The document discusses effective strategies for collaborating with virtual and remote teams, emphasizing the importance of measuring performance metrics. It compares various methodologies like Agile and Waterfall, highlighting their strengths and weaknesses. Additionally, it stresses the need for innovative data analysis to enhance team performance and decision-making processes.

1. Overcoming Virtual Challenges
How to work successfully with virtual and
remote teams
with Jennifer Bonine Rick Faulise
#Fake_Data

3. #Fake_Data:
Using Data and Results
to Drive Decisions

4. Session
Logistics:
• Speaker introductions
• Q&A at the end
• Call us if you need anything:
• jbonine@tapqa.com
• 612-877-1464

6. I need your help…..
GOAL : Understand your key learning or take-away
from this session
TASK: Write down on the post it in the chat window
with what you want to learn and leave with today

7. Rick Faulise
Speakers:
Jennifer Bonine

8. Speed Metrics Capture
• “What are you measuring?”

9. Business Benefit….
Better connected teams perform better

10. Data analysis is nothing new.
We’ve just never looked at all of it.

12. Alexander the Great

13. Iphone ~ 5 years
PC ~ 3 years
Car ~ 5 years
Lightbulb ~ 1 year
The only thing in common was time:

14. How many people are running agile?
How many people
believe agile is a good fit
for your organization?
How many people did a
analysis of your
organization goals and
choose agile?

15. Agile can work in every situation
So can every other methodology.

16. Preconceived
Notions Will
Limit Your
Decisions

17. Strengths Weakness
Agile Fast, People over process Difficult estimating, Easily taken off
track
Waterfall Simple understanding, Easy to manage Difficult to go back, no product until
completion
RAD Quick intervals, Increased reusability High team dependency, Requires
modularized app
Spiral Decreased risk, High documentation Costly, Requires specific expertise
Iterative Define solution before building, Moves
“Step by Step”
No overlap
Prototype End user involvement, Working model Scope creep, Constant repairs
Incremental Quick working model, High flexibility Lacks planning phase, needs entire
system documentation

19. How many of you are looking
to or have implement
DevOps?
DevOps only
solves two things:
• Speed
• Scalability

20. 80%Would be successful with:

21. We need to start looking at
data differently

22. Stranger =
Danger

23. Designed for
trust

24. You have to trust your data

25. Best and
Brightest
Latest and
greatest =

26. Are we herd
animals?

28. “Never trust a single data point” - Me
For both Technology and Personnel

29. Google is a highly innovative company
*From web.archive.org – Feb 21st 1999

30. Two companies at the top of technology yet
using extremely different approaches.
Innovation versus Experiences:

31. Emotional vs Informed
Decisions:

32. People are data
too

33. Where are the data points with people?
- Data in Hiring
- Data in Evaluating
- Predictive Behavior

34. Finding the right people:
- Choose the right skills to search for
- Interviewing tactics

35. # of anything = not good

36. Evaluating your
team
Velocity
Average story
points per story

37. Opposing
Data

38. Opposing
Data

39. Opposing
Data

40. Predictive Behavior!
- Judges Sentencing
- Neilson boxes
- Gracenote

41. Team vs Individual data
- How to gather
the data
- What are the
data points
- How to manage

42. Indicators vs
Actuals:

43. Visualize your data and monitor

44. What Data Helps tell your story?
- Velocity?
- Throughput?
- Escaped Bugs?
- Defect Removal Efficiency?
- New Bugs vs. Closed Bugs?
- Bug Burn Down?
- Defect Density?
- Code Churn?
- Story Churn?
- Code Coverage?

45. What sources will be need
to track project health and
what data will executives
want to see?
Group Exercise:

46. Thank you for attending!
Questions?

47. © XBOSoft, Inc. 2017 All Rights Reserved