Kanban Presentation from the BCS Kanban Day in March 2013

2. Let’s Challenge Preconceptions
• “Estimates inform us when things will finish”
• Kanban uses difficult maths
• You can’t limit WIP in big organisations
• Validated learning doesn’t deliver anything
© 2013 ripplerock Dan Brown @KanbanDan

3. • How good an estimate would you have in
30 seconds? 30 minutes?
5 minutes? 2 weeks?

5. Everything that doesn’t have a cross on it is a whole galaxy
“Your friends can’t help you now?”

6. Let’s Substitute Predictability for Estimation
• This presentation contains Maths.
• I will be asking you some questions.
• But …
• I have an example to make it as painless as possible...
© 2013 ripplerock Dan Brown @KanbanDan

7. Let’s go to the Drive-Thru
• What is a Drive-Thru
• Typically found in fast food
• You stay in your car
• You drive around the building
• You:
– Order your food
– Pay for your food
– Collect your food
• All through your car window
• After you collect you drive
away with your food
© 2013 ripplerock Dan Brown @KanbanDan

8. Drive-thu example
• Let me define my terms to be clear
• Lead Time - the time from a particular
customer driving up, to driving away with
a burger
• Throughput Rate - how frequently customers
drive away with food
• Original Drive-Thru only had 1 window
• So if it takes 90s to get served with 1 window:
– Avg Lt is 90 seconds
– Avg Tr is 1 customer per 90 seconds

9. Fast Forward in time…
• Some people worked out it could be improved
• 2 Window system
– order & pay at first window (45s),
– collect at second window(45s)
• How does that affect our measurements?
– Avg Tr is now 1 every 45s, Avg Lt is now 90s
© 2013 ripplerock Dan Brown @KanbanDan

10. Pop Quiz
• What happens with 3 ‘windows’?
• 30 seconds to order
• 30 seconds to pay
• 30 seconds to collect
• What is Lead Time?
• 90s
• What is Throughput rate?
• 1 every 30s
© 2013 ripplerock Dan Brown @KanbanDan

11. But who cares?
• Your customers care!
• Throughput Rate:
– How frequently new Features come “off the
line”
• Lead Time:
– “when will this Feature be done if we started
now”
• Allows us to predict when whole Product will
be done
© 2013 ripplerock Dan Brown @KanbanDan

12. Dan, when will the product be done?
• If you deliver 1 work item every 2 days
• Your Tr = 0.5 items per day (units must match)
• If your Lt is 11 days …
• If you have 100 work items to finish
• Your total Product Time = 11 + ( 100 / 0.5 )
• Pt = 211 days
• Product Time for a new project is:
– Lt + ( Number of Features / Tr )
• But take note of variance to the averages of Lt & Tr to give
tollerances!
© 2013 ripplerock Dan Brown @KanbanDan

13. But Dan, how can I use maths to help me?
• You can use Little’s Law (for stable systems) to
link Tr, Lr and WIP in a simple equation… but
• We don’t have time for that right now.
• You could always come talk to me afterwards…
• Or attend an LKU Accredited Kanban Course -
‘Real Kanban’ for example 
www.ripple-rock.com/training/real-kanban.aspx
© 2013 ripplerock Dan Brown @KanbanDan

14. Back to the drive-thru
• 2 windows are open, but
• Window 2 actually takes 50s
• Window 1 takes only 40s
• What is the Tr?
• WIP is 2, Tr = 1 per 50s,
• so Lt = 2 * 50s = 100s ( thanks to Little’s Law)
• Why is this not 90s?
© 2013 ripplerock Dan Brown @KanbanDan

15. But in the real world…
• …we get a queue between windows of 3 cars
(limited by space)
• WIP isn’t 2 then, it’s really the 2 at windows
plus the 3 queuing, so what is the WIP now?
• 5!
© 2013 ripplerock Dan Brown @KanbanDan

16. So what difference does that make?
• With WIP of 5
• Tr is still = 1 per 50s
• Lt = Tr * WIP
• What’s the new Lt?
• 250s!
• Increasing the WIP without reducing the
Tr increases the Lt!
• Maths done
© 2013 ripplerock Dan Brown @KanbanDan

17. Oh, and by the way

18. How do you make a footprint on the moon?
• You finish “One small step” at a time!
• NASA says:
“Do one thing at a time,
with supreme excellence.”
• A colleague once told me:
“As soon as our clients work out that all
they have to do is ‘put everything into
an ordered list, then finish them one at
a time’ we’ll be out of a job”
• We keep saying it, but we’re still in jobs…
© 2013 ripplerock Dan Brown @KanbanDan

19. NASA – Limited WIP in Action
• Do One Thing At A Time
• We’ve seen the maths and we can measure
why it works
• In the 1950s and 1960s
NASA were living it
• And they still are…
© 2013 ripplerock Dan Brown @KanbanDan

20. What is their “one thing” now
• Who supplies the International Space Station?
© 2013 ripplerock Dan Brown @KanbanDan

21. So what are NASA doing?
© 2013 ripplerock Dan Brown @KanbanDan

22. All of NASA?
• They have a separate division called the JPL
• They do the space
telescopes – like Hubble
• Now they are doing
James Webb SST
© 2013 ripplerock Dan Brown @KanbanDan

23. …With Supreme Excellence
• Not just about showing off…
• Focus on QUALITY!
• Post launch bugs mean something different to
NASA
• Remember the fuss about Hubble’s focus?
• James Webb will be out of reach of humans
© 2013 ripplerock Dan Brown @KanbanDan

24. What about us?
• Isn’t everything Safe to Fail?
• Yes and No.
• Yes before launch, No after launch.
• There are situations where the blue screen of
death isn’t just a phrase…
• But even when it’s not, fixing
bugs in production is the most
expensive place
© 2013 ripplerock Dan Brown @KanbanDan

25. If you love it, let it go…
• One of the key Kanban lessons:
• If you focus on Throughput,
quality drops, but then what?
• Bugs, Technical debt, slow throughput
25
Throughput Tech Debt Bugs
20
15
10
5
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
-5
(Faked exaggerated data – to illustrate the point)
© 2013 ripplerock Dan Brown @KanbanDan

26. With a quality focus…
• Focus on Quality what happens?
• Bug counts & Tech debt drop
• What happens to throughput?
25
Throughput Tech Debt Bugs
20
15
10
5
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
(Faked exaggerated data – to illustrate the point)
© 2013 ripplerock Dan Brown @KanbanDan

27. How did we get there
• By finishing ‘one small step’ at a time
• NASA started manned space flight with
Mercury
• Gemini was about learning how to go to the
moon
– 2 weeks in space for the first time
– Docking spacecraft
• Then came Apollo
© 2013 ripplerock Dan Brown @KanbanDan

28. Apollo 1 landed on the moon – right?
• Not quite
• Apollo 8 – round the moon
• Apollo 9 – test out the LEM
• Apollo 10 – drop the LEM
within 9 miles of the moon
• Apollo 11 –
– one small step…
© 2013 ripplerock Dan Brown @KanbanDan

29. Incremental steps
• They did it by doing it.
• The POC was real
launches with real
Validated Learning
• Each step moved NASA
forward and enabled the
next step
• The Moonshot started
with Wernher Von Braun
and the V2!
© 2013 ripplerock Dan Brown @KanbanDan

30. What can we learn?
• If NASA can limit WIP, so can we all
• Even the biggest of big bangs can be delivered
incrementally
• Validated Learning leads to success
• Tackle Risk by using
Collaborative Experimentation
© 2013 ripplerock Dan Brown @KanbanDan

31. My Challenge
• “Estimates inform us when things will finish”
– Only when things aren’t complex…
– Predictability based on real metrics is much better
• Kanban uses difficult maths
– Simple maths gets you most of the value
• You can’t limit WIP in big organisations
– If NASA can – so can we
– What is really stopping us?
• Validated learning doesn’t deliver anything
– It gets us through to where we need to be
© 2013 ripplerock Dan Brown @KanbanDan

32. Any Questions?
© 2013 ripplerock Dan Brown @KanbanDan