Analytics are nothing new to business. From measuring sales to optimizing marketing campaigns, we’ve clearly been doing this for a while. But companies now use data to guide decisions other than just those in the sales, marketing and financial realms.
In this post we’ll take a look at two ways companies are relying on data in ways you may not expect.
1. Workspace Optimization
Thanks to mobile technology, the global economy and remote workers, work habits have changed. It’s not uncommon for employees to work from home or work on different timezones to accommodate offshore clients and co-workers. People aren’t just sitting in their cubicles like they used to and cranking out work, so a lot of office space goes unused. Between pricy commercial rent and utilities costs, that’s a lot of wasted cash on space that isn’t being used.
Additionally, pesky whipper-snappers are entering the workforce in droves. This is a generation who maintained multiple AIM conversations while cranking through high school home, enjoys multi-play video games and values group achievement thanks to participation awards. Simply put: We’re collaborative. So we want workplaces that are collaborative, too. Internal chat systems are one way to provide the connection that this young workforce seeks. But to appeal to educated and tech-savvy pesky whipper-snapper applicants, companies need to find ways to make their offices more collaborative in the physical sense.
Motion, sound, temperature, and presence-tracking can be done through a network of sensors placed within an office. This data can help inform decisions about office design, furniture orders or even lease renewals.
2. Hiring and Promotions
Google is no doubt one of world’s most innovative companies, and they maintain that same caliber of forward-thinking when it comes to their internal matters. Google’s HR department – called “People Operations” – is a data-driven function that quantifies decisions about hiring, promotion, training and culture. The team includes number crunchers from a variety of backgrounds, including engineering and consulting. Over the past six years or so, the People Operations team has worked on a variety of projects to improve the company, including:
- Cap the number of interviews required for new hires (company analysis showed that more than four interviewers didn’t lead to a better hire)
- Creation of an on-boarding agenda for an employee’s first four days of work. This boosted productivity by up to 15 percent.
- Created an algorithm to review rejected applications. Google gets over two million applications every year. This helped the company hire some engineers its screening process would have otherwise missed.
Next up: The team will use data to define what makes a high-performing team at Google, determining the ideal team size, type of people on a team, and evaluate how team dynamics impact output. These questions are nothing new to the workplace, but answering them with hard numbers is a new approach. Typically HR, hiring, and promotions have been very qualitative things – based on relationships and responses to verbal interview questions. While those are helpful things to consider, they are also full of human bias. Bringing more facts to these decisions is clearly working for Google, and it’ll be interesting to see how other companies adopt this approach.
What other ways do you see companies using analytics in the workplace? Let us know in the comments.