Posted by George Huhn on Sun, Aug 15, 2010 @ 11:47 AM
"The bigger things may age you, but it’s the little things that make you old." W. Town Andrews
I remember a
call from a friend of mine a few years ago who was working in a pharmaceutical plant that I had consulted for several years earlier.
"George," he said. "I have a problem. I was reviewing some documents, and I noticed that the copy I was looking at was different from the original document. When I checked the original, I found that the original data had been painted over with White-Out and a different number written over it."
In the pharmaceutical industry, altering data is a big "no-no." In general, when original data needs to be modified, the practice is to neatly draw a single line through the data so it remains legible, and then write the new data, your initials, the date, and the reason for the change, such as "writing error." Not following this practice rigorously can lead to government actions ranging from FDA warning letters to criminal charges.
He took the document to the associate director who had made the alteration and she told him "not to worry about it." He then took it to her supervisor, and was told that it was not going to be changed.
Now, this wasn't a mission-critical document and it did not have any impact on the quality or safety of any shipping products. But it was against the company's own written standard operating procedures and yet they didn't fix it – they were going to ignore it.
My friend and I were both very surprised at this. Several years earlier, this never would have happened – this plant was known for best-in-class good manufacturing practices and regulatory compliance. But management had changed and a culture shift had also started.
A few years later, what had once been a thriving and productive facility was cited for numerous violations by the FDA and essentially shut down.
When I heard about this, I thought about the "broken window" theory in criminology, which comes from this example:
"Consider a building with a few broken windows. If the windows are not repaired, the tendency is for vandals to break a few more windows. Eventually, they may even break into the building, and if it's unoccupied, perhaps become squatters or light fires inside.
Or consider a sidewalk. Some litter accumulates. Soon, more litter accumulates. Eventually, people even start leaving bags of trash from take-out restaurants there or breaking into cars."
Maybe the altered document was the first "broken window." Once it wasn't fixed, it was easier to let the next infringement pass, and the next one after that, until the violations did begin to affect the quality of the products. But by then it was too late.
"Broken windows" can happen in all kinds of ways in any business. They can be things like unfixed software bugs, unanswered customer complaints, or disregarded safety practices. They are often cheap to fix, but also easy to ignore. And there's usually someone who cares, like my friend, pointing them out.
Fix the "broken windows;" don't ignore them.
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Posted by George Huhn on Mon, May 17, 2010 @ 02:27 PM
What does it mean when a meteorologist says "the chance of rain today is 60%?"
Each day in the United States, a massive amount of data is collected from weather stations, satellites, and weather balloons from around the world and sent to the National Meteorological Center near Washington, D.C. The data is processed to give a multi-dimensional picture of global atmospheric conditions, and then it is analyzed using various algorithms to develop local weather forecasts and predictions.
But this isn't how they make the "percent chance of precipitation" predictions. Even with the massive amount of data and super computer speed, their predictive algorithms alone just aren't good enough. So they use comparisons to historical data.
Basically, they take the current atmospheric conditions and compare them with days in the past that had very similar conditions. So when they say that "the chance of rain today is 60%," it means that it rained on 60% of the days in the comparison set.
And guess what? Assuming the data was entered properly, these predictions are 100% reliable all the time. Why? Because they are only predictions of probability – they aren't "wrong" on a particular day, whether it rains or not. But whether they are accurate or not in the long term is an entirely different question.
The only way to determine if the predictions are accurate is to collect the data and plot the actual versus the predicted conditions over time to learn the margin of error. If it only rained on 30% of the days that the prediction was 60%, then there is a problem with the data or the data processing.
You can do the same type of probability prediction and testing with your business projects, too. The more accurate your estimates, the more confidence you will have in your overall project-value ranking in your project portfolios.
Developing more accurate project risk estimates requires 4 basic activities:
1) Identifying the key drivers of cost, time, and resource risks in completing project tasks.
2) Preparing a database of these tasks that includes the corresponding cost, time, and resource estimates assigned to each project and the basis for those estimates at the beginning of the project.
3) Tracking the actual costs, times, and resources used performing the task as each task is completed.
4) Comparing the actual costs, times, and resources with the starting estimates.
After you have maintained this database for a period of time, you will be able to plot the actual versus the predicted results. This plot will show you the accuracy of your cost, time, and resource estimates as well as revealing the distribution of the actual results. (You will probably learn that your cost estimates were too low, your time estimates were too short, and your resource estimates were for too few. And that is a good thing to learn.) Eventually, you will be able to use the actual results data as a basis for future probability predictions, including understanding the uncertainty in those estimates.
I saw the data of one major pharmaceutical company who did this for their project "percent probability of success" estimates. The data between 20 and 85% was surprisingly linear; for example, about 50% of the projects that had "percent probability of success estimates" of 50% were ultimately successful. It also showed that all projects that had an estimated "percent probability of success" of 85% or greater succeeded and all that had an estimate of 20% or less failed.
If you’re involved in project portfolio management and you're looking for ways to improve your project planning, compiling and analyzing your historical data is a great way to test and improve your future estimates.
Does your company track and analyze historical project management data? Why do you think that most businesses don't?
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Posted by George Huhn on Fri, Apr 30, 2010 @ 10:38 AM
This last paragraph caught my attention:
Karl Popper, the great philosopher of science, once divided the world into two categories: clocks and clouds. Clocks are neat, orderly systems that can be solved through reduction; clouds are an epistemic mess, “highly irregular, disorderly, and more or less unpredictable.” The mistake of modern science is to pretend that everything is a clock, which is why we get seduced again and again by the false promises of brain scanners and gene sequencers. We want to believe we will understand nature if we find the exact right tool to cut its joints. But that approach is doomed to failure. We live in a universe not of clocks but of clouds.1
Our businesses are mixtures of clocks and clouds, but it is often difficult to distinguish which parts are clouds and which parts are clocks. The clocks are things that we can measure and control but clouds are things that we can only try to predict.
Confusion begins when we try to measure and control clouds as if they are clocks or we focus only on trying to control clocks without trying to predict and mange the clouds.
Like Leher's comment on science, it is also a mistake of modern business to try to pretend everything is a clock. While I am a strong proponent of using business analytics, such as
simulation and
optimization in
project portfolio management tools, the analytical tools that we use should be able to manage data from both clocks and clouds. And when we're using these tools, we should be ever mindful of the inherent uncertainty (cloudiness!) in the data and the resulting predictions. Business analyses should rarely be
chiseled in stone. Too often, they are treated like they are.
Look around your business today. Where are your clocks? Where are your clouds?
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Posted by George Huhn on Sun, Mar 28, 2010 @ 08:29 PM
I do a lot of work in industries where there is a tremendous amount of proprietary and confidential information passed around in mountains of documents. It is the type of information that might help a competitor tremendously to shorten their development and cycle times considerably.
So, you’d think that these companies would be among the first to use encrypted electronic communications, but you’d be wrong. Until last week, I had not received an encrypted document from a single client or ever been asked about encrypting the data that they provided to me on my business computers (I do anyway). I have been in places where the companies have been extremely careful about controlling their paper documentation, but seemingly oblivious to the risks of sending those very same documents out in e-mails without any encryption or password protection.
So I must say that I was delighted to receive an e-mail from a contractor who had actually encrypted and password-protected the document attached to it. They even knew that they shouldn’t send the password and the document together in the same e-mail. That’s progress!
The lack of using even the most basic document protection when sending sensitive documents by e-mail is a fundamental security risk to these companies. Perhaps the reasons that they don’t do it are because of the effort that would be required by the IT department to develop and enforce a policy around securing documents sent by e-mail, the belief that a security breach due to interception of a proprietary document “won’t happen to them,” and the inconvenience of applying the security layer to each e-mail.
I wonder if they have ever done a cost risk analysis for implementing such a procedure. It would be an interesting analysis to perform because the cost of implementing a secure e-mail documentation system would have both fixed and variable costs associated with it. Fixed costs would include items such as developing the systems, purchasing the software, training, implementation, and monitoring. Variable costs would include the time required to secure each individual e-mail that is sent or secure only certain high-value e-mails.
They could justify the fixed cost based on a risk analysis. For example, if a security breach could $500 million and the annual risk of that breach was one-half of one percent then the expected annual loss is ($500 million)*(0.005) or $2.5 million. If implementing a security system costs less than that, it is a no-brainer to do it.
As an aside, I wonder how many people really think that those long wordy legal statements that are often attached to corporate e-mails claiming confidentiality are adding any security.
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Posted by George Huhn on Thu, Dec 10, 2009 @ 02:02 PM
Good project execution is essential to achieving the strategic goals of a company, but most companies either don't measure it or don't measure it well.
In companies where the quality of project management execution is assessed at all, it is usually measured against meeting budget, timing, and resource objectives that were often ill-conceived to start with. So when projects go over budget or are under resourced or when timelines are missed, it is too often blamed on "execution," and rarely on the poor quality of the initial budget, timing, resource, and risk assessments (or lack thereof).
How often have you seen managers record a quantitative basis for their planning estimates at the beginning of a project and then assess them at the end of a project?
Too often managers look at Gantt charts as if they are THE PROJECT PLAN carved in stone. They aren't. Most of the time, Gantt charts represent the best guesses of well-intentioned people who tend to underestimate risks, resources, and timing (because that is what human beings tend to do). Most of the time, the "data" used to support the project planning either doesn't exist, hasn't been checked, or hasn't been derived empirically. Task start and end dates are fixed with virtually no meaningful or quantitative discussion about the probabilities of meeting those dates or modeling the dramatic cumulative effects of small amounts of slippage on project value.
A big contributor to those results may not be just poor project execution, but how and where the project finish lines were drawn at the start of the project. So it is past the time for managers to be measuring the quality of project execution based on chiseled-in-stone Gantt charts.
Instead, today's managers need to start using quantitative risk analyses, databases of empirical data from previous experiences, and statistical tools for probabilistic project planning so they can truly assess and improve the quality of project execution.
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Posted by George Huhn on Thu, Nov 26, 2009 @ 08:07 AM
The debate over global warming is heating up again. A group of allegedly stolen e-mails is giving fuel to the fire to those who believe that global warming caused by human activities or Anthropogenic Global Warming (AGW) is a scientific fraud of massive proportions.
However, the question shouldn't be whether or not global warming is caused by AGW. It isn't a yes or no question.
The question should be: What is the percent probability that AGW will have catastrophic effects (between 0 and 100% probability)?
(Those of you who truly believe that the percent probability is 0% can stop reading now. And if you don't believe that any kind of global warming is occurring then you can also stop reading.)
After we have estimated the percent probability, we need to estimate what the economic costs will be if AGW causes a global catastrophe because we did nothing to stop it.
Let's assume the costs would represent millions or billions of dead human beings, beneficial ecosystems destroyed, and mass extinctions of animal and plant species. (I recognize that putting this in sterile economic terms will seem heartless to many, but we don't really have another good way to put a number on it.)
Once we have these two values, we can calculate the "expected value" of the cost of AGW. We'd take the cost of a global catastrophe and multiply it by the probability of it occurring:
Cost($) * Probability of occurrence(%) = expected value of the cost of AGW($)
Once we have that value, it would be prudent of us to figure out what the cost and risks of trying to stop or ameliorate the severity of AGW would be. If the cost to stop it is less than the expected value of the cost of a global catastrophe caused by AGW and the associated risks trying are acceptable, then we're fools as a species not to consider paying the costs of trying to stop it.
What do you think the expected value is?
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