It’s pretty easy to quantify the hours you spend at the office every week, but it’s a little harder to determine exactly how much time you spend actually getting things done.

Sure, we waste time on digital distractions such as surfing the web, but even outside of that we “waste” time actually working. Sometimes, even, time spent “working” can actually be time wasted as well answering an unending amount of email and sitting in meetings.

Sapience, a company that provides employee productivity analytics for the enterprise, is looking to solve this problem. Sapience shows how much time employees work, but also what type of work they are spending their time on.

The founders came up with the concept from running outsourcing agencies in the past and wanting to better track worker productivity. According to Singh, it’s just as much for the individual employee as it is for the organization as a whole.

“The goal is to empower every employee so that they can increase their productivity and wellness,” said Khiv Singh, the associate vice president of sales and marketing for Sapience. “And then have enterprise-wide productivity data available for managers, so that they can create a mindful enterprise which promotes focus, which promotes coordination, which promotes better utilization of capacity and so on.”

Sapience can be deployed as a SaaS product or on-premise. The average cost ranges between $120 to $160 per person per year, based on what type of deployment users choose and how many features they want to deploy.

Currently, Sapience has more than 65 active clients and 100,000 active users in 10 countries. Customers include Dell, Xerox, Fujitsu, BMC Software, and Siemens.

Basically, Sapience is an advanced analytics dashboard that shows an employee or manager what kind of work (calls, marketing, meetings, management) they are spending their time on. The tasks are also separated into categories such as sales or marketing, and users can see what percentage of their time is spent on core activities and categories for their position. For example, you could label Salesforce as a “sales” activity.

Users can set goals based on that percentage. For example, if a salesperson can determine they are spending 30% of his or her time on sales activities and closing X number of deals, they can make a goal of spending 50% of their time on sales activities and see how the changes the number of closed deals.

By connecting to your calendar system, Sapience can also recognize if you’re offline and looks into the calendar to see if a meeting matches that timeframe. It then records that as time spent in a meeting.

You can also give access to users or admins to change tags or labels on time spent. For time used for an impromptu meeting, users would need to input what the time was spent on and label it as a meeting.

According to Singh, there are three modes of deployment for the product. The first mode is a self improvement mode, where the data remains with the user only. This is to encourage the user to understand how they are working in private.

The second mode is an anonymous mode where the names of direct reportees are available to managers, but not the individual members of the team. Managers can see work trends in teams and use the data to have conversations about what could be done differently.

“It’s not about pinpointing one individual, but about seeing, as a team, are they doing the right things,” Singh said. “And, if not, is there something in the processes that can be optimized?”

Lastly, the individual data mode reveals individual employee data to managers. However, even if a manager can see employee X spent a certain amount of time private browsing (any browsing not related to work), they can’t see the websites they visit. Or, if they can see that employee X spent a certain time on emails, they can’t see who the employee emailed or what the contents of the email were.

Mitesh Bohra, the co-founder and president of Infobeans, a Sapience customer, said that the key value of using the product lies in the big data driven discoveries like the most productive times of the day for certain employees or teams.

“We utilize these to identify not only best practices but also star performers – how much output are they producing for their input time/activity, are we challenging them enough or are they spread too thin,” Bohra said.

While the product does present unique opportunities, Bohra said there are also some challenges to its adoption including resistance to change and the fear of Sapience as a big brother type monitoring system.

The argument could be made that employers have every right to know how employees are spending their time. However, Singh said that Sapience is differentiating itself in term of the anonymity with which it provides productivity data.

“This always comes up. The first response we always get: ‘This is big brother.’ Companies have done these kind of things in the past and the only thing they can equate it to is big brother tools,” Singh said. “But, when they look at the application, when they look at the functionalities, when they look at the data it provides — that opinion changes.”

Singh said that Sapience doesn’t do screen scraping or keystroke capture, and they refuse to let customers deploy it in stealth mode to spy on employees. It has to be something employees are aware of.

One potential use case could determine the effect on workflow of working from home. Singh said that one example could be letting working parents go home early to pick up kids from school, and see if they are getting back online when they get home, accomplishing the same amount of work as in the office.

However it is used, Sapience will likely remain a controversial startup. But, it’s recent Series B funding round and steady sales growth mean that it’s taking a real shot at lifting the veil on employee work habits and productivity.

Subscribe to the Data Insider Newsletter

Learn the latest news and best practices about data science, big data analytics, artificial intelligence, data security, and more. Delivered Mondays and Thursdays

Subscribe to the Data Insider Newsletter

Learn the latest news and best practices about data science, big data analytics, artificial intelligence, data security, and more. Delivered Mondays and Thursdays