Seattle-based Zeitworks, which is launching its private beta today after raising a $4.5 million seed round in 2020, wants to give enterprises data-driven tools for improving the productivity of their teams and streamline their business operations. That's a market that's seeing quite a bit of growth right now, especially given how the pandemic has made remote work a standard business practice and how the overall talent crunch is forcing many businesses to do more with fewer employees. The overall idea here is to give businesses better insights into how teams work and where there are opportunities for improving business processes beyond simply using automation. "The problem that we're really addressing is that there's teams and companies in just about every industry who execute all kinds of repetitive business processes every day– and to be clear, it's business processes executed by humans," Zeitworks CEO and co-founder Jay Bartot told me. "Think about processing bank loans or insurance claims or HR onboarding of new employees, moving information from system to system. Oftentimes, those systems aren't interconnected or don't have APIs. The problem that we're solving is that the majority of these processes can't be optimized because they're undocumented and unmeasured. Unsurprisingly, understanding these processes is at the core of Zeitworks' product. But since these processes aren't documented, you can't exactly build a rule-based engine around discovering what people are doing. Instead, the company uses an AI-driven task mining system that uses signals from a wide variety of sources, mostly with a focus on the desktop applications these users interact with during their daily work. Bartot actually noted that he prefers the term'process intelligence' over'task mining,' given that task mining tends to be associated with creating RPA bots more than empowering teams and helping them work better. Now, in order to do all of this, Zeitgeist has to run its agent on an employee's desktop and those users' daily work is then tracked with quite a bit of granularity. Microsoft, with its Productivity Score, does something similar, but the company also faced quite a bit of backlash over it, given that managers could drill down to the individual employee and see how many emails they sent, chats they participated in, etc. The company later made some changes that put the focus more on the organizational level and away from individual users. "In our world, the kinds of productivity scores that we are recording are around this repetitive work -- the fact that people are processing bank loans or you know insurance claims repeatedly is a fundamental part of what we're measuring and what we're doing with pattern recognition," Bartot explained when I asked him about the potential for backlash. "So the productivity scores are really geared towards that specific kind of repetitive work.

When the job of a young east coast-based analyst – we'll call him James – went remote with the pandemic, he didn't envisage any problems. The company, a large US retailer for which he has been a salaried employee for more than half a decade, provided him with a laptop, and his home became his new office. Part of a team dealing with supply chain issues, the job was a busy one, but never had he been reprimanded for not working hard enough. So it was a shock when his team was hauled in one day late last year to an online meeting to be told there was gaps in its work: specifically periods when people – including James himself, he was later informed – weren't inputting information into the company's database. As far as team members knew, no one had been watching them on the job.

Microsoft 365's new Productivity Score feature could produce unwanted effects on its clients's ... [ ] performance. A few days ago, Forbes broke the news that Microsoft unveiled a new feature of its 365 services software that allows employers to secretly monitor and "score" their staff on productivity. On the surface, this is an obvious up-sale tactic by Microsoft to make clients further dependent upon its eco-system. Also obvious are the many privacy concerns that arise from employer surveillance. Yet, what's less obvious, to most, are the negative implications such slick snooping could have on the company's performance: via its corporate and risk cultures.

Now, one firm wants to take things even further. It is developing machine-learning software to measure how quickly employees complete different tasks and suggest ways to speed them up. The tool also gives each person a productivity score, which managers can use to identify those employees who are most worth retaining--and those who are not. How you feel about this will depend on how you view the covenant between employer and employee. Is it okay to be spied on by people because they pay you?