Tag Archives: measuring

Tainted Eggs and Sticky Accelerator Pedals

We’ve had hundreds of millions of eggs recalled in the last several weeks.  That’s more eggs than there are people in the United States.  According to CNN.com, there were 1,953 cases of Salmonella enteritidis reported in a 3-month period.  Salmonella hits you hard. It can leave you sick for a week with cramps, chills, headaches, vomiting, diarrhea.  And that’s if you are healthy.  The elderly, young or folks with weaker immunity can suffer much worse.

1,953 reported cases.  Even after the recall, there could be more cases since the symptoms can hit several days after consumption of tainted eggs.  That’s a lot of sick people.

Or is it?

Another recent recall involved Toyota vehicles and the problem of accelerator pedals.  Cars accelerated out of control.  People died.  There were multiple stories carried by the media in quick succession.  Police were interviewed.  Congressional hearings were held.  A company’s reputation was at stake.

Take a look at the graph published by the Wall Street Journal that shows the “daily number of complaints about vehicle speed and accelerator pedal control” and the dates of some key events.  I am not sure what the “normal average daily complaint rate” should be, but before the warning from Toyota in late September 2009, it seem like there were fewer than 10 complaints per day.  There’s a small spike after the September warning.  The complaints seem to show a temporary peak about 6 weeks after this. In late November, Toyota announces a recall, accompanied by another spike in the days following.  Finally, in late Jan and early February 2010, there are calls to investigate the possibility of faulty electronics.  Around the time regulators officially expand the probe, the complaints spike, reaching a height of over 150 on a single day.

It’s difficult for Toyota to claim that either the drivers were becoming less careful or that the complaints were unjustified.  We have seen such PR blunders before from companies.  When a company makes such a mistake, no amount of science, facts, statistics or promises can fix the PR damage.

Back to the tainted eggs.  According the the CDC, from May to Jul, we would expect about 700 cases of Salmonella instead of 1,953.  Clearly, there is a spike associated with the eggs.  And it’s also likely that not all cases relating to the eggs have been reported.

What do you think?

Can recalls “cause” complaints?  Should companies (and organizations) revise the way recalls are done?  How should we use such statistics in setting the communications or policies regarding recalls?

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How Much Oil is Leaking in the Gulf?

The oil continues to leak, and we are now starting see the oil hit the shores.  We have live images from the leak 5,000 feet below the water surface.  But how much oil is actually leaking from the wellhead?

Initial estimates (Day 5) from the US Coast Guard and BP placed the estimate at 1,000 barrels/day.  Last week, the “official” government group revised the estimates at 20,000 – 40,000 barrels/day.  Less than a week later, the estimate is now at 35,000 – 60,000 barrels/day.

When the late May estimates came out, there was an interesting quote from Ira Leifer, University of California, Santa Barbara: “It would be irresponsible and unscientific to claim an upper bound, …it’s safe to say that the total amount is significantly larger.”  He wants to make sure the estimate has an asterisk because he wants “to stand up for academic integrity.”  In fact, there’s a whole document available by the university that will explain how the scientists came up with their estimate.  (from WSJ article here)

But I suspect that most of us will not care too much for the actual method or the details.  Maybe a chart like below is helpful since it summarizes the “growth” of the estimates over time.  By doing so, I am (on purpose? inadvertently?) suggesting a story and a conclusion.  What do you read from it?

Report Date Barrels/Day Source / Reported by Method Link
April 24 (Day 5) 1,000 USCG, BP, thru cbc.ca Info from ROV (remote operating vehicles) and surface oil slick Link
April 28 (Day 9) 5,000 NOAA Satellite pictures Link
May 12 (Day 23) 70,000 Steven Wereley, Purdue, for an NPR story particle image velocimetry, based on videotape Link
May 12 (Day 23) 20,000 – 100,000 Eugene Chang, UC-Berkeley, for an NPR story “Pencil and paper” based on pipe diameter (from video) Link
May 27 (Day 34) 12,000 – 19,000 12,000 – 25,000
(depending on source)
Flow Rate Technical Group
(NOAA, USCG, Minerals Mgt)
Based on multiple methods
(blog entry author’s guess)
Link 1

Link 2

Jun 10 (Day 52) 20,000 – 40,000
25,000 – 30,000
(depending on source)
Plume Modeling Team of The Flow Rate Technical Group Revised from earlier, based on additional video from BP Link
Jun 15 (Day 57) 35,000 – 60,000 Deepwater Horizon Incident Joint Information Center, reported by cnn “based on updated information and scientific assessments,” Link

So what can we learn from this?  We all (think we) want lots of data.  It’s helpful when it’s summarized in a way that seems to make sense.  But when we are confronted with data that we are not used to seeing (how may of us deal in BARRELS of oil, or work with flow rates?) we need some anchor, some comparisons, something that helps us make sense of numbers.

No matter how you count it, this is a lot of oil.  But does it really matter that it’s 15,000 or 60,000 barrels/day?  If you are part of cleanup or doing planning for the the collection, it may help you with the planning.  But you’re also going to want to know some other info, such as how long will it flow, how the flow has changed over time and the related “total leakage”.  Even with this last bit of info, you’re more interested in the amount that ends up on the shore or the amount that actually possible to reclaim.

For most of us, the accuracy of the flow rates do not matter so much.  It’s a lot of oil, and we need some way to get a handle on it.  Most of us will not remember the actual number (or in this case, the changing range of numbers).

Besides, no one will really know the true amount that has spilled.

Unintended Consequences of a Unmanned Speed Gun

Perhaps you have seen these unmanned speed guns.  Some are temporary, perhaps around construction zones or around dangerous curves.  Some are permanently placed as part of a sign, a flashing set of numbers indicating your speed just under the sign with the posted speed limit.  Many work well; they are relatively low-cost reminders of the need to watch our speed.

Except when they don’t.  Near where my brother lives, there is a slightly upward-sloping stretch of a 4-lane street that starts at a stop light and goes near a school zone.  The speed limit is 40MPH.  Because of the slope, it’s actually difficuly to reach the speed limit by the time you reach the speed gun.  Difficult if you are using normal acceleration.  The “watch your speed” zone has now become a “how fast am I going” zone as drivers use the convenience of the speed gun to see how fast his or her car can reach.

And so we have an example of unintended consequences.  Here, it’s much worse than the typical ones.  The “fix” actually encourages the opposite behavior.

In systems thinking, we describe an “archetype” called “fixes that fail”.  Sometimes, “fixes” work for awhile, then fail.  Sometimes, they fail from the start.  Sometimes, they work in some cases, but fail in others.

What “fixes” are you working on now in your organization or personal life?  Could they be candidates for unintended consequences or “fixes that fail”?

Are you good at estimating?

We all estimate. Whenever we say, “I’ll be home in about 30 minutes” or “I need about 50 inches of tape”, we are estimating. Some of us even estimate as part of our jobs. Project managers, sales reps, executives, coders… whether we estimate lines of code, weeks of effort, new customers, revenue and profit, we make educated guesses based on our experience, observations and other sources.

But how good are we at estimating?

Here is a little exercise. On a sheet of paper, write down 1 through 10 on the left side of the page. Next to each number, draw two blanks, so that you can provide two answers for each number. Like this:

1. _________ _________
2. _________ _________
3. _________ _________
4. _________ _________

and so on to “10”.

Your job is to provide a “90% certainty” estimate for the questions below. You don’t have to get the answer correct, just provide a range of numbers–write your “low estimate” on the first blank and your “high estimate” on the second blank on each line.

  1. What was the production cost of “Gone with the Wind”?
  2. How old was Alexander the Great when he died?
  3. Wikipedia lists Burj Khalifa in Dubai as the tallest building. How tall is it in feet (or meters)?
  4. If you walk at the average speed of 3 miles/hour, how long in months would it take to walk the distance of Earth’s equator?
  5. How many times can Earth fit inside Jupiter?
  6. How many people signed the US Declaration of Independence?
  7. How many countries are there in South America?
  8. In what year did the world’s population surpass 2 billion people?
  9. How many pairs of legs does a common house centipede (Scutigera coleoptrato) have?
  10. What is the “as the crow flies” distance (on miles or km) between Beijing, China and Amsterdam, Netherlands?

For answers and the second part of this post, see comments.  But don’t scroll down or click on link before you take the quiz!