Friday, February 15, 2019

Garbage in .....



Garbage in; garbage out... GIGO to the rest of us

Re GIGO, this issue is raised frequently when I talk about Monte Carlo simulation, and the GIGO thing is not without merit. These arguments are made:
  • You have no knowledge of what distribution applies to the uncertainties in the project (True)
  • You are really guessing about the limits of the three point estimates which drive the simulation (partly true)
  • Ergo: poor data information in; poor data information out (Not exactly! the devil is in the details)
Here are a few points to consider (file under: Lies, damn lies, and statistics):

First: There's no material consequence to the choice of distribution for the random numbers (uncertain estimates) that go into the simulation. As a matter of fact, for the purposes of PM, the choices can be different among tasks in the same simulation.
  • Some analysts choose the distribution for tasks on the critical path differently than tasks for paths not critical.
  • Of course, one of the strengths of the simulation is that most scheduling simulation tools identify the 'next most probable critical path' so that the PM can see which path might become critical.
Re why the choice is immaterial:  it can be demonstrated -- by simulation and by calculus -- that for a whole class of distributions, in the limit, their infinite sum takes on a Normal distribution.

  • X(sum) = X1 + X2 + X3 +.... +XN, where N is a very large number, X(Sum) is Normal, no matter what the distribution of X is
As in "all roads lead to Rome", so it is in statistics: all distributions eventually lead to Normal. (those that are practical for this purpose: single mode and defined over their entire range [no singularities]),

To be Normal, or normal-like, means that the probability (more correctly, the probability density function, pdf) has an exponential form. See: Normal distribution in wikipedia

We've seen this movie before in this blog. For example, few uniform distributions (not Normal in any respect), when summed up, the sum took on a very Normal appearance. And, more than an appearance, the underlying functional mathematics also became exponential in the limit.

Recall what you are simulating: you are simulating the sum of a lot of budgets from work packages, or you are simulating the sum of a lot of task durations. Therefore, the sim result is summation, and the summation is an uncertain number because every element in the sum is, itself, uncertain.

All uncertain numbers have distributions. However, the distribution of the sum need not be the same as the distribution of the underlying numbers in the sum. In fact, it almost never is. (Exception: the sum of Normal is itself Normal) Thus, it really does not matter what distribution is assumed; most sim tools just default the Triangular and press on.

And, the sim also tends to discount the GIGO (garbage in/garbage out) problem. A few bad estimates are likewise immaterial at the project level. They are highly discounted by their low probability. They fatten the tails a bit, but project management is a one-sigma profession. We largely don't care about the tails beyond, certainly not six sigma!

Second: most folks when asked to give a 3-point simply take the 1-pointer they intended to use and put a small range around it. They usually resist giving up anything so the most optimistic is usually just a small bit more optimistic than the 1-pointer; ....  and then they put something out there for the most pessimistic, usually not giving it a lot of thought.

When challenged, they usually move the most-likely 1-pointer a bit to the pessimistic side, still not wanting to give up anything (prospect theory at work here). And, they are usually reluctant to be very pessimistic since that calls into question the 1-pointer (anchor bias at work here). Consequently, you get two big biases working toward a more optimistic outcome than should be expected

Third: with a little coaching, most of the bias can be overcome. There is no real hazard to a few WAG because unlike an average of values, the small probability of the tails tends to highly discount the contribution of the WAGs. What's more important than reeling a few wild WAGs is getting the 1-pointer better positioned. This not only helps the MC Sim but also helps any non-statistical estimate as well.

Bottom line: the garbage, if at the tails, doesn't count for much; the Most likely, if a wrong estimate, hurts every methodology, whether statistical or not.





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Tuesday, February 12, 2019

Technical debt -- a working definition


Technical debt: we've all written about it; I've described it in my book, Project Management the Agile Way (see below), but I guess the industry has never settled on a formal definition.

I've always thought of it as a "punch list" that is a "debt" that must be retired in the future .... stuff that needs to get DONE or fixed so that we can say to the sponsor: hey, it's DONE and the QUALITY is built in.

I saw this definition recently.

In software-intensive systems, technical debt consists of design or implementation constructs that are expedient in the short term, but set up a technical context that can make a future change more costly or impossible. Technical debt is a contingent liability whose impact is limited to internal system qualities, primarily maintainability and evolvability [SIC].

Frankly, it's a little too formal and I think it actually misses the point that debt may be as simple as a low level test not completed; a color not made right; a functionality with a bug that occurs very infrequently, etc.  Nonetheless, there it is for your consideration

If you click back to the original source, you pick up on this explanation which adds a bit of color commentary, to wit:

This metaphor is in essence an effective way of communicating design trade-offs and using software quality and business context data in a timely way to course correct.

While other software engineering disciplines such as software sustainability, maintenance and evolution, refactoring, software quality, and empirical software engineering have produced results relevant to managing technical debt, none of them alone suffice to model, manage, and communicate the different facets of the design trade-off problem at hand.

Of course, I take a bit of issue with the last phrase "design trade-off problem at hand": technical debt is not exclusively -- or even -- about design trades per se; as before: it could be as simple as a low level test not completed. One wonders if the guys who wrote this stuff have actually ever done it.



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Saturday, February 9, 2019

Two doors: risk and decision managers



A narrative*

Imagine two doors to the same room:
  • One labeled risk manager; the other labeled decision maker.
  • Though the risk manager's door, entry is for the inductive thinker: facts, experience, history looking for a generality or integrating narrative
  • Through the decision maker's door, entry is for the deductive thinker: visionary with a need to articulate specifics for the vision
Adding to the narrative:
  • Pessimists with facts enter through the risk manager's door
  • Optimists with business-as-we-want-it enter through the decision maker's door
Then what happens?
They seek each other (hopefully, if minds are open). In the best of situations, they meet in the middle of the room where this is buffer space and flexibility.

How does the inductive and deductive interact?
Risk management does not set policy for the project office; it only sets the left and right hand boundaries for the vision, or for the project policies.
The space in between is where the decision maker gets to do their envisioning, moving about, perhaps even bouncing off the walls, constrained only by the risk boundaries.




(*) Sound familiar? I hope so. You'll find a similar explanation known as the "project balance sheet" in Chapter 6 of "Maximizing Project Value: A project manager's guide". (Oh -- the book cover is shown below!)

In that balance sheet metaphor, the right side is for the fact-based inductive manager; the left side is for the visionary. And, since those two never agree fully, there is a gap.

And the gap is where the risk is. Risk is the balancing element between the vision and the facts. And who is the risk manager: the project team -- not the visionary. (That's why we pay the PMO the big bucks: to manage the risk!)

Wednesday, February 6, 2019

Burning up the team


Are you on one of those death march projects about to burn out. Want some time off? Perhaps it's in the plan

Google among others -- Microsoft, etc -- are well known for the "time off, do what you want toward self improvement and personnel innovation" model; formulas like you suggest lend objectivity to the process (not playing favorites, etc).

Losing productivity
Of course, the real issue is one that agile leader Scott Ambler has talked about: the precipitous drop in productivity once you reach about 70% throughput capacity of the team. Up to this point, the pace of output (velocity) is predictably close to team benchmarks; thereafter, it has been observed to fall off a cliff.

Brook's Law -- it's not been repealed
Other observers have put it down as "Brooks Law" named after famed IBM-370 project leader Fred Brooks: "Adding people to a late project makes it later" . Read: "Mythical Man-month" for more from Brooks

Did I mention Physics?
In the physics of wave theory, we see the same phenomenon: when the "load" can not absorb the energy applied, the excess is reflected back, causing interference and setting up standing waves. This occurs in electronic cables, but it also happens on the beach, and in traffic.

So it is in teams: apply energy beyond the team's ability to absorb and you simply get reflected interference.
Many have told me: the way to speed things up is to reduce the number of teams working and the number of staff applied.

WIP Limits
In agile/lean Kanban theory, this means getting a grip on the WIP limits... you simply can't have too many things in play beyond a certain capacity. The problem arises with sponsors: their answer is universally: throw more resources in, exactly opposite the correct remedy

6x2x1, or other
One of my students said this: "Daniel Pink  has an excellent book called "Drive: The surprising truth about what motivates us" that talks about inspiring high productivity and maintaining a sustainable pace.
One of the techniques is the 6x2x1 iteration model.
This says that for every six two week iterations the development team should have a 1 week iteration where they are free to work project related issues of their choice.

You can also run a 3x4x1 model for four week iterations.
Proponents of this approach have observed that the development teams will often tackle tough problems, implement significant improvements and generally advance the project during these free play periods. Without the time crunch to complete the story points the team also refreshes itself."

And now, we rest!



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Sunday, February 3, 2019

Getting "reskilled"


Dispatches from Davos 2019
There's a revolution afoot

The panel discussions are about "human-centered A.I", and the "Fourth Industrial Revolution" in an article reported by Kevin Roose

And, thinking about it, would you want A.I. to be other than human-centered?

Strategic thinking:
 “Earlier they had incremental, 5 to 10 percent goals in reducing their work force. Now they’re saying, ‘Why can’t we do it with 1 percent of the people we have?’”

Getting there (as reported)!
One common argument made by executives is that workers whose jobs are eliminated by automation can be “reskilled” to perform other jobs in an organization.

They offer examples like Accenture (*), which claimed in 2017 to have replaced 17,000 back-office processing jobs without layoffs, by training employees to work elsewhere in the company. 

Chat now
Got some back-office processing in your project office, or supporting your project office? The automated on-line chat is coming to a project near you!



(*) Full disclosure: A few years ago, I worked in a PMO largely staffed by Accenture (I was the customer; they were the consulting partner)




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Thursday, January 31, 2019

I've got to write a RFP



Ever been asked to write an RFP (request for proposal)? It may not be as easy as you think. My metric is about 2-3 hours per finished page, exclusive of specifications. Specs are normally just imported. So, it could take you the best part of a week to put an RFP in place.

My outline is given in the Slideshare presentation below

Beyond the outline, here's a few things to think about.

Source identification: Sources, per se, are not part of the RFP, but sources are its audience. And the RFP is written for a specific audience, so sources certainly influence the RFP

Source identification, or more better, source identification and validation (vetting), is both a science and an art. The science part is an objective list of source attributes; the art part is judgment, admittedly not objective.

Of course, there's sole source (the only one in the world who can do it) or selected source (the only one in the world you want as your contractor), but more often an RFP regulates competition among multiple sources.

Award criteria: How are you going to decide who wins?
  • Lowest cost, technically acceptable (pass/fail) is the easiest and most objective.  Just open the envelop of all those with passing technical grades and take the lowest cost -- no questions, no fuss
  • Best value is not easiest and not objective but it might get you the most optimum solution. Rather than pass/fail, you get to consider various innovations and quality factors, various management possibilities, what the risk is to you, schedule, and of course cost.

    Best value may not be lowest cost. That's always controversial, since cost is the one value proposition everyone understands. No one wants to spend more than the value is worth.

    The flexibility of best value (or, glass half empty: lack of objectivity) comes with its own risk: the award, if in the public sector, is subject to protest about how the best value was determined.
Risk transfer: what technical, functional, and business risks are you going transfer to the contractor via the RFP, and are you prepared to pay for that transfer? In effect, you're buying insurance from the contractor. All other risks are your to keep; you can be self-insured, or pass them off to an insurance party.

Here are some risk methods  you can put in the RFP:
  • Contract incentives, penalties, cost sharing, and other contract cost-schedule-scope controls: all are forms of risk management practises.
  • Liquidated damages: you get paid for your business losses if the contractor screws up
  • Indemnity: your contractor isolates you from liabilities if something goes wrong
  • Arbitration: you agree to forgo some of your legal rights for a simpler resolution of disputes
Statement of work (SoW): This is the part most PMs know something about, so a lot of words aren't needed. It may be the first thing an interested contractor reads. The SoW answers this question: what is it you want the contractor to do? A top-level narrative, story, WBS, or vision is usually included.

The SoW is where you can say how agile can the contractor can be interpreting the vision. Think about how anchored to your story are you?

Typically, unless you are pretty confident you are right, you don't tell the contractor how to do the job, but only what job needs to be done.

Specifications: How's and what's: Specs are where you can speak to measures of "how" insofar as you tell the contractor how something is to be measured; or you can speak to measures of what insofar as you tell the contractor what the metrics are and what the metric limits are

Requirements: And last but not least, the infamous Requirements backlog or matrix. Requirements are usually made a part of the SoW  as detailed "what's" or they can be a specification onto themselves.

Requirements are where problems surface on almost every project:
  • Are they objective, that is: having a metric for DONE
  • Are they unambiguous? ... almost never is the answer here. Some interpretation required. 
  • Are they complete? ... almost certainly never is the answer here. But, can you admit the requirements are incomplete? In some culture and context, there can be no such admission. Or, you may be arrogant about your ability to obtain completeness. My take: arrogant people take risks and make mistakes...the more arrogance, the larger the risks... etc

    But, where you can say: Not complete, then presumably the contractor can fill out the backlog with new or modified requirements as information is developed?
  • Are they valid? Can you accept that some requirements will be abandoned before the project ends because they've been shown to be invalid, inappropriate, or OBE (overtaken by events)?
  • Are they timely? Can you buy into the idea that some requirements are best left to later? ... you really don't have enough information at the beginning. There will be decision junctions, with probabilistic branching, the control of which you simply can't



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Sunday, January 27, 2019

Kanban at the Kitchen Table




Dana Rousmaniere and Frank Saucier collaborate in an interview to talk about kanban methods for the home. And, of course, it's all built around a kitchen table white board with some sticky notes.

Have you done this at home? I have; and it works... you wouldn't expect otherwise.

But, Frank carries it a bit further than I want to go. He has structured family meetings with a checklist agenda, and then daily check-ins on project tasks.
Whoa! that's a bridge too far for my wife ... no micromanagement here.
In fact, Frank admits: "There's sometimes some moaning and groaning... "

The larger point
But, of course, there's a larger point here: Almost everything we do, formally or informally structured, as some sequence and flow -- just think about driving to work, or walking in to open your home office at the beginning of the work day (or night)

Flow and process... sequential steps; they are the building blocks of everything

Now, the lean and kanban advocates are all about improving flow, thinning out the non value-add, and simplifying the process so that work flow and work process are pretty much birds of a common feather.

Then comes scale, even in the kitchen
Who can argue with lean? Does anyone really want to do the non-lean stuff, even if they have to? No one so long as the work flow on the kanban does not require coordination with other kanban's... in that case, we move on to scale, and scale brings overhead, and overhead brings flow control, and so we all slow down.

You don't see this much on the kitchen table, unless your home project is part of a larger project for a community organization -- then comes the bureaucracy of scale.

You might say that velocity and scale have a inverse correlation, perhaps even a causation -- larger scale, lower velocity

Is it too low tech?
"I like to use low-tech tools, because it’s more important to learn good habits than it is to learn to use a tool. That said, there are plenty of digital ways to do the same thing — a good, free tool is Trello, which is essentially an online Kanban board.

But, I find that with digital tools, a lot of great ideas get buried, and the simple act of moving a post-it across a visual board is very kinesthetic. I’ve also noticed that teams have better discussions when they’re around a physical board." Frank
What's the payoff?
With Frank I agree (from personal experience in the kitchen)
  • Get priorities squared away
  • Manage distractions
  • Teach others the tools as a life skill
  • Richer communications



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