Welcome to the data-driven world.
39% of executives say their companies are already highly data-driven, but mentioning data can often result in concerned faces. Why is this? Is it the toxic nature that 'metrics' have become synonymous with or is it because we view using data as a dangerous flirtation with placing more value in tools and processes?
This session will showcase how you can bring to life the scientific method in your coaching arsenal. I will share stories of data-based coaching in PwC and how we leverage it to have open, transparent conversations and more informed decision making.
4. Which of the
following best
describes decision-
making in your
organisation?
8%Rarely data-driven
Somewhat data-driven
Highly data-driven
53%
39%
PwC's Global Data and Analytics Survey: Big Decisions TM. Base: 2,106 senior executives
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5. “When a measure becomes a target, it
ceases to be a good measure”
- Charles Goodhart
16. We’ve had a 14% drop
in felony rate over the
last 4 weeks
17. Ah yes, now I am happy.
You won’t mind if I
check your numbers will
you?
18.
19.
20.
21.
22. The tyranny of metrics
● Penalizing hospitals based on the percentage of patients who fail to survive for thirty days beyond surgery
Patients sometimes kept alive for thirty-one days, so that their mortality is not reflected in the hospitals metrics
● The National Health Service (NHS) decided that wait times were too long for patients to enter emergency wards,
moving to evaluating hospitals based on what extent patients were admitted within four hours
Some hospitals responded by keeping incoming patients in queues of ambulances outside the hospital doors,
until staff were confident that the patient could be seen within the allotted four hours of being admitted
● No Child Left Behind (NCLB) legislation measured students grades 3-8 each year in math, reading and
science. Aiming to bring all students to academic proficiency whilst penalising and sanctioning schools
where students did not progress
Teachers diverted class time to teaching the subjects tested, neglecting other subjects as well as
reclassifying weaker students as disabled (thus removing them from the assessment pool), altering
results, reducing test difficulty or lowering the grades needed to pass them
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36. Data-based coaching uses
data visualisation as a basis
for safe conversations and
open questions, as well as
facilitating more informed,
transparent decision making
whilst staying true to our Agile
roots...
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37. Coaching in a data-driven world
Descriptive
reporting
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39. Data-based retrospectives
Let’s take
anything above 10
days - what
happened?
-Better BDD
needed
- Work as a
team when it’s
not working
- Too long for PO
feedback (20 days!)
- Better DoR check
needed as was not met
PO
Feedback
Data not
available
(improve DoR)
Rework due to
tech debt
- Better DoR check
needed
- Flowed quickly once
sat with the SME
Delayed due to
lack of clarity
on deployment
Data not
available
(improve DoR)
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40. Data-based retrospectives
What practices
could these relate
to?
-Better BDD
needed
- Work as a
team when it’s
not working
- Too long for PO
feedback (20 days!)
- Better DoR check
needed as was not met
PO
Feedback
Data not
available
(improve DoR)
Rework due to
tech debt
- Better DoR check
needed
- Flowed quickly once
sat with the SME
Delayed due to
lack of clarity
on deployment
Data not
available
(improve DoR)
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42. Coaching in a data-driven world
Descriptive
reporting
Questions
What happened?
What is happening?
Visuals
Diagnostic
discover & explore
- WIP Items per Week
- Scatter Plot
- Net flow per week
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46. Coaching in a data-driven world
Descriptive
reporting
Questions
Where is the problem?
Why is it happening?
What are the trends?
What happened?
What is happening?
Visuals
Diagnostic
discover & explore
Predictive
forecast
- WIP Items per Week
- Scatter Plot
- Net flow per week
- Estimate Correlation
- Stuck Work
- Cumulative Flow (CFD)
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47. Landing Zone
What is likely
to happen?
What
options are
there?
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49. Coaching in a data-driven world
Descriptive
reporting
Questions
Where is the problem?
Why is it happening?
What are the trends?
What happened?
What is happening?
Visuals
Diagnostic
discover & explore
Predictive
forecast
Prescriptive
anticipative
- WIP Items per Week
- Scatter Plot
- Net flow per week
- Estimate Correlation
- Stuck Work
- Cumulative Flow (CFD)
- PDS
- Landing Zone (Burn-up)
- Throughput Forecaster
What is likely to
happen?
What options are
there?
52. Coaching in a data-driven world
Descriptive
reporting
Questions
Where is the problem?
Why is it happening?
What are the trends?
What happened?
What is happening?
Visuals
What should I do?
What is the next best
action?
Diagnostic
discover & explore
Predictive
forecast
Prescriptive
anticipative
- WIP Items per Week
- Scatter Plot
- Net flow per week
- Estimate Correlation
- Stuck Work
- Cumulative Flow (CFD)
- Stale Work
- WIP by Person
- Aged WIP
- PDS
- Landing Zone (Burn-up)
- Throughput Forecaster
What is likely to
happen?
What options are
there?
@nbrown02 #LKCE18
53. Further reading
● Making Work Visible - tiny.cc/workvisible
● Focused Objective - bit.ly/SimResources
● Actionable Agile Metrics for Predictability - tiny.cc/danvac
● The Tyranny of Metrics - tiny.cc/tyranny
● Goodhart, Charles (1981). "Problems of Monetary Management: The U.K. Experience"
● PwC's Global Data and Analytics Survey 2016
@nbrown02 #LKCE18