cmmi explored - hm’s fourteen: essential beliefs for effective high maturity implementation

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© Rajesh Naik, 2013 Released under Creative Commons Attribution 3.0 Unported License

CMMI® - Explored

HM’s Fourteen:

Essential Beliefs for Effective High Maturity Implementation

1

2 © Rajesh Naik, 2013 Released under Creative Commons Attribution 3.0 Unported License AlignMentor

® CMMI and CMM are registered trademarks of Carnegie Mellon University

© Rajesh Naik, 2013 This work is licensed under a Creative Commons Attribution 3.0 Unported License. This means you are free (1) to copy, distribute, display, and perform the work, (2) to make derivative works, and (3) to make commercial use of the work so long as you give proper attribution to the author and retain the license notice. If you create derivative works using this work, they should also be made available under a similar license. For further information go to http://creativecommons.org/licenses/by/3.0/

For uses outside the scope of the license, contact Rajesh Naik at [email protected]


This presentation covers fourteen essential beliefs

that need to be internalized to implement CMMI®

high-maturity practices effectively

Contents of this Presentation



This presentation covers fourteen essential beliefs

that need to be internalized to implement CMMI®

high-maturity practices effectively

The material in this presentation is derived from the

following documents: – CMMI® for Services, Version 1.3 (CMU/SEI-2010-TR-034)

– CMMI ® for Development, Version 1.3 (CMU/SEI-2010-TR-033)

The viewer should refer to the above documents, for

the definitive requirements of High Maturity in CMMI®

Contents of this Presentation



The Fourteen essential beliefs are 1. Nothing is definite 2. Everything is interrelated 3. Nothing is permanent 4. Nobody likes variation 5. Statistics is non-intuitive 6. There are no bell-curves in real life 7. Outliers cannot be wished away 8. Skills impacts process performance 9. Statisticians should not be decision makers 10. Process performance cannot be decreed 11. Correlation is not the same as cause-effect 12. Process instability must be analyzed in real-time 13. Control of critical sub-processes impacts higher level performance 14. Simulation may be the only practical method to model reality today

HM’s Fourteen


The Fourteen essential beliefs are 1. Nothing is definite 2. Everything is interrelated 3. Nothing is permanent 4. Nobody likes variation 5. Statistics is non-intuitive 6. There are no bell-curves in real life 7. Outliers cannot be wished away 8. Skills impacts process performance 9. Statisticians should not be decision makers 10. Process performance cannot be decreed 11. Correlation is not the same as cause-effect 12. Process instability must be analyzed in real-time 13. Control of critical sub-processes impacts higher level performance 14. Simulation may be the only practical method to model reality today

HM’s Fourteen

We cover each of

these beliefs in detail

now…


We often like to think of outcomes as definite,

single numbers

1. Nothing is definite

21



single numbers

– But that is low maturity thinking, and does not reflect reality


21



single numbers


In reality, all activities have an inherent

variation and what we can predict is only a

probability


21



single numbers




probability

In HM thinking, estimates or target dates are

values that have a certain chance

(probability) of being achieved


21

21 +/-



single numbers




probability

In HM thinking, estimates or target dates are

values that have a certain chance

(probability) of being achieved

– Only when we attach probabilities to targets/ goals, can we start looking at ways to increase those probabilities


21

21 +/-


Another simplistic assumption (low-

maturity thinking) is that each goal/

objective of a project/ service is

independent of other goals

2. Everything is interrelated

Cost

Timeliness

Quality

Other

Goals


Another simplistic assumption (low-

maturity thinking) is that each goal/

objective of a project/ service is

independent of other goals

This gives rise to naïve decisions - E.g.,

we think that by adding more resources

we can bring forward the deadline,

expecting the cost and quality to remain

the same


Cost

Timeliness

Quality

Other

Goals


Another simplistic assumption (low-maturity thinking) is that each goal/ objective of a project/ service is independent of other goals

This gives rise to naïve decisions - E.g., we think that by adding more resources we can bring forward the deadline, expecting the cost and quality to remain the same

In real situations, everything is interrelated, and HM is about understanding these relationships and taking more informed decisions


Cost

Timeliness

Quality

Other

Goals

Cost

Timeliness

Quality

Other

Goals


Since change is constant, past performance

cannot be blindly used for predicting the

future

3. Nothing is permanent




future

– Past performance can only be taken as one of the inputs for future performance





future


This needs to be combined with expected

change in performance due to evolving

technology, familiarity, skills, and risks





future





While forecasting the future, we also need to

predict the impacts of our potential actions, to

take informed decisions





future





While forecasting the future, we also need to

predict the impacts of our potential actions, to

take informed decisions

(All this in a probabilistic, interrelated way )



Human beings (and institutions run by

human beings) like consistency, and

dislike surprises/ variations

4. Nobody likes variation





– Think of what happens when the summer is hotter or cooler than what has been in the past

– Why do people visit fast food chains? – not for the great taste or nutritional value; but just for the consistency of experience








Our customers, employees, and vendors

also expect minimal variations from us



Human beings (and institutions run by human beings) like consistency, and dislike surprises/ variations



Our customers, employees, and vendors also expect minimal variations from us

So, a key HM principle is to identify and reduce variation, wherever it is unacceptable



Let us do a quick exercise

5. Statistics is non-intuitive



If you throw a dice, what are the possible outcomes?

– An integer between 1 and 6 (both included), with a probability of 1/6 for each result






If you throw the dice twice, and add the two results, what

are the possible outcomes?


+







Without adequate time, most people come up with the

wrong answer

The right answer is

– An integer between 2 and 12 (both included), with different probabilities for each result – see chart on the left


+

0

0.05

0.1

0.15

0.2

1 2 3 4 5 6 7 8 9 101112







Without adequate time, most people come up with the

wrong answer

The right answer is

– An integer between 2 and 12 (both included), with different probabilities for each result – see chart on the left

When we combine distributions, our gut-feel falters

So, we need to start using stats to understand and predict

performance (and keep our guts aside )


+

0

0.05

0.1

0.15

0.2

1 2 3 4 5 6 7 8 9 101112


We (including statisticians) would like to fit the

world into neat, symmetrical bell-curves

6. There are no bell-curves in real life




But human activity does not typically result in neat

bell curves






bell curves

E.g., the air travel from Bangalore to Delhi takes

typically 2:40 hrs. On a real good day it can take

2:20 hrs. On bad days, it can take 3:00 hrs, or 3:30

hrs (or till they run out of fuel!). So, there is no

symmetry around the typical time






bell curves






In other words – “There is a limit to how well you can do; but no limit to how badly you can screw up ”






bell curves






In other words – “There is a limit to how well you can do; but no limit to how badly you can screw up ”

HM organizations will not blindly assume smooth,

neat distributions for their plans and estimates



If I prepare a chart of the flight time taken

for all my trips from Bangalore to Delhi over

the past 10 years, the chart is odd;

there are times the plane diverted to Jaipur

till the fog/ dust/ smog cleared

7. Outliers cannot be wished away

Fog diversions







I cannot ignore these events just because

they make it difficult to handle the math/

stats

– Unless, climate-change eliminates fog in Delhi altogether


Fog diversions







I cannot ignore these events just because

they make it difficult to handle the math/

stats

– Unless, climate-change eliminates fog in Delhi altogether

So, in HM thinking, outliers are a part of the

process (with low probability), unless the

root-cause is eliminated


Fog diversions


Competence makes a significant difference to

performance (speed, quality, throughput)

8. Skills impacts process performance




That is why managers fight to get the right

people in the their teams

– “Processes make us people independent” (who said that?) - is misunderstood and misused





That is why managers fight to get the right

people in the their teams

– “Processes make us people independent” (who said that?) - is misunderstood and misused

In HM organizations, estimates, plans, and

forecasts consider the skills of the people

doing the work

– Process performance baselines also factor the skill levels



Often, decision makers get over-whelmed

(and terrified) by analytics and abdicate

decision making to statisticians

9. Statisticians should not be decision makers





Statisticians can analyze data and prove or

disprove some hypothesis, but the decision

making still rests with the managers and

executives






Statisticians can analyze data and prove or

disprove some hypothesis, but the decision

making still rests with the managers and

executives

In HM organizations, managers/ executives

make effort to understand enough stats/

analytics to remain on top of decision making



Processes do not perform differently just because executive

management “decrees” a certain performance

10. Process performance cannot be decreed




In low maturity organizations, the distinction between

performance baseline (actual performance) and performance

target (desired performance) is not clear – and desired

performance is used for estimation and planning





In low maturity organizations, the distinction between

performance baseline (actual performance) and performance

target (desired performance) is not clear – and desired

performance is used for estimation and planning

In true HM organizations, baselines are not dictated by

management, but derived from past performance. And

management sets process performance targets (for driving

process changes)



11. Correlation is not the same as cause-effect

• Here is an example:

– One may be able to find a good correlation between the number of people carrying umbrellas/ raincoats to work in the morning, and whether it rained during the day

– But that does not mean that carrying umbrellas and raincoats causes rainfall






• Correlations can be established statistically,

but cause-effect is based on logical thinking

and requires domain knowledge (which is why

statisticians cannot be the decision makers )






• Correlations can be established statistically,

but cause-effect is based on logical thinking

and requires domain knowledge (which is why

statisticians cannot be the decision makers )

• HM thinking requires us to separate

correlation from cause-effect


12. Process instability must be analyzed in real-time

• Identifying process instability and doing root-

cause analysis must be as close to the event as

possible





possible

• If the root-cause analysis is done too far from the

event (more like a post-mortem), there is lesser

likelihood of identifying the true root cause





possible




– E.g., If you find out today that the time to reach office (from home) was out-of-control 6 weeks ago, you may not be able to recall the conditions that caused this





possible




– E.g., If you find out today that the time to reach office (from home) was out-of-control 6 weeks ago, you may not be able to recall the conditions that caused this

• HM organizations create the infrastructure, tools,

and processes to collect, analyze and report data

on a real-time basis to effectively debug their

process instability


13. Control of critical sub-processes impacts higher level performance

• If you want your weight in control, measuring and

monitoring your weight frequently (and putting it on a

control chart) is not going to bring your weight under

control






control

• To control weight, you may need to monitor and measure:

– The amount and type of exercise that you do

– The amount and type of calories that you eat

You may even have to measure the calories consumed and expended at various times during the day






control





• Similarly, (in a project) measuring schedule variance

alone is not likely to bring the schedule under control






control





• Similarly, (in a project) measuring schedule variance

alone is not likely to bring the schedule under control

• HM organizations identify and control sub-processes that

are critical to overall performance


14. Simulation may be the only practical method to model reality today

• Given that:

– There are multiple, interrelated goals to achieve



• Given that:


– Inputs and processes have their own variations (probabilities)



• Given that:



– Most of these variations do not fit neat symmetrical bell curves



• Given that:




– We need to predict the potential impact of our choices on the outcomes (multiple objectives)



• Given that:





• Simple, deterministic mathematical equations

alone do not suffice to reflect reality



• Given that:





• Simple, deterministic mathematical equations

alone do not suffice to reflect reality

• In HM organizations, random number based

computer simulations (e.g., Monte Carlo)

provide the best platform to model reality
















(Recalling…) HM’s Fourteen


Related Presentations

– CMMI® Explored – Concept of Maturity

– CMMI® - SVC Explored – Process Area Overview

http://www.slideshare.net/AlignMentor/cmmi-maturityconcept




http://www.slideshare.net/AlignMentor/cmmi-svcpaoverview









© Rajesh Naik, 2013 This work is licensed under a Creative Commons Attribution 3.0 Unported License. This means you are free (1) to copy, distribute, display, and perform the work, (2) to make derivative works, and (3) to make commercial use of the work so long as you give proper attribution to the author and retain the license notice. If you create derivative works using this work, they should also be made available under a similar license. For further information go to http://creativecommons.org/licenses/by/3.0/

For uses outside the scope of the license, contact Rajesh Naik at [email protected]


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