Jeremy Doyle People Analytics Digital transformation and the future of work
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Jeremy Doyle
People Analytics
Digital transformation and the future of work
What does it take to win in your
business?
vs.
A Regular Day
Generating Data
62
%
38
%
12
%
88
%
21
%
79
%
29
%
71
%
Speaking Time
Interactivity
88%
38%
79%
71%
Individual Behaviour
30◦
9 AM 10 AM 11 AM 12 PM 1 PM 2 PM
Pitch and Volume
We all generate reams of data traces. By tracking social behaviors over time one can identify communication problem areas and solutions as well as demonstrate how behavioral patterns drive success.
Team 1 Employee
Team 2 Employee
How it Works
What is People Analytics?
The basic concepts of people analytics are:
• View the organization from a holistic perspective with People at the center
• Individual and team behavior correlate to organizational KPI’s
• Data on these behaviors can be objective and quantifiable
• Capturing this often unstructured data will provide new visibility for decision making
“You can’t manage what you don’t measure” – Peter Drucker
$50x
$10x
$1x
Human Capital
(Salaries, wage, benefits)
Workplace Investment
(Real estate, IT, services)
ROI
(Revenue, earnings, growth)
People Analytics provides data to understand the organization like
never before, and to make optimal investments for performance
Sensing Technology
1997 2014
Social Sensing
• Ability to link key behaviors with specific KPIs
• Enables employees to drive change through understanding of behavioral profiles and self set goals and benchmarks
• Enables senior leaders to unlock the behavioral differences in high performing teams
• Enables direct line managers to spot delivery risks based on communication gaps early
• Enables continuous improvement in all aspects of business
The Technology Social Sensing & Analytics
Sociometer
Participants
Registration Data
Insights
Email/Chat Data
KPI Data
Dashboards
Analytics Data
Algorithms
Study Results
Targeted Improvements
A/B Test Everything
Privacy Policy
• Individual information must be kept confidential
• Only users should have access to their individual data
• Others can only see aggregated data
• Conversations are not recorded
• Only features such as tone of voice and volume level are
collected
• No content is captured
• Only patterns of communication
• Opt-In required
Quantifying Collaboration
Cohesion - How tightly knit is the group?
• Productivity
• Engagement
• Trust
Centrality – How freely does information flow?
• Autonomy
• Bottlenecks
• Influence
Exploration – Cross-functional collisions
• Adaptability
• Innovation
• Openness
F2F vs Digital – Volume across mediums
• Workload
• Job Satisfaction
• Retention
What do we need to know?
Past success
linked to informal
relationships?
Generational
expertise
(to be transferred)
Informal
leadership
Organizational
Gaps
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0 0.01 0.02 0.03 0.04 0.05 0.06 0.07
Information Vitality Analysis Dependence on a few influential individuals to share knowledge? Formal leaders are significantly more influential than most staff, but they are not alone
The highlighted individuals are integral to the business, however their extreme centrality may represent
process inefficiency or risks to knowledge retention
Are other team members building influence and expertise to fill gaps?
Centrality (Influence)
Exp
lora
tion
(Inn
ovat
ion)
Integration Initiatives
Can we increase INTEGRATION to drive productivity?
YES
0.7
0.8
3.1
-4.1
-5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0
Time Change (hours/week)
F2F
Phone/Lync
Physical Activity
Fewer long
meetings
Workload
grows with new
connections
Impacts of Change on Culture
wyze
Drill into your data to find what
behaviors you’re doing well…
…and what needs some work
Track your improvement over
time
Online travel company: Amenities and office layout Software firm: Work process and employee integration
10%
30%
0%
5%
10%
15%
20%
25%
30%
Productivity Job Satisfaction
Att
rib
ute
Im
pro
ve
me
nt
Network Size
• F2F network size • Drives productivity (software code) • Supports job satisfaction post layoff process
• F2F network size driven by lunch habits • Lunch space redesign aimed to increase network size
• Interaction frequency improves completion of interdependent code by 32%
• Remote teams communicated 8% less about dependencies which added cost of over $150 million/year
Collocated
Remote
Time and expense
Interaction Frequency
$150MM cost
-32% time
Highest Performing Lowest Performing Typical
• Extremely cohesive group
• Promoted group achievement
goals over individual rewards
• Three new employees (circled) were
not socially integrated with cohesive
core - even after over one month they
only spoke with their direct manager
Floor 1 Floor 2
• F2F network clearly shows two groups
• The physical layout of the branch
inhibited information sharing
• Future locations all one floor
Retail Banking: Layout and employee integration
• Performance driven by cohesion • Physical distance impedes knowledge sharing
• New employee integration is essential
Case Examples
Case Examples
0%
5%
10%
15%
20%
Sales
Redesign Impact on Sales
0%
2%
4%
6%
8%
10%
Cohesion Productivity Engagement
F2F Cohesion Drives Engagement
• F2F interactions driven by coffee machine location • Redesign aimed to increase F2F time and decrease email volume
0%
2%
4%
6%
8%
10%
12%
Exploration Sales
F2F Effects on Performance
Pharmaceutical Sales & Marketing
German Bank
• Identify processes responsible for human capital bottlenecks • Reveal informal processes driving performance
IT Firm / Engineering Processes
• Identified informal experts; extreme centrality may be barrier
• Informal experts had average completion rate
• Compensation system discouraged expertise sharing
Related Documents
