Tagged: Hardware

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 impoartantly, 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 talkle 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 difussion of innovations either possitively 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 practies, 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 unncessary 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 downsizex sought after results.

The beauty of the Studio’s human-experience-centered practice is a healthy obssession 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 technologysts are instrumental and serial innovation engines for the digital age.


Footnote: the term “team of creative technologysts” 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’ Clauded Shannon pioneered Information Theory and John Karlin set up the first Human Factors Engineering in industry. That HFE team was formed by a pyschologist, a statistician (the father of quality control visualization,) an engineer, and a physicist.