We are on a journey to transform our culture. We learn. We adjust. We improve. Behavioral change is at the heart of that process.
Data from the collaboration systems that people use every day empowers us with insights into the ways people work. Insights that help us continually learn, measure, and adapt.
We call this data-driven cultural transformation.
Measuring Change: Workplace Analytics
Manish Wardekar – Director Workplace Analytics
Data-driven transformation builds key competencies
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Reflect on common examples of collaborative drains. Which is most impactful in your organization? What could you do about it?
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Organizational context
Native Office 365 data
Org context allows
Workplace Analytics to
analyze every meeting
& message between all
internal or external
domains: teams,
customers, vendors, &
partners
Workplace Analytics
uses calendar & email
metadata, which
typically provides 20+
hours of time use data
per week for every
knowledge worker in the
organization
Meaningful outcomesUnprecedented, quantified insights
Clients are in the business
of producing results.
Pairing outcome data (e.g.,
sales attainment, employee
engagement, worker
productivity) enriches the
analytics & the insights.
Provides aggregated
behavioral analytics to
distinguish collaboration
patterns associated with
outcomes & comparative
analysis within an
organization (function,
division, region)
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Privacy
Customer is in Control• Product access limited - Customer decides on access privileges
• Sensitive data handling training recommended
• Data views are aggregated and de-identified
• Guided visual exploration of aggregated data
• Analyst access to de-identified user KPIs
• Customer determines mailboxes to include in scope
• Exclusion of sensitive topics, functions (Based on keywords)
• Only email/meeting headers are used; no body
• Rights protected, private emails/meetings are excluded
Start with
transparency &
curiosity
Experiment for
insight
Achieve data
democracy at
all levels
Couple
behavioral
science with
data science
Institute system
for continuous
improvement
The digital exhaust we can now access
has been the missing catalyst to drive high impact, sustainable cultural
transformations
Data-driven cultural transformation rests on five principles
ApproachAnalyzed individual team collaboration behaviors across
the org and relative to broader engineering benchmark
LearningsOverall collaboration volume is high compared to
internal engineering benchmarks
After-hours collaboration is 3x higher than the
benchmark
Manager email and meeting practices generate
significant workload across the org
Business factors, like product release cycles, have little
impact on overall collaboration volumes
OutcomesLT modeling behaviors – scheduled focus hours,
reduced after hours, curtail large meetings
Organization-wide initiative targets travel and
collaboration norms, in-region hiring, org-wide training
Progress monitored as part of LT business rhythmCR
EA
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AC
ITY
The leader of a high-performing group of 600+ engineers needed to identify and address collaboration
behaviors driving employee survey weakness in work-life flexibility
ApproachAnalyzed meeting data (e.g., length, time, size, etc.) to
develop view of calendar fragmentation
Created algorithm that selects meeting times based on
fragmentation impact on attendees
LearningsMeetings confirmed to be major cause of fragmented
schedules; lead to feelings of ‘lack of control’
Human preferences, like time of day, are significant
factors in optimizing schedules
OutcomesLarge opportunities uncovered for improved
collaboration and more focused coding time
New visibility encouraged new norms to ‘bunch’
meetings for more effective time use
CR
EA
TE C
AP
AC
ITY
Engineers in a large Office 365 team began showing signs of stress and dissatisfaction due to meetings that
randomized their days. This fragmentation forced them to constantly switch contexts and slowed down
projects. Managers needed a way to encourage focus time while keeping lines of communication open.
Meeting fragmentation (3000-person Office 365 organization)
Meetings defragmented (3000-person Office 365 organization)
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Building Stronger Managers
• Employees with 2x the average of their peers are 67% less likely to be disengaged
4x higher than those with regularly scheduled 1:1sLeadership viewed 2x more unfavorably
Microsoft Corporation: Proprietary and Confidential Information
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Engaged new employees receive
twice as much training in their first
12 weeks as disengaged new
employees.
Disengaged employees are sucked
in too quickly without an
opportunity to learn: their work
week spans match that of tenured
employees within the first 2 weeks
of employment. They also exhibit
significantly higher meeting hours
and lower focus hours.
0 1 2 3 4 5 6 7 8 9 10 11
Week of Employment
Cumulative New Employee
Training HoursEngaged
Not Engaged
Not…
Engaged
0 1 2 3 4 5 6 7 8 9 10 11
Week of Employment
New Employee
Average Work Week Span
Engaged
Not Engaged
Not Engaged
Engaged
Difference
+ 220%
Difference
-20%
Improving Onboarding and Training Experience
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