Design Thinking 2019 #DesignThinking2019
FULL LENGTH TRANSCRIPT VERSION
When did Design Thinking/Human Centered Design become a priority in your career?
I recall zooming out every once in a while at elementary school just to grasp the obvious fact that some grown ups would have conceived every single object that exists anywhere in the world… and whatever else was yet to come anytime in the future.
Intriguingly, even simple items would look intricate and complex enough to me when noticing all sorts of tiny details. At that early age I wondered if a single individual could possibly come up with all sorts of different objects… and if everything had been designed from scratch at some point.
So, I vividly remember feeling a bit overwhelmed by the staggering scope of what it would actually take to recreate my surroundings if I were to conceive each thing, big and small, on my own. That was mind-boggling and really hard to conceptualize back then.
The next minute I would put my mind at ease by zooming back in whatever contraption I was assembling. That typically involved a patchwork of worn out plastic bricks and school stationery items. All good enough to hold stuff together and to go a bit beyond squarish shapes. Other times, I would just draw what I couldn’t build and fantasize about it.
Either way, the entertaining game of making something interesting came with a kid’s craftsmanship pride. My father took notice and always displayed unconditional parental encouragement. So, he became the human my gadgets were centered on.
Admittedly, my early design work was directed by what I was personally interested in. In hindsight, operating within one’s belief system only while striving to deliver a signature design… might, or might not, match what is really needed. That becomes a hit or miss scenario, rather than adequately setting up a project for success.
Basically, success was based on the chance around (a) one’s own thinking was in lock-step with (b) consumer sentiment, (c) production economics and, most importantly, (d) the context of the end-user experience, instead of researching those first.
While “flying our on jets” (aka dogfooding) equips us with invaluable first hand insights to better design, we need to be aware of the fact that the designer might not necessarily share the optics and expectations of the target users. What’s obvious to us might not be that clear for everyone else, and the opposite is also true.
Purposely optimizing and professionally obsessing for and about meaningful human-centered outcomes was an acquired taste. Fortunately enough, role model professors and peers, coaches and mentors made all the difference.
Prioritizing and intersecting psychological, physiological and sociological considerations became an unequivocal expectation throughout my undergrad studies in Industrial Design at Massana Centre d’Art i Disseny. The most influential professors came from the worlds of architecture and industrial design, as well as fine arts, history and journalism.
The compelling effectiveness of people-first problem-solving was solidified by a grad degree in Human Factors Engineering at BarcelonaTECH. Dr. Pedro Mondelo, the program’s director at UPC, Universitat Politècnica de Catalunya, emphasized the delivery of lean (efficient) and highly productive (effective) systems, which was best achieved with human-centered and customer-focused methodologies. I’m glad to share that I was part of the 1991 class, the first one in Spain.
Things definitely came together for me by 1994. My paper on design and ergonomics for INSHT’s publication (Department of Labor, Government of Spain) addressed those and other related topics in context.
A few years later, I joined the MBA program at Chicago’s DePaul University as a Honeywell Be Brilliant Scholar, which introduced me to Behavioral Economics and seminal studies on choice, valuation and decision-making. In my view, Behavioral Economics is integral to Design Thinking’s Business Viability principle.
More recently, an MIT certificate on Big Data & Social Analytics focusing on the field of Human Dynamics and Social Physics brought along data science’s ability to scale Human-Machine-Systems. I have had the privilege to serve at MIT’s Advisory Board for IDSS, Institute of Data, Systems and Society, over the past few years, and I am now grateful for the opportunity to join CMP’s Design & Innovation Advisory Board.
As a Nokia Studio Head and Distinguished Member of Bell Labs, I pay my respects to those early BL pioneers who assembled the first interdisciplinary team devoted to Human-Factors-Engineering in the high-tech industry all the way back in 1947.
The Studio at Nokia’s Software Group thrives as an open collaborative environment involving customers and partners. Our workspace displays legendary Bell Labs artifacts as a proud reminder of our community’s ingenuity and source of inspiration.
BL’s leadership and foresight also coined the “creative technologist” job to overcome the kind of technical myopia that silos can inflict, and also stated “Designing for People” as the mission to innovate. BL is now part of Nokia’s family and joins the vision to deliver thoughtful technologies for a connected world that is “Expanding Human Possibilities.”
Design Thinking 2019 #DesignThinking2019
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.
ETR turned out to be a very productive undertaking and I would like to thank IEEE’s Spilios Markis, Chi-Ming Chen and Chris Mayer for all the help provided prior and during workshop.
My contribution focusing on addressing the unprecedented flexibility of advanced software defined systems and artificial intelligence. That intersection defines game changing technologies leading to zero-touch automation and, therefore, fostering self-service opportunities at both operational and service consumption levels.
“Zero touch” implies extreme automation to its fullest while self-service reveals that this new order elevates the criticality of HMS (Human Machine Systems.) More touch points surface compared to what legacy technologies allowed given their constraint and restricted nature. That prompts a new take on HCI (Human Computer Interaction) and QbD (Quality by Design) to best deliver service quality throughout: concept exploration and service definition, fulfilment and adaptation, assurance and security… across multi-domain, highly decomposed, re-configurable and exceptionally dynamic end-to-end systems involving integration and service delivery in continuous motion.
These are thought out to (a) dramatically optimize support personnel ratios and (b) shift staff’s attention and efforts to value based activities and innovation. These are small agile teams and new talent tasked with jobs involving (c) far greater scale with (d) a wider interdisciplinary scope, and all to be performed at (e) digital speed. In this next-level productivity and more demanding and challenging context, success relies on new tools embracing Design Thinking’s HCD (Human-Centered-Design.)
That is applied to capability models and subsequent modes of operation for (f) HITL (Human “IN” The Loop) Computing largely devoted to deep domain expertise supported by Science Visualization, as well as (g) HOTL (Human “ON” the Loop) for system-wide supervisory responsibilities and ease of service creation and onboarding. HOTL draws from highly abstracted Visualization techniques and Low Code Development revealing the behavior of end-to-end systems and subsystems and adequate flow control.
These are coupled with effective Cybernetics gearing up for context aware 360-closed-loop-control, zooming in and out between distributed and central levels. Last but not least, effective and efficient tools that are characterized by ease of use and consumability do attract many more new users from many more different domains to interact with these systems in a self-service fashion and create new business opportunities as a result.