Fixing Blame for the Deepwater Horizon Blowout is a Bad Idea

Much of the news coverage about the BP Deepwater Horizon oil blowout focuses on who is to blame and who is trying to avoid blame or pass it on to someone else.  There is a consensus that BP has a lot of the blame.  The Minerals Management Service (MMS) of the U. S. Department of Interior gets a lot of blame, particularly due to a scandal during the Bush Administration alleging sex and cocaine parties in which the MMS and the oil companies participated. Democrats blame Bush, because it happened on his watch. 

Interior Secretary Salazaar and President Obama are blamed because they weren’t quick enough to clean house at MMS.  Everyone, including the U. S. Coast Guard gets blamed because the capping of the well to stop the spewing oil and natural gas is taking so long.

OEE – A way to Speak with Data, But It Only Works If We Use It

Speaking with data is an important part of the journey to becoming a World Class organization.  It is a way to make the invisible visible, to see things that we are otherwise likely to miss. It is also a way to get the attention of people who control the purse strings, when we need resources to solve a problem. I first discussed speaking with data in my post March 15, 2010. (http://bobduckles.blogspot.com/2010/05/speak-with-data.html)

OEE, which stands for Overall Equipment Effectiveness, can be a useful tool for managing and continuously improving.  There are three components to OEE:

1.     Availability (Planned uptime minus unplanned downtime)

2.     Performance  (Planned operating time minus minor stoppages and running slow. It is calculated by dividing the number of pieces produced by the pieces that would be produced at the rated or standard speed)

3.     Quality (All pieces produced minus defective pieces produced divided by all pieces produced)

Some companies have a mistaken view of the OEE of their equipment. I have been told that a certain machine has an OEE of .90 or .95, when I can see that it is running slowly, creating scrap, or is down fairly often. There is a convention that any OEE of .85 or above means that the equipment is working at a world-class level.  

Fairly high numbers in each of the three components can lead to an OEE that is still below level of .85. I have seen estimates that OEE in American manufacturing tends to run around .60.  I have not seen studies on which this claim is based, but it feels right to me as a ballpark. I have also been in plants where most of the equipment does not even reach that level.

Let’s consider a few examples:

OEE	=	Availability	x	Performance	x	Quality
	=	0.8	x	0.9	x	0.99
	=	0.71

The first example does not reach and OEE of .85.  One combination that does reach the world-class level is:

OEE	=	Availability	x	Performance	x	Quality
	=	0.9	x	0.95	x	0.99
	=	0.85

This combination still falls short:

OEE	=	Availability	x	Performance	x	Quality
	=	0.9	x	0.9	x	0.9
	=	0.73

It does not make much sense to make these calculations, unless we use the data. It is also important that we not use the data to beat people up, but to help us figure out where we need to focus our attention in order to improve.

One way to do this is to calculate the OEE for a given machine daily, at the machine. If the OEE is consistently .85 or better, there are probably other pieces of equipment that need our attention more than this one.    We still might want to ask whether this is an unusual level for this machine.  To know this, we would need to have a history.  I advocate not only manually calculating but also manually plotting OEE for each piece of equipment we are monitoring.   Here is a way to present the data. 

(Click on the image to enlarge it) 

On the graph we see that on Monday, the 5th, we suddenly had a drop to .15.  We should want to know what caused this drop.  Our first question: Was it a problem of availability, of performance, or of quality? A glance at the bottom of the chart, where the three components are recorded, we can tell immediately that or biggest problem was availability.  The machine was down.  We ought to find out right away what caused the machine to go down, so that we can take action to insure that this problem never happens again.

On Friday, the 9th,  we had another drop in OEE. A quick look at the data tells us that this time we had a problem with performance.  That is where we need to dig in to find out what happened and take corrective action.

Increasingly, calculations such as OEE are made by statistical packages into which data is, in some cases,collected automatically. Interesting high level graphs and reports can be generated. When I work with clients, I insist that the operator, at the machine, create this graph manually.  If we only have a report that comes out at the end of the week we miss an opportunity to act.  When OEE suddenly drops, we want to start asking what happened right away—the same day.  OEE charts on the machines that are being monitored can a part of visual control.

To begin to use OEE, I would not suggest that we start monitoring and charting every machine. Begin with some critical operations that we need to improve. Strive for consistency, then strive for improving OEE.  Some equipment may never need to be plotted because it is reliable and has a capacity far in excess of what we need.

World class OEE, .85 or better, is a factor to consider when ordering new equipment and calculating the needed capacity. 

I have had occasion to work with teams planning a new line and the equipment to be purchased for them. They planned as if the equipment would run at its stated capacity 100% or the time.  The improvements above .85 can be pretty challenging.  While part of achieving world class is demanding excellence of ourselves, plan with a .85 OEE in mind, nothing higher.

To get operators to record the data and make the calculations, we should explain that these data will help us solve problems around availability, performance, and quality.  Then, we need to earn credibility by using the data for that purpose.  It is discouraging to engage in an activity that does not add value to the product or the process.  Too often we start data collection and quickly forget why we are doing it. Start small.  Stay with it.  Show some results.  Spread the process from the early examples.

Notes: The Lean Thinker  has recently described how to calculate the three components of OEE. I chose to focus more on what to do with the OEE calculation, once you have it.  


While for reasons that I hope are clear, I object to capturing the data and doing the calculations in a centralized system.  I do not object to the operator having templates on a screen into which we can plug the data that give us the components and overall OEE that we then plot manually.

Leadership in the Workplace

I have mentioned that leadership places a crucial role in bringing out the best in people and the organization at the workplace.  We will explore the nature and role of leadership.

I have explored leadership with clients by contrasting it to management.  Management focuses on maintaining the states quo. This is important.  Organizations need to have consistency.  There need to be standard procedures.  Value-adding processes cannot accomplish their purpose without support around people, machines, methods, materials and measurement. These support systems need to be managed.

Leadership is focused on change.  If we want to move the organization to a new way of operating that is lean, world class, and brings out the best in people and systems, we often need to change the way we do things.  Many of my posts so far have been about things that need to change and how they need to be changed.

An Important Form to Speak with Data

One of the most useful forms for recording and presenting data, for speaking with data, is the production control form.  I am including a sample here.

This form tells us how a production line, a production cell, or a single production operation is running hour-by-hour.  When used to its greatest advantage, a manager or supervisor can walk through a department and tell very quickly what operations most require attention.  The leaner the operation, the more critical this information can be. The information is recorded each hour by a production operator.

In the example above, the first column divides the day into one hour blocks.  In this case, we have started at 7 a.m. and carried it through 4 p.m.  The information in this column can be modified depending on the start time and the length of the shift.  For example a ten hour shift would have a couple more rows.  The form can have extra rows to be used when the operation is running overtime. A chart for second or third shift would have appropriate time labels in the first column.

Quality Process and Quality Results

How do we assure that our customers receive the highest possible quality in our products?  The first thing that comes to many people’s minds is that we need to have plenty of inspection.  Defective products will get made and we need to catch them before they get to the customer.

Unfortunately, inspection (as well as various kinds of testing) does not catch every defect. No inspection process catches every defect.  Many let 20%, 30% and more escape.  Inspections can also catch products that turn out not to be defective.

In workshops, we demonstrate the unreliability of inspection by having each participant independently count the number of a certain letter (for example, “e”) that can be found in a text. All counters do not come up with the same number. If the letter were a defect, some would not be caught in the inspection process.

Inspection does not add value.  It only catches some of the defective products and leads us to other work that does not add value either, but does add cost.

Two Extremes

There are two extreme types of organization.  Most lie somewhere between the extremes.  At one end we have the World Class organization.  At the opposite end we have the Fire-fighting organization.

The obvious difference between the extremes is how smoothly they appear to run.  The World Class organization has few crises.  Things seem to run smoothly.  Problems arise, but they are quickly contained and soon prevented from happening again. 

The Fire-fighting organization is continuously fighting fires, rushing from one crisis to the next.  The same problems recur. Prevention is poor.  The World Class organization has a calm, laid-back feel to it.  The Fire-fighting organization has a frantic feel.

There are some less obvious characteristics that distinguish the two extremes.   In Fire- fighting organizations there is a lot of blaming.  Any problem will lead to fixing blame, or to wanting to fix blame.  In the World Class organization rather than asking who is to blame, we want to know what happened.  Sometimes the blaming or the desire to fix blame is personal.  It will also be focused on functions.  Production blames maintenance for not maintaining or fixing equipment.  Maintenance blames production for misusing the equipment and breaking it.  Production blames the quality organization for interfering with their ability to meet production goals.  Quality blames production for making “garbage.”  There is always someone else who bears the brunt of the responsibility.