Join me on Conference Day: Tuesday, September 21 at 1:15 pm.
At the time of writhing this, we happen to be immersed in the makings of a brave next normal where everything can be revisited and rethought to be better delivered as a seamless service. The ‘experience economy’ is finally taking hold. This means that a ‘customer-first’ mindset and an unwavering commitment to ‘outstanding quality’ are essential to win hearts and minds because what ‘value’ is (and is not) at any given point of time remains a human consideration informed by our experiences.
Digitalization has not only accelerated beyond expectations during the recent pandemic, but has also furthered the relentless adoption of pervasive communication technologies and AI, Artificial Intelligence, across industries. Given the exponential rise of autonomous systems that can enable on-demand self-service coupled with instant mass customization… the more we digitize, the greater the reach and, therefore, the more pressing the need to excel at Human Centered AI with moral imagination and creative confidence.
Jose de Francisco is the Chief Designer at Nokia CNS, Cloud & Network Services, and Co-Head of Nokia’s Chicago Innovation Center, a leading R&D facility integrating all of the company’s business groups. His professional experience encompasses interdisciplinary leadership responsibilities in strategy, product management, research, design, new ventures and marketing.
Award-winning designer and a Distinguished Member (DMTS) of Bell Labs for work on next generation mobile platforms and applications, Jose holds several active patents and an extensive design portfolio featuring 20+ brands. He has served with the Advisory Boards for MIT’s Institute of Data, Systems and Society (IDSS) and Illinois Tech’s Entrepreneurship Center. Jose is currently engaged with Design & Innovation Global, the think tank behind the premier Design Thinking conference series in the United States and is a core team member of TM Forum’s DMM (Digital Maturity Model) and DOT (Digital Organizational Transformation) projects.
Holds several professional certificates in Design and Data Science from MIT, earned an MBA in International Marketing and Finance from Chicago’s DePaul University as a Honeywell Europe Be Brilliant Scholar, and is the recipient of postgraduate degrees in Human Factors Engineering and Business Administration from BarcelonaTech (UPC) and Ireland’s University College Dublin (UCD) respectively. He started his academic life in the Industrial Design program of Barcelona’s Massana Art & Design Center as an Epson Scholar.
Passionate about innovating to create new value, Jose co-authored the ‘Human Factors Engineering Manifesto’ and believes in the exceptional value that comes with consistently delivering ‘Quality Experiences by Design’ (QXbD.) His endeavors can be followed on innovarista.org.
I would like to thank the team at CMP’s Design & Innovation Global for the opportunity to present at Design Thinking Digital Summit. This was my first public talk in my new job as Chief Designer for Nokia Software, which made the occasion even more memorable for me.
I am also grateful for the continued one one one discussions that some of us are having over LinkedIn messaging, and the opportunity to exchange insights on the topic.
Value (singular) refers to the correlation between perceived and comparative worth and quality of a solution in the shape of a product and/or service.
Perceived value is a performance metric, a lagging indicator that confirms the degree to which design’s outcomes are met: market desirability and customer delight being two examples.
Brand Equity Value (BEV) is the ultimate measurement of composite business performance as a whole.
Values (plural) relate to our design belief system and, therefore, the culture that equips the job with moral imagination, drive, purpose and meaning.
Design’s human centricity is the soul of any system. Reality dictates that, in today’s world, all end-to-end technological solutions happen to be Human Machine Systems (HMS) without exception. Note the emphasis on the ‘end-to-end’ scope… there is no escaping that fact.
Values (plural) also refers to qualitative and quantitative leading indicators that inform the quality of design work in progress.
This means both new data and insights generated as we rapidly experiment, prototype options and conduct multivariate testing… these are intensive hyper-iterative cycles that orient and inform a design’s progression and improvement through all the steps from ideation to blueprinting. This is quintessential to Design Thinking. Simply put, without that effort there is no Design Thinking as such.
As an example, in Quality eXperiences by Design (QXbD) we assess: usefulness, utility, usability and affectivity values, which are ranked by effectiveness and efficiency parameters. That construct shapes the experiential qualities that define a system’s capability and behavioral model leading to production design blueprints.
QXbD‘s intertwines these with continuity and differentiability appraisals as we assess business model attractiveness and viability and, last but definitely not least, the technologies’ development, delivery, servicing feasibility over the product and/or service lifecycle. Note that the context is System Design as a holistic and interdisciplinary undertaking.
Designing to Optimal Values makes the job interesting, rigorous and tactical. Delivering optimal value relies on the honesty of Value Stream Mapping (VSM) cost-benefit analysis. How we define the scope and impact of the benefits, as well as difficult trade-offs, is a function of the design belief system and the solution’s soul.
One more thought… by now it becomes quite obvious that Value Propositions are best conceived by undertaking painstaking interdisciplinary design work.
I would also like to thank those of you who joined the live session and, as usual, I am happy to continue the discussion to trade insights as well as contrasting thoughts and viewpoints. We can have that conversation over LinkedIn messaging to keep things going.
The preceding post on QXbD research notes – Part 1.1 shared a retrospective with insights from my early college years, which were influenced by Bruno Munari‘s “projected methodology” and the Bauhaus‘ design principles.
Research Notes Part 1.2 (this post) takes me back to BarcelonaTech’s school of engineering in the early 90s, which I joined to study Human Factors Engineering while pursuing my last year of Industrial Design at Escola Massana, an art & design school.
Those days, Donal Norman’s “The Psychology of Everyday Things” and Henry Petroski’s “The Evolution of Useful Things. How Everyday Artifacts Came to be as They Are” became must-read books for anyone interested in thoughtful design principles in a new light. Norman was an Apple Fellow and became VP of the Advanced Technology Group in the mid 1990s. He popularized the term of User Experience.
Petroski was an engineer whose best known work focuses on failure analysis. He stated that the best Industrial Design involves “seeing into the future of a product” and that Human Factors Engineering is concerned with “how anything will behave at the hands of its intended and not intended users.” Here is a summary of some of his design principles:
- Tools make tools.
- Artifacts multiply and diversify in an evolutionary way.
- There always is room for improvement.
- Good can be better than best.
- Efficacy can be subjective, want overpowers need.
- Form follows failure: inventors should be technology’s severest critics.
- Focus on different faults means different solutions to the same problem.
- Engineering is invention institutionalized.
- Sometimes it is about a new job, sometimes about a better or faster job.
“Though the best designs deal successfully with the future, that does not mean they are futuristic […] There is an apparent reluctance to accept designs too radically different from what they claim to supersede […] if things are redesign too dramatically and the function that they perform can be less obvious”.
“Loewy summarized the phenomenom by using the acronym MAYA, standing for most advanced yet acceptable. Dreyfuss emphasized the importance of a survival form, thus making the unusual acceptable to many people who would otherwise reject it [Industrial Designers] have learned to strive for a delicate balance between innovation in order to create interest, and reassuringly identifiable elements”.
Donald Norman pointed to design issues leading to human error and making users unfortunately blame themselves in the process. He claimed that the “paradox of technology” takes effect when added functionality comes with unwanted complexity, which denies the sought-after benefits. These are some of the design principles:
- Design should be user-centric and consistent.
- Identify the true root cause of a problem.
- Well designed products teach the user how to use them.
- Make things visible, give clear clues, enough information and feedback.
- Get mapping and system state right, simplify task structure.
- Design for error, exploit the powers of constraint.
- Make possible to reverse actions, and make it harder to do what cannot be reversed.
Following up on the topic of technology’s paradoxes, it is worth reviewing Geoffrey A. More’s “Crossing the Chasm“, which was published in 1991. He explored the rationale behind the failure of emerging technologies, which fail to take hold.
There can be a deep chasm between enthusiasts and early adopters and the broader user groups shaping the mass market. Avoiding the Valley of Death starts with an understanding the adoption lifecycle: different user groups come along with different expectations. That prompts the need for the design of specific transitions and adaptations.
“Whole Product R&D […] begins not with creative technology but with creative market segmentation. It penetrates not into protons and processes but rather into habits and behaviors […] it implies a new kind of cooperation between organizations traditionally set apart from each other.”
HUMAN-MACHINE-SYSTEM DESIGN PRINCIPLES
BarcelonaTech’s teaching addressed Human-Machine Systems as an interdisciplinary undertaking. Human dynamics entailed the study of individuals and collectives such as teams and organizations. That would encompass the following disciplines and an strengths and limitations
- Psychology – skills, cognitive appraisal and workload, workstyles…
- Physiology – form factors, motions, anthropometry, biomechanics…
- Social Sciences – teamwork, organizational behaviors, culture…
Tools and machines involved hardware and software components. HMS’ holistic approach consistently tackled end-to-end solutions. These were placed in context and in specific physical environments. The sough-after outcomes of “Designing for People” zeroed in on:
- The delivery of capable high performance systems as defined by productivity by effectiveness and efficiency metrics, and success rates.
- Designing for users’ wellbeing and safety.
- Human Error is often a consequence of poor design.
- Addressing the broader user base possible, typically set at 95% coverage with adaptations, accounting for diversity rather than designing for just averages.
- Extreme case and stress testing, factoring life-long / lifecycle changes as solutions evolve and/or can be deployed in other context and environments.
We followed this iterative methodology, starting with due diligence on:
- Initial problem statement and goal setting.
- Operations assessment: use cases’ current state / present mode.
- User Taxonomy and Analysis: jobs, tools, work motion studies (tasks, workflows, success and failure rates) often relying on instrumentation.
- Data collection, processing, analysis and insights.
- Identification of value based activities, waste and risks.
- Critical success factors and possible scenarios at play.
- Information, process, hardware and software specifications.
- Contextual and environmental considerations.
The next phase focused on Human-Machine-System design, including all relevant subsystems and interactions across them:
- Operations review: new target state and mode.
- Interaction Matrix* correlating human and design factors.
- Prioritization criteria and conflict resolution.
- Job and process streamlining, often leading to redesign, or new design.
- Goal setting based on metrics optimizing for system wide operability.
- Iterative improvement cycling through experiments, prototyping, simulations and testing.
The *Interaction Matrix correlated human factors (rows) for a given design option with the following “realization” ones (columns) and the degree to which those relationships were weak, medium or strong (matrix).
- Customer acceptance criteria.
- Operability levels, including safety.
- Conformance with functional requirements.
- Reliability and performance levels, as well as maintenance.
- Productization feasibility and costs.
- Aestetics and affective considerations.
Just a quick reminder about the fact that this article is still discussing topics set all the way back in the early 90s. Those days, Total Quality Management (TQM) and Lean lead the way. Note that ISO 9000 standards had been first released in 1987.
The top three key values were: Customer Intimacy, Operational Excellence and Product Leadership:
“customer intimacy: tailoring offerings to match demand […] detailed customer knowledge with operational flexibility […] customizing a product and fulfilling special requests […] engendering tremendous customer loyalty“.
“operational excellence: providing customers with reliable products or services at competitive prices and delivered with minimal difficulty or inconvenience“.
“product leadership: continuous stream of state-of-the-art products and services. First, they must be creative […] Second, must commercialize their ideas quickly […] business and management processes have to be engineered for speed. Third, product leaders must relentlessly pursue new solutions”.
High operational performance was broken down as follows:
- Productivity & scalability.
- Flexibility & adaptability.
- Mix complexity.
J.M. Juran discussed quality in the context of “Big Q” and “Little Q” where the former addresses a business problem and is all encompassing, while the latter is siloed and focuses on tackling technical issues. Big Q delivers the sort of value that users can appreciate.
Strategic Quality Management was meant to learn from customer experiences and leveraged House of Quality charts to design with.
The first step was to map out a taxonomy of customer attributes (CA) decomposed in primary, secondary and tertiary levels, the latter being the most granular list of customer requirements and expectations… all largely based on surveys and user feedback. This was done for the value chain consisting of end users, consumers, retailers, distributors, regulators, etc. Weightings were set to prioritize attributes based on contextual relevance.
CA items would then be placed on the left rows of the above spreadsheet for the purpose of cross-checking them with technical features to be shown as column headers. That was done by correlating CA and engineering characteristics (EC). The resulting center matrix was used to assess what items were positively and negatively impacted, co-variance, and to what extend. Each cell featured icons and color coding for strong, medium, weak relationships.
The pyramidal roof at the top was filled out afterwards to look into technical synergies and conflicts alone. Basically, becoming aware of how engineering characteristics interact and making decisions on optimizations and conscious trade-offs.
SOME OTHER THOUGHTS…
Attending both Art and Engineering schools was a fascinating experience to say the least. The opportunity to cross-pollinate across disciplines could made anyone feel like being in a reenactment of the Renaissance’s blending of arts and sciences.
Both Industrial Design and Human Factors Engineering optimize for the human experience and, therefore, make their professions be about “Designing for People”. Technology that does not account for human skills, strengths as well as limitations, all in context and in the scenarios and environments will operate under… becomes greatly exposed to failure.
Striving to make designs that fit people’s potential, rather than just expecting users to just fit… does require an interdisciplinary and iterative practice, painstaking attention to detail being critical. At that point, it also became clear that addressing the Big Q also had to do with articulating the business value of design.
- D. Norman. The Psychology of Everyday Things. Basic Books, 1988.
- G.A. Moore. Crossing the Chasm. Harper Business, 1991
- H. Petroski. The Evolution of Useful Things. Vintage Books, 1992.
- J. Krafcik and J. Womack. Triumph of the Lean Production System. MIT Sloan Management Review, 1988. Accessed on May 18 2019 http://www.lean.org/downloads/MITSloan.pdf
- J.R. Houser and D. Clausing. The House of Quality. Harvard Business Review, May 1988. Accessed on May 18, 2019 https://hbr.org/1988/05/the-house-of-qualityT.S. Clark and E.N. Corlett. La Ergonomia de los Lugares de Trabajo y de las Maquinas. Tylor and Francis, 1984.
- M. Treacy and F. Wiersema. Customer Intimacy and Other Value Disciplines. Harvard Business Review, January – February 1993. Accessed on May 18, 2019 https://hbr.org/1993/01/customer-intimacy-and-other-value-disciplines
- House of Quality Template. QFD Online. Accessed on May 19, 2019 http://www.qfdonline.com/templates/