{"id":7659,"date":"2018-04-04T18:17:24","date_gmt":"2018-04-04T22:17:24","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-digit\/submission\/humanyze-ing-the-workplace-gathering-and-analyzing-unique-data-on-employee-interaction-to-improve-productivity\/"},"modified":"2018-04-04T18:17:24","modified_gmt":"2018-04-04T22:17:24","slug":"humanyze-ing-the-workplace-gathering-and-analyzing-unique-data-on-employee-interaction-to-improve-productivity","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/humanyze-ing-the-workplace-gathering-and-analyzing-unique-data-on-employee-interaction-to-improve-productivity\/","title":{"rendered":"Humanyze-ing the workplace: gathering and analyzing unique data on employee interaction to improve productivity"},"content":{"rendered":"

\u00a0\u00a0\u00a0\u00a0 <\/b><\/strong>The people analytics industry is expected to grow to $1B in value by 2022<\/strong>. Corporate people functions and a diverse array of 3rd<\/sup> 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<\/strong> \u2013 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.<\/p>\n

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\u00a0platform, Humanyze Elements;<\/strong> 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<\/strong> (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\u2019s 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 \u2013 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).<\/p>\n

How Humanyze process works<\/em><\/strong><\/p>\n

\"\"<\/a><\/p>\n

Different areas of analysis for Humanyze<\/strong><\/em><\/p>\n

\"\"<\/a><\/p>\n

Humanyze\u2019s 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<\/strong> given the ongoing value of using the software and the dashboards it provides). From Humanyze\u2019s 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.<\/p>\n

The most significant challenge to Humanyze\u2019s model,<\/strong> and to the people analytics field in general, is likely to be increasing sensitivity around data ownership\/ privacy.<\/strong> 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, \u201cA 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.\u201d<\/p>\n

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.<\/p>\n

 <\/p>\n

Sources:<\/b><\/strong><\/p>\n

[1] There will be little privacy in the workplace of the future. The Economist. Print Edition, March 28, 2018<\/p>\n

[2] Managing human resources is about to become easier. The Economist. Print Edition, March 28, 2018<\/p>\n

[3] How much should your boss know about you. BBC. http:\/\/www.bbc.com\/capital\/story\/20180323-how-much-should-your-boss-know-about-you<\/p>\n

[4] 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<\/p>\n

[5] Humanyze Corporate Site. https:\/\/www.humanyze.com\/<\/p>\n

[6] Bernstein, Ethan, and Stephanie Marton. “Sensing (and Monetizing) Happiness at Hitachi.” 性视界 Business School Case 418-019, September 2017.<\/p>\n

[7] Humanyze. Wikipedia. https:\/\/en.wikipedia.org\/wiki\/Humanyze<\/p>\n

[8] Project Aristotle. Google. https:\/\/rework.withgoogle.com\/print\/guides\/5721312655835136\/<\/p>\n","protected":false},"excerpt":{"rendered":"

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 \u2013 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.<\/p>\n","protected":false},"author":1943,"featured_media":7660,"comment_status":"open","ping_status":"closed","template":"","categories":[776,964,2203,2007,366,1352],"class_list":["post-7659","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-data-analytics","category-data-exhaust","category-data-privacy","category-hr","category-machine-learning","category-people-analytics","hck-taxonomy-organization-humanyze","hck-taxonomy-industry-information","hck-taxonomy-country-united-states"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/competing-with-data-challenge\/","yoast_head":"\nHumanyze-ing the workplace: gathering and analyzing unique data on employee interaction to improve productivity - Digital Innovation and Transformation<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-digit\/submission\/humanyze-ing-the-workplace-gathering-and-analyzing-unique-data-on-employee-interaction-to-improve-productivity\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Humanyze-ing the workplace: gathering and analyzing unique data on employee interaction to improve productivity - Digital Innovation and Transformation\" \/>\n<meta property=\"og:description\" content=\"The people analytics industry is expected to grow to $1B in value by 2022. 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