Tuesday, October 17, 2017

A world without a 0?


Can you imagine project management without the help and usefulness of the number 0?
Indeed, could we do modern project management without 0?

On the other hand, the Romans, and the Greeks and Egyptians before them, did pretty well in project management, and they had no 0; they didn't even have the concept of a number 0.

Recall your Roman numerals: 10 = X; 20 = XX; 50 = L, and so forth. No need for a zero in any of that!

Good grief! the pyramids, the Greek Parthenon, the highways and aqua ducts of ancient times, all managed without a 0! Boggles the mind to think of it.

On the other hand, engineering and project problems could be solved in the ancient world.
They had Euclidean methods that were quite effective.(*)

And before there was 0?
And so what preceded the zero? Apparently some civilizations understood "void" or "null", but the Greeks thought the concept challenging to the teachings of Aristotle, and so they passed on developing 0.  These are "place holder zeros" and they predate the numerical zero by several millennia

At last, a 0
Yea! for India. Apparently, India is in the lead to be credited with the invention of 0.
A National Geographic essay on this very subject sheds some light:
Researchers at the University of Oxford's Bodleian Library recently conducted carbon dating on an ancient Indian text known as the Bakshali manuscript.

They found that some pages in the manuscript date to the third or fourth century, five hundred years older than previously thought. That pushes back the origin of what would eventually become the zero symbol, 0, we use today.

The manuscript shows a series of Sanskrit numerals. In it, zero is represented by a small dot.

Some doubt
Ooops! There are some doubters about the Indian origin of 0. ZerOrigIndia, or Project Zero, in the Netherlands, partners with researchers in Mumbai to pinpoint the origin of zero.

Nonetheless, I think we can all agree with this statement:

" .... zero was crucial to the zero-to-nine decimal system upon which algebra developed in 9th century Persia and was essential for physics principles documented by scientist Blaise Pascal in the 17th century."

_____________________________
(*) The Greek mathematician Euclid put down his theories (**) of a system of proofs which came to be known as geometry. His books of "Elements", circa 300 BCE, actually went as far as showing how to solve equations (early algebra) and define irrational numbers, all with geometry. So, no need for 0, though there was a centuries-long fuss over "what is a 'point', and how is it measured?"

(**) There were many earlier mathematicians that contributed to a body of knowledge that gave Euclid a foundation to work from



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Saturday, October 14, 2017

Large scale strangers


Anything on a large scale requires strangers to work together effectively. No strangers? Probably not really a large scale.

And so how does this work? I've always said: strangers don't trust each other. Why? There's no common basis for trust -- "I believe in you; you believe in me." is missing

Nonetheless, here we are with complex projects -- some on a global scale -- with all manner of strangers cooperating effectively. We don't necessarily trust each other so what is the trust mechanism?
  • Trust in money for one thing. We can exchange products and services with complex and large scale projects because we trust the value of those efforts when "monetized".(*) Which, if you've never really thought about it, is trust in the full faith and credit of governments to protect the value of money -- monetary policy is you will. Right now, that's pretty much the dollar, pound sterling, euro, yen, and the yuan -- the world's reserve currencies
  • Trust in the portability, perpetual storage, convertibility in and out of transactions, and no requirement to be physical give money its prominence in society(**). No matter how long you keep it, or where, it never wears out or spoils.
  • Trust in the rule of law insofar as it applies to terms and conditions for employment, contracting, purchasing, accounting, etc. In other words, trust in the value of anti-corruption
  • Trust in the general acceptance of a global morality -- stealing and assault are illegal everywhere
  • Trust in certain standards, like time for one thing, Newtonian physics if you're working in the not-quantum world, and Euclidean geometry if Einstein's relativity is not bothersome to  you. One second is one second everywhere (atomic clock arguments set aside -- we're not talking space station stuff here)
Now, here's another one, perhaps off the center stripe, so I offer it separately:
  • The power of bureaucracy (yuk!). No, it's true. Bureaucracy is what makes it possible to organize large number of strangers effectively; pass instructions around; receive and integrate product into a product baseline. We would never have advanced from the 18th century cottage industries without effective bureaucracies to put thousands of strangers together
  • The ability to translate or transliterate languages, both written and spoken. Though there are curiosities: Chinese has never spread beyond China even after being around for thousands of years; English is a global language after only a few centuries
  • And, of course, the separator between humans and animals is imagination; language facilities imagination among strangers.
_________________________________
(*) What about barter you ask -- or what about favors? Small ball stuff. Barter and favors don't scale.
(**) Only about 10% of the money in the world is physical  
Some of the ideas in this posting are derived from "Sapiens" by Harari, and "Empires of the Word" by Ostler


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Saturday, October 7, 2017

Confucius simplified


Some of you read my recent posting on data quality and integrity, the discussion of which is anchored by a statement attributed to Confucius

Fair enough

But, the "publish" button was hardly pushed when this rolls in from herdingcats. I call it Confucius simplified:

If you make [a] serious allegation or claim and don't have serious evidence, no one is going to take you seriously




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Wednesday, October 4, 2017

Information quality; information integrity


In the early 21st century when the 4th edition to the PMBOK was being designed for publication in the first decade, there was debate about adding "data quality" to Chapter 11, Risk Management. The idea behind data quality being to evaluate risk in the presence of not only uncertainty, but also to look at the impact of making risk-informed decisions in the presence of lousy data.

I'm extending "data" to "information" for this discussion. The working difference being that information is multiple data elements integrated, and that data integrated data set integrated with context.

And, also think of information in the large sense. With all that, I offer this bit of insight from Confucius:
“If names are not correct then statements do not accord with facts.

And when statements and facts do not accord, then business cannot be properly executed.
When business is not properly executed, order and harmony do not flourish.
When order and harmony do not flourish, then justice becomes arbitrary.
And when justice becomes arbitrary, people do not know how to move hand or foot.

Hence whatever a wise man states he can always define, and what he so defines he can always carry into practice; for the wise man will on no account have anything remiss in his definitions.’
Confucius, Lúnyŭ† (Analects), xiii:3 (Chinese, early fifth century BC)2”

Empires of the Word.”(*)
 Nicholas Ostler 

My favorite
So, Confucius might have been a good member of the Chapter 11 team, but for his age. I think he said it all about data quality, data integrity, and indeed business integrity in the largest sense of the word when he said:

"And when statements and facts do not accord, then business cannot be properly executed."
_______________________

(*) If you love language or history, then "Empires of the Word" is a good read on the history of language


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Sunday, October 1, 2017

Interrogating or discussing?


".... interrogations, like battles, are never won but only lost"
John LeCarre
And so, you might ask, the lesson for project managers is what exactly?

My definition first: Interrogations, in the PM space, are just an adversarial or autocratic way to have a discussion. Someone in authority uses that authority to dominate, intending, of course, to "win"

And so, the lesson is: domineers don't win much, even when they're sure they've won it all. They often lose some aspect of .... respect, esteem, moral authority, mystique, and personal power as they "get up close and personal" as a means to overpower their "discussion partner".

After all, the closer at hand the more the weaknesses and blemishs appear. Afar is more mystical; mystique is what often sustains power and adds interest. But, you can't interrogate from afar, so be prepared to give at the office if interrogation is your thing.




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Thursday, September 28, 2017

Bring me a solution


I've always been an advocate of "bring solutions when you bring problems". In other words, no whining.

Some argue the opposite: Bringing a solution is like bringing an advocate that has something to lose if the solution is not adopted ... prestige, face, standing, etc.
Perhaps fostering or initiating an opportunity to discuss the problem before a solution gets locked in is better

Well, yes, perhaps.
And, I'm sure there are situations that need/require brainstorming and an open source approach.
But, not every solution is so elusive or difficult.

In most cases: come with a solution (or a solution candidate), but be open and insensitive (on a personal level) to an alternative.

We're all big people here! (Or, here's your opportunity to be the adult!)



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Sunday, September 24, 2017

Inspiration


Does your work inspire you?
  • Super if so
  • Frustrating if not

Kristi Hedges tells us in an hbr.org essay that psychologists T. Thrash and A. Elliot have posited three contributors to an inspired work life:
  1. We see new possibilities
  2. We're receptive to outside influences
  3. We've a feeling of energy and motivation
Not working for you? Hedges goes on (I paraphrase her ideas):
  • Inaction is your enemy; get up and get moving (my paraphrase)
  • Keep on learning; if you think you've arrived at the pinnacle of knowledge for your job (career), you're mistaken. Not learning new stuff is actually going backward; you're knowledge will atrophy
  • Expand your network; new people brings new ideas
  • Keep it simple; narrow the scope or choices so you can focus and set priorities
The one that works best for me is the "keep on learning".  Writing this blog is an example; you might be amazed at the background reading and research that goes into it, from which I get many ideas for my professional role.
 


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Thursday, September 21, 2017

Precision without accuracy


I've often said the game of American football is a game of precision informed by inaccuracy.
From sometimes 25 yards away, in the split of a second, among the tangle of potentially 20+ actors all scrambling, a referee makes a judgment (hypothesis) about where the tip of an oblong ball happened to be when the action stopped.
Then, a steel chain is laid down to measure off the distance from the tip to the end of the chain (facts). The latter is precise; the former is often wildly a guess, but nonetheless is transformed instantly into "fact"
And, you may ask, what has this to do with project management, or management at all?
It's all about two schools of thought about managing with uncertainty -- managing what we know about risk (or, what we don't know, which is trickier even)
  1. School of objectivity: facts come from what we observe; estimates are derived from experience and projected onto to knowable future circumstances.
    Risk is a matter of estimating impact (see: experience) and then applying a probability derived from the facts about how often such has occurred before.
    This is the "frequency-based" view of assessing risk
  2. School of subjectivity: Nothing wrong with observable facts, to be sure. But in the school of subjectivity, it's what you believe to be the case that carries the day. The set of beliefs, however, is not set in stone; in fact, to be a good subjectivist, you have to be willing to update your beliefs in the context of new facts (observations)
Not that the objectivist would ignore new facts; they wouldn't.
But, the subjectivist begins where an objectivist never would: with a guess (gasp! ... a guess! shocking!)

  • But, a guess about what? Not "facts", of course, but rather a guess (conjecture) about a hypothesis of the circumstances that might lead to facts (observables).
  • Or, if there are observables, then a guess about the circumstances (hypothesis) that led to those observables.
  • Either way, if the hypothesis is discoverable, or verifiable, then new facts are predictable.
And, so that sets up a set of conditional relationships:
  1. Hypothesis, and 
  2. Hypothesis (conjectured or validated) given some observables
  3. Facts, and 
  4. Facts (or new facts) given that a hypothesis is actually valid
These four make up the eco-system of the subjectivist. There is constant working about of a "a priori" hypothesis; facts, and do they fit the "a priori"; and either a modified hypothesis, or if its valid, then predicted new facts.

If you are one that wrestles with the four above, then you are not only a subjectivist, you are a Bayesian, and you reason according to Bayes theorem

And, you may not have known that you were either a Bayesian or a subjectivist!




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Monday, September 18, 2017

"I wouldn't do that"



"Doubt is unpleasant, but certainty is absurd"
Voltaire

Interested in quantitative risk management, understanding risk metrics, and risk management?
This one may be for you:
Matthew Squair is working on a new book, entitled "I wouldn't do that". He's made a draft of Chapter 1 available, at least for a short time.
Why another book on risk management? The shelves are already full (even if only virtually full). Squair addresses the question. He writes:
" ..... in the face of the uncertainties posed by complex systems and new technologies, can we also achieve an acceptable level of safety. Answering this question both philosophically and practically is the purpose of this book"
Squair's focus as a consultant is risk-safety .... connecting those dots. But, he really writes in a larger context. Thus, if you're the least interested in managing with uncertainty, and self-educating with a very readable explanation of quantitative risk considerations, look through the Chapter 1 sample.

Here's the opening statement:
A nuclear reactor’s defences are overwhelmed by a tsunami, an aircraft manufacturer’s newest aircraft is brought low by design faults while another aircraft’s crew is overwhelmed by a cascading series of failures.

Why do these things happen?

Can we predict such events and protect ourselves from them, or are we destined to suffer like disasters again and again?
Do you actually care? You do! But, maybe not all that much

Squair posits that for there to be risk, there has to be value first. That is, if there is really nothing at stake then there really is not a risk to be considered. It's an interesting idea, really: start thinking first of value, or the value of an outcome, and then posit the risk proposition to that value.

Squair, again:
" ... there is an exposure to a proposition about which we care and about which uncertainty exists. If there is complete certainty then risk does not exist. For risk to be meaningful it also implies that we must value a specific outcome of the proposition."




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Friday, September 15, 2017

Silence is concurrence


"Churchill always interpreted a lack of objections, whether by admirals or by cabinet members or by the British public, as the equivalent of wholehearted support. He read dissenters’ inability to state a contrary conviction as a lack of conviction itself.
From "Gandhi and Churchill" by Arthur Herman
Another way to say this, more concise I think is: "Silence is concurrence!".
  • If you object, speak up. 
  • If you concur, verbalize support. 
  • Or, sustain. 
To wit: lead, follow, or get out of the way!



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Tuesday, September 12, 2017

Rules for A.I.


Developing A.I. stuff?
Many are
What about the rules of behavior for A.I. capabilities?

Oren Etzioni has an opinion on this
  • The A.I. system must be subject to the full gamut of laws that apply to its human operators and developer
  • The A.I. system must clearly disclose that it is not human (*)
  • The A.I. system can not retain or disclose confidential information without explicit approval from the source of that information
 Etzioni points out that in 1942, at the dawing of the age of science fiction about robots, Isaac Asimov proposed three rules also:
  • A robot can not harm a human being, or cause a human being to be harmed
  • A robot must obey the orders of a human being, except when in conflict with the first rule
  • A robot must protect its own existence, provided no conflict with the first two laws
So, now we have a book of six rules, but somehow they don't address the moral issue of whose life is the higher priority, whether it's an autonomous car avoiding an accident or a A.I. system engaged in life support, like in a medical operating room.

More to come. Elon Musk reportedly says that A.I. represents "an existential threat to humanity". But, isn't it too late to not press on and try to get it right?

_______________________________
(*) Several instances have arisen from the innocent to the not so innocent where the general public did not know whether a system was human or artificial.



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Saturday, September 9, 2017

Organization by coercion


"It is impossible to organize an army solely by coercion. At least some of the commanders and soldiers must believe in something ...."
From the book "Sapiens" by Harari
Fair enough

Now, consider that wisdom rewritten in project team terms:
It is impossible to organize a team, and expect productive outcomes, solely by top-down direction. At lease some of the team leaders and team members must believe in the team's mission and the leader's vision
 And, I submit, to be believed begins with being believable. A play on words, to be sure, but somewhere between the banal and "pie in the sky" an innovative vision and reasonable path forward must be evident:
  • In pictures for the visualists
  • In words for the readers
  • In person for those that are attracted by charisma to a cause
If there's to be sacrifice, then an appeal to and wrapping in a higher calling--'duty, honor, country' in the military--not just money, will be in the mix. I think we all know that money speaks, but only so loudly. After a certain volume, it's "the other stuff" that makes up the culture and value system that motivates.


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Wednesday, September 6, 2017

Psychology of uncertainty


"We study natural stupidity rather than artificial intelligence"
Amos Tversky
Tversky--now deceased--was a partner with Daniel Kahneman, who together wrote some of the most influential papers on the processes of decision making under uncertainty.(*)

If you're a project manager or business manager, then you have that task routinely. If you've not read at least the seminal work "Judgment Under Uncertainty: Heuristics and Biases" you're really not informed. [Science, New Series, Vol. 185, No. 4157. (Sep. 27, 1974)]

 My suggestion: Get informed.

You've really no excuse for putting it off.
 ____________________________________
(*)Kahneman won a Nobel for their work; Tversky was deceased at the time of the award which only goes to living recipients. Kahneman is the author of "Thinking Slow and Fast", a book derived from their work.




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Sunday, September 3, 2017

Myths and mystics


In the awesome book "Sapiens", author Yuval Harari posits three revolutions for mankind, the first of which is the "cognitive revolution" which he dates from about 70,000 years ago.

What's really important about the advent of cognition is that h.sapiens developed the ability to imagine the non-existent -- that is, the stuff that has no physical reality. Harari more or less calls all that stuff "myths".

Myths require:
  • Someone to imagine them; and 
  • Someone to sell them to the uninformed; and 
  • The uninformed have to become believers and users and maintainers
In project parlance, myths require:
  • A visionary
  • A sales and marketing strategy
  • Managers, practitioners, and users
 A marketing guy I worked with many years ago, long before Harari wrote his book, instructed me in the art of myth-making, the value of being mystic, and the value of encapsulation so that others couldn't see the sausage being made.

My marketing mentor asserted that myth was a force multiplier, adding power and influence. I agree. Just look around at the 'trapping' that attend power--some call it the arrogance of power .... all intended to multiply that power.

Not arrogant? Not powerful.

But in the competitive project space, myths attend competitors -- are they really 10 feet tall, and should we go up against them, or not?

There is a larger consequence, however, that I found fascinating in Harari's telling of the cognitive revolution:
  • Cognition of non-real things, like organization and social structure, behavior norms, and beliefs -- even if not realizable, enabled large scale socialization among strangers and mechanisms of command and control that extends far beyond any personal relationship.
  • Harari asserts that one person can have personal effective interaction with up to 150 people. Up to that limit, organizations can be totally flat, informal, almost structureless. To get beyond the 150 limit, you need myths and mythology that enable the unreal.
  • With myths, you can have world-wide religious beliefs, large corporations, continental governments, etc. 
  • Thus, societies, and to a lesser extent, projects can scale almost limitlessly44
What a concept! Myths -- you've got to love it!
 


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Thursday, August 31, 2017

Visual language


Need to tell a story?
  • Proposal
  • Message
  • ESL audience
Then this Khan Academy series on visual language is a place to start.
There's power in framing, stretching, shaping .... not to mention color, contrast, shading.



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Monday, August 28, 2017

Creative constraints


Most of us are familiar with the Theory of Constraints as postulated by Eliyahu Goldratt in his famous book: "The Goal".  In ToC, constraints are not good; they're the bad guy

Now, comes along a TED talk that sets up the opposite proposition: Constraints are 'somewhat' the good guy because they frame the issue, estabish a target, and get us beyond "writer's block".

Take a look:
"The power of creative constraints"




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Thursday, August 24, 2017

Analyze, optimize, etc


According to Tom Friedman, author of "The World is Flat, "we’re in the middle of a change in the “climate” of technology."

And .... We’re moving into a world where machines and software can  
  • analyze (see patterns that were always hidden before);  
  • optimize (tell a plane which altitude to fly each mile to get the best fuel efficiency); 
  • prophesize (tell you when your elevator will break and fix it before it does);  
  • customize (tailor any product or service for you alone) and  
  • digitize and automate just about any job.
This is transforming every industry.

Could it happen to the PM job jar? Perhaps.

Certainly the challenge is to maintain value-add skills and knowledge that are not rules-based. The more your job has elements of randomness, the safer you are

Random is your friend!


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Sunday, August 20, 2017

Average is not always the answer


Doesn't all data sets have an average?
Actually, not
  • Yes, data taken from a common distribution along a common scale  has a parametric value* that emerges from a long run of repetitions

    The repetition-weighted sum we commonly call the average, even if it's not the most frequent outcome, and even if it's not an allowable outcome (the average of integers is often not an integrer, as the average value of the roll of one die is 3.5)
  • Data that cluster's about a central value always has an average. This clustering idea we call the "central limit theorem"
Here's a couple of issues
  • No, not every data set we run across in PM are from a common distribution, or has a common scale, and so the concept of average doesn't apply. Example: big projects and little projects don't have a common scale: big numbers for the former; small numbers for the latter
  • Not every data set clusters
Three ideas you may not have thought about:
  1. Clustering: When there's clustering, there will be an average. Usually, data taken from a common scale clusters You can't average feet and inches; nor apples and oranges. Common scale required!
  2. Not clustering: Data taken from many different scales doen't cluster, but rather follows a "power law". This gives rise to the so called "80/20" rule and other other ideas commonly shown on a Pareto Chart of descending values... so, no cluster effect, and NO AVERAGE.

    Almost all issues dealing with money is power law stuff.
    There's just no meaningful average of big projects (on one scale) with little projects (on another scale). The 80/20 rule is more the way to look at it since a Pareto Chart is scale-free!
  3. Independent events: Something happens; when will it happen again? You're doing something; when will it be finished? This isn't clustering, and it's not 80/20 stuff. You read this page; when will you read it again? Or, how long will it take you to finish reading?

    This leads to the so-called "additive rule": just add a constant to what you know to get the next outcome. Where does the constant come from? You estimate it! This leads to: "just give me five more minutes to get this done" sort of thing.

    Of course, there's no average because there's no common scale because everything is independent, memory-less (the present does not depend on the past, though the past may figure into your experience to give an estimate of the constant).
___________________________
* Parametric values, like average, are calculated; often they are not observed or even reliazable in the data set
This discussion adapted from the chapter on Bayes Rule in "Algorithms to Live By" by Christia and Griffiths


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Thursday, August 17, 2017

The Lord Beaverbrook model


Lord Beaverbrook, a genious in getting things done with big bureaucracy under the extreme pressure of war, had this philosophy
Organization is the enemy of improvisation
It is a long jump from knowing to doing
Committees take the punch out of .....  [fill in the blank]

------------------
Lord Beaverbrook was a close advisor and confidant of Winston Churchill during WW II. His genius: making processes work. His first job was making the production of aircraft stupendous enough to win the "Battle of Britain" in the air in 1940.


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Monday, August 14, 2017

Everyone estimates!


We all make estimates; and we all make estimates all the time.
  • When I make the 20 mile trip each Tuesday to a client site, I estimate adjustments to a baseline based on weather and road construction and if I know about an accident.
Really, no one sets out to do anything meaningful without some estimate in mind re time, or cost, or risk; usually we can also notionally estimate the scope.

So, now we hear from renown Agilist Mike Cohn, author of "Agile Estimating and Planning", about his views estimating new scope:

Rule 1: Estimating is not a vote. Well, actually, there's a lot of voting in estimating as a group agrees on a consensus, so I don't agree with Mike on this one, but he's welcome to his idea.
Rule 2: Most estimating is relative and so most people know notionally whether or not some is bigger or smaller; more or less complex, etc than an understood baseline
Rule 3: Everyone participates; even if you don't know what you're talking about. Seems curious, but Mike's idea is that most estimating is relative (see above), so even the uninformed can make some contribution to the discussion. My take: perhaps, but the uninformed often don't have "permission" to be in the decision making.

Anyway, to end with the beginning in mind: We all make estimates; and we all make estimates all the time.



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Friday, August 11, 2017

Auteur model of innovation



Good grief!  Yet another model to learn about.  Now we hear about the auteur model of innovation, an idea coined by John Kao, an innovation guru.

Auteur: an innovator that has a distinctly personal style and maintains artistic control over all design and production aspects of his/her work [a definition adapted for projects from the film industry where the auteur model has been practiced for many years].

Sounds a bit autocratic!  Whatever happened to the empowered team and even more broadly: the wisdom of the crowds?  What happened to the embedded customer model--think: SCRUM -- and other customer-intimacy models like the market leader ideas of Treacy and Wiersema? 

Indeed! where is system engineering in this model?
In our world, the project world, and especially the technology project world where anyone can have an idea, the auteur model is a rare occurrence; a successful implementation, sustained over time, is even more rare.But take a look at the poster child for the auteur model:  today that is Apple.

Without its innovative leader, the company foundered; with its bold visionary, the company prospered. And, in a decidedly not-agile way of doing things, it is said Apple never asks its customers anything.  They sure did not ask about a name for the iPad!
 
Obviously, the dependency on one personality is Risk 1 for this model -- both an upside opportunity and a downside risk.  For the successful, it's evident opportunity triumphs! Obviously, Tim Cook is having a good run post Steve Jobs; but I think everyone would agree Jobs set the bar.But it's evident that Apple, and others with this model, go a step or two further.
  • Step 1: make  your own market where one didn't exist;
  • Step 2: exploit that market with the simplest possible product that has the highest possible wow! factor. 
  • And, step 3: guard the gate!  Be selective about letting others ride the coattails of your own auteurist [is that a word?]
Mr Kao writes: "Mr. Jobs is undeniably a gifted marketer and showman, but he is also a skilled listener to the technology. He calls this “tracking vectors in technology over time,” to judge when an intriguing innovation is ready for the marketplace.

Skilled listener?  Perhaps so.  One of the mantra's of the agile movement today is to be value on simplicity.  Apple has certainly gotten that.   Jobs told us that the floppy was dead 18mos before it was indeed dead; and now Cook has done away with the headphone jack (gasp!)

  The best possible example of the wisdom of simplicity.  Not that things Apple builds are simple; they are simply minimally complex!


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Tuesday, August 8, 2017

Dilbert on Agile



Among some comments to a posting on TechCrunchIT, is this snippet about Dilbert's run-in with Agile:







Dilbert: We need 3 more programmers.
Boss:
Use agile programming methods.
Dilbert:
Agile programming does not mean doing more work with less people.
Boss:
Find me some words that do mean that and ask again

Dilbert is a creation of Scott Adams



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Saturday, August 5, 2017

When to stop?


You're doing something. Fair enough
What if there's no obvious end-point?
  • Like finding the "just-right" SME for the team ... you never know when that is going to happen
  • When should you stop looking at candidates?
Actually, there's a computer science answer to this.
Look no farther than the "optimal stopping" algorithm!

As explained by authors Christian and Griffiths*, there are two ways to make a mistake trying to find the "best" SME ... assuming you are interviewing candidates in random order
  1. Stop too soon, hiring "suboptimally", missing out on the best candidate you never get to interview
  2. Stop too late, passing up the pick of the litter hoping there is an even better candidate
Obviously, the first person you interview is the "best" so far ... there's only one. The next one you interview has a 50/50 chance of being the best; and the third person has a one in three chance, etc. But how long to go on with this?

After a lot of research, and numerous academic papers, the computer science community has arrived at an algorithm (of course they have): "Look, then leap". 

Look, then leap
Step 1: set a fixed time to look over the field. Don't choose anyone (or anything) in the "look" phase
Step 2: after the look phase, leap! Leap on the best candidate that then comes along, or go back to a "best" in the look phase if they are still available.

What's the chance that you'll get the "best" candidate? About one chance in three ... actually, long term, 37%. Here's an abbreviated chart of the odds, as developed by validation of the optimal stopping algorithm:
  • 3 candidates; take the best after 1; 50% chance of getting the best
  • 6 candidates; take the best after 2; 43% chance of the best
  • 10 candidates; take the best after 3; 40% chance of the best
  • Huge number; take the best after 37% of huge; 37% chance of getting the best
Actually, look before leaping is not bad advice for a whole host of activity!
______________
* "Algorithms to Live by", Brian Christian and Tom Griffiths


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Wednesday, August 2, 2017

A commentary on Agile



I was looking back at some prior essays on Agile and came across the April 2012 PMNetwork magazine. Specifically I was attracted (again) to page 58 for an interview with some agilists on the state of the practice.

Here are a couple of quotes from Jim Highsmith worth tucking away:

Agile project management embraces both “doing” agile and “being” agile—and the latter is the hardest. It defines a different management style: one of facilitation, collaboration, goal- and boundary-setting, and flexibility.

... agile is changing the way organizations measure success, moving from the traditional iron triangle of scope, schedule and cost to an agile triangle of value, quality and constraints.

My take:
Doing agile and being agile: Good insight, but these ideas are certainly agile but not unique to Agile.
  • To my way of thinking, all enlightened project managers have been doing this all along, or they should have been.
Now, I certainly agree: Agile calls for a reset of manager's and management's approach (aka style) to projects.
  • Fixed price, for a fixed scope, in a fixed schedule is ok if you're in "we've done it before" or some kind of production, but not if you are trying to cure cancer, etc.

Value shift: Agile shifts the discussion from fixed value to best value. And, what is best value?
It's the best the team can do, with the resources committed, towards achieving project goals that will ultimately lead to business success.

Who says what's "best"? In the Agile space, that is a collaboration of the project team, the sponsor, and whoever holds the customer/user's proxy. That's the key:
  • The customer/user--through their proxy--gets an input to the value proposition because they may use or buy the outcomes, but the customer/user has no money at stake; it's other people's money, OPM
  • The sponsor also gets an input  because it is their money at stake. (The sponsor may be a contracting office, as in the public sector)
  • The project team gets an input because they are in the best place to judge feasibility.

Measuring success: Highsmith's second idea is certainly Agile, but it may be too agile for some. Why so? First, there's still "other people's money (OPM)".... . you can't work with OPM and not have metrics of performance to stack up against the money. So, the cost-schedule-scope tension may be hard to manage, but at least there are metrics.

I don't have a problem with another paradigm, say Highsmith's value, quality and constraints, so long as they come with metrics that align with the value that sponsors put on money.

That's why I associate myself with best value: It's OPM with metrics that align with a value proposition leading not only to project success but to business success as well.



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