For the past few years, everyone has been talking about “Big Data.” Articles speak of the promise of analyzing data to reveal patterns, trends, and associations, especially relating to human behavior and interactions. Companies have established enterprise analytics teams, and human resources functions have created metrics teams to perform “talent analysis.” How much of this effort is focused on creating the optimal contingent workforce? To answer that question, we need to examine the purpose of Big Data analysis.
Simply put, big data analysis is the process of integrating and analyzing internal metrics, external benchmarks, social media data, and government data to deliver a more informed solution to business challenges. So, the right starting point when answering our question is to identify those challenges, and determine what it is that we need to know.
As spend on contingent workforce in the US crosses the $100 billion mark, companies want to validate their use of contingent workers, optimize their use, and understand where they best fit into their organization’s plans. This third objective is new – only recently have companies begun to view contingent workers as strategic. As objectives change, so do the questions that are asked, and the data needed to answer those questions. In the past, the objective was to find satisfactory temporary workers at the lowest possible price point and minimal risk. The question usually asked was, “What happened?” In response, companies employed Vendor Management Systems with reporting capabilities that provide “rear view mirror” statistics on positions filled, time required to fill positions, attrition levels, and pay and bill rates.
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Now, in order to understand how to strategically use non-employees to promote business interests, the questions shift to “Why did it happen?” and “How do we control what happens next?” To answer these questions, a comprehensive, ‘Big Data’ view is needed.
Let us discuss the data that needs to be tracked and catalogue the ways in which it can be analyzed:
- Data is worthless without asking the right questions. Start by identifying the questions that your organization needs to answer. These differ for each company, based on their priorities. You many need to know the correlations between pay rate and fill rate, the right type of temporary worker (agency contractor, freelancer, independent consultant, outsourced project team) for each assignment, the correlation between pay and retention, or what attributes are of greatest importance when finding “best fit” candidates.
- Measure what matters. Gather and analyze data that directly applies to the questions that you have identified. Stop trying to boil the ocean!
- Establish a business framework for deciding whether positions should be filled with permanent employees or non-traditional talent. Then use data to assess which group best meets each criterion. For example, if positions must be filled rapidly, can you best meet that goal using permanent or temporary employees? What has been your past experience? Would you answer differ by skill, or location?
- Use the data to rate the effectiveness of different talent acquisition sources.
- Establish benchmarks by comparing your contingent workforce management program performance to market standards. Conduct quarter-to-quarter trend analyses, and use this data to predict future demand and performance. Periodically check predictions for accuracy, and adjust as needed.
- Contingent workforce analysis must be conducted at the macro and micro levels. Examine the workforce overall, as well as by location, department, supplier and/or hiring manager. Hone in on the outliers. That’s where you’ll gain the most insight.
- Apply emerging technologies. For example, DCR’s Smart Track VMS utilizes Natural Language Processing to assess the hiring decisions of each hiring manager, identifying trends and preferences that are indicators of the intangible qualities of a “best fit” candidate.
The need to attract and hire the best talent is critical to business success. That has always been true. This makes it imperative for businesses to gain clear insight into their entire workforce – permanent and non-employees alike. But insights gained through Big Data is only the first step. Remember that data is necessary, but not sufficient, to enact change. Big Data only helps when executives can translate insights into initiatives that drives business performance.
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