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How Data Analysis Is Changing Workforce Management

Jan 3, 2017

How does the average HR department find the story contained within their scattered data? A growing number of strategies are answering that very question, better managing complicated workforce decisions and expanding the frontier of predictive modeling available to businesses. For companies still unconvinced about the potential of data analysis, here is how businesses are using workforce management analysis to reach deeper truths about motivation, productivity, and team dynamics.

Bridging the Gap with Data

The initial goal of workforce management data analysis going forward will be closing rifts between disparate data. As data becomes more of a commodity, more organizations realize the salient value of adopting a unified data strategy versus scattered data islands. Consolidation of dissimilar data from operations, accounting, sales, and other departments might not have a clear advantage at first, but the possibility for workforce related insight makes breaking data silos worth it.

Consider the potential for your employee retention strategies. Not every career has a linear path. Employees transition between departments and projects, making it difficult to track their overall path without a unified data strategy. In these instances, a customized career development plan absolutely requires that total picture.

Measuring aptitudes and performance across departments and roles helps objectively identify the best growth trajectory for an employee. Are this person’s best skills being underserved in his or her current role? Is he or she a strong leader in the making, but only has flat growth on the current career path? Unified data strategies help to identify overlooked potential, enabling organizations to make adjustments that reduce turnover and maximize potential.

Moreover, the interconnectedness of your data within the warehouse opens up the types of questions you are able to ask. Do company-wide retention strategies need to be revised? Is turnover higher for a certain position? Does management in a specific office or department need to be retrained? The most insightful answer often comes to the forefront when you compare otherwise disparate data.

Finding Unconventional Solutions

Inside the data are unexpected insights that otherwise get overlooked. Beyond productivity measures, attrition levels, and clarified succession planning, unique findings can be determined from analyzing workforce data. Sometimes, that can provide significant savings to an organization.

When Toyota was looking for ways to consolidate their U.S. operations into one centralized location, data gathered from their workforce influenced corporate decisions. Their analysis began by conducting internal focus groups to find what percentage of employees were willing to relocate with the company. With confidence, Toyota was able to say what percentage of each division was willing to make the move and weigh the overall cost.

What companies in Toyota’s situation could do is analyze the data from their internal focus groups to help identify which skill sets would be needed after any potential move. Let’s say 90% of their HR workforce accepted the offer, but only 50% of IT did. Toyota would either need to search for a new headquarters where those technical skills were widely available, or at the very least understand the compensation necessary to attract top talent.

Ultimately, their data analysis, guided by experienced professionals and analytic best practices, helped Toyota decide to move from their Torrance, CA headquarters to Plano, TX, a decision which provided their many employees with more affordable housing than what was available in the radius of Los Angeles County. In the end, they made a transition that improved their financial situation and even boosted morale in the process. Data helped them get their win-win situation.

Expanding Potential with Analytic Power

The power of today’s advanced analytics solutions opens up a whole new level of insight. Analytics platforms are capable of getting granular with their observational lens, allowing managers to incorporate long overlooked data points that hide insight that inform the decision-making process. Being able to spot what adds value takes experience in connecting the dots with data points.

Consider this situation: a healthcare organization is trying to prepare its workforce for the holidays to ensure the best patientcare outcomes. The HR department has data ranging from total patient admission and the variety of patient care types to employee scheduling and call offs going back years.

In the past, old school data mining might have limited the depth of comparison but predictive modeling compares the above cross-section of data with industry trends, weather patterns, and other historic data sets in a multifaceted way that helps predict future results. The result is efficient scheduling that plans for a certain amount of employee call off without excessive waste in labor dollars.

Outsourcing Your Workforce Management Analysis

The value of using robust data analysis on workforce management has a large return on investment, but not every company is equipped to do their own investigation. Some lack the analytical tools to review and make future predictions off of their own internal data. Others lack the expertise to see patterns and make informed decisions. In those instances, working with a team of data analysis experts closes the gap quite easily.

At w3r, our team of data analytics experts are well-versed in guiding human resource leaders through workload planning, deployment analysis, and process workflow analysis. Contact us today to take your enterprise to the next level.

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