“The ultimate test of a practical theory, of course, is whether or not it can be used to build working systems. It is good enough to use in the real world? […] Almost uniquely among the social sciences, this new social physics framework provides quantitative results at scales ranging from small groups, to companies, to cities, and even to entire societies […] it provides people –e.g., government and industry leaders, academics, and average citizens- a language that is better than the old vocabulary of markets and classes, capital and production […] the engine that drives social physics is big data: the newly ubiquitous digital data now available about all aspects of human life. Social physics functions by analyzing patterns of human experience and idea exchange.” – Social Physics by Alex Pentland.
Back in 2010 I worked on the Amazing Learning Unit, a research project leading to a proof of concept demonstration. The anecdote behind it’s name was that by calling it A.L.U. we played with the fact that those same three letters formed Alcatel-Lucent’s stock ticker. On a more serious note, we partnered with Lego and the Illinois Math & Science Academy (IMSA) to unveil a simulation at Mobile World Congress in 2011, which was very well received.
The Amazing Learning Unit’s concept entailed “Lego robotics” equipped with Touchatag’s RFID readers and Android phones and tablets. As you can see in the above picture, these “mobile units” were designed to look, behave and roam around like autonomous screens, cameras and sensors with wheels.
Driven by human factors engineering principles, the thinking behind the project was centered not on technology, but on taking down the classroom’s physical walls, which can make today’s schools and school districts behave like “geofenced silos”. This is an environment that can constrain kids’ exposure to an outside world that’s growing more connected and diverse. The project’s main goal was to enable boundariless collaborative learning, our technologies being the means to that end.
The concept called for the robots to roam around the classroom and sense what a kid was playing with, or what book she/he was reading. Classroom’s objects and books would feature the Touchatag’s stickers to that end. The result is a mobile sensing network that falls in the IoT, Internet of Things, category.
Leveraging social analytics, we thought of a “serendipity engine” which would then connect the kid with another child from any other school who would be engaged in a similar activity, and whose skill and learning behaviors happened to be a good match for them to play together. The smartphone screens would prompt interactive online activities jointly with video calls engaging them in context-aware and “peer-to-peer collaborative learning”.
We discussed what’s now known as collaborative filtering and matchmaking options to promote role model behaviors and how to adequately display them to help realize everyone’s potential, and to do so in everyone’s best interest. We also looked into sensitive matters centered on behavioral analytics, privacy and the pros and cons of emotional and persuasive design features.
As part of the project’s research, gamification techniques were thought out to incentivize players, such as competitive challenges, progressive skill levels, in-game rewards and scoreboards. Circling back with a recent post on working with personas, the ones created for this project were modeled after our own children and my kid inspired and enjoyed participating in the project’s living lab.
The prototype unveiled at Mobile World Congress showcased some of the above concepts. It is worth sharing that the business goal was to help experience some as complex as the IP Multimedia Subsystem (IMS) in a new and radically light back in 2010. I strived to humanize what can otherwise come across as overlay technical and rather obscure sets of technologies behind network infrastructure, platforms and telecommunication services, the essence of our company’s product portfolio. Therefore, we purposely placed the emphasis on creating new experiences such as the one delivered by the Amazing Learning Unit. Our inventiveness and technologies became transparent and were in place to deliver the magic.
Interestingly enough, this research project led to discussions with MIT and a leading global network operator. That time around, we looked at how this kind of experiences can be applied in enterprise environments to raise productivity and foster collaborative and multi-disciplinary workstyles. Enabling new organizational and decision making cultures in other words. The following phase of the research was titled Immersive Mobile Systems, IMS in short : )
“A great idea is only the beginning. The Back End of Innovation provides a strategic road map to successful commercialization. Learn how to bring new products to market and commercialize them for maximum impact on the bottom line. Uncover new ways to solve problems we all encounter in today’s dynamic business world.”
Back End of Innovation #BEICONF
I am working on the talk that I will deliver at Back End of Innovation 2016 and just came across BEI’s banner on prominent sites, such as CNN’s Innovation section (left screenshot).
The organizers have made available a discount code, which I can share if you were interested in attending. If so, feel free to send me a message on LinkedIn.
The conference’s agenda features speakers from 3M, Cisco, Coca-Cola, Fidelity, Johnson & Johnson, Keurig, Pepsi, Vodafone and Xerox among others and I will be there proudly representing Nokia.
My talk’s title is “Lean Ops Innovation: Dynamic Service Delivery,” which is scheduled on November 17 at 11:30. Here is the abstract:
“Network Operators in the telecommunications industry operate complex sets of technologies and environments. This sector’s future relies on furthering software defined systems supporting the next wave of pervasive digital services, which all of us come to rely on in our day-to-day lives.
Nokia’s Applications & Analytics (A&A) team has evolved and redefined Lean principles to intertwine advanced analytics, automation, programmability and human factors engineering, the four pillars of a new LeanOps’ framework. The outcome is effective service delivery enabled by highly efficient systems that remain nimble and agile at any scale and at any point in the life-cycle.
Join Jose for this session to learn:
- A new Lean Ops framework intertwining analytics, automation, programmability and human factors.
- How to effectively interweave Design Thinking, Lean, DevOps and Agile to deliver breakthrough innovation.
- Unlocking the value of Human Factors Engineering in the cloud age and, therefore, expanding the human possibilities of technology.”
Earlier in the year I gave a talk at IEEE Communications Quality & Reliability – CQR 2016 also on Nokia’s Lean Ops.
Back then, my focus was HCI, Human-Computer-Interaction and operational efficiencies. As an example, immersive user interfaces taking advantage of 3D data visualization coupled with autonomation and assisted automation, as well as continuous optimization lead to effective decision support systems (DSS) that mitigate human error and elevate value based tasks.
That was discussed in the context of the kind of complex operational environments experienced in the telecommunications industry by network operators. As shared above, my presentation at BEI will focus on the underlying construct instead.
This is my “75 word” bio for this event: “Jose is a Design Director at Nokia’s Applications & Analytics Group. His 15+ years of experience feature leadership responsibilities in strategy, product management, R&D, and marketing. Jose worked with Bell Labs and holds three patents. He is a Member of the Advisory Board at MIT IDSS and is the recipient of an MBA from Chicago’s DePaul University as a Honeywell Europe’s Be Brilliant Scholar. Jose holds a postgraduate degree in Human Factors Engineering from BarcelonaTech.”
This is the second time that I’m featured as part of BEI’s Speaker Faculty and I would like to take this chance to thank the team at Informa for their kind invitation.
I will be happy to meet at BEI and hope to see you there : )
“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.