Getting people analytics right is tricky for businesses. After all, the very sources of all the data–people–are complex beings.
Big data—yes, it is that term again—is here to stay.
There is a change, however, in the way big data is now being discussed. People are no longer characterizing big data as the best thing to happen to the business world, and big data no longer sits on the pedestal it once did.
The business world is now gradually warming up to a new buzz term “people analytics,” which is essentially a more human subset of big data. The term is taking the corporate world, and especially the human capital management space, by storm. This powerful new category of data analytics is often touted as HR’s weapon of choice for reclaiming its seat in the boardroom.
People analytics is also credited with bringing back human data to the decision-making process, as opposed to solely relying on machine data for making business decisions.
In simple terms, people analytics is the analysis of data that relates to people within an organization or industry. This people-related data is used to optimize the decision-making process and business outcomes.
For instance, the C-Suite may think that the solution to high employee turnover is not enough experienced managers in the company, whereas the employees would probably know that the real reason for employee turnover is bad decisions made by the C-Suite. When done correctly, people analytics is capable of informing great business decisions and also increasing employee satisfaction.
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The Tricky Business of Analytics
Getting people analytics right is tricky business. After all, the very sources of all the data—people—are complex beings that cannot simply be programmed like machines. There are no standardized metrics and methods when it comes to processing data from people. Analyzing data from people should take into account qualitative and quantitative variables.
Reducing data from people to mere numbers and failing to recognize the qualitative aspects and sentiment behind the data is dangerous. This sort of data fails to give a decision-maker true context. The biggest risk of using this sort of people analytics to “quantify” people data is that businesses can go back to square one of having an overwhelming amount of data and not knowing what to do with it.
An article from the Harvard Business Review talks about what people analytics can’t capture. It highlights how people analytics oftentimes only skims the top layers of an issue, and why many HR professionals are still stuck using conventional methods for gathering data due to the restrictive nature of people analytics. The author goes on to tell us how HR professionals need to talk to as many stakeholders as possible when it come to assessing an employee's performance.
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A Call for Old Methods
Realizing that people data is tricky, many business leaders and decision-makers are turning to traditional methods for gathering people data. Think about traditional face-to-face interviews, surveys and note-taking in today’s digital age. While there is nothing inherently wrong with using these methods, they certainly have their shortcomings, especially for large enterprises.
In order for large businesses to collect sufficient people data, they must interview hundreds to thousands of people in person. Manually collecting this amount of data, analyzing it, and connecting the dots is a mammoth task that is a drain on time and resources. Also, the amount of data that is collected from face-to-face interviews, can be overwhelming. A HR analyst may have to cull out massive chunks of irrelevant data in order to find some worthy gems that are capable of informing decisions.
Because scaling face-to-face interviews is cumbersome, many enterprises have turned to automated surveys to gather insights. Surveys, however, typically do not offer the depth of insight required for decision-making. HR professionals may end up with an underwhelming amount of data. If you really think about it, programming a machine to understand surface-level insights gathered from people through automated surveys or questionnaires is nearly impossible today.
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When it comes to analytics, the information that you arrive at is only as good as the data that is fed into the your chosen business intelligence platform. This is especially true when it comes to people analytics, since we already know that the data sets that we deal with are complex to begin with.
In order make people analytics work, what HR professionals and other decision-makers in business need today is a happy medium: a balance between the depth of insights that you get from in-person interviews and the speed that automated surveys can provide.
Even as HR professionals are increasing their use of data analytics, they have also felt a need for real dialogue before data is analyzed. Enter virtual interviews. In essence, virtual interviews are automated face-to-face interviews that can be launched to as many stakeholders as possible. They give HR professionals the power to ask, collect, and quickly and effectively analyze employee and other stakeholder insights.
Through this digital dialogue that virtual interviews can facilitate, decision-makers have access to actionable information.