Friday, September 18, 2015


Designing Structure to Help People Prevent Errors

Are we making slips or mistakes?

Dr. Donald Norman (1988) presented two fundamental categories of errors that people make while interacting with work processes and systems:

  • Slips: …result from automatic behavior, when subconscious actions that are intended to satisfy our goals get waylaid en route.
  • Mistakes: …result from conscious deliberations
Norman warns us that the same mental processes that make us creative and insightful by allowing us to see relationships between apparently unrelated things, that let us leap to correct conclusions on the basis of partial or even faulty evidence, also lead to error.

Slips

All of us experience making slips each day. In fact the more skilled we are the more prone we are to simple slips. For example, when learning how to drive, we usually do not pull out in front of another vehicle without really paying attention. All of us as skilled drivers have probably experienced the horror of looking quickly and then pulling from the curb and almost being hit by another driver. People learning to drive will look two or three times, paying great attention and then only pull from the curb when the “coast is clear.” Slips are almost always small things and can be readily fixed. They are generally more embarrassing than dangerous. Norman has defined six types of slips:

 Types of slips:

  1. Capture errors
  2. Description errors
  3. Data-driven errors
  4. Associative activation errors
  5. Loss-of-activation errors
  6. Mode errors
Let’s consider each type of slip and an example in real life:

Capture Errors - A frequently done activity suddenly takes charge instead of the one you intended. The capture error usually happens when two different actions sequences have their initial stages in common. For example, it is a nice Saturday morning and your spouse asks you to drive to the store and pick up some orange juice for breakfast. You pull out of the driveway and start on your journey. The next thing you know you are pulling up to park at your workplace! The routine of driving to work has captured your intended action of driving to the store.

Description Errors - The intended action has much in common with others that are possible. As a result, unless the action sequence is completely and precisely specified, the intended action might fit several possibilities. For example, many of us who travel a lot have had the experience of coming from a client meeting, finding our rental car and then after some difficulty of attempting to get into the car, find we have the wrong car. Apparently, Ford has made several white Ford Taurus vehicles. Much to our embarrassment, we then start looking for the car we rented that morning.

 Data-Driven Errors - Automatic actions are data-driven, triggered by the arrival of the sensory data. But sometimes data-driven activities can intrude into an ongoing action sequence, causing behavior that was not intended. For example, while checking into a hotel, the clerk took a phone call from another guest who was calling for a wake-up call. The clerk then got off the phone and informed me that I would be in room 630. I mentioned to him, that earlier he said I would be on the first floor. He then confessed that he just took a call to wake a guest at 6:30 and had confused it with my room number.  I would be in room 110.

Associative Activation Errors
As we have noted, external data can trigger actions. Internal thoughts and associations can also lead to slips. For example, while watching TV the telephone rings on the show I am watching; not realizing the telephone ring is from the television show, I pick up my own phone and greet a dial tone! Associative activation errors can also come from associations between thoughts and ideas.  When we are in a social situation and are thinking we should not say something that might be inappropriate, and then to our shock and surprise we say it!

Loss-Of-Activation Errors

Many of us have committed this error and attributed to ourselves that age must be taking it toll on our mental abilities. Lack-of-activations errors occur because the presumed mechanism -- the activation of the goals, has decayed. For example, we walk from one room to another. Finding ourselves in the room, we are suddenly struck with the reality; why are we in this room? Looking around frantically, we cannot remember why we made the trip. We then go back to the room from whence we came to be “activated.” Looking around, we suddenly remember and then will renewed determination return to the other room to complete the action.

Mode Errors

Mode errors occur when devices have different modes of operation, and the action appropriate for one mode has different meanings in other modes. For example, on Microsoft Outlook I can make distribution lists to send certain types of communication to identified groups of people. A fantastic time saver! Periodically, I find it necessary to edit this list. When I select the entry to be deleted, I read from left to right and find the delete button and click. To my surprise, I have now deleted the entire list! The correct button is further to the right under “Members.” See Figure 1 for the example.
 
Figure 1: Mode Error Example on Outlook 
 
  In the next installments of this conversation we will cover the following topics:
 
    • Design lessons from the study of slips
    • More on the nature of mistakes
    • Creating structure to help people avoid slips and mistakes


Reference:

  1. Psychology of Everyday Things, Donald A. Norman, Basic Books, 1988


 

Monday, June 1, 2015

Cheating on Standardized Tests and Systems Arch Types


Peter Senge introduced the mainstream business community to system archetypes in his book, The Fifth Discipline. These arch types describe patterns of behavior of a system. Systems that we take for granted can be expressed by circles of causality. By understanding the system arch types, we can understand the system at a deeper level and identify leverage points which enables efficient changes in a system.

Let’s consider a recent example. The map below is a Systems Dynamic Model that explains the reinforcing loops that encourage cheating by teachers on standardized tests. Recently, several teachers were sentenced to prison terms over a cheating scandal in Atlanta, Georgia. By using over-justification schemes, we have turned honest people into criminals.





 Reference: https://www.leveragenetworks.com/blog/teacher-cheating-dynamics-scandal-or-scapegoating

Dr. W. Edwards Deming would be livid. When people are put into impossible situations with goals and targets that cannot be met under the current system, you get unintended consequences. We have seen it with nurses falsifying reports to achieve targets and teachers in Atlanta changing test scores. Charles Goodhart's law sheds light on this problem; "When a measure becomes a target, it ceases to be a good measure."  

It would be interesting to see a model for health care with the advent of P4P (pay for performance) schemes. Fraud headlines will be coming soon. Here we will have “goals gone wild” turning professionals into crooks.

Wednesday, December 31, 2014

"When a measure becomes a target, it ceases to be a good measure." Charles Goodhart (1975)[i]

From the Telegraph, UK: “In February 2010, the first report into the scandal of appalling nursing at Stafford Hospital — where patients were left in filthy sheets, their dressings unchanged while nurses shouted at and mocked them — concluded that in order to achieve the coveted Foundation status, the hospital trust’s management had become obsessed with meeting government targets rather than looking after the patients…Nurses elsewhere endlessly repeat this complaint. Everything has to be documented. Everything is driven by ‘performance targets’ which have to be audited.”[ii] “ Meanwhile, nurses were instructed by senior nurse colleagues to falsify waiting times, and to claim that patients had been seen more quickly than they were.”[iii]

From the healthcare example, we can see the effects of Charles Goodhart’s insightful quote on the use of targets and unintended consequences. Dr. W. Edwards Deming was more direct and to the point; “Fear invites wrong figures.”[iv]

When leaders and managers employ the use of numerical goals, the intent is usually to cause improvement as opposed to using the measure for judgment. Deming noted three unintended consequences of numerical goals: 

“Will a numerical goal be achieved? Anybody can achieve almost any goal by:
• Redefinition of terms
• Distortion and faking
• Running up costs”[v]

The unintended consequences of goals and targets where there is no method is pervasive throughout industry, government, healthcare and education. We have had several attempts to improve education over the last three decades. This has led to teachers being fired and charged criminally.[vi] Donald T. Campbell warned of this problem in what has become known as Campbell's law:

"The more any quantitative social indicator (or even some qualitative indicator) is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor."
Associates in Process Improvement (API) has attempted to strike a balance on the use of goals and targets:[vii]

“Advice about the use of numerical goals in setting an aim for an improvement project could include “Never use them” or “Always provide one and let other people figure out how to achieve it.” This book’s authors recognize the abuses associated with numerical goals and the potential unintended consequences when people are held responsible for results they are not capable of achieving…We do not believe these instances of poor practice or abuse should preclude beneficial use of numerical goals.

We also recognize some hardy souls need only the challenge of a numerical goal to find ways to actually improve the system. Our experience indicates that a middle ground between these two extremes is achievable and useful.

First and foremost, numerical goals must be connected to methods for achieving the goals. Leaders should understand that to improve a stable system beyond the current level of performance a fundamental change is needed…here are some initial considerations to develop methods for achieving numerical goals:

  • Observe other organizations that have accomplished similar goals.
  • Give some basic concepts or ideas that could feasibly result in achieving the goal.
  • Draw out ideas from participants themselves by asking questions such as, “What would it take to get a 50 percent reduction in time to ship an order?” From the healthcare example above; what would it take to reduce wait time and patient harm?
  • Ask experts on the changes being considered what level of improvement is possible.
Numerical goals can also be a convenient way to communicate expectations. What are the consequences of not meeting the numerical goal? Are small and incremental improvements expected, or are large breakthrough changes necessary? If the numerical goal is used well, it communicates not only the expectation but also the support that will be offered. Large changes to big systems usually require investment of time and capital. When first using a goal to break the current bounds of the status quo, leaders must furnish:

  • An explanation of the need for and feasibility of the goal
  • Assurances the goals will be used to cause new thinking and learning, and not for judgment
Systems thinking informs us that one can create the illusion of improvement by only focusing on one measure of the system. Improvement requires that we focus on multiple measures to mitigate the unintended consequences noted by Deming. Specifically, three types of measures can be used to ensure a fundamental change in patient waiting time:
  • Outcome Measures – Waiting Time
  • Process Measures – Number of patients scheduled; number of drop in patients
  • Balancing Measures – Cost per patient; patient satisfaction. 
Please note the bold and underlined statement used earlier; First and foremost, numerical goals must be connected to methods for achieving the goals. This is directly from our learning from Deming and has been verified in our work experience in API. A project where the solution is unknown, may not have a method. This has to be developed. Deming would chide his audiences; “If you have a method, why did you not do it last year? There can be only one reason; you were goofing off.” Of course this got a laugh, but there is a lesson here as well. The people with whom we are working usually have full time jobs. Taking time to develop, test and implement changes in the unknown, is already a daunting task. What they need is help from sponsors, not expectations for more judgment; they already have plenty of that. So if the sponsor is showing up and removing barriers and doing their part, they will have a good idea of when the team is to be finished. Deming would call this “substituting leadership.”

References:


[i] Goodhart, C.A.E. (1975). "Problems of Monetary Management: The U.K. Experience". Papers in Monetary Economics (Reserve Bank of Australia) I.
[iii] http://www.telegraph.co.uk/health/healthnews/9851763/Mid-Staffordshire-Trust-inquiry-how-the-care-scandal-unfolded.html
[iv] W. Edwards Deming. The New Economics for Industry, Government, Education (p. 94)
[v] W. Edwards Deming. The New Economics for Industry, Government, Education (p. 43).
[vii] Langley, Gerald J.; Moen, Ronald D.; Nolan, Kevin M.; Nolan, Thomas W.; Norman, Clifford L.; Provost, Lloyd P. (2009-06-03). The Improvement Guide: A Practical Approach to Enhancing Organizational Performance (Kindle Locations 1916-1918). Wiley Publishing. Kindle Edition.

Friday, December 12, 2014

Where are all the Innovative – Cuddly leaders?

The temptation of consultants and others is to reform leaders based on our personal perspectives; what good leadership means to us personally. This can mean the projection of our personality type on the leader.

Let’s review the basic personality types. Maccoby and Scudder (2010) have offered the following description of the evolution of the theory of personality as developed by Sigmund Freud and Erich Fromm:

Sigmund Freud first used his model to help explain psychopathology, but he also employed it to describe three normal personality types he called:

1.  Erotic – a caring personality with a strong value of loving and caring relationship. Fromm’s work refers to the non-productive version of this type as the Receptive Orientation.
2.    Narcissistic – independent and not open to intimidation; characterized by an ego with a large amount of aggressiveness at its disposal, which also manifests itself in a readiness for activity. Fromm’s work refers to the non-productive version of this type as the Exploitative Orientation.
3. Obsessive – ideals of hard work and conscientiousness; characterized by a demanding super-ego, strong commands programmed in childhood. Fromm’s work refers to the non-productive version of this type as the Hoarding Orientation.

Erich Fromm described the non-productive orientations and their related productive characteristics in an effort to move people toward increased productivity. He accepted and modified Freud’s types and added a fourth type to Freud's trio; the marketing personality. Just as the obsessive personality is the bureaucratic prototype; the marketing personality fits the typical Interactive Social Character.

4. Marketing – the ego-ideal is radar-like, orienting behavior to what is "appropriate" according to group values and pressures; to avoid looking bad.

Dr. Michael Maccoby has described the four basic types of personality developed by Freud and Fromm as the Caring, Visionary, Exacting and Adaptive. These terms are very much in line with the original work from Freud and Fromm.

Many books on leadership are written from the perspective of the leader being caring. When the author develops this scenario of the “caring boss,” they may be projecting on to the leader those traits they value. Circumstances and context often define the need for other strengths in our leaders. Maccoby observed that many of the leaders he encountered were far from cuddly; in fact some, at times, could be downright mean. This dissonance in what authors found desirable versus the reality caused Maccoby to reflect on his past and present work with leaders (the following is taken from Narcissistic Leaders ---Who succeeds and who fails.):

“The emergence of a new kind of leader caused me to reexamine all of my theories about leaders and personality. I went back to the psychoanalytic teachings of Sigmund Freud and the psychoanalyst and social philosopher Erich Fromm (1900– 1980) and sifted through thirty years of experience inside corporations, working with CEOs both as a consultant and psychoanalyst.

I rethought my understanding of historical figures and literature. What emerged surprised me. The psychological portrait of today’s business leaders that takes into account their personality traits, describing how they achieve innovations, engage followers, and react to the euphoria of success as well as the stress of setbacks, most closely fits the normal personality type that Freud called narcissistic: “People belonging to this type impress others as being ‘personalities’; they are especially suited to act as a support for others, to take on the role of leaders and to give a fresh stimulus to cultural development or to damage the established state of affairs.” In other words, these are the type of people who are most likely to say that they want to change the world.

I’m using the term “narcissism” to describe some of the most important business leaders in the world; but how could a word that’s become synonymous with all sorts of self-centered behavior—a sense of overall superiority and entitlement, a lack of empathy or understanding of others, the need for constant attention and admiration, and overall arrogance— apply to them? These days, in both the psychiatric field and in colloquial conversation, “narcissism” has become a term for egoism, egocentricity, or just plain bad manners. But I believe the concept of narcissism has been widely misunderstood ever since Freud coined it after Ovid’s pathologically self -involved creature from Greek mythology. I want to bring about a radical new definition of the term and the way we think about leadership, and show you how your understanding of productive narcissism can help you.

The type of person who impresses us as a personality, who disrupts the status quo and brings about change. Narcissists have very little or no psychic demands that they have to do the right thing. Freed from these internal constraints, they are forced to answer, for themselves, what is right, to decide what they value, what, in effect, gives them a sense of meaning. They create their own vision, a sense of purpose that not only engages them but also inspires others to follow them.”

Maccoby also identified the strengths and weaknesses of the Productive Narcissist:

STRENGTHS OF THE PRODUCTIVE NARCISSIST

        Visioning to change the world and create meaning
        Independent thinking/ risk taking
        Passion
        Charisma
        Voracious learning
        Perseverance
        Alertness to threats
        Sense of humor

WEAKNESSES OF THE PRODUCTIVE NARCISSIST

        Extreme sensitivity to criticism
        Not listening
        Paranoia
        Extreme competitiveness
        Anger and put-downs
        Exaggeration
        Lack of self-knowledge
        Isolation
        Grandiosity

When the weaknesses manifest themselves in the leader, these weaknesses are then targeted to be “fixed” by authors, consultants and others.  Unfortunately, these weaknesses come with the strengths. The leader, if aware, can learn to mitigate these weaknesses, but from time to time, given the circumstances, they may rear their ugly head.

We have focused on the Productive Narcissist (Visionary) leader. However, the other basic types of personality all have strengths and weaknesses. For more on the other types and more importantly, how to have a productive relationship with your Productive Narcissistic Boss, we highly recommend reading Maccoby’s book; Narcissistic Leaders ---Who succeeds and who fails.


References:


Maccoby, Michael and Tim Scudder, Becoming A Leader We Need with Strategic Intelligence (2010).   Note graphic and narrative are taken from p. 92 of this workbook.

Thursday, December 12, 2013

Jack Welch and the Gymnastics of Self-Justification


The following post is a comment on the link below which will take you to an article by Jack and Suzy Welch:


This article reminds me of the process reengineering aftermath when the authors tried to rewrite history on “shooting the wounded,” getting rid of people etc. The authors wrote article after article saying they were misunderstood. Regardless “Process Reengineering” became a synonym for getting rid of people. The ability for self-justification is a human trait that we all possess; intelligent people are even more adapt at this core competency. Welch is obviously practicing in this article.

 Still, the fundamentals are still wrong. Deming’s equation comes to mind:

·         X=Individual

·         Y=System

·         X + [XY] = 8

As Deming would note, “One equation and two unknowns, unsolvable.” In many organizations the system in not under suspicion.  Management merely sets Y = 0 and then attributes the results to X. 

Leadership should be up close and personal. If this is the case, then it will be obvious who is contributing and who is not. We have witnessed several people who have been let go in organizations over the years. Typically, it is obvious to everyone that the person does not fit. Tragically, even though this is apparent to everyone, the separation process goes on way too long for the health and morale of the organization. It is usually very difficult for leaders to admit that they have hired someone who does not fit. Meanwhile the organization suffers, relationships with customers are damaged and the firm still faces the evitable change that must take place.

Deming used to identify “substitutes for leadership.” Yank and Rank was certainly a poor substitute. 



Monday, June 3, 2013

Why is stability of the data so important?

Recently on a popular Six Sigma site the following question appeared:

 "I have a question if I have variable data ( that is not normally distributed) I then transferred it to Attribute data and worked out the DPMO from the opps/defects. If the DPMO is normally distributed can I carry on using stats such at t – tests etc. Or because it is originally attribute data I should use chi squared etc? Any advise appreciated."

From this question, you could run a three day workshop. My short attempt at an answer included:

"As others have said, stay with the continuous data. Before doing anything else put the data on an appropriate control chart and learn from the special causes. As Shewhart noted: things in nature are stable, man made processes are inherently unstable. I have taken this from Shewhart’s postulates. T test and other tests all rest on the assumption of IID; Independent and Identically Distributed. If there are special causes present these assumptions are violated and the tests are useless. Even though the “control chart” show up in DMAIC under C for many novices, it should be used early. Getting the process that produced the data stable is an achievement. It is also where the learning should start. Calculating DPMO, and other outcome measures can come later; after learning and some work. Best, Cliff"

Why the fixation on outcomes, calculating capability, DPMO and the like?  Without any knowledge about stability of the data such calculations are very misleading. In 1989, I sat in a workshop where Dr. W. Edwards Deming made the following comment, "It will take another 60 years before Shewhart's ideas are appreciated." At the time, I thought he was nuts. Control charts were everywhere. Then they disappeared. Now I see Deming as a prophet.

Historically, we are going through a period in improvement science that is not unlike the dark ages. We have people grasping for easy path and quick answers generated by the computer that might as well be "unmanned." Getting the process stable is an achievement! Our first move with statistical software should not be a normality check, but a check of the data to see if we have data that is stable and predictable. If we have such a state, then our quality, costs and productivity are predictable. Without this evidence, we are flying blind.

Thursday, March 14, 2013

We are doing a 4.5 Sigma program?

Dr. Bill Latzko has published a very short and informative paper on the ideas underlying the Six Sigma program. Advocates of Six Sigma often talk about achieving Six Sigma quality meaning 3.4 parts per million. Latzko discusses this and the assumptions in this great paper:

http://www.latzko-associates.com/Publications/SIX_Sig.pdf

Dr. Taguchi idea of reducing variation around a target should be studied and understood by those who are interested improvement. Focusing on meeting specifications has been a step backward that Deming warned us about in his last book: “Conformance to specifications, zero defects, Six Sigma Quality, and all other (specification-based) nostrums all miss the point.”

We can do better.