Unintended consequences come in many forms and have many causes.  “Revenge effects” are a special category of unintended consequences, created by the introduction of a technology, policy, or both that produces outcomes in contradiction to the desired result.  Revenge effects may exacerbate the original problem or create a new situation that is equally undesirable if not more objectionable.
     Discussions of revenge effects often focus on technology – the most tangible cause of a predicament.  However, “[t]echnology alone usually doesn’t produce a revenge effect.”  It is typically the combination of technology, policy, (laws, regulations, etc.), and behavior that endows a decision with the power to frustrate its own intent.
     This installment of “The Third Degree” explores five types of revenge effects, differentiates between revenge and other effects, and discusses minimizing unanticipated unfavorable outcomes.

     The Law of Unintended Consequences can be stated in many ways.  The formulation forming the basis of this discussion is as follows:
“The Law of Unintended Consequences states that every decision or action produces outcomes that were not motivations for, or objectives of, the decision or action.”
     Like many definitions, this statement of “the law” may seem obscure to some and obvious to others.  This condition is often evidence of significant nuance.  In the present case, much of the nuance has developed as a result of the morphing use of terms and the contexts in which these terms are most commonly used.
     The transformation of terminology, examples of unintended consequences, how to minimize negative effects, and more are explored in this installment of “The Third Degree.”

     An organization’s safety-related activities are critical to its performance and reputation.  The profile of these activities rises with public awareness or concern.  Nuclear power generation, air travel, and freight transportation (e.g. railroads) are commonly-cited examples of high-profile industries whose safety practices are routinely subject to public scrutiny.
     When addressing “the public,” representatives of any organization are likely to speak in very different terms than those presented to them by technical “experts.”  After all, references to failure modes, uncertainties, mitigation strategies, and other safety-related terms are likely to confuse a lay audience and may have an effect opposite that desired.  Instead of assuaging concerns with obvious expertise, speaking above the heads of concerned citizens may prompt additional demands for information, prolonging the organization’s time in an unwanted spotlight.
     In the example cited above, intentional obfuscation may be used to change the beliefs of an external audience about the safety of an organization’s operations.  This scenario is familiar to most; myriad examples are provided by daily “news” broadcasts.  In contrast, new information may be shared internally, with the goal of increasing knowledge of safety, yet fail to alter beliefs about the organization’s safety-related performance.  This phenomenon, much less familiar to those outside “the safety profession,” has been dubbed “probative blindness.”  This installment of “The Third Degree” serves as an introduction to probative blindness, how to recognize it, and how to combat it.

     Another way to Be A Zero – in a good, productive way – is to operate on a zero-based schedule.  An organization’s time is the aggregate of individuals’ time and is often spent carelessly.  When a member of an organization spends time on any endeavor, the organization’s time is being spent.  When groups are formed, the expenditure of time multiplies.  Time is the one resource that cannot be increased by persuasive salespeople, creative marketing, strategic partnerships, or other strategy; it must be managed.
     “Everyone” in business knows that “time is money;” it only makes sense that time should be budgeted as carefully as financial resources.  Like ZBB (Zero-Based Budgeting – Part 1), Zero-Based Scheduling (ZBS) can be approached in two ways; one ends at zero, the other begins there.

     Interest in Zero-Based Budgeting (ZBB) is somewhat cyclical, rising in times of financial distress, nearly disappearing in boom-times.  This can be attributed, in large part, to detractors instilling fear in managers by depicting it as a “slash and burn” cost-cutting, or downsizing, technique.  This is a gross misrepresentation of the ZBB process.
     ZBB is applicable to the public sector (various levels of government), private sector (not-for-profit and commercial businesses), and the very private sector (personal finances).  Each sector is unique in its execution of ZBB, but the principle of aligning expenditure with purpose is consistent throughout.
     This installment of “The Third Degree” describes the ZBB process in each sector, compares it to “traditional” budgeting, and explores its advantages and disadvantages.  Alternative implementation strategies that facilitate matching the ZBB approach to an organization’s circumstances are also presented.

     To be effective in any pursuit, one must understand its objectives and influences.  One influence, typically, has a greater impact on process performance than all others – the dominant characteristic of the process.  The five main categories of process dominance are worker, setup, time, component, and information.
     Processes require tools tailored to manage the dominant characteristic; this set of tools comprises a process control system.  The levels of Operations Management at which the tools are employed, or the skills and responsibility for process performance reside, differ among the types of dominance.
     This installment of “The Third Degree” explores categories of process dominance, tools available to manage them, and examples of processes with each dominant characteristic.  Responsibility for control of processes exhibiting each category of dominance will also be discussed in terms of the “Eight Analogical Levels of Operations Management.”

     Effective Operations Management requires multiple levels of analysis and monitoring.  Each level is usually well-defined within an organization, though they may vary among organizations and industries.  The size of an organization has a strong influence on the number of levels and the makeup and responsibilities of each.
     In this installment of “The Third Degree,” one possible configuration of Operations Management levels is presented.  To justify, or fully utilize, eight distinct levels of Operations Management, it is likely that an organization so configured is quite large.  Therefore, the concepts presented should be applied to customize a configuration appropriate for a specific organization.

     Standards and guidelines published by industry groups or standards organizations typically undergo an extensive review process prior to acceptance.  A number of drafts may be required to refine the content and format into a structure approved by a committee of decision-makers.
     As one might expect, the draft review and approval process is not consistent for every publication.  The number of drafts, time to review, and types of changes requested will vary.  Though each review is intended to be rigorous, errors often remain in the approved publication.  The content may also require interpretation to employ effectively.
     This is certainly true of the aligned AIAG/VDA FMEA Handbook.  In this installment of the “FMEA” series, the Handbook’s errors and omissions, opacities and ambiguities will be discussed.  Where possible, mistakes will be corrected, blanks filled in, and clarity provided in pursuit of greater utility of the Handbook for all FMEA practitioners.

     The AIAG/VDA FMEA Handbook presents standard and alternate form sheets for Design, Process, and Supplemental FMEA.  The formats presented do not preclude further customization, however.  In this installment of the “FMEA” series, suggested modifications to the standard-format form sheets are presented.  The rationale for changes is also provided to facilitate practitioners’ development of the most effective documentation for use in their organizations and by their customers.

     No matter how useful or well-written a standard, guideline, or instruction is, there are often shortcuts, or “tricks,” to its efficient utilization.  In the case of the aligned AIAG/VDA Failure Modes and Effects Analysis method, one trick is to use visual Action Priority tables.
     In this installment of the “FMEA” series, use of visual tables to assign an Action Priority (AP) to a failure chain is introduced.  Visual aids are used in many pursuits to provide clarity and increase efficiency.  Visual AP tables are not included in the AIAG/VDA FMEA Handbook, but are derived directly from it to provide these benefits to FMEA practitioners.

     As mentioned in the introduction to the AIAG/VDA aligned standard (“Vol. V:  Alignment”), the new FMEA Handbook, is a significant expansion of its predecessors.  A substantial portion of this expansion is the introduction of a new FMEA type – the Supplemental FMEA for Monitoring and System Response (FMEA-MSR).
     Modern vehicles contain a plethora of onboard diagnostic tools and driver aids.  The FMEA-MSR is conducted to evaluate these tools for their ability to prevent or mitigate Effects of Failure during vehicle operation.
     Discussion of FMEA-MSR is devoid of comparisons to classical FMEA, as it has no correlate in that method.  In this installment of the “FMEA” series, the new analysis will be presented in similar fashion to the previous aligned FMEA types.  Understanding the aligned Design FMEA method is critical to successful implementation of FMEA-MSR; this presentation assumes the reader has attained sufficient competency in DFMEA.  Even so, review of aligned DFMEA (Vol. VI) is highly recommended prior to pursuing FMEA-MSR.

     To conduct a Process FMEA according to AIAG/VDA alignment, the seven-step approach presented in Vol. VI (Aligned DFMEA) is used.  The seven steps are repeated with a new focus of inquiry.  Like the DFMEA, several system-, subsystem-, and component-level analyses may be required to fully understand a process.
     Paralleling previous entries in the “FMEA” series, this installment presents the 7-step aligned approach applied to process analysis and the “Standard PFMEA Form Sheet.”  Review of classical FMEA and aligned DFMEA is recommended prior to pursuing aligned PFMEA; familiarity with the seven steps, terminology used, and documentation formats will make aligned PFMEA more comprehensible.

     To differentiate it from “classical” FMEA, the result of the collaboration between AIAG (Automotive Industry Action Group) and VDA (Verband der Automobilindustrie) is called the “aligned” Failure Modes and Effects Analysis process.  Using a seven-step approach, the aligned analysis incorporates significant work content that has typically been left on the periphery of FMEA training, though it is essential to effective analysis.
     In this installment of the “FMEA” series, development of a Design FMEA is presented following the seven-step aligned process.  Use of an aligned documentation format, the “Standard DFMEA Form Sheet,” is also demonstrated.  In similar fashion to the classical DFMEA presentation of Vol. III, the content of each column of the form will be discussed in succession.  Review of classical FMEA is recommended prior to attempting the aligned process to ensure a baseline understanding of FMEA terminology.  Also, comparisons made between classical and aligned approaches will be more meaningful and, therefore, more helpful.

     Suppliers producing parts for automotive manufacturers around the world have always been subject to varying documentation requirements.  Each OEM (Original Equipment Manufacturer) customer defines its own requirements; these requirements are strongly influenced by the geographic location in which they reside.
     In an effort to alleviate confusion and the documentation burden of a global industry, AIAG (Automotive Industry Action Group) of North America and VDA (Verband der Automobilindustrie) of Germany jointly published the aligned “FMEA Handbook” in 2019.  Those experienced with “classical” FMEA (Vol. III, Vol. IV) will recognize its influence in the new “standard;” however, there are significant differences that require careful consideration to ensure a successful transition.

     Preparations for Process Failure Modes and Effects Analysis (Process FMEA) (see Vol. II) occur, in large part, while the Design FMEA undergoes revision to develop and assign Recommended Actions.  An earlier start, while ostensibly desirable, may result in duplicated effort.  As a design evolves, the processes required to support it also evolve; allowing a design to reach a sufficient level of maturity to minimize process redesign is an efficient approach to FMEA.
     In this installment of the “FMEA” series, how to conduct a “classical” Process FMEA (PFMEA) is presented as a close parallel to that of DFMEA (Vol. III).  Each is prepared as a standalone reference for those engaged in either activity, but reading both is recommended to maintain awareness of the interrelationship of analyses.

     In the context of Failure Modes and Effects Analysis (FMEA), “classical” refers to the techniques and formats that have been in use for many years, such as those presented in AIAG’s “FMEA Handbook” and other sources.  Numerous variations of the document format are available for use.  In this discussion, a recommended format is presented; one that facilitates a thorough, organized analysis.
     Preparations for FMEA, discussed in Vol. II, are agnostic to the methodology and document format chosen; the inputs cited are applicable to any available.  In this installment of the “FMEA” series, how to conduct a “classical” Design FMEA (DFMEA) is presented by explaining each column of the recommended form.  Populating the form columns in the proper sequence is only an approximation of analysis, but it is a very useful one for gaining experience with the methodology.

     Prior to conducting a Failure Modes and Effects Analysis (FMEA), several decisions must be made.  The scope and approach of analysis must be defined, as well as the individuals who will conduct the analysis and what expertise each is expected to contribute.
     Information-gathering and planning are critical elements of successful FMEA.  Adequate preparation reduces the time and effort required to conduct a thorough FMEA, thereby reducing lifecycle costs, as discussed in Vol. I.  Anything worth doing is worth doing well.  In an appropriate context, conducting an FMEA is worth doing; plan accordingly.

     Destructive behaviors existed in organizations long before they were given special names.  The term “cancel culture” is not typically associated with business environments, but its pernicious effects are prevalent.  Unlike a boycott, cancel culture destroys an organization from within, through covert and fraudulent actions.
     Cancel culture effects all levels of an organization, but “managerial schizophrenia” is a common precursor and potent ingredient.  Adverse behaviors signal abandonment of cultural and professional norms, the subsequent failures of collaboration, and the resultant degradation in group performance.  Combatting these intertwined organizational cancers requires commitment from all levels of management and revised methods of oversight.

     Thus far, the “Making Decisions” series has presented tools and processes used primarily for prioritization or single selection decisions.  Decision trees, in contrast, can be used to aid strategy decisions by mapping a series of possible events and outcomes.
     Its graphical format allows a decision tree to present a substantial amount of information, while the logical progression of strategy decisions remains clear and easy to follow.  The use of probabilities and monetary values of outcomes provides for a straightforward comparison of strategies.

     A Pugh Matrix is a visual aid created during a decision-making process. It presents, in summary form, a comparison of alternatives with respect to critical evaluation criteria.  As is true of other decision-making tools, a Pugh Matrix will not “make the decision for you.”  It will, however, facilitate rapidly narrowing the field of alternatives and focusing attention on the most viable candidates.
     A useful way to conceptualize the Pugh Matrix Method is as an intermediate-level tool, positioned between the structured, but open Rational Model (Vol. II) and the thorough Analytic Hierarchy Process (AHP, Vol. III).  The Pugh Matrix is more conclusive than the former and less complex than the latter.

     Committing resources to project execution is a critical responsibility for any organization or individual.  Executing poor-performing projects can be disastrous for sponsors and organizations; financial distress, reputational damage, and sinking morale, among other issues, can result.  Likewise, rejecting promising projects can limit an organization’s success by any conceivable measure.
     The risks inherent in project selection compels sponsors and managers to follow an objective and methodical process to make decisions.  Doing so leads to project selection decisions that are consistent, comparable, and effective.  Review and evaluation of these decisions and their outcomes also becomes straightforward.

     Choosing effective strategies for waging war against error in manufacturing and service operations requires an understanding of “the enemy.”  The types of error to be combatted, the sources of these errors, and the amount of error that will be tolerated are important components of a functional definition (see Vol. I for an introduction).
     The traditional view is that the amount of error to be accepted is defined by the specification limits of each characteristic of interest.  Exceeding the specified tolerance of any characteristic immediately transforms the process output from “good” to “bad.”  This is a very restrictive and misleading point of view.  Much greater insight is provided regarding product performance and customer satisfaction by loss functions.

     Regardless of the decision-making model used, or how competent and conscientious a decision-maker is, making decisions involves risk.  Some risks are associated with the individual or group making the decision.  Others relate to the information used to make the decision.  Still others are related to the way that this information is employed in the decision-making process.
     Often, the realization of some risks increases the probability of realizing others; they are deeply intertwined.  Fortunately, awareness of these risks and their interplay is often sufficient to mitigate them.  To this end, several decision-making perils and predicaments are discussed below.

     Myriad tools have been developed to aid collaboration of team members that are geographically separated.  Temporally separated teams receive much less attention, despite this type of collaboration being paramount for success in many operations.
     To achieve performance continuity in multi-shift operations, an effective pass-down process is required.  Software is available to facilitate pass-down, but is not required for an effective process.  The lowest-tech tools are often the best choices.  A structured approach is the key to success – one that encourages participation, organization, and consistent execution.

     Lesser known than Six Sigma, but no less valuable, the Shainin System is a structured program for problem solving, variation reduction, and quality improvement.  While there are similarities between these two systems, some key characteristics lie in stark contrast.
     This installment of “The War on Error” introduces the Shainin System, providing background information and a description of its structure.  Some common problem-solving tools will also be described.  Finally, a discussion of the relationship between the Shainin System and Six Sigma will be presented, allowing readers to evaluate the potential for implementation of each in their organizations.