“[They] lost their quality leadership to new, aggressive competition. The most obvious consequence was lost of market share (…) [due to] quality features that were perceived as better meeting customer needs [and] they did not fail in service as often.”
“Loss of market share is not the only reason behind [it] (…) a second major force has been the phenomenon of life behind the quality dikes. We have learned that living in a technological society puts us at the mercy of the continuing operation of the goods and services that make a society possible (…) without such quality we have failure of all sorts (…) at the least these failures involve annoyances and minor costs. At their worst they are terrifying.”
“A third major force has been the gathering awareness by companies that they have been enduring excessive costs due to chronic quality-related wastes (…) about a third of what we do consists of redoing work previously done (…) lacking expertise in the quality disciplines, they are amateurs in the best sense of that word.”
J.M. Juran’s assessment on Quality issues in the 1960s-70s.
What follows are some of the insights driving the work that I’m doing on reviewing, leveraging and updating QbD (Quality by Design) in the context of today’s fast growing and all-encompassing digitalization.
I am dusting off my research from 2010 on the 3Q Model. Back then I was a senior manager at Alcatel-Lucent’s Solutions & Technology Introduction Department. My current role is Senior Studio Director at Nokia Software’s Solutions Engineering. Note that the scope is End-to-End Solutions. These are holistic system-wide (cross-sectional and longitudinal) undertakings intersecting different domains to deliver the higher value of the whole. I have discussed QbD for Digital Transformation projects at the Design Thinking 2018 event and at the IEEE (Institute of Electrical and Electronics Engineers) conference on CQR (Communications Quality and Reliability) back in April and May of this year. Interestingly enough, both events were held in Austin, Texas.
QbD was first coined by Juran, a renown pioneer of quality practices, whose work on that specific topic started in the mid 80s. He linked Quality to customer satisfaction and reliability as the two dimensions to focus on:
“Features” were defined as “quality characteristics,” which meant properties intended to satisfy specific customer needs. That would also include “promptness of delivery,” “ease of maintenance,” and “courtesy of service” to name some examples. “The better the features, the higher the quality in the eyes of customers.”
As far as reliability and, therefore, replicability and consistent performance, “freedom from deficiencies” conveyed the fact that “the fewer the deficiencies the better the quality in the eyes of customers.” A “deficiency” is a failure that triggers dissatisfaction, which calls for incurring higher costs to redo prior work.
“Fitness for use” was mentioned as an attempt to capture the above two together. The so-called Juran Trilogy entails Quality Planning, Quality Control, and Quality Improvement.
More than three decades have passed since Juran started to work on “New Steps for Planning Quality into Goods and Services.” Let’s decompose QbD’s acronym at face value and distill its essence.
As a designer, my belief & practice system focuses on “serial innovation” consistently delivering superior value. This is achieved by means of purposeful and elegant solutions equipped with capability models and optimal functionality leading to Quality Experiences.
Customer Delight, rather than just satisfaction, being the sought after outcome. This applies to both small and large undertakings, and as A. Kay, a pioneer in graphical user interfaces, best put it, “simple things should be simple, complex should be possible.”
Following that train of thought, “Designing Quality into Solutions” should become center stage to: (a) collaborative and iterative ideation, (b) agile development, (c) continuous delivery and (d) the dynamic diffusion of (e) new and mass-customizable digital services for consumer and enterprise markets, as well as no-for-profit. Overall, QoB is key to Operational Excellence.
In a world where “Continuous Improvement” leads to incremental and breakthrough innovations, Quality’s critical KPI, Key Performance Indicator, can be expressed in terms of measurable advances in QoUX, the Quality of the Users’ Experiences. These are lagging (outcome) metrics that are far from static because they evolve within and over lifecycles. Therefore, reliability is not just applied to production operations, but also to the solution’s consistent performance and serviceability over time and under changing scenarios and events.
Given Quality’s unequivocal narrative around the “experiential” paradigm and, therefore, human-centric-optics, QbD’s best work should optimize for user “delight,” which is defined as superior “satisfaction,” rather than just aiming for requirements compliance.
It is very tempting to rally around core competencies within comfort zones that exist, and then settling on just aiming for “customer satisfaction” around “must-meet” baseline requirements. Though, that might not suffice given the necessity to innovate and better compete by leveraging unique sources of sustainable differentiation.
Let’s now state the obvious: “designing” Quality Experiences into digital solutions is best addressed by means of Human-Centered methodologies that optimize for (f) users’ “acceptance criteria” and (g) the kind of “adoption levels” that foster user base growth.
The opposite approach would risk the adverse effects (and hidden costs) that can be incurred when technical myopia leads the way. A. Cooper’s “The Inmates are Running the Asylum” captures that very well. His book is referenced below.
Just for the record, the year is 2018 and we are gearing for a pervasive digital world dominated by software defined systems. The 4th Industrial Revolution’s floodgates are set wide-open.
Low and high tech perform best when playing a supporting role. Technology enables “Services” which justify it, otherwise the so-called Chasm and Valley of Death wait around the corner. It pays to emphasize that “Services” are defined by “Use Cases.” So, it shouldn’t take much effort to see that “Use(case)ability” (“usability” being the proper term) is a CSF, Critical Success Factor. “Fitness for use” in other words.
Let’s take that further and couple “usability” with designing for usefulness,” “utility,” “consumability & serviceablity” as well as “affectivity” because perception and human affects orient satisfaction and dissatisfaction levels.
QbD cannot be put to work without adequately addressing Human Dynamics, which entails psychological (e.g. cognitive models, information architecture) physiological (e.g. device form factor, workstation ergonomics) and social dimensions (e.g. network effects increasing value for users.) That happens to be the SoW (Scope of Work) of HFE’s (Human Factors Engineering) interdisciplinary teams in Design Studios… and the topic of my next post on QbD’s Intellectual Capital.
A few more thoughts…
In spite of one’s day-to-day work and/or belief system being either closer to or removed from the kinds of jobs and tasks that make tech human, it makes sense to engage in meaningful outcome oriented and goal driven practices by applying HCD, Human-Centered-Design. The purpose is delivering quality and achieving customer acceptance and delight, given that customers are human beings. That is the reason why Design Thinking has outgrown the field of industry design and is applied to a wide variety of domains and disciplines nowadays.
Tech’s roller-coaster industry is packed with well intended technologies that fail. We all know that this is a fiercely competitive environment in constant change. Though, it is also true that, in many of those cases, UX, User Experience, professionals were not engaged at any part of the process, or were purposely involved at the back-end, or were called to come to the rescue in the eleventh hour. That leaves no room for Design to make a difference. Superficial changes just amount to bells-and-whistles and shiny-objects to disguise the underlying quality issues that are likely to re-surface at some point.
QbD’s top objective should be excelling at effectively & efficiently addressing our customers’ acceptance and adoption criteria. That remains true even in the context of full automation. Humans still get promoted and demoted (or fired) based on those system’s performance. D. Newman’s recent article on Forbes magazine rightly states that “you cannot run your business without people (…) you cannot operate technology without people (…) research have shown that people are a critical component for digital transformation.”
Today’s best practice calls for “reverse engineering” solutions by working from that human-centered understanding around Human Machine Systems (HMS.) That is substantially different from only relying on a far riskier “if you build it, they will come” model and its costlier brute-force mindset.
When dealing with challenging, intractable and complex projects, overlooking that fact typically results in exponential project risk and plenty of the, otherwise, avoidable zig-zagging course corrections ahead (e.g. opportunity costs in financial analysis and hidden and latency costs in systems engineering.)
Agile’s iterative development and ability to pivot shouldn’t be a refuge for either subpar or no design effort, but a vehicle to best implement QbD and augment development capacity while minimizing technical debt. This is why this revision of QbD for today’s tech industry calls for Design Sprints to lead the way.
Last but not least, before dismissing this QbD revision as a philanthropic and humanistic only endeavor, I suggest deep thinking around its (1) business criticality and (2) contribution to risk mitigation.
J. de Francisco
Bell Labs, Distinguished Member of Technical Staff
Nokia Software, Senior Studio Director @ Solutions Engineering
A. Cooper. The Inmates are Running the Asylum. Why High-Tech Products Drive Us Crazy and How to Restore the Sanity, Sams Publishing, 2004.
D. Newman. 3 Reasons People are Critical for Digital Transformation Success. Forbes, June 2018.
J. de Francisco. IEEE ETR 2018, Emerging Technologies Reliablity Roundtable – Human Factors Session (2). Innovarista: Innovation at Work, July 2018 innovarista.org
J. de Francisco. IEEE ETR 2018, Emerging Technologies – Human Factors Session. Innovarista: Innovation at Work. May 2018 innovarista.org
J.M. Juran. Juran on Quality by Design: the New Steps for Planning Quality into Goods and Services, The Free Press, 1992.
Following up on my last post about IEEE ERT 2018, here are a couple of charts for my “discussion brief,” which include a Human-Machine-System Capability Mapping chart (above) and concept illustrations of the Experiential Decision Support System (below.) The charts’ text conveys context setting remarks, which I am also providing here.
The goal of furthering machine intelligence is to make humans more able and smarter: the opposite engineering approach typically becomes a source of self-defeating technical myopia waiting to happen and missed opportunities. This simple mapping exercise can be customized to assess and roadmap capability levels.
The more sophisticated automation becomes, the more obvious the criticality of the human factor in both consumer and enterprise environments… rather than less. And, in any case, customer acceptance and adoption criteria remain Quality’s litmus test for emerging technologies.
Digitalization is fostering (a) XaaS, (b) Self-Service, (c) the Shared Economy and the (d) Maker Movement. All elevate human involvement and drive the push for opening and democratizing technologies. These make (e) citizen science and citizen developers shape the next generation prosumers at mass market scale.
Digital Transformation initiatives embracing the above allow (f) nimbler enterprise teams to operate at far greater scale, scope and speed, and shift focus from routine operations to dynamic value creation coupled with extreme efficiencies.
This entails (g) interdisciplinary workstyles and collaborative organizational behaviors that include (h) customer co-creation models. In this new context, humans remain (i) the ultimate critical element in system reliability and safety. Left shifting Quality by Design (QbD) prioritizes Human-Centered-Design tools and processes to deliver high performance workforce automation systems.
Cost-effective Lean Ops systems intertwine analytics, automation, programmability and flexible systems integration. All optimized for dynamic behaviors given Soft System’s perpetual motion. This means designing “for-ever” rapid and seamless reconfigurability instead of just engineering “day 1” implementations.
Operational Excellence dictates system-wide as well as subsystem level visualization, and a combination of centralized & distributed closed loop controls under user friendly operational modes. Cognitive models involve Situational Awareness (SA,) Sense Making (SM,) Root Cause Analysis (RCA,) Scenario Planning (SP,) and ROA (Real Options Analysis.)
The Experiential element is not just about programming known rules and policies but, most importantly, it grows by assimilating iterative learning in the context of cyclical automation: routine decisions and manual operations can be streamlined and collapsed, then switching to “exception” based management for that particular event.
Productivity calls for streamlining operations so that (a) waste can be eliminated & prevented, and (b) value based tasks can be performed effortlessly, in less steps, at speed & without error. High performance behaviors and sustainable competitiveness also call for the ability to (c) experiment and create new capabilities, as well as leveraging (d) process mining for customer journeys & value stream mapping (CJM & VSM) to continuously optimize them and guarantee service levels.
Service Operations Centers (SOC) should be equipped with Experiential Decision Support Systems (DSS) featuring (d) collaborative filtering, (e) actionable data stories conveying hindsight, insight & foresight and (f) adaptive cybernetics. Advanced visualization for both (f) intuitive & highly abstracted infographics and (g) scientific views is of the essence.
Quality is best addressed as a human experience, which determines (d) meaning and, therefore, the degree to which a system is lean vs. over-engineered or subpar (both being defective and carrying obvious and hidden costs.) A new take on QbD for Soft Systems, which are inherently fluid by definition, emphasizes acceptance testing probing for: usefulness & utility, usability & affectivity, consumability & serviceability and safety thru use cases and lifecycle events.
Exploring Other Methods. November 7, 4:00 PM Understanding How Design Thinking, Lean and Agile Play within Service Design.
“Since service design serves as the umbrella discipline for delivering service experiences, there are many sub methods to address different types of problems. For example, Design Thinking is helpful on the front end to empathize and identify customer needs where Agile is helpful in software development and digital experience design. This group explores well-known methods and how they play a role in the service design universe.”
I’m back in Chicago and I would first like to thank everyone who joined my session about “Exploring Other Methods” for your participation (full house) and encouraging feedback. I hope to cross paths again in the near future. In the meantime, we can take advantage of LinkedIn to stay in touch. I would also like to express my gratitude to Michael DeJager and Tyler Peterson for all of their tireless help.
Here are the links for a couple of the items that I briefly discussed when providing context for Exploring Other Methods: a photo album of where I work, Nokia’s Chicago Technology Center, and the first version of the Human Factors Engineering Manifesto. Regarding requests about the slideware for my talk… I ran an interactive whiteboarding session with my iPad connected to the projector and I did not produce formal slides.
The discussion’s narrative was centered on how to best approach HSM, Human-Machine-Systems, to craft a compelling Service Experience. In that context, “Human” refers to relevant stakeholders and “Machine” to any technology involved. The “Systems” approach prompts a holistic undertaking which includes Front Stage, Back Stage factors and the continuum across the too.
Service Design is about innovation, whether capability-wise that qualifies as incremental, breakthrough and/or disruptive innovation. Today’s Service Design also entails a wide range of low and high-tech at any point in the process. While this is just anecdotal evidence, when I asked everyone about who can do away without any technology, there was an implicit understanding of the rhetorical nature of my question and, therefore, the obvious pervasiveness of digital experiences.
We are a technological society. Good design is concerned with human factors and crafts technological solutions to enable human experiences that contribute to our quality of life and the quality of the work we do. That is Human Factors Engineering (HFE) reason for being, a field pioneered by Nokia Bell Labs in 1947.
From that perspective, it pays to intertwine any relevant practices and tools for the healthy purpose of figuring out what combination works best for any given Service Design project. While process repeatability is a desired outcome, what makes an interdisciplinary team smart is the ability to mix, match and blend what’s needed for each undertaking.
We can think of it as an a-la-carte menu featuring elements from Design Thinking, Agile and Lean methodologies just to name a popular handful to start with. I did not discuss some other such as Concept of Operations, Goal Directed Design or Outcome Driven Innovation, but I do recommend expanding one’s horizons beyond the aforementioned few. Note that while featuring commonalities, each one works with different optics. A holistic approach to Service Design also requires a composite method, leveraging as much (or as little) as needed from any, and with any needed adaptations.
Rather than summarizing what I shared at Service Design Week, I’m taking this chance to further reflect on those insights. So, given that we operate in highly dynamic environments, why wouldn’t designers also apply dynamic methodologies?
I’d like to think twice about cookie-cutter and one-size-fits-all approaches because Service Design typically prompts problems and opportunities where fixed-gear-techniques that might have worked well in the past can end up betraying one’s confidence: they might no longer serve or be the best fit whichever purpose they were originally conceived for. Design typically takes us beyond our comfort level, and that makes it an exciting profession.
Statistically speaking, the more one does the very same thing, the closer one gets to mastering that craft (e.g. deliberate practice model). But, paradoxically, you also get closer and closer to confronting environmental deviations, anomalies and rare events in an ever-changing world with even-growing moving parts and targets (e.g. black swan model). Besides, Service Design practitioners shouldn’t deny themselves the benefits that come with continuous improvement. So, here is a quick recap: innovation in Service Design’s outcomes and method innovation go hand by hand. As Einstein put it:
“Insanity is doing the same thing over and over and expecting a different result.”
“If we knew what it was we were doing, it would not be called research, would it?”