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How to make data actionable?
Lessons from the teams on how to turn numbers
into stories, ownership, and great drivers of change
PEOPLE ANALYTICS CONFERENCE
2/06/2023
Anita Zbieg, PhD
Co-founder & CEO Network Perspective
anita@networkperspective.io
www.networkperspective.io
Where does my experience
come from?
up to 85%
of employees’ time
is consumed on meetings,
emails, and chats[1]
what if your teams
could spend this time smarter?
insights & benchmarks
data actions
workweek collaboration
www.networkperspective.io
Co-pilot app for teams to work smarter
How to make data actionable?
actionable able to be acted on,
having practical value
data distributed & personalised
telling the story
I understand & care about
providing me with feedback
not judging me
motivating me to act
Data
company with 1k employees
generates each month
~160k works hours
~4 mln interactions
~0.8 GB of meta-data
20K
already processing data
from companies employing
~20K people
1B
big data & AI driven:
~30M work hours, ~300M events,
~600M connections yearly
Data! yes! big!
strong ethics upfront!
-> meta-data only (no content)
-> individual data hashing
-> reports on a team level
(min. 5 people)
Bottleneck Centrality ChannelsActiveBig ChannelsActiveSmall ChannelsSubscrdBig
ChannelsSubscdSma
ll
ChatsDuration ChatsInterruptions
ChatsQueue ChatsQueueIn ChatsQueueOut
CollaborationCrosTe
m
CollaborationExterna
l
CollaborationIntraTe
a
CollaborationTime CooperationPaths
DailyMeetingDuratio
n
DailyMeetingFreque DailyMeetingSiz DirectorRoles DiversityOfConnectio EmailsAfterHours EmailsQueue FocusedWorkDuratio
DeepWorkStreakCo
DeepWorkStreakLen
g
GroupInternalMeetin
g
IcRoles IndividualWork Internal Meeting Occ
InternalMeetingDura
ti
InternalMeetingFreq
u
InternalMeetingMem InternalMeeting InternaMeetingSize LiftingInteractions GuidanceDailyChats GuidanceDailyEmails GuidanceDailyMeetin
GuidanceDailyOveral
l
GuidanceMonthlyCh
a
GuidanceMonthlyEm
GuidanceMonthlyMe
e
GuidanceMonthlyOv
e
GuidanceWeeklyCha
t
GuidanceWeeklyEma
i
GuidanceWeeklyMee
t
GuidanceWeeklyOve
r
ManagerRoles ManagerSupport MeetAttendees_2 MeetAttendees_3_4 MeetAttendees_5_8 MeetAttendees_9_18
MeetAttendees_over
_18
MeetDuration_1h_2h
MeetDuration_2h_4h
MeetDuration_30m_1
h
MeetDuration_bel_30 MeetDuration_ov_4h MeetiAfterHours MeetConflicting MeetsLongAndLarge MeetiMultitasking
MessSentAfterHours ModeOCollaboration ModeOfDeepWork ModeOfMultipleCont
MultipleContextWor
k
NetworkSize NewbieRoles
1on1eMonthlyDuratio
n
Metrics! yes! so many!
Metrics! yes! personalised!
this is your team
this is your team
this will help you
work smarter
Stories
this is your team
this will help you
work smarter
this is your team
this will help you
work smarter
this is your team
this will help you
work smarter
this is your team
this will help you
work smarter
this is your team
this will help you
work smarter
this is your team
this will help you
work smarter
we do understand
we do care
this will help us
Drivers for change
You are here
This is work smart
reference & min/max in
your company
This is work smart
reference & min/max in
your company
Data is not enough
You need actions to be actionable
But the real magic happens
when blending data with actions
28
action data
29
action data
magic
The impact can be real & quick
Team experiencing too many meetings, high context switching,
and no time for deep work (to solve complex problems & innovate)
After 3 months
-> 8 hours more for deep work weekly
-> 4 hours less spent in meetings weekly
The team experiencing the work done rather as disconnected
parts from what is done by other teams
After 3 months
-> cross-team collaboration from 6 to 11 teams monthly
You can make
the data actionable!
we’re still learning
how to get there
Anita Zbieg, PhD
Co-founder & CEO Network Perspective
Linkedin
anita@networkperspective.io
www.networkperspective.io
get in touch with me ---->>>

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Anita Zbieg: How to make data actionable? Lessons from the teams on how to turn numbers into stories, ownership and great drivers of change

  • 1. How to make data actionable? Lessons from the teams on how to turn numbers into stories, ownership, and great drivers of change PEOPLE ANALYTICS CONFERENCE 2/06/2023 Anita Zbieg, PhD Co-founder & CEO Network Perspective anita@networkperspective.io www.networkperspective.io
  • 2. Where does my experience come from?
  • 3. up to 85% of employees’ time is consumed on meetings, emails, and chats[1] what if your teams could spend this time smarter?
  • 4. insights & benchmarks data actions workweek collaboration www.networkperspective.io Co-pilot app for teams to work smarter
  • 5. How to make data actionable? actionable able to be acted on, having practical value data distributed & personalised telling the story I understand & care about providing me with feedback not judging me motivating me to act
  • 7. company with 1k employees generates each month ~160k works hours ~4 mln interactions ~0.8 GB of meta-data 20K already processing data from companies employing ~20K people 1B big data & AI driven: ~30M work hours, ~300M events, ~600M connections yearly Data! yes! big! strong ethics upfront! -> meta-data only (no content) -> individual data hashing -> reports on a team level (min. 5 people)
  • 8. Bottleneck Centrality ChannelsActiveBig ChannelsActiveSmall ChannelsSubscrdBig ChannelsSubscdSma ll ChatsDuration ChatsInterruptions ChatsQueue ChatsQueueIn ChatsQueueOut CollaborationCrosTe m CollaborationExterna l CollaborationIntraTe a CollaborationTime CooperationPaths DailyMeetingDuratio n DailyMeetingFreque DailyMeetingSiz DirectorRoles DiversityOfConnectio EmailsAfterHours EmailsQueue FocusedWorkDuratio DeepWorkStreakCo DeepWorkStreakLen g GroupInternalMeetin g IcRoles IndividualWork Internal Meeting Occ InternalMeetingDura ti InternalMeetingFreq u InternalMeetingMem InternalMeeting InternaMeetingSize LiftingInteractions GuidanceDailyChats GuidanceDailyEmails GuidanceDailyMeetin GuidanceDailyOveral l GuidanceMonthlyCh a GuidanceMonthlyEm GuidanceMonthlyMe e GuidanceMonthlyOv e GuidanceWeeklyCha t GuidanceWeeklyEma i GuidanceWeeklyMee t GuidanceWeeklyOve r ManagerRoles ManagerSupport MeetAttendees_2 MeetAttendees_3_4 MeetAttendees_5_8 MeetAttendees_9_18 MeetAttendees_over _18 MeetDuration_1h_2h MeetDuration_2h_4h MeetDuration_30m_1 h MeetDuration_bel_30 MeetDuration_ov_4h MeetiAfterHours MeetConflicting MeetsLongAndLarge MeetiMultitasking MessSentAfterHours ModeOCollaboration ModeOfDeepWork ModeOfMultipleCont MultipleContextWor k NetworkSize NewbieRoles 1on1eMonthlyDuratio n Metrics! yes! so many!
  • 10. this is your team this will help you work smarter
  • 12. this is your team this will help you work smarter
  • 13. this is your team this will help you work smarter
  • 14. this is your team this will help you work smarter
  • 15. this is your team this will help you work smarter
  • 16. this is your team this will help you work smarter
  • 17. this is your team this will help you work smarter we do understand we do care this will help us
  • 19.
  • 20.
  • 22. This is work smart reference & min/max in your company
  • 23. This is work smart reference & min/max in your company
  • 24. Data is not enough
  • 25.
  • 26. You need actions to be actionable
  • 27. But the real magic happens when blending data with actions
  • 30. magic
  • 31. The impact can be real & quick Team experiencing too many meetings, high context switching, and no time for deep work (to solve complex problems & innovate) After 3 months -> 8 hours more for deep work weekly -> 4 hours less spent in meetings weekly The team experiencing the work done rather as disconnected parts from what is done by other teams After 3 months -> cross-team collaboration from 6 to 11 teams monthly
  • 32. You can make the data actionable! we’re still learning how to get there
  • 33. Anita Zbieg, PhD Co-founder & CEO Network Perspective Linkedin anita@networkperspective.io www.networkperspective.io get in touch with me ---->>>

Editor's Notes

  1. Work habits are described as metrics built from collaboration data from calendar, chats & emails and show the experience in a team during a week of work
  2. Work habits are described as metrics built from collaboration data from calendar, chats & emails and show the experience in a team during a week of work
  3. Metrics have Work Smart reference points
  4. Metrics have Work Smart reference points
  5. Metrics have Work Smart reference points
  6. Metrics have Work Smart reference points