 In the past decade and a half, I have seen entire industries being disrupted by upstarts using absolutely none of the traditional resources businesses needed in the past to keep growing. Examples: Uber vs. Taxis, Twitter vs. the Press, Netflix vs. Cable. Uber doesn’t own a single car, Twitter doesn’t have a newsroom, Netflix doesn’t own a content distribution network. How are they doing it? They’re all platforms, they use technology to connect and manage supply and demand in real time. Platforms are powerful because they eliminate gatekeepers and create community feedback loops called network effects. Example: more demand attracts more drivers, more drivers increases geographic coverage, more coverage gets faster pickups, fast pickers means more users join the platform, and so on. In turn, driver downtime goes down, which reduces prices, which leads to more scale. In the past, dominance was achieved through supply economies of scale via increased production efficiencies. Today, it’s all about creating demand economies of scale using technology on the demand side to create ever larger networks of value and scale. Building a platform: This isn’t about creating a good or service and channeling it to customers! First, a platform starts with enabling a direct interaction and the exchange of value between participants – producers and consumers. The platform also enables the quantification of value by creating a sort of value unit between participants. Example: for AirBnb the value unit is the listing information created by the seller that is served to buyers based on their search criteria. Second, platforms are really good at attracting users and encouraging interactions. The most difficult is to generate pull because it’s pretty much a chicken-and-egg-type problem: users won’t come to a platform unless it has value and a platform won’t have value unless it has users. The solution to that is called the feedback loop. Example: Facebook realized it had no value unless users had a meaningful number of connections. So instead of trying to get more people to the platform, they focused on getting the existing users find their friends and help them connect. Third, platforms use the data they collect about producers, consumers, the value units created and the goods or services exchanged in order to get the best matching between supply and demand possible, and most importantly, in real time: the more data a platform has and the more effective it becomes to use this data to foster more effective matching and more interaction the more successful it will become. That’s the feedback loop. Iterate to remain: Once a platform has established its core interactions, it’s time to iterate by layering more peripheral interactions on top of them. Let’s by the way take this with a grain of salt, as we need to remember that platforms aren’t entirely planned – most of the activity is controlled by the users which means platform builders must allow themselves to expect serendipitous discoveries by closely monitoring usage behavioral data to unlock new value … Uber X and Uber Pool are great examples, cloud kitchens and Doordash are also coming up to change the way we eat (see my note about cloud kitchens here). Let me know what you think! DM me @philippemora
My name's phil mora and I blog about the things I love: fitness, hacking work, tech and anything holistic. Head of Product and VP Engineering. thinker, doer, designer, coder, leader.
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Let me know what you think! DM me @philippemora
My name's phil mora and I blog about the things I love: fitness, hacking work, tech and anything holistic. Head of Product and VP Engineering at Sikka Software. thinker, doer, designer, coder, leader. This is a really good vlog post by Jorge Conde on where healthcare is going - its totally related to my favorite quote from “The Strain” “In order to fix the hardware you need to re-write the software”. In this talk at the recent a16z summit he explains why biology is the original IT industry and in turn, biology is making us re-invent IT technology itself. In nov 2017, the U.S. spent $2.6 trillion on healthcare in 2010; this is expected to double by 2020. Why so expensive? And why has healthcare been so resistant to the innovations that could bring costs down; why is it still so time-consuming and difficult to bring effective solutions to market? By enabling a more powerful understanding of biology, tech is literally "rewriting" how the healthcare industry discovers, tests, and brings new medicines to market... and ultimately, to patients. Let me know what you think! DM me @philippemora
My name's phil mora and I blog about the things I love: fitness, hacking work, tech and anything holistic. Head of Product and VP Engineering at Sikka Software. thinker, doer, designer, coder, leader. 
At Sikka, I introduced iterative product creation in 2015. It did take us two years however to find our footing and after a lot of trial and error, we finally settled for a design and implementation methodology that works for us (and enables us to deliver those Minimal Lovable Product weekly drops that delight our customers).
Iterative software development = How to create technology that we can build, test and release in small parts rather than building the whole thing and releasing it all at once.
See, after trying Agile and see it fail miserably (for all the good reasons), I did innovate at Sikka and opted for our simple “sikka lean” against continuous delivery and faux-fake-agile.
My personal nirvana would have been a healthy combination of design thinking, agile and lean; however one must always find the right spot based on the DNA of the teams we're working with. For this reason, I'd like to take this opportunity to summarize my take (and an extended summary of a few others) on what are the most efficient iterative design methods in 2017. Lean iterative product creation
This is more or less the de-facto way of developing for innovation and new products: lean - iterative, intuitive, creative (vs. the traditional incremental, staged, uncreative tech methodologies favored in the distant past).
Lean basically focuses on evolving a product based on continuous market feedback by testing every new idea and every assumption with users on a daily (more reasonably weekly) basis. The product team starts by creating a small initial set of features (I call this the “Minimal Lovable Product”) and drops it to the marketplace in order to get immediate end-user validation early on. We then continue to iterate the product in fast build-measure-learn cycles, while the product team prioritizes the features and direction as user feedback data keeps coming in. The lean product development was pioneered and perfected by Toyota for manufacturing (then adopted by Apple) - and very well summarized by Eric Ries in his book “the lean startup”. 
The beauty of Lean is that it connects metrics directly to product development. In other words, there is immediate understanding of the effect of a new feature on the business’s revenue. It places the end user in the driving seat of the product and its roadmap.
Design Thinking
I love Design Thinking. Personally when I ideate I always start by applying Design Thinking to my thought process. Design Thinking, which applies the creative approach of designers to any problem was invented at Stanford’s D-School. It’s a very solid and beautiful process for design and ideation amongst creative types. However it really takes forever if done well to actually hatch anything that makes sense because it heavily relies on guided exploration and brainstorming. And difficult to implement when you don’t have superbly creative types in your product team. But IDEO has been extremely successful and the first to apply Design Thinking to business-driven products.
Benefits of design thinking
Common issues with design thinking
agile
First and foremost, Agile is dead. Agile was created in 2001 as a simple way to implement lightweight development processes to make software better and was built around 4 basic principles: trust, collaboration, improvement, and accuracy.
Then the old-guard (stuck in a closet waterfall mindset and non-technical with no hands-on code writing experience) stepped in and made it “a process”. the result: well, another process. So let’s go back to Dave Thomas’ (and his friends) original manifesto: “We are uncovering better ways of developing software by doing it and helping others do it. Through this work we have come to value:
That is, while there is value in the items on the right, we value the items on the left more.”
I am not going to spend time on scrum and other methodologies that have been invented to implement agile but I’d say this, the key reasons why dev teams love agile are:
However, for as long as agile software development is not part of an agile organization incorporating agile governance and agile budgeting, there is no point in trying to fit a square peg into a round hole … it will fail, here are the common issues that “faux-agile” mindsets have a real hard time to understand:
Companies using adapted versions of Agile (DevOps): Apple, Facebook, Google, GM and Spotify When the Agile mindset is strong, here are the 3 main benefits to the organization:
conclusion
Rapid development methodologies have three major caveats: first, they require a uniform mindset across the board at every level from all teams, most importantly dev and product. The most common pitfall is for dev to demand waterfall-style specifications, supremely detailed flows, prototypes and mocks, though not in the form of PRDs and MRDs but already broken down in long and cumbersome encyclopedia-britannica-style epics and user stories, thus completely negating the purpose and philosophy of rapid development frameworks.
Second, issues will arise when old-school organizational practices, such as re-introducing QA as separate of dev (QA does not typically exist in modern devops orgs) compounds the previous issue by adding another layer of administrative thus slowing down the process. often to a crawl. Remember, in 2017, the data represents the user, and nobody else. The sooner you get your product in the hands of your users, the more and the faster you learn from them. Lastly, devops organizations must understand that with rapid iteration comes with a lot of cost in terms of code written and re-written - teams must provide for some "adjustment" periods typically dedicated to refactoring and re-alignment.
My name's phil mora and I blog about the things I love: fitness, hacking work, tech and anything holistic. Since July 2015, I've been the Head of Product at Sikka. We're using big data, analytics, machine learning and AI to redefine medicine - our angle is the business of being a doctor. What we do is very, very cool. If you want to talk to me about that, you are more than welcome to contact me here or follow me on medium or twitter and chime in.
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i blog about the things I love: fitness, hacking work, tech, Experiences and anything holistic.
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