Big Data and the Future of the Hourly Workforce

Topics: Prediction, Better, Productivity Pages: 7 (2089 words) Published: August 20, 2013
BIG DATA
AND THE FUTURE OF THE HOURLY WORKFORCE
Companies are pouring tens of billions of dollars into Big Data to find patterns they can use to predict the future.

How Big Data is Changing the way Operating Executives Manage their Hourly Workforce

T

Does Big Data Matter?
hose who wonder whether Big Data is really as big of a deal as the press is making it out to be should take note of Target. To better understand how to market new products to their customers, analysts at the retailer studied years and years of customer purchase data. They were looking for patterns that would enable them to predict the future.

What they found was a way to spot a pregnancy in the first trimester, based on changes in a woman’s buying behavior. A key indicator is the switch to unscented lotion.1 It is amazing what can be found when you delve into data. The Center for Disease Control looks for what people search for on Google in order to spot outbreaks of diseases. People are using Twitter to accurately predict the opening box office revenue for movies. Political campaigns do house-by-house studies to determine where to target their messaging. Companies are pouring tens of billions of dollars into Big Data to find patterns they can use to predict the future. The reason for this is clear. The amount of money that can be made or saved through better data targeting is immense. Small changes on the margin, sales or productivity increases of just a few percent are worth tremendous amounts of money. And often, they’re as easy to find as looking at what kind of lotion a woman purchases.

1

“how companies learn your Secrets”, the new york times, February 16, 2012. http://www.nytimes.com/2012/02/19/magazine/ shopping-habits.html

B i g Data a n D t h e F u t u r e o F t h e h o u r ly Wo r k F o r c e

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Reducing Overspend in the Hourly Workforce: Better Measures, Better Analytics, Huge Improvements One area where the use of data analytics can be used to drive quantifiable impact is in optimizing spend on the hourly workforce. The hourly workforce accounts for more than half of the positions in many U.S.-based companies, driving approximately 17% of annual GDP. Annualized attrition in these positions is high, as are the associated training and productivity costs. The By leveraging cost of hiring an hourly Big Data across worker, on average, their 40,000+ ranges between $1,000 FTE hourly and $5,000 per hire, and lost productivity from workforce, a sub-optimal hire can they were able add another $3,000 to to improve $10,000 per employee retention by to that price tag. With 12%, customer this level of spending, a company with 1,000 service by 10%, people in hourly jobs is and productivity likely to spend $5 to $10 by 15%. Million per year on their workforce in areas where data analytics can help them reduce this amount by 20-50%. Across all companies in the US, this equates to tens of billions of dollars in collective savings. Recently, operational executives have started utilizing data analytics by utilizing powerful web-based software to pinpoint performance and attrition areas within the hourly workforce. These solutions allow them to systematically identify root causes of efficiency (and inefficiency)

and implement solutions to improve operating outcomes. These solutions are driven by predictive analytics, whereby they can analyze billions of data points across key workforce metrics to identify unique patterns within the data that highlight improvement areas to capture savings. A review of some recent examples of how Big Data has driven staggering results to Fortune 50 companies shows just how impactful these solutions can be: • Customer Satisfaction and Time Management Competencies: It’s now an accepted fact that core competencies and capabilities can be systematically measured and tracked across a labor force. Psychometric testing has been in place for decades, with assessments like MyersBriggs an accepted tool across...
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