Tagged: Hardware

The Impact of Groupthink in Decision Systems


“Together with his identical twin brother, Scott, he has laid the groundwork for the future of space exploration as the subjects of an unprecedented NASA study on how space affects the human body, which is featured in Scott’s New York Times best-selling memoir, Endurance: A Year in Space, A Lifetime of Discovery.”

“Currently, Mark is on the Commercial Crew Safety Board at Space X […] and is the co-founder of World View, a full-service commercial space launch provider.”

Endeavour to Succeed. College of DuPage, Department of Physics. February 14 2019.


I managed to attend Captain Mark Kelly’s talk in Chicago just the day before I was leaving for Barcelona’s Mobile World Congress. M. Kelly’s presence and insightful remarks commanded both admiration and utmost respect.

Among many other fascinating topics, he discussed NASA’s None of US is as Dumb as All of Us as a reminder of the negative impact of ‘groupthink‘ in the context of faulty decision making. Most specifically, he referred to dramatic mistakes leading to the Space Shuttle Columbia disaster, which disintegrated upon re-entry in 2003.

“Large-scale engineered systems are more than just a collection of technological artifacts. They are a reflection of the structure, management, procedures, and culture of the engineering organization that created them.”

“They are also, usually, a reflection of the society in which they were created. The causes of accidents are frequently, if not always, rooted in the organization—its culture, management, and structure.”

“Blame for accidents is often placed on equipment failure or operator error without recognizing the social, organizational, and managerial factors that made such errors and defects inevitable.”

Nancy G. Leveson, MIT. Technical and Managerial Factors in the NASA Challenger and Columbia Losses: Looking Forward to the Future. Controversies in Science and Technology Volume 2, Mary Ann Liebert Press, 2008.

NASA 1Groupthink is part of the taxonomy of well-known cognitive biases and takes hold when divergent thinking and disagreement are discouraged (and even repressed) as part of group dynamics.

Hindsight is 20/20 and, statistically speaking, ‘black swan’ events are characterized by seemingly random surprise factors. Groupthink can obfuscate the early detection of predictors such as leading outliers and anomalies, which left unattended can overwhelm a given system over time… and be the source of cascading effects and critical failure.

Groupthink’s negative impact compromises any best intentions such as organizational cohesiveness in the spirit of consensus, agility, productivity, timely project progress and de-escalation management.

Often times, there might be neither adequate situational and risk awareness nor a basis for sense making drawing from the comparative analysis that comes with diligent scenario planning.

Individuals and organizational cultures with a succesful track record can also experience complacency. Over-confidence fosters the sort of behaviors and decisioning that served the group well in the past.

Though, when in the mix of a changing environment defined by new parameters under the radar, only operating within the perimeter of a given set of core competences and comfort zones, makes those specific behaviors blindsight and betray the team’s mission and purpose.

Many plans do not survive first contact (or a subsequent phase for that matter) as their implementation creates ‘ripple effects’ of various shapes and propagating speeds. Some of that can be experienced as ‘sudden risk exposure.’ Once passed the ‘point-of-no-return,’ if that challenge is met with neither contingency planning nor the ability to timely course correct, pivot or even deploy a basic safety-net offsetting the impact, the project fails to ‘cross the chasm’ and is headed for what’s technically known as the ‘valley of death.’

This was one of the key issues discussed by Clyton M. Christiansen when I took his Harvard class on the ‘Innovator’s Dilemma,’ and is also a key point behind Risto Siilasmaa’s ‘Paranoid Optimism’ as well Paul Romer’s ‘Conditional Optimism,’ all of which advocate for scenario planning and sensing optimization to be able to calibrate or re-assess the path forward.

“Michael Shermer stated in the September 2002 issue of Scientific American, ‘smart people believe weird things because they are skilled at defending beliefs they arrived at for nonsmart reasons.”

Groupthink can also manifest itself by means of ‘eco chamber’ effects’ as misguided consensus amplifies what becomes a “self-serving” bias. That is, in effect, a closed feedback loop process that magnifies logical fallacies. These can come across as reasonable enough postulates, though if based on rushed judgement and selective focus they can also suffer from ‘confirmation bias.’ This is the case when new evidence is only used to back-up the existing belief system rather than share new light.

In the context of Decision Support Systems and Cognitive Analytics, the above reasoning deficits become root causes of errors impacting operations. That can involve both (a) Human-Human and (b) Human-Machine interactions, as well as impacting programming work resulting in (c) biased algorithms and automation pitfalls when left unsupervised.



Carisa Callini. Human Systems Engineering. NASA, August 7 2017. https://www.nasa.gov/content/human-systems-engineering

Carisa Callini. Spaceflight Human Factors. NASA, December 19 2018. https://www.nasa.gov/content/spaceflight-human-factors

Clayton M. Christensen. The Innovator’s Dilemma. Harvard Business Review Press, 1997.

COD Welecomes Astronaut Mark Kelly. Daily Herald, February 13 2019. https://www.dailyherald.com/submitted/20190201/cod-welcomes-astronaut-mark-kelly-feb-17

Geoffrey Moore. Crossing the Chasm. Haper Collins, 1991.

MIT Experts Reflect on Shuttle Tragedy. MIT News, February 3 2003. http://news.mit.edu/2003/shuttle2

Tim Peake. The Astronaut Selection Test Book. Century. London, 2018.

Scott Kelly. Endurance: A Year in Space, a Lifetime of Discovery. Knopf. New York, 2017.

Scott Kelly. Infinite Wonder. Knopf. New York, 2018.

Steve Young. Astronaut: ‘None of Us is as Dumb as All of Us.’ USA Today – Argus Leader, May 13, 2014. https://www.argusleader.com/story/news/2014/05/13/astronaut-none-us-dumb-us/9068537/

Will Knight.  Biased Algorithms are Everywhere, and No One Seems to Care. MIT Technology Review, July 12 2017. https://www.technologyreview.com/s/608248/biased-algorithms-are-everywhere-and-no-one-seems-to-care/


Agile Software in a Hardware World


“The world of IoT and connected devices is expanding rapidly. We all carry super computers in our pockets and interact with everything from home automation, cars, consumer electronics, and healthcare devices.”

“In this complex hardware + software environment the product development cycle can be tricky. For example, you can’t just follow agile software practices by the book when you’re building a connected pace maker. So how do we approach product development when the stakes are high and the moving parts are many? During this discussion we’ll be tackling topics such as:”

“How do you roadmap a product which includes both hardware and software components? How does agile development fit in? How does the regulatory landscape affect how we approach development and iteration? How do you build teams around these integrated products? And how do you keep them in sync and working together?”


I’d first like to thank the team at DevMynd for their kind invitation. I am looking forward to joining the panel discussion in Chicago this coming Thursday, February 22. In the meantime, I will welcome any comments and insights as I gear up for this discussion.

I’m working on outlining some of the myths, dilemmas and trade-offs that I have encounter as an Industrial Designer and in Product Management.

From a design perspective, there are two topics worth looking at: Design Thinking as a Human-Centered methodology and its outcomes in terms of: (a) utility, (b) usability, (c) consumability, (d) affectivity and (e) the composite and differential value of the resulting digital experiences that involve software and hardware.

This “new brave world” equips us with the freedom to explore new form factors, cognitive models and, most importantly, the development human x technology networks. Some of the specifics come down to design semantics re-defining HMS, Human-Machine-Systems, in the context of multi-modal user interfaces and innovative interactions where Machine Learning and new visualization paradigms happen to surface.

From a Product Management viewpoint, there is a need for also pondering about how to best leverage Design Thinking beyond Industrial Design and Software Development to tackle product and service strategy. Here my focus gravitates toward addressing: (a) success factors and (b) limiting factors under control, as well as (d) other determining factors beyond our area of influence that can impact the diffusion of innovations either positively or negatively. Moreover, I like to couple business model innovation with behavioral economics and information network effects.

This construct really boils down to capturing the essence behind (e) stakeholders’ acceptance criteria and (f) the users’ engagement, adoption and growth rates. This means defining capability and maturity levels and how to best factor for the fact that they adapt and evolve over time. Obviously, this leads to taking a close look at how to best intersect Lean and Agile practices, but not only, so that we can lead and navigate constantly changing environments in “digital time.”

Let’s get down to a more tactical level: end-to-end system design entails a mix of loosely and tightly coupled elements, and a platform approach to operate at speed, scale and wider scope that what black boxes can match. A reality check unveils a hybrid world where decisions on capacity and performance levels, as well as serviceability and dependency levels drive decisions toward optimizing for distributed systems and, therefore, the rising value of end-to-end solutions vs. point solutions only.

In that context, inter-disciplinary teams involving creative technologists and domain experts make our organizations effectively diverse, smarter and innovative. Otherwise, self-defeating arrogance, conflicting silos and technical myopia can make pre-production and production be costlier by promoting unnecessary friction and getting everyone to work harder and harder rather than smarter. Typically, that negates productivity, forces a number corrective actions, and significantly shifts and/or downsized sought after results.

The beauty of the Studio’s human-experience-centered practice is a healthy obsession for delivering “meaning.” The definition of “meaningful outcomes” (rather than churning outputs) makes these organizations behave based on value and impact. We strive to foster not just customer satisfaction and net promoter scores, but measurable customer delight and network effects (superior and service-level performance indicators) which, in turn, set and streamline technical requirements.

Long story short, the Studio’s mindset (critical thinking / wonder & discovery / problem solving) and workstyle (collaborative / experiential / iterative / adaptive) help explain why creative technologists are instrumental and serial innovation engines for the digital age.


Footnote: the term “team of creative technologists” was first coined by Nokia Bell Labs back in the 1940s to single out the differentiated value of inter-disciplinary undertakings. In the late forties, Bell Labs’ Claude Shannon pioneered Information Theory and John Karlin set up the first Human Factors Engineering in industry. That HFE team was formed by a psychologist, a statistician (the father of quality control visualization,) an engineer, and a physicist.