Thanking Troy Henikoff for a recent1871 walk-thru, which I joined as part of an MIT delegation. We first met at Techstars Demo Day back in 2014. Three years have gone by since, Troy is now a Managing Director with Math Venture Partners, an early to growth-stage fund focusing on entrepreneurial undertakings featuring “an unfair advantage in acquiring and retaining customers to produce outsized returns.” Here is a sample of Math’s portfolio.
1871 is a digital startup incubator and is positioned as Chicago’s premier center for entrepreneurship in the tech sector. Techstars is a startup accelerator and, as pointed out above, Math Venture Partners is an investment firm.
Long story short, 1871 is first and foremost optimized as a community environment. The underlying supporting framework provides collaborative workspaces, training focusing on design, technology and business, which includes senior mentorship, incubators and accelerators. All of these opportunities are available following the under-one-roof collocation practice downtown Chicago.
“What is 1871? The story of the Great Chicago Fire of 1871 isn’t really about the fire. It’s about what happened next: A remarkable moment when the most brilliant engineers, architects and inventors came together to build a new city. Their innovations — born of passion and practical ingenuity — shaped not just Chicago, but the modern world. What started 140 years ago continues to this day. Come to a place where you can share ideas, make mistakes, work hard, build your business and, with a little luck, change the world.” – 1871
Matter is 1871’s neighbor and Chicago’s healthcare startup incubator. As shared in this Chicago Tribune’s article, Chicago has major hospitals, medical schools, pharmaceutical and device companies, a powerful healthcare hub which Matter seeks to galvanize by supporting entrepreneurial initiatives and innovative tech.
Chicago’s area is also home to leading institutions such as University of Chicago, Northwestern University, Loyola University Chicago, The Illinois Institute of Technology, and DePaul University just to name a few. So, academia and industry intersect to take advantage of talent and business opportunities.
My personal interest in environments such as 1871 has to do with a “give & take” experience. Born in Hispania and back in the distant Roman times, Seneca the Younger believed that we are learning even more when we share knowledge that we might already posses. Basically, he was talking about Human Factors and Information Interaction: a virtuous feedback loop kicks in when we strive to articulate thoughts and structure conceptual frameworks to better convey insights. That, in turn, springs new thoughts.
I pride myself about having developed a mix of creative and in-depth expertise on innovation practices thanks to a fortunate interdisciplinary career spanning 20+ years already. That personal belief is backed by specific achievements and, admittedly, some disappointments, both having delivered teachable moments worth reflecting upon.
So, in a “give and take” scenario, my “giving” has to do with sharing know-how and synthesizing relevant advice to entrepreneurs, which I have been able to provide by joining Dr. Moises Goldman’s 1871 mentoring sessions on several occasions.
Going back to Seneca the Younger’s thinking, in exchange for volunteering my time (and whichever insights I can provide) I always get to “take” away valuable experiences back home with me such as:
(1) a sense of great satisfaction and fulfillment that comes from helping others in a meaningful way,
(2) a contagious entrepreneurial spirit that one can instinctively embrace in discussions driven by passion and determination,
(3) their combined positive impact in my own work since they re-energize my thoughts and goals.
My grandma used to remind me about a Spanish saying that translates into “tell me who you walk with and I’ll tell you who you are,” which might equate to “birds of feather flock together” in English. In any case, and leveraging Human Factors again, social and professional networks can be graphically depicted by nodes (individuals) and links (relationships), which can carry information such as reputation and influence levels, as well as information dissemination paths. So, I’m glad to count those who I interact with at 1841 as part of my network and can only hope that this is a mutually beneficial relationship.
“Develop foresight, to sense and understand the context around the dilemmas that challenge you. The goal is not to predict what’s going to happen but to provoke your creativity and prepare you for your biggest challenges, many of which are going to come in the form of dilemmas (…) leaders are sense makers, and they help others make sense- often by asking penetrating questions.” Get There Early by Bob Johansen.
Situational Awareness (SA) involves sensemaking. SA deals with critical information on what’s going on with a project as well as around it. Know-how, past experiences, lessons learned and best practices are of the essence. These work well when addressing incremental innovation. Though, our perception is also shaped by motivation, expectations, filters as well as organizational behaviors (culture, workstyle, decision making, roles and responsibilities, processes) and, possibly, conflicting priorities.
Taking things to new levels, disruptive innovation gets us immersed in what turn out to be game changing environments. In this specific context, creative destruction takes place and so do errors in judgment. Dealing with uncertainty, ambiguity and rapidly superseding cascading events can quickly render one’s viewpoint out of focus and even out of place.
Those just sticking to what they know because relying on one’s “assumptions and belief system” has consistently served they well, might now suffer from complacency, myopia and tunnel vision instead… experiencing blindsiding denial in the process. Clayton’s “The Innovator’s Dilemma” and Taleb’s “The Black Swan” and “Antifragile” are worth understanding.
Early awareness takes continuous listening and monitoring. Lets first think of project sensors gathering data and probes strategically placed to explore and discover clues which might not yet be visible. Leading indicators form a set of metrics that change in advance to a given event taking hold and can be used to raise alerts. Lagging indicators signal conditions in place for changes to take hold and become the new pattern.
Defining a narrow set of key performance indicators (KPI) improves visibility, saving us from clutter and information overload. KPIs can correlate and synthesize need-to-see data and can work with high level abstractions. These are usually delivered as “dashboards” that we can easily work with. Here is a “6 R” framework on KPI quality to mitigate distortions:
|Relevancy: validity and utility level in context.||Resolution: meaningful detail and abstractions.|
|Range: scope (fields) and scale dimensions.||Recency: lifecycle – growth, decay and refresh velocity, ephemeral vs. durable.|
|Robustness: complete or sufficient to support the analysis, portrays what’s being measured.||Reliability: data integrity and error free, factors signal to noise rate, accounts for outliers.|
The above is based on a “5 R” version I first learned on an MIT course about big data and social analytics.
I would also like to share that perfect data might be elusive and different quality levels can be applied. Hence, we talk in terms of things being “directionally correct” or “good enough” to keep things moving. In some other cases, over-engineering data by going beyond what’s really needed (data overload) can shortchange focus, efforts and budgets, which would be better allocated to other priority and/or pressing tasks. We can also face crunch time situations when we need to operate without benefiting from more data since delays would trigger higher risks.
Nonetheless, acknowledging that we need to make those kind of judgment calls does not excuse giving up on perfecting how to work with data. But, data alone will not deliver SA: this involves intertwining analysis and synthesis cycles as well as fine tuning sensemaking, which is an iterative and continuous improvement process.
Keeping cognitive biases at bay is a challenge. Subjective statements supporting adversarial stances such as “been there done that, it just doesn’t work” (even if that experience happened in a different context and a distant past) or the “not-invented here” (NIH) “not-one-of-us” syndromes can be easy to spot. But, there is a wide range of logical fallacies and “devil’s advocate” plays which can be perceived as reasonable even though the underlying logic is flawed.
I designed the above chart drawing from the all familiar Strengths-Weaknesses-Opportunities-Threats (SWAT) model. As far as Frequently Asked Questions (FAQ) is concerned, the one I get the most is about the difference between “clash” and “shift”. Basically, the clash’s bucket is there to outline ongoing mismatches and adversarial confrontations. Those having reached critical mass can be plotted in the “clash x critical” quadrant.
The “shift” column captures game changing items that are still evolving, where a succession of disruptive believes and assumptions reshape the context and prompt new environments that can render a project obsolete… shouldn’t we gear up in advance or course correct as needed. Looking into impact levels, correlations, outliers and then sorting things accordingly is part of the thought process.
The next FAQ relates to how to best address “core” vs. “beyond comfort zone”. A core competence is an existing skill and capability. This refers to traits worth leveraging and further developing provided that they continue to make a difference. Though, asking any person, organization or system to just focus on what they already know and do well might not necessarily be the best approach in today’s rapidly changing and commonplace uncertain environments. Therefore, the need for assessing what and how to continuously grow beyond a given comfort zone, and at what point that new capability can be rolled up as a core competency.
One other thought, let’s keep in mind that being aware and alert are good things. Taking no action or seating tight while waiting for the dust to settle happen to be options available to us, though paralysis by analysis or paralyzing fear are not.
What about “organic” vs. “inorganic”? The former entails opportunities that can be approached with existing competencies and, possibly, scaling by growing resources. The latter talks to efforts that involve collaborating (collaborating with customers and partners, coopetition with competitors) and even acquiring other ecosystem players in the value chain, mergers being another example.
Last but not least, perspective is of the essence and the journey is comprised by experiences (where we come from) situational awareness (where we are) and foresight (where we are headed). Antonio Machado (Spanish poet, 1875-1939) stated that we make our path as we walk, which anyone working on innovation projects can relate to. Delineating and providing a sense involves the following “journey points”, which I will discuss on another post on agile project planning:
Hope this remains of interest. As usual, I will welcome your comments and emails to continue our discussion.
“The Mother of All Demos is a name given retrospectively to Douglas Englbart’s December 9, 1968 […] The live demonstration featured the introduction of a complete computer hardware and software system called the oN-Line System or more commonly, NLS. The 90-minute presentation essentially demonstrated almost all the fundamental elements of modern personal computing: windows, hypertext, graphics, efficient navigation and command input, video conferencing, the computer mouse, word processing, dynamic file linking, revisions control, and a collaborative real-time editor (collaborative work). Engelbart’s presentation was the first to publicly demonstrate all these elements in a single system. The demonstration was highly influential and spawned similar projects at Xerox PARC in the early 1970s. The underlying technologies influenced both the Apple Macintosh and Microsoft Windows graphical user interface operating systems in the 1980s and 1990s.” – The Mother of All Demos, Wikipedia.
Compelling demonstrations can make all the difference when introducing emerging technologies. There is no slideware or paper substitute for the kind of revelations, quality insights, and lasting emotions that we all get when experiencing things live and first hand. On the research side, interactive demonstrations have become invaluable tools that expose and test concepts. Moreover, they prompt invaluable feedback by questioning, validating, unveiling unsuspected items as well as winning hearts and minds to further advance a cause.
Those are some of the reasons why I prioritize demo development and my research process involves activities such as field trips and ethnographic insights captured in environments like the Museum of Science and Industry (MSI) in Chicago and open-door showcases at renowned institutions like Fermilab. Successful science exhibits make complex topics approachable and engaging. They are carefully designed with craftsmanship pride to be perceived as astute, immersive and to appeal to our brain’s intuition and intellect.
The above graphic features quotes from Albert Einstein and Nicholas Negroponte on the left, coupled with Salvador Dalí and Arthur C. Clarke on the right. I created that poster’s first version a few years ago and became my reference framework for prototyping and demonstration since. The photographs are courtesy of Wikipedia. Here are further insights on what these quotes mean to me:
1.- DEMO OR DIE – The introduction of inventions and diffusion of innovations relies on effectively conveying clear and concise value. Interacting with engaging demonstrations can be best supported by well thought out whiteboarding sessions. This communication strategy works best when allowing dynamic conversations instead of long agendas packed with presentation monologues. Most people can talk about the many times when they were either overwhelmed, underwhelmed or just bored to death by slideware… and became suspicious of hype. Note that we all deal with an unfavorable Signal-to-Noise (S/N) ratio in today’s information rich environment and, therefore, compete for customers and/or users’ undivided attention. Once again, memorable hands-on demonstrations can make all the difference.
2.- GROW TO LOOK LIKE THE PORTRAIT – High tech is a fast paced industry. One can be left wondering if the technology, toolset, application and/or overall system being discussed will grow and scale as needed beyond day one. There can also be concerns around maturity levels, roadmapping options and future proofing when working with emerging technologies. Demos can be used to convey a tangible vision based on attainable end-goals. They can also be used for what-if-analysis, sunny and rainy day scenarios (which can include full lifecycle and stress tests) and plot plausible journeys to go from A to B and any steps in between. Helping everyone come to terms with what lays ahead is key to defining product strategies and planning decisions “to grow to look like the portrait.”
3.- EXPLAIN IT SIMPLY – Apparently unavoidable jargon and well intended technical kumbaya can become easily entangled. Complex explanations suffer from information overload. Convoluted narratives pleasing the presenter’s ego can make unclear what specific problem or pain point he/she solving, and what the sought after benefits and priorities are. When “less is more” it definitely pays to define a vantage point, zoom out, distill fundamentals and synthesize the essence. Knowing your audience and getting the job done in the clearest and most effective terms possible means striking a balance and staying away from oversimplifying or complicating matters. This is an iterative exercise that often demands more time, effort and reviews than the usual information dump. We also need to be able to step-zoom to deliver the next level of detail and to conduct deep dives… without incurring information overload. Humanizing technology, storytelling techniques and ease of information visualization are key to developing a coherent narrative.
“The meaning of a communication is defined by the Change and Affect it creates for the audience. Stories are concerned with transformation. In stories something Changes to create an emotion […] The Change has to resonate with the Audience to generate an Affect; a feeling, a reaction or an insight […] We shall consider these two defining characteristics of narrative to clarify the purpose of any communication […] Change and Affect create meaning. – “Crackle and Fizz. Essential Communication and Pitching Skills for Scientists.” – Caroline van den Brul. Imperial College Press.
4..- IT’S MAGIC – This is all about the so called X-FACTOR: an unsuspected quality making something be different and special in unequivocal terms. To be more precise, the X-FACTOR’s experience can be broken down as follows:
- SURPRISE FACTOR – this relies on managing perceptions and the discovery process, the tipping point being delivered by a timely and unsuspected clever twist and a defining punch line – the “aha” moment.
- WOW FACTOR – high impact, impressive, awe-inspiring outcome, benefits and results that can be easily understood and embraced – the “I didn’t know we could do that” and “I want to know more” moment.
- COOL FACTOR – elegant sophistication and grace, clear object of desire – the “I want that” moment, this being most demos’ ultimate Call-To-Action (CTA.)
The art and science behind the above is known as “affective design.” Techniques such as perceptual learning and emotional intelligence in design (emotional design in short) are applied in Human-Computer-Interaction (HCI) to foster pleasant ease of use, drive further engagement and productive usage in the process. Widespread digitalization and the advent of wearables make HCI commonplace, which is influencing product design.
The above is a demo’s “full disclosure” chart, which breaks down what’s real and what’s not. This is needed because vaporware can be an issue of concern.
1.- PRIOR ART – In the above example, a given percentage of the demonstration system involved known technologies, some from third party partners.
2.- STATE OF THE ART – The greatest and latest features, cutting edge delivered by technologies that are available today.
3.- FUTURE ART – A sneak preview of new features and capabilities that are planned, undergoing development and/or committed, but not yet available.
4.- ART OF THE POSSIBLE – Proof of Concept illustrating experimentation results and potential, bleeding edge capabilities that are not yet committed.
By the way, vaporware is the result of positioning 3 and 4 as part of 2. Avoiding unpleasant misunderstands prompts the need for disclosing these four different maturity levels. Note that one graphic applies to a comprehensive demonstration system encompassing those four aspects and their relative weight.
One other thought, there is a difference between incremental and disruptive innovation. The first delivers improved qualities such as better performance in A/B comparison testing as an example, “A” being prior art and “B” state of the art. Most would agree on defining disruptive innovations as game changers which deliver unique capabilities that clearly supersede legacy and conventional systems. That alone renders “A” obsolete. A/B comparison testing leads to discussions on the difference between Present Mode of Operations (PMO) and Future Mode of Operations (FMO.)
“Humanists must be educated with a deep appreciation of modern science. Scientists and engineers must be steeped in humanistic learning. And all learning must be linked with a broad concern for the complex effects of technology on our evolving culture.” – Jerome B. Wiesner.
“See inner relationships and make connections that others usually don’t see; we learn to think the unthinkable. On the other hand we may be uncomfortable with the insights that arise from from seeing the world differently. However, we need innovation and creativity that steams from seeing things differently […] I recommend that you start to manage your own dilemmas.” – Get There Early: Sensing the Future to Compete in the Present by Bob Johansen. 2007 Edition published by Berrett-Koehler.
“They preferred to think they worked not in a laboratory but in what Kelly once called ‘an institute of creative technology.’ This description aimed to inform the world that the line between the art and science of what Bell Labs scientists did wasn’t always distinct […] many of Kelly’s colleagues might have been eccentrics […] working within a culture, and within an institution, where the very point of new ideas was to make them into new things.” – The Idea Factory by John Gertner. 2012 edition published by The Penguin Press.
“He kept asking Kay and others for an assessment of trends that foretold what the future might hold for the company. During one maddening session, Kay, whose thoughts often seemed tailored to go directly from his tongue to wikiquotes, shot back a line that was to become PARC’s creed: the best way to predict the future is to invent it.” – The Innovators by Walter Isaacson. 2014 edition published by Simon & Shuster.
Inventions involve the creation of a novelty which is, therefore, something new and different. Note that innovations take matters further since they entail realization, introduction and adoption processes. I am fortunate enough to have experienced both. My research work is credited as either inventor or co-inventor in patents and awards. But that alone does not necessarily imply actual development. Getting into innovating as such came to fruition when undertaking product management responsibilities.
Those of us thinking of the commercialization of inventions and the so-called diffusion of innovations are attracted to qualitative and quantitative metrics. These are valuable insights and data speaking to the correlation between inventing and innovating, which leads to articulating best practices, processes, budget and resource allocations. However, it is also true that success can, often times, be powered by outliers.
As the “black swan theory” states: there can be easily dismissed and hard to predict impactful events that end up changing everything. Long story short, the art of serial innovation is a dynamic endeavor: just relying on what you think that you knew well can cloud and betray one’s otherwise better judgment. This is when “objects in the mirror are closer than they appear,” metaphorically speaking, and things just happen at unprecedented speed.
Most would agree that good ideation can come to the surface anytime and anywhere from subject experts, users themselves as well as unusual suspects. Inventing takes a higher commitment level to address how things should work… and there can be alternative and competing solutions to a given problem. Serial innovation becomes a greater challenge since is it measured by repeated success.
I created the above framework in the context of the high tech sector. It conveys a need for striking an equilibrium point between unmanageable complexity (right) and either self-defeating oversimplification or undifferentiated simplicity for that matter (left.)
Semantics matter: anyone can argue the merits and faults of simplicity and complexity. Though, delivering elegant sophistication displays consensus thanks to a clear level of quality and refinement, functional depth and differentiation, effortless operations and ease of use. One other thought: I would also like to claim that purposely engineering effortless ops and ease of use drives everyone’s energy to focus on value based activities. We democratize innovation in the process.
The first chart became a vehicle to discuss the difference between invention and serial innovation. Let’s now look at the difference between incremental and disruptive innovation.
Innovating drives changes. Nonetheless, legacy systems can continue to benefit from incremental innovation. This means bettering and further optimizing current technologies and operations. Existing footprint and know-how combined with economies of scale, as well as risk aversion, expensive switching costs when considering emerging tech and possible resistance to change… all favor that phenomenon. So, it pays to understand Daniel C. Snow’s teaching on “old technologies’ last gasp” when outlining transition and/or transformation plans.
The lower right quadrant is where new paradigms are set to deliver disruptive innovation. B2 is is clearly set beyond the reach of legacy systems: diseconomies of scale and diminishing competitiveness with declining returns being key reasons. B2 means that legacy tech is clearly outdated and superseded.
Disruptive innovation is the game changer. That’s the kind of paradigm shift that new entrants and green field players will take advantage of. The so-called industry establishment can continue to skim incremental innovation, though only up to a point at which they are rendered “old guard” and obsolete. That is the essence behind Clayton Christensen’s Innovator Dilemma.
The upper row shows quadrants A and B1, and an obvious intersection zone in between. Established players can operate hybrid environments to cross G.A. Moore’s chasm. They can gradually transform or fully re-invent themselves at that intersection. The above chart is designed to help leaders and management consultants plot portfolios in each quadrant as well as their evolution (e.g. course and speed.) based on KPI (Key Performance Indicators) or set phased discontinuity.
Quick recap. Incremental innovation delivers better (technical, operational, financial) performance, which is usually presented in the form of A/B (before and after) comparison tests. Disruptive innovation brings about unique capabilities that legacy systems cannot match. We are talking about emerging technologies, so capability and maturity models come into play. I will discuss that in one of my next posts on Lean Ops Redefined.
We have discussed insights around invention and serial innovation, incremental and disruptive innovation. My next tool is design to map out where value exists, new value is created and value migration across the two.
No doubt, disruptive innovation alters the landscape: value migrates (or circles back) to any of the above quadrants. Some markets are placing a premium in the upper right quadrant already. That’s where end-to-end solutions and services create new value and dominate, which commands higher margins. Service focus seeks understanding and developing customers’ experiences instead of a product push or pull approach. Solution focus forces a more holistic systems engineering approach encompassing the value (supply) chain and relevant ecosystems.
That combination delivers significant competitive advantages with the advent of virtualization and cloud computing technologies. Early draft versions of that chart showed a different breakdown, namely: hardware, platforms, applications and services. When testing and putting this kind of charts to work, I could plot everything by applying color coding, then size of the addressable market, revenue and growth would determine each circle’s size. In any case, that basic template can be customized as needed.
“Inventing the future” can certainly take unique instincts, skills, workstyles and eccentric behaviors. When acknowledging that talent is a critical success factor, we then need to get serious about quipping individuals to make a difference while understanding that it takes a cross-functional team to make things happen. Serial innovation takes foresight, situational awareness, leadership and organizational agility. I hope that the above tools helped with mapping and discussing concepts such as (c) defining value, (b) transformation, and (a) moving the needle with elegant sophistication as the defining delivery.
Wondering about the last chart on Lean Ops? That one is just a sneak preview in advance to an incoming post also centered on “Innovation Management Essentials.”
As usual, looking forward to comments and emails, as well as meeting at any of these venues: