Text Analyze This


What are the different connotations ascribed to the term “human capital” by HR professionals and what is a simple way to illustrate the variety?

The opportunity to examine these two questions came up recently as part of some work with Society for Human Resource Management’s (SHRM) Measures and Metrics task force.

The Measures and Metrics task force is one of many that have been convened to establish standards around HR metrics. This innovation over past attempts is the employment of the American National Standards Institute (ANSI) protocols for standards development.

The Measures and Metrics task force is drawn from HR practitioners, consultants and other interested parties from around the world. Its remit is to develop measures and metrics that will be useful for investors – ones that might become standard elements of the United States’ Securities and Exchange Commission’s (SEC) Form 10K, for example.

The term “human capital” is ubiquitous, but it often means different things to different people. The term was invented by economists (see our previous blog post, “A Capital Idea?”), but has now entered the business lexicon and is often championed by HR.  It was a natural choice as the basis for the task force’s metrics nomenclature

In order to ensure that everyone was talking about the same thing, members of the task force were asked to write down their views on what they understood by the term “human capital.” Many members responded.  Reading through the definitions, it became clear that there were disparate views on what human capital meant or ought to mean.  As to be expected with such a popular term, there were some common themes and words – education and experience, for example – but also some new words and ideas.

I thought it would be a good idea to create a “word cloud” (similar to the “category cloud” on the right margin of this blog) of the submissions. I used a free web-based application called Wordle, though there are many such free text analytic applications available.

The image you see on the left of the page shows the words used in the submissions to describe “human capital.” The size of the word is proportional to the number of times the word is used in the document. This particular application shaped the words around a footprint shape (this is a customizable feature and you can choose from a variety of shapes and styles).

Right away, you can tell which are the most common words used. Such text analytics can be very useful. From this blog’s tag cloud, for example, you can see which are the most popular topics discussed.

There are a number of other possible uses.  HR leaders can look at HR communications to ensure that the message is not being overwhelmed by certain words and phrases. Compensation professionals can examine job descriptions to check for an appropriate balance in the verbiage between strategic and operational responsibilities. Team leaders can ascertain the common themes among team members’ inputs on various topics. Job seekers can ensure that their resumes are hitting the right notes in terms of key words and capabilities.

Text analytics is a growing field and has come a long way. It will grow in importance as the web evolves towards a semantic structure and capability (the “semantic web”).  Words in a document are now akin to numbers in a spreadsheet. Evidence-based HR enthusiasts should familiarize themselves with text analytics and leverage them as they would quantitative analytics – to help answer critical questions and make better decisions.

 

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About thenelsontouch

Amit is the founder and managing director of Nelson Touch Consulting, a management consultancy that specializes in maximizing the return on human capital through strategy, incentives and analytics.
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