Humanyze-ing the workplace: gathering and analyzing unique data on employee interaction to improve productivity
The people analytics industry is expected to grow to $1B in value by 2022. Humanyze, a Cambridge based startup, is at the forefront of the people analytics charge – the firm has developed a software platform for integrating multiple sources of data, and an innovative badge which gathers diverse data to feed that platform. Humanyze has the potential to create and capture significant value, as long as it can manage concerns around data privacy.
The people analytics industry is expected to grow to $1B in value by 2022. Corporate people functions and a diverse array of 3rd party providers are scrambling to integrate current sources of data regarding employees and introduce new sources of data; increasingly sophisticated analysis of these data is yielding actionable insights to improve employee productivity and satisfaction. Humanyze, a Cambridge based startup, is at the forefront of the people analytics charge – the firm has developed a software platform for integrating multiple sources of data, and an innovative badge which gathers diverse data to feed that platform. Humanyze has the potential to create and capture significant value, as long as it can manage concerns around data privacy.
Employees throw off a bunch of data as they go about their workday (e.g., emails, phone calls, calendar invites, ID swipes, chat, room usage). Humanyze integrates the metadata from these sources (interesting research conducted by the founders shows that the content is not needed to achieve a high degree of fidelity in findings) into its software platform, Humanyze Elements; in addition to these common data sources, Humanyze has developed a badge, the size of a matchbox and worn around the neck, that gathers data on interactions (e.g., who each employee is talking to, how much, with what inflection/ volume level) via a microphone, Bluetooth sensors to track location, and an accelerometer to capture activity. Analysis (custom and using proprietary ML algorithms) can be conducted on the resulting data set to test hypotheses around diversity and inclusion, engagement, teamwork, compliance with policies, and many other areas; initiatives to improve any of these areas can be tested and progress tracked. Data and analyses are viewable in aggregate to managers and at the individual level for each employee. Google’s recent Project Aristotle (an effort to identify the practices of its best performing teams) determined that psychological safety was one of the best predictors of team success. A common indicator of psychological safety is equally shared airtime, previously very difficult to measure – Humanyze enables testing of such indicators. The incremental data Humayze gathers (and seamless integration with traditional data), gives Humanyze an edge over its people analytics competitors, allowing it to create significant value for diverse clients (rumored to include organizations from BCG to the US Army).
How Humanyze process works
Different areas of analysis for Humanyze
Humanyze’s model for capturing value is not fully transparent, however sources suggest that the company moved away from an initial, project-based consulting fees approach to its current software play (likely a subscription model given the ongoing value of using the software and the dashboards it provides). From Humanyze’s perspective, it would make sense to consider trying to capture some of the value created by its insights through performance fees (e.g., percentages of costs savings/ productivity improvements from Humanyze enabled initiatives) although it may be difficult to get firms to agree to such agreements and difficult to implement them (e.g., aligning on the actual magnitude of improvements). An additional way Humanyze could consider trying to capture value is by keeping disguised data from its diverse customers (with their permission and heavily anonymized/ cleaned of course) to conduct cross-industry/ function analyses based on the data of multiple firms; accepting payment in data in this fashion, could allow Humanyze to build a significant moat (i.e., rich data set, better trained ML algorithms) relative to its competitors and relative to the HR/ people analytics functions of individual firms.
The most significant challenge to Humanyze’s model, and to the people analytics field in general, is likely to be increasing sensitivity around data ownership/ privacy. Humanyze has taken many positive steps to manage this challenge (e.g., focusing on metadata instead of content, aggregating data reporting, deleting incidentally recorded content quickly), but it will need to be very thoughtful in how it communicates (and how its customers communicate) to employees regarding how the data they throw off will be used. There is also some regulatory/ country risk: in the US at least, the norms around data generated at work belonging to the employer are fairly strong (going all the way back to Ford assembly line workers being heavily observed both at and outside of work), but Europe is taking significant steps to give employees ownership of their data through its General Data Protection Regulation, and countries like China present significant questions around how much data the state has a right to (e.g., creation of social credit scheme). If Humanyze is conscious of these challenges, and continues to create significant value for both employers and employees, they should be manageable; per the BBC, “A PwC survey from 2015 reveals that 56% of employees would use a wearable device given by their employer if it was aimed at improving their wellbeing at work.”
It will be interesting to watch Humanyze as its data store and analytics capabilities get richer over time and potentially one day allow interesting cross-industry analyses. Hopefully employees will continue to feel that the benefits they get from increased analysis of their workplace behavior outweigh the potential downsides.
 There will be little privacy in the workplace of the future. The Economist. Print Edition, March 28, 2018
 Managing human resources is about to become easier. The Economist. Print Edition, March 28, 2018
 How much should your boss know about you. BBC. http://www.bbc.com/capital/story/20180323-how-much-should-your-boss-know-about-you
 Global Workforce Analytics Market Will Reach USD 1056.38 Million by 2022: Zion Market Research. https://globenewswire.com/news-release/2017/09/19/1124696/0/en/Global-Workforce-Analytics-Market-Will-Reach-USD-1056-38-Million-by-2022-Zion-Market-Research.html
 Humanyze Corporate Site. https://www.humanyze.com/
 Bernstein, Ethan, and Stephanie Marton. “Sensing (and Monetizing) Happiness at Hitachi.” Harvard Business School Case 418-019, September 2017.
 Humanyze. Wikipedia. https://en.wikipedia.org/wiki/Humanyze
 Project Aristotle. Google. https://rework.withgoogle.com/print/guides/5721312655835136/
Student comments on Humanyze-ing the workplace: gathering and analyzing unique data on employee interaction to improve productivity
Really like the ability to get super specific about behaviors (a la Project Aristotle). I can see the value of combining Humanyze with something akin to the Toyota Production System to push productivity and efficiency. The Humanyze badge can also demystify the people analytics of how jobs get done. As an example, CEOs often complain that they receive filtered info from their direct reports and don’t often hear about issues until it’s too late. Humanyze could introduce a new level of transparency and interactivity within an organization, essentially flattening the org structure. Of course, Humanyze is, quite literally, big brother. Ensuring correct use of the information and the security of such info is equally complex as it is difficult.
Thanks for writing about this! I think it’s a really interesting model. There are a couple of challenges I see arising from this. First, it turns the workplace into some sort of surveillance state where every employee action is tracked – beyond the privacy implications and cybersecurity risks if that data were to be stolen, I think constant monitoring could dissuade potential employees from joining or create a negative fear-based work environment, if implemented poorly. A second question I have is how the company bridges the gap between correlating behaviors / workplace environment factors with positive outcomes, and taking that one level further to draw causal links. Like the concern about the pay-for-performance value capture model you allude to, I think it must be incredibly difficult to really pinpoint the drivers of organizational value creation from a behavioral aspect.
On the value capture side, I think they could both sell a SaaS data platform model as well as corresponding consulting services. With their core data platform, they could aggregate best practices across organizations that they then deploy on consulting engagements to improve workforce productivity.
Hi Jared, really interesting post and company, thanks! Humanyze is a fascinating concept and one that makes me quite nervous. Whilst I can see and understand all of the benefits to an organisation of having this data constantly monitored and the take aways that could be derived from it, as an employee it sounds dystopian and controlling, at best. You mention in your post that the company will need to think closely about how to communicate to employees what it is doing so as not to intimidate or anger them. I think it will be very interesting to see how this plays out over the next few years and whether Humanyze needs to offer some sort of training for the management of companies it is working with so that they can learn the best way to ‘sell’ the Humanyze products to their employees and gain employee buy-in.
Super interesting post! This is incredibly interesting and incredibly scary at the same time. I’m actually really surprised that 56% of employees would be open to wearing something like this especially when it’s somewhat unclear how the insights lead to real authentic change and not manufactured behaviors. I’d be curious how much they were told before getting asked the question. I think my biggest concern (in addition to data privacy) is similar to the concerns people had in the soccer case around people becoming robots. If people know that their every word and movement and interaction is being recorded and analyzed, I find it hard to believe that they will continue acting in an authentic / genuine way. I’d imagine people being falsely positive when talking about the CEO behind his/her back for example if they’re being tracked. Maybe this is a good thing to some extend but overall I’d be very concerned.
Very interesting and frightening post! I completely agree with you that the greatest challenge this Company faces is with customer adoption due to data privacy concerns. This risk may be mitigated by more and more millennials and centennials entering the workforce. Both generations have been found to be more trusting of institutions that harbor their personal data. Many believe this is largely due to the fact that Millennials and Centennials grew up with internet access and connected devices and they are more tech savvy than any generation before. While this may be frightening and does pose several risks, the Company may face less of a challenge with adoption as it considers the future millennials and centennials generations entering the workforce.