Tuesday, September 10, 2024

Slow is smooth; Smooth is fast


The blog title is actually from the mantra of the U.S. Navy SEALS
Slow is smooth; smooth is fast.

U.S. Navy SEALS

Now, this bit of wisdom may strike you as similar to the project tips we've been working with for years, to wit: "quality is free", and "it's cheaper and faster to do it right the first time" which recognizes the cost and schedule penalty of rework.

It's about rhythm and balance

From the SEALS website, we learn: "This phrase isn't just about being slow or fast; it's about finding a rhythm that balances precision and pace, ultimately leading to swifter progress. The SEALs swear by it... but how can we apply it beyond military contexts?

More depth:

Of course, there's a YouTube on "Smooth and Fast"

On the website, link given in the first sentence, there is a long-form article on the concept. Two chapters stand out:

Applying "Slow is Smooth, Smooth is Fast" Beyond Military Contexts

Incorporating the Mantra into Business Practices 
Using the Mantra for Project Management

The Role of "Slow is Smooth, Smooth is Fast" in Team Dynamics

Promoting Smoothness in Team Operations
The Mantra's Impact on Team Efficiency

In the PM domain, the recommendations are: 

  • Be deliberate; take the time to consider and prepare
  • Quality trumps speed (the cost of rework is embedded in this one)
  • Keep refining (Sort of a Bayesian idea, not so much continuous improvement)
In team dynamics, few errors and quality outcomes build trust, confidence, and high morale.



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Friday, September 6, 2024

Stability! It counts for a lot



Stability!
It counts for a lot.
It implies -- for behaviors and management decisions -- predictability, reliability, under-control (but not risk-free, of course), coherent narrative, steady-state goals, and a strategy that is understandable to those who have the job of implementing it.

Perhaps you are aware, as many are, that stability requires feedback to effect error correction and trap excesses and blind alleys. 
Ah yes!
We know about feedback.
Open loop systems -- those with outcome but no feedback -- are prone to many uncontrolled and unexpected responses. Who can predict what a stimulus will do to a system that has no feedback? Actually, that's a really tricky task.

So, what about feedback? 
What's to know?
  • Timing is everything! Getting the feedback "phased" in time such that it has a correcting effect rather than a destructive effect is vital. The former is generally called "negative feedback" for its corrective nature; the latter is generally called "positive feedback" for its reinforcing rather than corrective nature. And, when its too late, it's generally called ineffective.

  • Amplitude, or strength, or quantity is next: It has to be enough, but not too much. Tricky that! Experimentation and experience are about the only way to handle this one.
What could possibly go wrong?
Actually, a lot can go wrong.

No feedback at all is the worst of the worst: the 'system' is 'open loop', meaning that there are outcomes that perhaps no one (or no thing) are paying attention to. Stuff happens, or is happening, and who knows (or who knew)?

Timing errors are perhaps the next worst errors: if the timing is off, the feedback could be 'positive' rather than 'negative' such that the 'bad stuff' is reinforced rather than damped down. 

Strength errors are usually less onerous: if the strength is off, but the timing is on, then the damping may be too little, but usually you get some favorable effect

Practical project management
Feedback for correcting human performance is familiar to all. Too late and it's ineffective; too much over the top and it's taken the wrong way. So, timing and strength are key

But, the next thing is communication: both verbal and written (email,etc). Closing the loop provides reassurance of the quality and effectiveness of communication. You're just not talking or writing into the wind!

And, of course, in system or process design, loops should never be open. Who knows what could happen.

I should mention:
The study of feedback systems generally falls within what is called 'cybernetics'. As described by sciencedirect.com, MIT mathematician Norbert Wiener defined cybernetics as “the study of control and communication in the animal and the machine." 

From Wikipedia, we learn: The core concept of cybernetics is circular causality or feedback—where the observed outcomes of actions are taken as inputs [ie, feedback] for further action in ways that support the pursuit and maintenance of particular conditions [ie, 'ways that support' requires the correct timing and strength]



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Monday, September 2, 2024

The least Maximum schedule


To minimize your maximum schedule is a good thing. Or, it should be.
Here's how to do it:
  • Subordinate all other priorities to the most important tasks. This begs the question: is there an objective measure of importance, and from whom or what does such a measure emanate?
  • If you can measure 'importance' (see above) then do the densest tasks first, as measured by the ratio of importance to time.

    Note: a short time (denominator) will "densify" a task, so some judgement is required so that a whole bunch of short tasks don't overwhelm the larger picture. In the large picture, you would hope that the density is driven by the numerator (importance)

  • Always do an 'earliest start', putting all the slack at the end. You may not need it, but if you do it will be there.
  • Move constraints around to optimize the opportunity for an earliest start that leads to least maximum. See my posting on this strategy.

  • If a new task drops into the middle of your schedule unannounced, prioritize according to 'density' (See above). This may mean dropping what you are doing and picking up the new task. Some judgement required, of course. It's not just a bot following an algorithm here. 

  • If some of your schedule drivers have some random components, and you have to estimate the next event with no information other than history, then "LaPlace's Law of Succession" may be helpful, to wit:
    • To the prior random (independent) outcomes (probability) observed, add "1" to the numerator and "2" to the denominator to predict the probability of the next event. (*)

      So, by example, if your history is that you observed, measured, or obtained a particular outcome independently 3 of 4 times (3/4), LaPlace's Law would predict (3+1)/(4+2) as the probability for the next similar outcome, or 4/6. This figure is a bit more pessimistic, as you would expect by giving extra weight to the number of trials (denominator).
_________________________

(*) (n+1)/(d+2) isn't just a guess, or throwing a dart at a board. It is a rigorous outcome of an algebraic limit to a long string of 1's and 0's with historic probability of n/d. Although LaPlace did the heavy lifting, Bayes gets the popular credit for the idea of using prior observations as the driver for new estimates with a modified hypothesis.


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Tuesday, August 27, 2024

Never a dull moment ..;.



For some, boredom is the great fear. Got to keep moving!
"He had a function, an excuse for activity. For a few hours at least he wouldn’t be bored. ... he drank the coffee, which was still too hot. He reflected that the fear of boredom had driven him the whole of his life."
Ann Cleeves, Novelist

The fear or boredom was a driver ...
Frankly, I know how he feels

Add value
It shouldn't be motion for motion's sake
It should be about the utility of what you are doing
I need an activity plan for every day ... how will this day add value to what I am about?

About utility
Utility is the marginal difference between face value and the value you -- or someone else -- puts on what your are doing or offering. 

If you think about it, almost anyone can offer up face value if they have the skills for that domain, but if you are in constant motion -- avoiding boredom -- then that activity should be directed at more than just face value.

Even if it's just reading a book, the question is: how much better off are you for having engaged in that activity? For me, I read a lot of history because I think there are lessons there to be applied forward that will add value to my endeavors. And, of course, I might avoid a risk I might not otherwise understand.

If you are driven to activity ...
Make it count for something.




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Friday, August 23, 2024

Leonardo's Lament



"The supreme misfortune is when theory outstrips performance"
Leonardo da Vinci

And then there's this: 

During the technical and political debates in the mid-1930's by the FCC with various engineers, consultants, and business leaders regarding the effect, or not, of sunspots on various frequency bands being considered for the fledgling FM broadcast industry, the FCC's 'sunspot' expert theorized all manner of problems.

But Edwin Armstrong, largely credited with the invention of FM as we know it today, disagreed strongly, citing all manner of empirical and practical experimentation and test operations, to say nothing of calculation errors and erroneous assumptions shown to be in the 'theory' of the FCC's expert.

But, to no avail; the FCC backed its expert.

Ten years later, after myriad sunspot eruptions, there was this exchange: 

Armstrong: "You were wrong?!"

FCC Expert: "Oh certainly. I think that can happen frequently to people who make predictions on the basis of partial information. It happens every day"



++++++++++
Quotations are from the book "The Network"
 


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Monday, August 19, 2024

Out of Sight Activity


Back in yesteryear, I recall the first time I had a management job big enough that my team was too large for line-of-sight from my desk and location.

Momentary panic: "What are they doing? How will I know if they are doing anything? What if I get asked what are they doing? How will I answer any of these questions?"

Epiphany: What I thought were important metrics now become less important; outcomes rise to the top
  • Activity becomes not too important. Where and when they worked could be delegated locally
  • Methods are still somewhat important because Quality (in the large sense) is buried in Methods. So, can't let methods be delegated willy nilly
  • Outcomes now become the biggie: are we getting results according to expectations?
There's that word: "Expectations"
In any enterprise large enough to not have line-of-sight to everyone, there are going to be lots of 'distant' managers, executives, investors, and customers who have 'expectations'. And, they have the money! So, you don't get a free ride on making up your own expectations (if you ever did)

At the End of the Day
  • I had 800 on my team
  • 400 of them were in overseas locations
  • 400 of them were in multiple US locations
  • I had multiple offices
  • It all worked out: we made money!





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Friday, August 2, 2024

Do LLMs reason or think?


In a posting on "Eight to Late", the question is posed: Do large language models think, or are they just a communications tool?

The really short answer from Eight to Late is "no, LLMs don't think". No surprise there. I would imagine everyone has that general opinion.

However, if you want a more cerebral reasoning, here is the concluding paragraph:
Based, as they are, on a representative corpus of human language, LLMs mimic how humans communicate their thinking, not how humans think. Yes, they can do useful things, even amazing things, but my guess is that these will turn out to have explanations other than intelligence and / or reasoning. For example, in this paper, Ben Prystawksi and his colleagues conclude that “we can expect Chain of Thought reasoning to help when a model is tasked with making inferences that span different topics or concepts that do not co-occur often in its training data, but can be connected through topics or concepts that do.” This is very different from human reasoning which is a) embodied, and thus uses data that is tightly coupled – i.e., relevant to the problem at hand and b) uses the power of abstraction (e.g. theoretical models).



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