WCQI Day 2 – morning

My day 2 at WCQI is Day 1 of the conference proper. I’m going to try to live blog.

Morning keynote

Today’s morning keynote is the same futurist as at the LSS in Phoenix last month, Patrick Schwerdtfeger, and not only was I dismayed that it was they exact same  I was reminded yet again how much I dislike futurists. I’m all about thinking of the future, but futurists seem to be particularly bad at it. It is all woowoo and bro-slapping and never ever a serious consideration of the impact of technology. Futurists are grifters.

These grifters profit by obscuring facts for personal gain. They are working an angle, all of them: the health gurus and the life hackers peddling easy solutions to difficult problems, the futurists who basically state current trends as revelations.  They are all trying to pull off the ultimate con – persuading people they really matter.

They are selling themselves: their books, their podcasts, their websites, their supplements, their claims to some secret knowledge about how the world works. But I fundamentally doubt that anyone who gave 40 talks in the last year has the bandwidth to do anything that really matters. It is all snake-oil. And as quality professionals, individuals who are dedicated to process and transparency and continuous improvement, we deserve better.

I’m not sure how these keynotes are selected but I think we need to holistically view just what we want to be as a society and the pillars we want for our conferences.

Anyone know a good article that evaluates futurists and life hackers with the prosperity gospel? Seem like they are coming from a similar place in the American psyche.

Ooh, artificial intelligence. Don’t get me wrong there is real potential (maybe not the potential people feel like there is) but most discussions on artificial intelligence is hype and bluster, and this presentation is no different. Autonomous vehicles block chains. Hype and bluster.

There is definitely people thinking this seriously, offering real insights and tools. We’re just not there. The speaker admits he gets 90% of his income from speaking. Pretty sure he isn’t actually doing that much. He might be an aggregator (as most of his slides with real content were attributed) but I keep struggling to see value here.

Gratuitous Steve Jobs picture.

After this there is some white space for vendor stuff.

At least I could multi-task and did some work.

Quality 4.0 Talks

I didn’t attend many of these last year because they were all standing and had a thrown together feeling. This year the ASQ seems to have upped the game. Shorter sessions can be good if the presentation is tight. At 15 minutes that is a hard bar to set.

First up we have Nicole Radziwill on “Mapping Quality Problems to Machine Learning Solutions” Nicole’s very active in the software section, which under the new membership model I’ll start paying a lot more attention to.

In this short presentation Nicole focuses on hitting the points of her 2018 Quality Progress article. Talking about quality 4.0’s path from Taylorism as “discovery & learning.”

She references Jim Duarte’s article Data Disruption.

Hit on big data hubris and the importance of statistics and analysis. The importance of defining models before we use them.

From ” Let’s Get Digital” in Quality Progress

Covers machine learning problem types at a high level.

  1. Prediction
  2. Classification
  3. Pattern Identification (Clustering)
  4. Data Reduction
  5. Anomaly Detection
  6. Pathfinding

High level recommendations were domain expertise, statistical expertise, data quality and human bias.

Next up is Beverly Daniels on “Risk and Industry 4.0”

It is telling that so many of the talkers make Millennial jokes. As a Gen-Xer I am both annoyed because no one ever made Gen-Xer jokes (the boomers never even noticed we were at the conference) AND frustrated because this is something telling about the graying of the ASQ.

Quick review of risk as more than probability. Hit on human beings as eternally optimistic and thus horrible at determining probability. As this was a quick talk it left more questions than answers. Getting rid of probability from risk is something I need to think about more, but her points are aligned to my thoughts on uncertainty.

Focusing on impact and mitigation is interesting. I liked the line “All it does is make your management feel good about not making a decision.”

Thoughts on day 1 of ASQ WCQI

Thoughts from the pre-day at ASQ World Conference of Quality Improvement. May become a more meaty post.

Food, Drug and Cosmetic Division (FDC)

  • What separates this division for the biomedical division? The commonalities between food, drug, cosmetics and medical devices are more pronounced in the US with the common regulatory responsibilities. But I have trouble seeing the cosmetics industry more closely aligned to me than a medical device.
    • I think there is more commonality between cosmetics and type 1 and drugs and type 3 than there is often between drug and cosmetics. Though the drug to cosmetic or drug to food is a slippery slope.
  • The type of conferences the FDC division attends tend to be more focused on nutrients and OTC then cutting edge bio it feels like.
  • I’d love to see a SWOT, force-field analysis and definitely an X-matrix as they discuss strategic plan.
  • Yep, ASQ is not getting technology. Oh dear, I feel what they really want is a stack exchange (ASQ should totally have licensed stack exchange instead of whatever is powering my.ASQ)
  • Love to understand the decrease in CPGP. I think there is a a value statement the ASQ has failed to make.
  • Would like to learn more about the new CHA BoK. Will it recognize the greater value of the tool outside of food industry? Can it do that without weakening the BoK’s value for the food industry?
  • Still no training for the CPGP. Still volunteering and hoping to get called on. Part of forming that value statement will need to be good training.
  • Maybe I should be glad my attempts to volunteer this year never went anywhere. Lots of talk on expense reports and I am super bad at expense reports.
  • Pins. Between badges and ribbons and pins I feel like I am back in the boy scouts.

Business Meeting

  • Still not feeling the commitment to transparency that should be at the heart of a quality organization
  • Change is hard
  • Technology is super hard. But really we mean to get it this year (how about a smart phone app, pretty please)
  • I think I like the new membership structure but still not sure how technical organizations will work

Risk Management is about reducing uncertainty

Risk Management is all about eliminating surprise. So to truly start to understand our risks, we need to understand uncertainty, we need to understand the unknowns. Borrowing from Andreas Schamanek’s Taxonomies of the unknown, let’s explore a few of the various taxonomies of what is not known.

Ignorance Map

I’m pretty sure Ann Kerwin first gave us the “known unknowns” and the “unknown knowns” that people still find a source of amusement about former defense secretary Rumsfield.

KnownKnown knowns Known unknowns (conscious ignorance)
Unknown Unknown knowns (tacit knowledge) Unknown unknowns (meta-ignorance)

Understanding uncertainty involves knowledge management, this is why a rigorous knowledge management program is a prerequisite for an effective quality management system.

Risk management is then a way of teasing out the unknowns and allowing us to take action:

  1. Risk assessments mostly easily focus on the ignorance that we are aware of, the ‘known unknowns’.
  2. Risk assessments can also serve as a tool of teasing out the ‘unknown knowns’. This is why participation of subject matter experts is so critical. Through the formal methodology of the risk assessment we expose and explore tacit knowledge.
  3. The third kind of ignorance is what we do now know we do not know, the ‘unknown unknowns’. We generally become aware of unknown unknowns in two ways: hindsight (deviations) and by purposefully expanding our horizons. This expansion includes diversity and also good experimentation. It is the hardest, but perhaps, most valuable part of risk management.

Taxonomy of Ignorance

Different Kinds of Unknowns, Source: Smithson (1989, p. 9); also in Bammer et al. (2008, p. 294).

Smithson distinguishes between passive and active ignorance. Passive ignorance involves areas that we are ignorant of, whereas active ignorance refers to areas we ignore. He uses the term ‘error’ for the unknowns encompassed by passive ignorance and ‘irrelevance’ for active ignorance.

Taboo is fascinating because it gets to the heart of our cultural blindness, those parts of our organization that are closed to scrutiny.

Smithson can help us understand why risk assessments are both a qualitative and a quantitative endeavor. While dealing with the unknown is the bread and butter of statistics, only a small part of the terrain of uncertainty is covered. Under Smithson’s typology, statistics primarily operates in the area of incompleteness, across probability and some kinds of vagueness. In terms of its considerations of sampling bias, statistics also has some overlap with inaccuracy. But, as the typology shows, there is much more to unknowns than the areas statistics deals with. This is another reason that subject matter experts, and different ways of thinking is a must.

Ensuring wide and appropriate expert participation gives additional perspectives on unknowns. There is also synergies by finding unrecognized similarities between disciplines and stakeholders in the unknowns they deal with and there may be great benefit from combining forces. It is important to use these concerns to enrich thinking about unknowns, rather than ruling them out as irrelevant.

Sources of Surprise

Risk management is all about managing surprise. It helps to break surprise down to three types: risk, uncertainty and ignorance.

  • Risk: The condition in which the event, process, or outcomes and the probability that each will occur is known.
    • Issue: In reality, complete knowledge of probabilities and range of potential outcomes or consequences is not usually known and is sometimes unknowable.
  • Uncertainty: The condition in which the event, process, or outcome is known (factually or hypothetically) but the probabilities that it will occur are not known.
    • Issue: The probabilities assigned, if any, are subjective, and ways to establish reliability for different subjective probability estimates are debatable.
  • Ignorance: The condition in which the event, process, or outcome is not known or expected.
    • Issue: How can we anticipate the unknown, improve the chances of anticipating, and, therefore, improve the chances of reducing vulnerability?

Effective use of the methodology moves ideally from ignorance to eventually risk.


DescriptionMethods of Mitigation
Closed Ignorance
Information is available but SMEs are unwilling or unable to consider that some outcomes are unknown to them.

Self-audit process, regular third-party audits, and open and transparent system with global participation
Open Ignorance
Information is available and SMEs are willing to recognize and consider that some outcomes are unknown.
Surprise occurs because an individual SME lacks knowledge or awareness of the available information.

effective teams xxplore multiple perspectives by including a diverse set of individuals and data sources for data gathering and analysis.

Transparency in process.
Surprise occurs because a group of SMEs has only similar viewpoints represented or may be less willing to consider views outside the community.
Diversity of viewpoints and sue of tools to overcome group-think and “tribal” knowledge
Surprise occurs because the SMEs are unable to anticipate and prepare for external shocks or internal changes in preferences, technologies, and institutions.

Simulating impacts and gaming alternative outcomes of various potentials under different conditions
(Blue Team/Read Team exercises)
Surprise occurs when inadequate forecasting tools are used to analyze the available data, resulting in inter-relationships, hidden dependencies, feedback loops, and other negative factors that lead to inadequate or incomplete understanding of the data.
System Thinking

Track changes and interrelationships of various systems to discover potential macro-effect force changes

Risk Management is all about understanding surprise and working to reduce uncertainty and ignorance in order to reduce, eliminate and sometimes accept. As a methodology it is effective at avoiding surrender and denial. With innovation we can even contemplate exploitation. As organizations mature, it is important to understand these concepts and utilize them.


  • Gigerenzer, Gerd and Garcia-Retamero, Rocio. Cassandra’s Regret: The Psychology of Not Wanting to Know (March 2017), Psychological Review, 2017, Vol. 124, No. 2, 179–196.
  • House, Robert J., Paul J. Hanges, Mansour Javidan, Peter Dorfman, and Vipin Gupta, eds. 2004. Culture, Leadership, and Organizations: The GLOBE Study of 62 Societies. Thousand Oaks, Calif.: Sage Publications.
  • Kerwin, A. (1993). None Too Solid: Medical Ignorance. Knowledge, 15(2), 166–185.
  • Smithson, M. (1989) Ignorance and Uncertainty: Emerging Paradigms, New York: Springer-Verlag.
  • Smithson, M. (1993) “Ignorance and Science”, Knowledge: Creation, Diffusion, Utilization, 15(2) December: 133-156.