. For instance, employment brand managers could point such software systems to blogs, social networks, online publications, and even internal employee forums to monitor for trends.
Learning and development function leaders could deploy the system across a bevy of common internal documents, including development plans, performance appraisals, performance improvement plans, business development plans, and even documented corporate strategies to determine emerging knowledge, skill, and ability needs.
Recruiting functions could use the technology to analyze applicant surveys, new hire surveys, and online forums to determine emerging trends impacting the performance of recruiting process. On a grander scheme, recruiting functions could leverage text analytics to comb through thousands of academic research abstracts, identifying common hypothesis, solutions, and sources to rev up hiring initiatives.
Organizations interested in using text analytics systems must understand upfront that these systems were designed primarily for organizations to analyze consumer feedback. If you believe that employment opportunities are a product, leveraging such technologies shouldn’t be that big of a stretch.
These technologies are still very new, most coming to market only within the last year. Implementing them will be complex, just as figuring out new methodologies to use them will be innovative. In time, such systems will become easier to use. Emerging providers include Clarabridge, Attensity, Business Objects, and SAS.
Emerging Tool/Approach: Predictive Modeling
Predictive modeling isn’t new, but its application in HR is still relatively rare, and for that reason we still consider it an emerging approach. Several of the barriers that inhibit the development and widespread adoption of world-class analytics are solved by predictive modeling systems.
It is one thing to hypothesize a connection between employee absenteeism and production-line performance, then set out to prove it, but it is an entirely different thing to sit back and let statistics tell you what is related without forming any hypotheses. Manually hypothesizing correlations and setting out to prove them is time-consuming and requires significant knowledge of HR, the business, and statistics.
Predictive modeling, on the other hand, only requires that you have access to massive volumes of HR and business performance data, business intelligence software, and the skills needed to set the software to task.
Predictive modeling is used extensively by marketing professionals to determine what impacts consumer behavior. As predictive analytics have been around for some time, many executives already have some exposure to them and trust in their validity.
The potential applications of predictive modeling like text analytics are huge in HR. Imagine being able to forecast the exact budget needed to power all HR systems at the optimal level required to produce specific predetermined levels of workforce productivity. Predictive modeling can identify what HR systems drive increases in productivity, inhibit productivity, present risk, etc. It can be used to power decision models or simply alert you/your managers to potential issues.
Unlike the text analytics market, a majority of the business intelligence systems supporting predictive modeling are mature. The market includes common desktop software (Microsoft Excel), opensource enterprise class applications (Pentaho), and commercial business intelligence leaders (Business Objects, etc.).
Key Principles with Emerging Tools/Approaches
Any time an individual or organization can leverage a new tool or approach that significantly impacts their capacity to perform, an opportunity arises to develop a competitive advantage.
Unfortunately, leveraging new and emerging tools often requires that users step out of their comfort zone. This practice is not uncommon in HR, if it were we wouldn’t be using IVR in HR call centers, workflow management systems in recruiting, or text messages to communicate with candidates.
The keys to keep in mind when using these new tools and approaches include:
- Set your sights on solving business problems as opposed to HR problems. If any words more common among HR practitioners make it into your proposal for adopting these tools, you have ignored this key.
- Understand that you will be blazing new territory. With that role will come a bevy of challenges and obstacles to overcome.
- Realize that moving forward with plans to add these capabilities to your talent management function may require that you hire talent from outside the HR profession.
- Prepare yourself for failure in at least 60% of your initial attempts. Numerous studies have shown that more often than not top performers fail at least 60% of the time when trying something new. Too many HR functions set much higher expectations and give up too quickly. If Tiger Woods stopped playing golf because he lost a majority of the tournaments he entered, he would have quit a long time ago.
Continuing to compete and thrive in an emerging global economy powered by evolutionary technologies that are changing at an ever-increasing pace will require HR practitioners to become significantly more strategic.
The technology exists today, as does the need to deploy it, but too many in leadership roles lack the courage to depart from the status quo. If you look at what frustrates the executive committee most about the current state of HR, nearly every concern could be solved with a more robust analytics infrastructure and a talent management workforce capable of understanding the business and being able to prove their impact on its performance.
Start the conversations now, give the tools a shot, start asking questions, prove what works and what doesn’t, and most importantly, have fun for a change!