big-data imageToday's post comes to us courtesy of our newest Board member, John Frehse, Managing Partner at Core Practice and a sought after speaker on the topic of workforce management. John's post aims to help organizations get started in making sense of big data and using it to solve real problems.

As technology advances allow us to analyze every aspect of business operations, many companies are inundated with data. Although we celebrate the advances in technology, this “data revolution” has also blurred the line between valuable insight and mundane non-value added information. As a result, many companies are now buried in indecipherable numbers. To successfully pierce through the mountains of useless data and focus on the strategic insights, it is critical businesses have the tools to translate heaps of distracting data into useful information.

For many organizations, payroll and labor IT systems are a significant source of operational data. As labor is almost always the number one controllable cost, dedicating time to this aspect of your business can yield significant financial and operational improvements. Many techniques, including Lean and Six Sigma, encourage large amounts of data analysis and dissemination of this information to all levels of the organization. The challenge often begins with employees' ability to efficiently and effectively digest massive amounts of data.

The following three data sets are a good place to start:

1. The Workforce to the Workload Mismatch (WF/WL)

The Workforce to the Workload Mismatch shows how well the employees are matched up to the required hours needed to get the work done. Looking at the Workforce to Workload Mismatch on a granular level can show where labor waste occurs and more importantly why it occurs. Is Friday always understaffed? Are there too many people in the beginning of the month and not enough at the end of the month? Are there seasonal or variable spikes in demand that are not met? Seeing this mismatch and understanding root cause will quickly allow for improvements.

2. Demand Volatility (LVIX)

The Labor Volatility Index (LVIX) is a complex analysis that measures how much and how often the volatility in the demand for a service or product changes. The LVIX is prescriptive in guiding management teams to the best labor strategies based on their current situations and the challenges they face. The analysis provides management teams with how much labor is needed to satisfy demand. When we look at labor effectiveness and utilization, managers and supervisors are often told that they could have done a better job putting the right people in the right place at the right time. The LVIX provides a more sophisticated analysis, yielding a deeper understanding of the degree of difficulty required to achieve this goal.

3. Absenteeism

Absenteeism is loosely defined as periods of time where employees do not come to work. There are both planned activities like vacations and holidays, and unplanned activities like sick time and general call-offs. Unplanned absenteeism in particular negatively impacts the entire organization. Increasing visibility and transparency on this issue will immediately help improve the problem. Scrambling to find replacements or operating with less people than appropriate kills quality, service, and performance for everyone. Do more unplanned absences happen on Mondays after a holiday weekend? How likely are employees to show up for overtime on Saturday or Sunday compared to a Tuesday? Do employees call off on certain days and then show up for overtime opportunities? Identifying the trends can help isolate the behaviors and take corrective action.

By focusing on these three key performance metrics, management teams are able to quickly analyze large amounts of data, avoid data paralysis, and make strategic and well-informed decisions about important labor-related topics. By bringing a little focus to your Big Data strategy, you can reap big rewards.


big data whisperer
I recently had the opportunity to interview  Aram Faghfouri, senior data scientist at Kronos; Holger Mueller, vice president and principal analyst at Constellation Research; and David Wright, vice president of architecture at Kronos, about the challenges and rewards associated with making big data small.  Everybody's talking about Big Data, which is increasingly becoming a major strategic focus for firms that sell technology and consulting services.  The mountain of data that the former help organizations create provides an equally large opportunity for the latter to help interpret.

For many organizations, mining their transactional data for analytical "pots of gold" can seem both daunting and potentially dangerous when they begin to contemplate issues like data security and privacy.  Aram, Holger and Dave shared their views on the following topics that may help you transform your mountain of data into nuggets of insight:

 You can listen to our conversation here.

What are you doing to leverage data to transform your workplace?

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