economic frameworks
TRANSCRIPT
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i290 lean/agile product management unit 2: economic frameworks
@jezhumble https://lapm.continuousdelivery.com/
This work © 2015-16 Jez Humble Licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
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grasp the principles of cost of delay
understand the principles of decision theory
calculate the value of information
make product decisions in an economic framework
know how to apply optionality
learning outcomes
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“you may ignore economics, but economics won’t ignore you”
— Don Reinertsen
“The measure of execution in product development is our ability to constantly align our plans to whatever is, at the moment, the best economic choice.”
— Don Reinertsen
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decision theory
The analysis of complex decisions with significant uncertainty can be confusing because 1) the consequence that will result from selecting any specified decision alternative cannot be predicted with certainty, 2) there are often a large number of different factors that must be taken into account when making the decision, 3) it may be useful to consider the possibility of reducing the uncertainty in the decision by collecting additional information, and 4) a decision maker's attitude toward risk taking can impact the relative desirability of different alternatives.
Craig W Kirkwood, Decision Tree Primer, p1
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risk matrix
probability (0-1)
impa
ct ($
)
low probabilitylow impact
high probabilitylow impact
low probabilityhigh impact
high probabilityhigh impact
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decision tree
temperature sensor:
• development cost: $100k, revenue $1m
• probability of success: 0.5
pressure sensor:
• development cost: $10k, revenue $400k
• probability of success: 0.8
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decision trees
Craig W Kirkwood, Decision Tree Primer, p4
EV=$400,000
EV=$310,000
EV=$0
EV=$400,000
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exercise
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value of information
• information reduces uncertainty about decisions that have economic consequences
• information affects the behavior of others, which has economic consequences
• information sometimes has its own market value
Douglas Hubbard, How to Measure Anything (3rd edn), p145
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measurement
A quantitively expressed reduction of uncertainty based on one or more observations
Douglas Hubbard, How to Measure Anything (3rd ed.), p31
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perfect information
Value of information = EV after - EV before = $100k
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value of information
Expected Opportunity Loss (EOL) = chance of being wrong x cost of being wrong
Expected Value of Info (EVI) = Reduction in EOL; EVI = EOLbefore info — EOLafter info
Expected Value of Perfect Info (EVPI) = EOLbefore info (since EOLafter info is zero if info is perfect)
Douglas Hubbard, How to Measure Anything (3rd ed.), ch. 7
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build-measure-learn
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not normally binary decisions — a continuum
humans are risk averse when the stakes are high
use utility functions; reduce stakes
don’t capture time dependence
use calculus monte carlo analysis
problems with decision trees
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opportunity cost
In microeconomic theory, the opportunity cost of a choice is the value of the best alternative foregone, where a choice needs to be made between several mutually exclusive alternatives given limited resources. Assuming the best choice is made, it is the "cost" incurred by not enjoying the benefit that would be had by taking the second best choice available.
Wikipedia
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time is money
t = m
Δt = Δm
Δt ( ) = Δm
cost of delay
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cost of delay
Task A: upgrade package to support credit card encryption
CoD: fine of $50,000 per day we’re not in compliance.
Duration: 2 weeks
Task B: Complete a feature for a key customer
CoD: we’ll close $100,000 per week with this feature
Duration: 1 week
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cost of delayTask A: 2 weeks, CoD $250k / weekTask B: 1 week, CoD $100k / week
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urgency profiles
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exercise
Should I wait for the feature?
We have completed sufficient features for 85% of our target customers.
We can:
• Take 2 more months to finish last 15%
• Launch what we have, add last 15% in next release, 6 months from now
Cost of delay for project: $200,000 / month
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exercise
Delay 85% of functionality by 2 months:
$200,000 x 0.85 x 2 = $340,000
Delay 15% of functionality by 6 months:
$200,000 x 0.15 x 6 = $180,000
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technology adoption lifecycle
Geoffrey Moore, Crossing the Chasm
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three horizons
Baghai, M., Coley, S. and White, D., The Alchemy of Growth
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Intuit horizons and metrics
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optionality
Nassim Taleb, Antifragile