3. Brief History of Civilization
Agriculture era
Labor intensive
Local
Challenges: Mass production & distribution
Industrial era
Mechanization, Mass production
Globalization, Manufacturing driven economy
Challenges: Product Design, innovation
Knowledge era
Extreme Globalization, Anytime-Anywhere (e.g. Internet)
Knowledge driven Industries, Economies
Challenges: Thinking, Collective-wisdom
“Everything in this world is done twice – once in the Mind and then in the
outside world” – Stephen Covey
Challenge in knowledge era is the first part – accuracy & speed of thinking,
collective thinking
4. Legacy of Industrial Era
Current Management, Leadership, Quality Management philosophies in Software
industry (e.g. CMM, Six Sigma, PMI) are influenced by the Industrial Era experiences
Improper application of mass production principles to design/creation principles
Knowledge Era products need a different approach on Quality, Management, Engineering
– Human centric & Knowledge centric
Industrial Era Product/Business20% 80%
Knowledge Era Product/Business20%80%
Design/Creation
Intensive
Mass-production &
Distribution Intensive
Management, Leadership, Quality Management, …
CMMI, Six Sigma, PMI, …
5. What is the raw material for software?
It’s Knowledge/ Idea
Where does the transformation from raw material to finished product
happen?
It’s in the Minds of people
Computer is only a tool to capture & facilitate the thoughts
How do we know then, how the transformation is happening?
Break the transformation into smaller steps
Bring visibility (e.g. pictures, documents, models, prototypes…)
What is the measuring equipment to verify whether transformation is
happening correctly or not? (the calipers?)
Another knowledge body (e.g. peers, customers, experts…)
Collective wisdom (Peer Reviews, Brainstorming…)
Knowledge Era Product Engineering
From raw material to finished product, the object is not physical in nature. There
are no Laws of Physics governing the engineering principles, like in Mechanical
or Civil engineering
The Paradigm Shift in Knowledge Era
6. Knowledge Era vs Industrial Era Production Systems
Characteristics Industrial Era Knowledge Era
Raw Material
Transformation
Engines
Productivity
Interaction
The equation
Input OutputInput Output
Intangible in nature: knowledge, Idea…Physical in nature
Machines: Stereotype,
Repetitive
‘Touch time’ of Tools
People: Idiosyncratic, changing
‘Touch time’ of Minds
People work around the
machines
People work with people (including
Customers) – High collaboration,
communication
Man-Machine-Material Capable People-Collaborating-with
Common Protocols
8. What is ‘Process’?
Think of a phrase or sentence to describe ‘Process’.
Typical responses:
Set of steps to perform to get output from input
Sequence of operations to be performed
Standard way of doing things
Repeatable tasks to be performed
Clearly documented instructions to do a job
…..
9. Game with Mathematics
1 1 1 = 6
2 2 2 = 6
3 3 3 = 6
4 4 4 = 6
5 5 5 = 6
6 6 6 = 6
7 7 7 = 6
8 8 8 = 6
9 9 9 = 6
Is this possible?
What Operations do you perform
to get this Consistent output?
10. Repeatable Process ??
(1 + 1 + 1)! = 6
2 + 2 + 2 = 6
3 x 3 - 3 = 6
√4 + √ 4 + √ 4 = 6
5 + 5 / 5 = 6
6 + 6 - 6 = 6
-7 / 7 + 7 = 6
√ 8 + √ 8 + √ 8 = 6
√ 9 x √ 9 - √ 9 = 6
f (x) = y
If ‘y’ needs to be consistent
while ‘x’ is varying,
can f() be constant?
333
11. Repeatable Process or Consistent Outcome?
ProcessInput Output
In Knowledge Era scenario like Software, Input has high variability –
people, technology, project contexts…
In order to maintain Output consistent, Process should change
Contextual
Process
Variable
Input
Consistent
Outcome
‘Repeatable Process leads to Consistent Outcome’ is an Industrial Era
paradigm
Because Input is fairly homogeneous
Focus should be on Contextual Process (not Repeatable Process) and
Consistent Outcome
13. How to ‘Manage’ when Variability & Diversity are
high?
Productivity/Efficiency?
Quality?
Consistency/Repeatability?
…
Can we define ‘Rules’ and ‘Dos & Don’ts‘ for all possible cases?
Values & Principles are the way
Agile practices driven by principles & values
‘Simple Rules, Rich Relationships’
Contextual Team-Process
Innovation thrives in diversity
14. Defect Prevention context
Most Defects relate to
Materials & Machines
Number of Causes are
relatively less
E.g. Poor Soldering
Defect Fix is mostly physical in
nature
E.g. Tune Temperature,
Voltage…
Once fixed the machines stay
tuned
Industrial Era
Most Defects relate to Human
Errors
Number of Causes are relatively
large
E.g. Poor Coding
Defect Fix is mostly not physical
in nature
E.g. Thinking, Communication,…
Person’s characteristics
continuously change
Knowledge Era
One of the most important ways of Defect Prevention in Knowledge Era is taking
people through Experience/Learning:
– Learn & Adapt cycles in Agile; Short iterations; Retrospective
16. Mind Switch Game
Round 1
Keep a timer for 30 seconds
Keep adding number 3 successively for 30 sec
Keep a timer for 30 seconds
Keep adding number 4 successively for 30 sec
Note down the total count of numbers
Round 2
Keep a timer for 60 seconds
Keep adding numbers 3 & 4 alternatively in two tables for 60 sec
Note down the total count of numbers
Observe count dropping by about 50% in round 2
16
17. Most important factor for Productivity, Efficiency, Quality…
Touch-time
of MindImpacted
Clarity, Vision
Emotions
Motivation
Positive
Energy
Workplace
distractions
Mind Capacity
Interactions
with people
Whoisresponsible?
Onus on
Individual
Onus on
Others
Family
Social
Managers
Peers
Subordinates
Customers
Partners
Onus on
Organization
Workplace Design
Organization Design
Org Policies
Self-Managed
Individual
Self-Managed
Team
-Time boxing
- Focus
- Scrum Master:
Prevent interference
Remove obstacles
18. Some Facts about Software Projects
Studies have shown that :
Almost 80% of Software Defects are human errors – oversight,
communication gap, lack of collaboration, distractions etc.
Knowledge Workers’ Productivity varies as much as 25 times
based on their state of Mind
18
20. Management/Quality is more Intrinsic in
Knowledge Era
A Construction industry analogy
L&T Constructions have different supervisory ratios
One Supervisor for every 25 civil construction laborers
One supervisor for every 10 mechanical worker
One supervisor for every 5 electrician
Moral of the story: Higher the skilled labor, higher the supervision
needed !
For Software Engineering ?
So, by deduction, one supervisor for one engineer !!!
In other words, PRACTICALLY, each Software Engineer needs to
be self-supervised
Self managed individuals , Self managed teams
22. What Moves the Iceberg?
Wind
Current
20% Visible part
80% Invisible part
23. What makes Projects successful?
Hard
aspects
Soft
aspects
20% Visible part
80% Invisible part
Effort
Schedule
Cost
Defects
……….
……….
Shared vision
Motivation
Team engagement
Customer engagement
Communication
Collaboration
Lagging Indicators
Effect
Leading Indicators
Cause
24. Measurement Considerations
Because of idiosyncratic human beings as the transformation engines and dealing
with intangibles like knowledge, idea…etc., measurement is a challenge
What we CAN measure are perhaps not very significant
E.g.: Defect Removal Efficiency, Effort/Schedule variance, … - Mostly Lagging Indicators
Those which are significant, are not so visible/measurable
People experience, Motivation, Collaboration, level of engagement of people (‘touch time’ of
mind)
Sensing & Sense-making is more important than hard measurements
‘If you can't measure, you can't manage’ is an Industrial Era paradigm
Focus on Visual Management in Agile
Wind
Current
What moves the Iceberg?
25. Fundamentals of Software Production
In Software production we are dealing with
Human beings as the transformation engines and
Knowledge as the raw material
‘Touch time of minds’ is the key imperative for higher
productivity and quality
Capable people Collaborating with Common protocol
(process) are the critical success factors
Agile/Scrum practices harness these fundamentals
effectively
26. Knowledge Era Paradigms
26
Why? What? How?
If you understand ‘why’, you
can figure out ‘what’ & ‘how’
easily in all situations