In common language, “materiality” could be replaced with “importance” or “relevance.”  In a business setting, however, the word has greater significance; no adequate substitute is available.  In this context, materiality is not a binary characteristic, or even a one-dimensional spectrum; instead it lies in a two-dimensional array.
     Materiality has been defined in a multitude of ways by numerous organizations.  Though these organizations have developed their definitions independently, to serve their own purposes, there is a great deal of overlap in both.  Perhaps the simplest and, therefore, most broadly-applicable description of materiality was provided by the GHG Protocol:
“Information is considered to be material if, by its inclusion or exclusion, it can be seen to influence any decisions or actions taken by users of it.”
     Recognizing the proliferation and potential risk of divergent definitions, several organizations that develop corporate reporting standards and assessments published a consensus definition in 2016:
“Material information is any information which is reasonably capable of making a difference to the conclusions reasonable stakeholders may draw when reviewing the related information.” (IIRC, GRI, SASB, CDP, CDSB, FASB, IASB/IFRS, ISO)
     The consensus definition is still somewhat cryptic, only alluding to the reason for its existence – corporate financial and ESG (Environmental, Social, Governance) reporting.  As much can be surmised from the list of signatory organizations as from the definition itself.

     Claims about the impact of sustainability initiatives – or the lack thereof – on a company’s financial performance are prevalent in media.  Claims cover the spectrum from crippling, through negligible, to transformative.  Articles making these claims target audiences ranging from corporate executives to non-industry activists, politicians, and regulators.  Likewise, the articles cite vastly differing sources to support claims.
     These articles are often rife with unsupported claims and inconsistencies, are poorly sourced, poorly written, and dripping with bias.  The most egregious are often rewarded with “likes,” “shares,” and additional “reporting” by equally biased purveyors of “the word.”  These viewpoint warriors create a fog of war that makes navigating the mine-laden battlefield of stakeholder interests incredibly treacherous.
     The fog of war is penetrated by stepping outside the chaos to collect and analyze relevant information.  To do this in the sustainability vs. profitability context, a group from NYU Stern Center for Sustainable Business have developed the Return on Sustainability Investment (ROSI) framework.  ROSI ends reliance on the incessant cascades of conflicting claims, providing a structure for investigating the impacts of sustainability initiatives on an organization’s financial performance.

     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.”

     October 7, 2022 is National Manufacturing Day in the United States.  It is a day of special events introducing future professionals to myriad career opportunities in a variety of manufacturing industries.  One day isn’t really enough, though, is it?  The entire month of October is dedicated to promoting the impact manufacturing industries can have on a region’s economy, quality of life, and individuals’ career satisfaction.

     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.

     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.

     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.

     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.

     An effective safety program requires identification and communication of hazards that exist in a workplace or customer-accessible area of a business and the countermeasures in place to reduce the risk of an incident.  The terms hazard, risk, incident, and others are used here as defined in “Safety First!  Or is It?”
     A hazard map is a highly-efficient instrument for conveying critical information regarding Safety, Health, and Environmental (SHE) hazards due to its visual nature and standardization.  While some countermeasure information can be presented on a Hazard Map, it is often more salient when presented on a corollary Body Map.  Use of a body map is often a prudent choice; typically, the countermeasure information most relevant to many individuals pertains to the use of personal protective equipment (PPE).  The process used to develop a Hazard Map and its corollary Body Map will be presented.

     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.

     There is a “universal sequence for quality improvement,” according to the illustrious Joseph M. Juran, that defines the actions to be taken by any team to effect change.  This includes teams pursuing error- and defect-reduction initiatives, variation reduction, or quality improvement by any other description.
            Two of the seven steps of the universal sequence are “journeys” that the team must take to complete its problem-solving mission.  The “diagnostic journey” and the “remedial journey” comprise the core of the problem-solving process and, thus, warrant particular attention.

     Digital Twin technology existed long before this term came into common use.  Over time, existing technology has advanced, new applications and research initiatives have surfaced, and related technologies have been developed.  This lack of centralized “ownership” of the term or technology has led to the proliferation of differing definitions of “digital twin.”
     Some definitions focus on a specific application or technology – that developed by those offering the definition – presumably to coopt the term for their own purposes.  Arguably, the most useful definition, however, is the broadest – one that encompasses the range of relevant technologies and applications, capturing their corresponding value to the field.  To this end, I offer the following definition of digital twin:
     An electronic representation of a physical entity – product, machine, process, system, or facility – that aids understanding of the entity’s design, operation, capabilities, or condition.

     Last year, I was invited to speak at a corporate “roundtable” on the subject of lightweighting.  Though the host’s unfavorable terms compelled me to decline, I do not dismiss the topic as insignificant or unimportant.  To the contrary, it is important enough to address here.  For everyone.  For free.
     Lightweight design is increasingly critical to the success of many products.  The aerospace and automotive industries are commonly-cited practitioners, but lightweighting is equally important to manufacturers of a wide variety of products.  Running shoes, health monitors, smart watches (probably dumb ones, too), various tools, and bicycles all become more appealing to consumers when weight is reduced.  Any product that is worn or carried for a significant time or distance, lifted or manipulated frequently, is shipped in large quantities, or is self-propelled is a good candidate for lightweighting.

     Companies, universities, athletes, hospitals and physicians, municipalities, and any other entity that can be compared in any way often claim to be “world-class.”  Is this a quantitative or qualitative assessment?  Can “world-class” be objectively determined, or is it subject to the biases inherent to the assessor?  Does it mean, simply, that the entity – whatever type it may be – is “good enough?”
     The first definition of world-class on Dictionary.com is “ranking among the world’s best; outstanding.”  This sounds like a grand achievement and a worthy goal.  Unfortunately, it is completely meaningless.

     Modern gurus of self-help have changed the narrative from “improve your weaknesses” to “play to your strengths.”  However, the –abilities that drive performance in manufacturing and service operations require both approaches.  A successful strategy includes extracting maximum value from well-developed –abilities and continually improving the weaker ones.  The –abilities that drive performance include stability, reliability, profitability, and others.  Some are more critical in a specific context; some have multiple interpretations; all deserve attention.
     The –abilities that drive performance are straightforward concepts.  The problem is that many managers and entrepreneurs lose sight of the basics while pursuing higher-level objectives.  Let this post be a warning against this and a reminder of how solid fundamentals create a path to success.

     In Part 1, the D•I•P•O•D Process Model and template were presented and explained.  In this installment, an example deployment will be illustrated to demonstrate the variety of factors to be considered in an analysis.  Practitioners are warned against developing a false sense of security or accomplishment in a special note on troubleshooting.  Then, a number of common errors will be shared to help practitioners avoid them.

     Well-designed models can be invaluable aids to development and analysis.  3D CAD models assist the detection of physical interferences in an assembly and the rapid calculation of stresses within its components.  Mold-flow analysis helps injection molders predict processing problems.  Various forms of simulation help us evaluate potential performance and identify risks before any products are manufactured, tooling built, routes established, or services performed.
     Successful process planning, troubleshooting, and continuous improvement begins with applying fundamentals.  Therefore, a model need not be as sophisticated as mold-flow or finite-element analysis requires to be useful, nor does it require high-performance computers with extensive computational capability.  For many purposes, a simple diagram can provide the guidance needed for users to achieve breakout performance by focusing attention on what is relevant to the achievement of objectives, while clearing the clutter of distractions.  The D•I•P•O•D Process Model is a great example of effective simplicity when used for process planning, development, or troubleshooting.

     For a coherent discussion of culture to take place, it is important to define the term in its intended context.  Social psychologist Goodwin Watson referred to ‘culture’ as “the total way of life characteristic of a somewhat homogeneous society of human beings,” differentiating its use in social science from the vernacular “refinement of taste in intellectual and aesthetic realms.”
     Watson also quotes anthropologist Ralph Linton’s definition of ‘culture’ as “the configuration of learned behavior whose component elements are shared and transmitted by the members of a particular society.”
     Key components of each definition will help us translate the concept of culture from a discussion of at-large society to one of a corporate environment.

     Many manufacturing and service companies succumb to competitive pressure by embarking on misguided cost-reduction efforts, failing to take a holistic approach.  To be clear, lean is the way to be; lean is not the same as cost reduction.  Successful cost-reduction efforts consider the entire enterprise, the entire product life cycle, and, most importantly, the effects that changes will make on customers.

     On this date, in 1944, Allied forces launched the campaign that would ultimately liberate northern Europe from Nazi occupation.  A great deal has been written about the military efforts to storm the beaches of France and advance inland.  Much of this has been intended, at least ostensibly, to honor the soldiers that endured the hardships of war and the commanders that led them to victory.  Some of it also commends civilians for their labor and sacrifice in support of the war effort.
     Despite all of this, questions remain:  Have we truly honored the “Greatest Generation?”  What about the previous generations – those that sent their children and grandchildren to war, while food and other supplies were rationed at home?
     To truly honor them, we must learn and embody the lessons they have to teach us about fortitude, resilience, and character.  Opportunities to hear from them directly are vanishing rapidly.  The youngest of this generation are in their 90s, and it is estimated that we lose 372 of them each day.