Employee Productivity Analytics: An Emerging Tech Category

In this special guest feature, Brian Berns, CEO of Knoa Software, discusses how big data solutions have the potential to uncover workflow inefficiencies, process bottlenecks and application usability issues. With employee productivity analytics, there are many benefits that are within the grasp of every enterprise. Brian is a successful software industry veteran with over 20 years of executive experience, including as president at Ericom Software. He also held the position of Division VP at FICO and SVP of North America at Brio Software (acquired by Oracle). Additionally, Brian has been the founding member of several successful software start-ups including Certona and Proginet. Brian has a BA from Yeshiva University, an MS from NYU, including studies at the NYU Stern School of Business MBA program, and computer science at the graduate school of the NYU Courant Institute of Mathematical Sciences.

In summer 2017, I suddenly began receiving emails from Microsoft that detailed my Office 365 activity.  These messages told me things like how much time I spent multitasking during meetings and working after hours, along with how much “focus time” I had and who my “top collaborator” was.

I couldn’t believe how little focus time I had each week, but more importantly, I realized that this data could be extremely powerful for me and my team. By categorizing and organizing this big data and sending me insights about my work patterns, Microsoft didn’t just clarify how much more productive I could be; it also opened my eyes to how important and useful this information is.

A new IT category

Microsoft’s MyAnalytics and Workplace Analytics give priceless insight into employees’ time management, user productivity, workplace collaboration and more. However, Microsoft isn’t the only software giant to realize the power of “employee productivity analytics”; SAP is also onboard.  Its SAP UEM application allows companies to observe and understand exactly how their employees interact with the enterprise software suites that they use every day. In other words, they can now easily pinpoint all activities that lead to errors, identify apps that are under-utilized, gain insight into workflow and process inefficiencies, detect situations in which employees must use workarounds to navigate slow, buggy software, and more.

So why did it take so long for this valuable information to be made available? Big data and analytics have long been used to shed light on all aspects of business, except one: human capital.  In the age of the Internet of Things (IoT), when companies can effortlessly monitor the performance and location of tens of millions of devices, it is surprising that we are provided with so little insight into how employees spend their time and use key business applications.

Another example: most online retailers use customers’ behavioral patterns to identify likely future purchases, yet they don’t have the slightest idea whether their employees are struggling to perform simple tasks like shipping products, creating invoices, and checking inventory.

How Employee Productivity Analytics can help

Companies must make sure that their employees have positive experiences with their business software. If you give them outdated, clunky software that causes frequent errors and lags and forces users to repeat work and develop workarounds, you will create a negative employee experience. Employee productivity analytics can help you determine how each person and application is performing, and take corrective action to make sure you are getting the intended value out of your software.

Employee productivity analytics can play a key role in managing today’s changing workforce as well. Organizations are constantly looking for innovative ways to recruit, motivate and retain young talent. Insight into how millennial workers collaborate, use their work hours, and overcome technological challenges is invaluable in this regard. Analytics also enable managers to identify training needs and address them rapidly, before employees lose interest and seek greener pastures.

And it’s not just management that benefits from employee productivity analytics; smoother business processes and improved collaboration result in a more engaged workforce as well. By increasing engagement, you can positively impact both employee job satisfaction and the company’s bottom line.

A real-life example

A large energy company needed help identifying the reasons for frequent help desk calls and user errors.  To pinpoint the technological issues and areas causing the most difficulties for their employees, they used employee productivity analytics to:

• Concentrate on the most common transactions and make sure employees were given the necessary education and documentation to succeed
• Compare the productivity of employees at new sites with those at more established sites to identify transaction and support trends
• Track sensitive transactions to address user errors as they happened

Employee productivity analytics enabled this organization to proactively identify and resolve problems much more rapidly than previously. As a result, their user satisfaction ratings saw a tremendous boost.

Now that we have big data solutions like these to uncover workflow inefficiencies, process bottlenecks and application usability issues, just think about the benefits that are within our grasp. I look forward to seeing all the new tools that will be developed as the employee productivity analytics category continues to grow.

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