Microsoft May Hold the Productivity Crown, But Productivity Reporting Is Ripe for Disruption
There is a lot to like about Microsoft's response to the collaboration and productivity challenges that arose when offices around the world were pushed into working from home (WFH) in March. Microsoft had previously been late to the internet and cloud computing party, but turned it around from being late adopters to global leaders. This time Microsoft appears to be taking the lead on workplace productivity.
The scaling of Microsoft Teams could not have come at a better time, as adoption rates have skyrocketed. And the recent release of the Microsoft Office Productivity Score speaks directly to collaboration and productivity ... or does it? A close look at the documentation exposes some red flags for me. For example “... the Productivity Score was built to help you understand how people are using productivity tools and how well the underlying technology supports them in this” and “giving you visibility into how your users are adopting and using your productivity investments.”
On the surface, this sounds fine. But on reflection, how much does this speak to how staff really engage with each other and the organizations’ mission and purpose? This is not a criticism of Microsoft alone, but of virtually all technology providers (and IT departments, for that matter).
Ever since computers were introduced into organizations, the IT function has been obsessed with the “up-time” and “availability” of the facilities they manage. The granularity with which you can slice and dice your cloud usage, for example, is way beyond the analytics we might use to understand how our employees are engaging with each other around a common purpose.
Resource utilization reporting creates a focus on under-utilized resources. Eli Goldratt taught manufacturers in the 1980s that full machine utilization is a false metric and that managing the flow through bottleneck units is the road to higher productivity. This is a lesson yet to be learned by human productivity platforms.
Who Might Disrupt Microsoft's Standing?
No organization is immune from a major market disruption. The larger an organization, the more prone it is to being blindsided. Microsoft, with the internet and cloud computing, like IBM before it, with personal computing and IT services, has been able to adapt its organization to prior major disruptions. But even Microsoft would admit that you can’t always rely on playing catch up.
The COVID-19 pandemic has not only accelerated the adoption of digital technology, it has amplified the importance of the human factor: employee safety, well-being and engagement (with each other and the organization).
We are seeing the field of people analytics now looking to break out of the HR silo that has nurtured it into mainstream business. This hasn't happened yet. But one could imagine the next disruptors coming from the ranks of the technology providers that break out of their “resource utilization” mindsets to employ proven measurement and monitoring capabilities to truly embrace the principles of people analytics.
Related Article: People Analytics: Big Benefit or Big Brother?
What Might a New Measure of Productivity Look Like?
Firstly, we need to address the industrial era definition of productivity as simply more goods and services produced by less people in less time. This efficiency view of productivity is rapidly becoming outdated as automation is elevating jobs to become more knowledge intensive. The recent World Economic Forum Future of Jobs report places “critical thinking and analysis as well as problem-solving, and skills in self-management such as active learning, resilience, stress tolerance and flexibility” at the top of its future jobs demand. Such future jobs cannot be effectively assessed by industrial efficiency measures. The new disrupter would:
- Balance longer term, less tangible tasks e.g. complex problem solving, progressing innovation, etc., with short-term efficiency measures (explore vs exploit).
- Monitor and report on people centric issues, like people-to-people engagement, sentiment, purpose alignment and not just tool usage.
- Address the imbalance in reporting on knowledge stocks (how much we have) over knowledge flows (how we use what we have).
- Address the imbalance between explicit knowledge reporting (content) over tacit knowledge reporting (real knowledge).
The disrupter will speak to the real issues for organizations trying to navigate their way out of arguably the biggest social, economic, health and well-being disruption in several generations.
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An Example: Knowledge Stock and Knowledge Flows
The example below is taken from our soon to be published sixth annual benchmarking study of Microsoft’s Yammer networks. Our aim is to demonstrate how knowledge can flow from a community and innovation platform like Yammer, through an execution platform like Microsoft Teams, to achieve tangible outcomes. We identify five “staging areas” for collaboration: Yammer discussions, Teams Channels, Teams Chat, Teams Meetings and Teams Calls. Knowledge must ‘flow’ in these areas if a productive outcome is to be achieved.
We use the proxy of personal network overlaps to measure the degree of tacit knowledge sharing. The networks are formed from the online interactions conducted in each collaboration area. For example, if my network of connections in Yammer overlaps significantly with my Teams Channels network, then we will infer a relatively high level of tacit knowledge is flowing between my more open Yammer discussions and my more task-oriented Team Channel discussions. The personal networks are ranked, so a strong overlap means the people I interact with the most in one area are the same in another. When we aggregate the personal networking overlaps to an enterprise level we can start to visualize these tacit knowledge flows:
In this knowledge flow representation we are looking to visualize the long-term vs short term; people vs tools; stocks vs flows and explicit vs tacit elements. For this organization, the “knowledge stocks” are reflected in the height of the boxes (average size of the networks) and the width (average number of interactions). The “knowledge flows” reflect the aggregated overlapping networks. The flows, for example, show the Chat space as a potential “bottleneck” resource, with strong flows both in and out. It is also instructional to look at the Meetings and Channels spaces, where relatively light flows are coming in but stronger flows coming out; a transformation that is most welcome!
While this example uses Microsoft Yammer and Teams, the model is generic and could be applied to any combination of collaboration platforms providing the same facilities, be it Zoom, Slack, Google G Suite, Facebook, Cisco, Atlassian Confluence and the like.
Related Article: Knowledge Graphs: Adding the Human Factor to Unlock Real Intelligence
Disrupters Are Welcome
No doubt Microsoft has the inside running when it comes to facilitating collaboration and enterprise productivity. But the gap between the current status quo on collaboration and productivity reporting and what is more meaningful for organizations moving into a new, more human-centered normal way of working, is large enough for potential disrupters to take hold.
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About the Author
Laurence Lock Lee is the co-founder and chief scientist at Swoop Analytics, a firm specializing in online social networking analytics. He previously held senior positions in research, management and technology consulting at BHP Billiton, Computer Sciences Corporation and Optimice. Connect with Laurence Lock Lee:
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