Product management and dual track agile

1. PRODUCT
MANAGEMENT
Dual-track Agile

3. Overview
Useful and
usable

6. Opportunity
track
Discovery and Validation

7. Opportunity Discovery
May take weeks.
Focus on the observable behavior / stories (as opposed
to imaging a specific solution, which is just an image in
our head): e.g. it is tedious to write an SMS vs imaging a
fancy phone or chat application
Break away from proposed solutions and wishes.
Efficiency: what is missing? → the answer is the
opportunity.

8. Techniques / What to look for?
Describe situations and observe.
What was the last time when you were trying to do that?
Ask for details.
Gather information, and leave interpretation for later, and go for data. Leave
time to do the interpretation after the data is gathered.
Describe the process, describe what people are doing, and take notes. How
did you feel about it?

9. The solution
Don’t think about it (yet)!
Interview questions → Confirmation bias
Note it down, put it into a bracket, and take it away & postpone it.

10. Opportunity Validation
Reduces the risk seriously; this is the most significant step in risk reduction.
90% of ideas don’t work → validation allows us to fail early.
About the promise of a solution.
Failure as a result of skipped validation:
https://en.wikipedia.org/wiki/Pontiac_Aztek

11. Preparing for the Validation --- Process
1. Analysis: mindmap of opportunities and groups; abstract & specific opportunities; groups &
subgroups.
2. Make a list of limitations (e.g. the shop is local), the relationship of the business to its environment.
3. For each limitation: 0-7 score → the likeliness to change it
a. Backdraw
b. Benefit
4. Order the opportunities / user groups from the most likely to be interested to the least likely
(postits).
5. Collect the group of people for the most important opportunity and how could it be validated (e.g.
fake door tests), i.e. test / prove that the give group will be willing to use / buy it. Persona is

12. Measure of interest
Commitment / effort: the only true measure of interest. If the customer is willing
to make some commitment / effort -> s/he is interested. So: ask for commitment /
effort early on.
Commitment / effort can be: prospective customer’s time, money or reputation
(contacts, posting your post, sharing your site on FB, liking your page, giving his
data e.g. email address to sign up etc.)

13. Rule of “fuck yeah” or no:
in only fuck yeah case go ahead after the
validation.

14. Solution track
Discovery and Analysis

15. Solution Discovery
Persona to represent the target audience.
Write a story about them, how the solution/product would solve their problems.
Design studio:
Goal: get the best of our common ideas.
Lead engineer, UX, PM sits together and do rapid iterations.
Foster the atmosphere of cooperation.
Avoid being jealous.

16. Rapid Design Process
1. Draw a storyboard (the story of the user).
2. Iterate until converge (e.g. 3 iterations).
3. Parallel draw / update (with what they liked in
the previous iteration) wireframes (5 min).
4. Describe the wireframes (1-1 min).
Important: No discussion, no judgement, no debate,
no opinions

17. Cardboard Prototype
Iron out of small issues by A/B testing.
What would you do? → just observe
Iterate on the go and update the prototype if necessary (and take notes about
the learnings).
Disproved stamp on the failed design, and put it on the wall.

18. Prototypes and Fidelity & Data richness
Any combination is
possible, what makes
sense in experimentation
Alternatives to data
richness (e.g. in the
context of physical
products): personalization,
smartness, flexibility
POC
MVP
Cardboard
Clickable
wireframe
Data richness
Fidelity

19. Charter customer group
Useful in B2B
http://svpg.com/charter-customer-programs/

20. User journey and the funnel
User journeyTouchpoints
See an Ad Landing Trying Registering First ... Retained
...
StoriesEmotional
Experience
#Users
!
!

21. Framing
Who we are
What are we doing and Why?
There are no bad answers.
Simple
Exploring
Safe
Interview

22. Experiment
Hypothesis / Assumptions
Setup
Target group
Metric
Threshold / Evaluation criteria
[Expected output]
Reflect on the experiment itself!
Improve the process (of improving

23. Recommended literature