How to go through the Valley of Death

While I was writing my blog post on the 10+1 books an entrepreneur should (have) read, I realized how difficult it is for someone who wants to start with her business immediately to go through this reading list. But even after reading all these books, it takes some time to put all these theories in order and use them in practice.

Thankfully, the last semester I was called in the University – where I do my PhD  – to prepare two lectures on entrepreneurship. I wanted to create a meaningful step-by-step guide on how you start a startup, and how you may increase the chances of success. Thus, I chose to follow the concept of a (successful) startup financing cycle and emphasize on how you may work to overcome the “Valley of Death” phase.

In general, before going deeper on this “manual”, you should be aware of two very influential and useful concepts: the lean startup methodology and the design thinking product development approach. The mindset of these methodologies will help you make sense of what is presented here, while you may apply them on multiple stages and phases of any organization.  The roadmap I came up with is consisted of the following 5 steps and 3 phases (the incorporation may happen till the step of prototyping):


Step 1: Choosing and Building your Idea

Generally, you should choose a topic you are good at, which has a market and of course you want to work on for the upcoming at least 5-10 years.

Your idea may (a) create a new market, (b) provide a new solution on a problem, (c) improve an existing solution, (d) use new channels for reaching customers or (e) improve costs. Typical, you should not bet on creating a new market, unless you have a great innovation.

Your idea will possibly change, the co-founders should be between 2 and 3 people, and the most important success factor is your timing on dynamics you cannot control; the PEST (i.e. Political, Economical, Social, Technological) environment, as well as existing competition, will affect your chances of success. The culture of your social network on accepting success and risk, is also something you cannot change and definitely affects your choices, especially on difficult situations.

Typically, your idea may be (a) problem-driven or (b) solution driven. On the first case, it is easier to find a market and make your customers understand you; you know that your customers have a problem or would like a better solution, and you look on business models and technologies that solve this problem (e.g. Services on Demand, Bait and Hook, Multi-sides platforms etc., you may read this). On the latter case, you are aware, you have a patent or you expect a revolutionary technology to rise, and you look for the market to disrupt (e.g. 3D printing, drones, BlockChain, Big Data, AR/VR etc.). In that case, you may look occasionally on the Gartner hype cycle.

The idea is suggested to be simple, and it may do over the Internet what is done already in real life (of course this approach created the .com bubble, because few took into consideration the PEST environment).

After you find your idea, you may map it to competition with the Idea Maze.

Step 2: Testing your Idea Fast(er)

Don’t forget that your idea is useless without implementation, and your implementation is useless without customers. Don’t also forget to search on well-known tech-blogs on similar startups/companies, but also to search for related patents.

On this step you have to do two things: (a) estimate the size and characteristics of the market, to see if it worths to cope with, and (b) try (smart) to understand your customers.

On the first part, you may use the top-down analysis to estimate the market. Initially you can refer to consultants’ reports on the size of the market, the trends of the market, and the tendency on increase/decrease of the size; a saturated, shrinking market is never ideal case to enter (you may run a Porter’s 5 forces analysis here too). You may use Google Adwords Keyword Planner to see how many people in the countries you target have a similar problem, thus they search with specific terms. Taking into consideration the market pie, and the competition, you may define the part of the market you should capture the first 3-5 years. Then you can end up with a target market. Don’t forget to take into consideration the geo-political environment from the PEST(EL) analysis.

On the latter part,you will use the bottom-up approach to estimate the market. You either know the customer (and you are lucky), or you have to run questionnaires and face-to-face interviews to learn your customer. You should read this book, and don’t forget to ask them for the price they are willing to pay; then you can start segment your market. You may also try to build a landing page to start communicating your message. At the end, if you know what features your customers want and what price they are willing to pay, with the proper segmentation, you can calculate the size of the market you can capture. Then put the market growth aspect and you know where you can be in 3-5 years. If you are uncertain on your estimations, you may run three different scenarios (pessimistic, optimistic, probable).

Now you can put the numbers from both analyses together, and see if you have overestimated or underestimated something. If you have failed to identify your market, do it again or specify better your market related to your idea. This is the market you could reach if everything was perfect (you won’t soon). At the end you will feel some uncertainty, it’s an exciting factor of building a startup.

Step 3: Developing an early Prototype

If you really find a market that worths it, you now have to prove that you can execute what you promised; first of all to yourself and then to possible investors and customers. Many KickStarter campaigns use a prototype to raise funds.

A prototype is an early sample, model, or release of a product built to test a concept or process or to act as a thing to be replicated or learned from. It is  the Apple I, it is the Wii-U Gamepad prototype, it is the iPad prototype, it is the Microsoft Courier. It can even be a scenario concept, or for software it may be a script or a mockup design; as long as it is used to learn faster and make early decisions on the product design, anything can be a prototype.

A prototypes proves:

  • The feasibility of idea/concept
  • The capability of team to deliver
  • Popularity/acceptance from users

A prototype doesn’t prove:

  • Customers’ willingness to pay
  • The business model
  • The viability of an idea
  • The cost structure of the operations

To run a prototype you need typically at least a product manager, a designer and an engineer (or a ninja person with diverse background). Read Sprint book to see how to enable prototyping in your organization.

Step 4: Testing the market with an MVP

At this stage, this prototype has to take the form that will interact with the initial customers (the early adopters). So,you have to start working on various parts of the business model that you have ideated initially, mark the hypotheses that increase the risk and create a plan on exiting to the market. This is where the MVP applies.

Accordingly to Eric Ries, MVP is the product with the minimum set of features, and no more, required to make early adopters start paying and giving feedback. Thus the MVP is a version of the product that tries to maximize the process of learning, with the least possible effort.

Before you move forward, you need to clarify the difference between an MVP and a prototype.


  • Tests business model hypotheses
  • Tries to reach the customer, even if it is not profound to them
  • It’s a Lean Startup tool

A Prototype:

  • Tests design hypotheses
  • Applies on a controlled environment, on focus groups
  • It’s a Design Thinking tool

But both of them focus on fast feedback and fast learning.

An MVP considers that the product is the business model, and may require “hacking” or “mockuping” typical business processes. For example, many MVPs hack others’ business processes (e.g. Zappos, Amazon), others mock smart algorithm or AI with human power (e.g. Food on the Table), others launch a storyboard or video (e.g. Machete the movie, or Dropbox), many others use crowdfunding as validation (e.g. Pebble, Oculus VR), and many books started as blogs (e.g. Running Lean, The art of the start). Many consider also a landing page with subscription property as an MVP, personally I believe it is a prototype of an early idea.

Don’t forget that price is a vital part of the MVP, and should apply on day one to validate the business model. The price is a part of the product (the 4 Ps of marketing), the price defines the customer segment you target, while a paying customer is one of the best metrics of the business model.

Then, iterations start. Till this step nothing is linear, while you may need to run multiple cycles before validating an MVP. Many startups had to restart from step 1, and even change completely the market they addressed. There is even a handy list of available pivot types.

Phase 1: Polishing the Product

Now it’s the time to start polish our product. Brand, price, channels, packaging, company identity is good to be aligned and be addressed by professional designers. The question is if you can charge the customers enough to fuel the scale of the business on the next steps, or external funds will be needed.

Step 5: Improving your proven Business Model

If you have reached this step, you have a first finalized version (v.1.0) of your business model. Now it’s time to start improving it and make it scale. To achieve this, first you have to see the broader picture, and identify the general category where your business model belongs to. Thus it will be easier to identify the workflow of your customers through your company. The most common (digital) business models accordingly to Lean Analytics are:

  1. E-commerce: one sells to many, e.g. Amazon.
  2. SaaS: a solution as a platform for many, e.g. Dropbox or Gmail.
  3. “Free” Application/Hardware: A free or cheap initial purchase, with later purchases for usage, e.g. Candy Crush, Printers, Gillette.
  4. Content Producer: Selling high quality content, e.g. news sites, even Netflix and Amazon productions.
  5. User Generated Content: Users are the producers and the consumers, while you make profit from ads, e.g. Google Search, Facebook.
  6. Two-sided markets: Facilitate the transactions between two market segments, e.g. eBay.

Having identified your business model, you have to describe your customer lifecycle based on Lean Analytics and then track the one metric that matters in each phase; by putting realistic goals (i.e. lines in the sand), you can improve progressively your business while you also learn what works and what doesn’t work on your business.

If you still feel your business model is quite flat, you may adjust some Business Model Innovations, meaning you may apply business models from other industries in your own in order to develop a competitive advantage. If you need a practical guide go for 10 types of innovation, or go to FutureEnterprise blog for some recent examples.

Phase 2: Building a strategy for Growth

Without an unfair advantage it’s difficult to move forward; this is an international game. So check if you have any of the following unique advantages:

  • Inside info of your market
  • An expert in your team
  • A dream team
  • The proper network of people around
  • A community (for me this is a winning point)
  • Existing customers
  • Good SEO ranking
  • Intellectual property/patents

Then, based on your competences you should choose the proper strategy. You may have heard of many strategies, like the Blue Ocean strategy, but at the end everything is summarized in the three main strategies based on Porter’s generic strategies:

  • Cost Leadership (broad market, low cost)
  • Differentiation (broad market, differentiated characteristics)
  • Niche (narrow market)


Don’t try to mix any strategies (you may see IKEA or Zara who became hybrid in time), don’t try to cover everything, don’t try to build a clever strategy. At this step you need to clarify and focus on one strategy.

In execution level, try to start local, think global. Step by step you have to grow.

Phase 3: Preparing to Scale

Now you are ready to grow. Before entering a growth organization lifecycle, with your stricter management structure and your expected crises, you need to deal with two more things: your culture and funds that will grow your organization.

For your culture you need a vision, a mission, strong objectives and a passionate team. You may choose among this styles of culture.

For fundraising, the best quick guide to understand funding is this fantastic infographic. But when you look for fundraising, do not forget the pecking order theory ; the order you look for funds should be the following:

  1. Your own funds (e.g. from revenues)
  2. Debt without risk
  3. Debt with risk
  4. Convertible loan
  5. Giving equity away

The principle where this theory stands is that if you are a good manager, you know what you do, and you do the best you can. Thus you wouldn’t like to sell much part of your business. In practice that also is signaling to your investors, the fact that you share the risk and you believe on what you are doing. Additionally, think how much time it needs to pitch your idea around investors, and how much time it needs to close an investing deal compared to a using your own funds or getting a loan (in a proper economy, not Greece of course 🙂 ).



Q: How much time each step should take?

A: A rough estimation is available in this course, but as long as you may enter in multiple iterations this can only be estimated on money you have to burn in each pivot you make.

Q: Is that all? Is this methodology complete?

A: No, in practice there are many issues, like building your brand day by day, building the right corporate entity, choosing the proper team, choosing the type of customer support, and many more. What I learned from my experience is that there is always a book, a blog post or a Quora reply that replies your specific pain.

Q: Is success guaranteed? 

A: No. If your idea sucks, if you don’t execute, if the team doesn’t collaborate or/and you learn nothing from feedback collected, (you may be a revolutionary but most possibly) you will fail miserably. It’s not the problem of any methodology or guide; Stats are still heartbreaking (90% of tech startups fail, 75% of VC-backed startups fail), and you play againts the odds to get through the Valley of Death. If you want to know the chances and understand the landscape, read Zero to One.

Q: Did it work for you? Why do you share it?

A: Not yet. I have read a lot of books, news and blog posts. I have practiced many more methodologies and tools, I have been wondering a lot how a step-by-step guide would be. But as long as I spent some of my time on filtering information out and put everything in order, I considered it nice to share it with you; I would love to have a roadmap when I started my journey back in 2012.


10+1 Books for Entrepreneurs

  1. Four Steps to the Epiphany: When you have studied engineering and you want to enter the world of entrepreneurship, you would look for a manual. This is a perfect step-by-step guide that changed my mindset and I still refer to once in a while.
  2. Running Lean: When you read Lean Startup (and you read it 1-2 times more), you feel like you have read a blog with experiences. How do you apply it? The missing manual is this book, you may start being Lean with some cost-saving techniques.
  3. Lean Analytics: When you have made it to launch, you need to track everything and improve your solutions. This is the perfect book for (business and technical) engineers to be data-driven, track everything and improve their offering progressively. Lean is not an idea any more, it is a framework.
  4. The Power of Habit: If you want to understand how you can change your own but also your customers’ lifestyle for good, you should start with the Power of Habit. Then you may summarize it with a practical reading (i.e.Hooked).
  5. Ten Types of Innovation: I always wondered why there is no playbook for business models. Business Model Generation started everything but it lacked a practical reference, now building innovative business models looks that easy.
  6. The Information Design Handbook: When you have to communicate a message, in a presentation or a user interface, you have to understand the basics of information design. This is the ideal book, from developers to entrepreneurs.
  7. The Art of the Start: When you start a venture, you need some practical advices. Even how you choose on your company name, how you become more confident or how you pitch your idea. This blog-post collection from Guy Kawasaki is a handy book for starters (“startupers” and not only). I see there is also an updated version, but I have not read it.
  8. ReWork: You may read many books on how you should change your mindset when you do business. This is a pleasant, extended and useful collection of practical topics an entrepreneur will meet in her venture.
  9. Steve Jobs: You may have seen the movies, you may don’t like Apple, but if you want to read the story of an eccentric revolutionist, to see how his belief and vision changed the digital world, and understand why Pixar & Next were more important than Apple in his career, this is the best reading. Success is not linear, cannot be copied and may not be pleasant to others (or to the reader).
  10. Presentation Zen: Everyone tries to pitch or present an idea. This is the bible of presentations.

Lately I came up with the following book, and I still read it:

  • Sprint: I was looking for a book to implement design thinking. Even from the prologue I am excited with this book and can’t wait finishing it. It was too close to pick Zero to One, but it is mostly a book of entrepreneurial philosophy for meta-learning.

This is my recommended reading list from my personal book library. These books formed my perception on entrepreneurship and “disrupted” my mindset. I experienced the “aha!” moment while reading them, and you may like them as well.

Feel free to suggest additions or your own reading list with your comments.

An initial list of the books I ordered to read

Why Complexity Matters in Business Models

During the session “key technology frontiers” in EBN in Brussels last week where I had a presentation, it was mentioned that “3D printing makes complexity no matter“, meaning that 3D printing makes complexity not important on construction phase, only on the design phase (a relative nice article in TechCrunch).

This phrase made me think about complexity in general, and how people are used to hate complexity. Tag lines like “think simple“, “make it simple” or “simplicity matters” has made us think of products and services in a matter of users, where we need a simple UI to achieve our goals (i.e. for a good reason when you design an interface). This simplicity has been present in marketing also for years. When we have to convey a message or some information, we need to be clear and simple, and then allow the recipient to ask for clarification if needed (read this if you want to see the power of a simple message). In this post I will describe why and when complexity matters in business.

When complexity matters

Technically speaking, a solution in many cases needs a complex structure abstracted through simplified interfaces to the users. In hardware:

  • First Mac computers by Apple put great challenges on engineers to fit a architecture into a small box. And they still do trying to become smaller and decrease need in user input.
  • iPod made it simple to carry on your digital music, but think how difficult it was for a device to run for hours without two AA batteries… Sync with your media player and have only 2 major buttons (instead of play, stop, forward, backward, power, radio/tape).
  • Your MacBook has prolonged battery life, but it needed a complex architecture to achieve this.

This simplicity is also important in software, where UX and UI books and courses try to make it a science to build simple interfaces:

  • The first Google search algorithm took into account connections with referring nodes, thus it used networking properties to improve indexing in search results. Initially such an approach looked impossible to respond in time.
  • All the image and video analysis systems are based on complex neural networks that have been developed for years.

Even in business, we are accustomed to say that every successful company makes revenues from one offering (i.e. the Pareto principle), but we forget how complex enterprises choose to be in many cases:

  • Microsoft had both Windows and Office as offerings, and Office helped them penetrate a market where IBM was a leading hardware player. Lately it makes profit mainly from business solutions.
  • Apple boosted its revenues and rebooted with Steve Jobs when iPod was combined with iTunes and Mac computers.
  • Google is well-known for its multisegment business model, but it has formed a complex ecosystem of services that drive search to their main search engine, and constantly improve results. And initially it succeeded because it could sell ads effectively.
  • Multisegment and Freemium business models are complex business models and have screwed up many entrepreneurs. Many books, including Business Model Generation, state Google and Skype were such great success because of their business models. But few are able to replicate such business models as effectively as they did.

When simplicity matters

Of course, there are cases that a business or people must think simple and act properly:

  • Personal communication: Everyone hates to find out or think that you may hide something in your collaboration. Colleagues, managers, board of directors etc. The message must be clear and straightforward.
  • Presentations: I will not write much on this, just read Presentation Zen.
  • Execution: It is a matter of the product/project manager to make it clear to her team members how they must execute each task, in order to accomplish the team goals. It is a matter of each team member to perform as well as possible, to produce unique, complex, modular components that have simple interfaces with other components and can be easily integrated and reused.
  • Marketing: The brand, the product, the ad, must be clear what value it adds to the customer. This simplicity allows customers to match needs with solutions and become more loyal to brands.

When simplicity took over everything

Lately unfortunately I see this trend appearing  in startups; there are many people that do believe and reproduce the motto “keep it simple”. I have heard pitches like “our idea is simple“, or “choose a problem and bring an MVP fast, you don’t have to build something complex“.

In some cases such statements  may be useful and accurate, but in my view they destroy some other very important factors of creativity and success: uniqueness, imagination and vision to make great impact. As you can read in Zero to One, in some cases you should dream big to build a “monopoly” based on some “magical” technology. Unfortunately I miss this magic in many startups I follow lately. Of course you may have to deliver simple tasks up front to test your idea, where human tasks hide AI or technical complexity because humans are still better in some tasks, but at the end think of what you want to deliver should include a level of complexity, otherwise everyone will copy you and you will move into a state of full competition, where you try to define what you “make different” than others.

Why I believe this trend of oversimplifying has taken up so much popularity? I would say because of two main reasons:

  • The Lean Startup (interpretation): When you are an engineer and you want to predict and control how things work, sometimes if you cannot understand how the business world works, you choose to go simpler in a business level. And modern startups are technically driven mostly, so their business model or structure is quite simplified. Lean talks about testing every hypothesis on the market and the product; it does not refer to oversimplified business models, but it talks about tested and validated business models. MVP is not about a prototype, and it includes price, promotion and channels testing in many cases.
  • Business Schools: Over-simplification brings up the “one golden rule” that MBA and business students “must” remember to succeed in their life. When a manager does not know the complexity of her business she works in, she cannot handle this complexity. So, business schools prefer to say their graduates to make their business focus on one thing, and they will succeed. No no no. Managers should know how to handle complexity and make everything look like being simple. Just think how many people love to hate Steve Jobs for doing nothing in his life, while they forget how challenging it was for him to change the tech landscape… and he needed to fail miserably once to achieve it.

In brief, when an entrepreneur lacks some capacity, she should choose the right moment to hire someone with this capacity, to make complex things look simple. Neglecting to build the whole business in a proper way upfront, even if this structure is going to change sooner or later, creates an unbalanced venture and thus it is more risky  to collapse.

To sum up

In the initial steps of a company, of course, it makes it easier for everyone to focus on a unique offering, narrow down in one problem, and execute. If this is not the perfectly timed idea that meets a need, and builds a community and a customer-base fast, if it is not located in a trend that is not a hype yet and will be soon mature enough to become mainstream, this simplicity in business will not drive a startup for long; Soon, a meaningful business model will be needed to make the business distinct and self-sustainable. And someone that copies the idea but can create the proper business model will have more chances to succeed.

Someone may reply that making something complex increases the risk of failure. Or she may talk about the lifecycle of a business, where complexity comes later in the life of the venture. The answer is “yes, if you don’t know yet how your business works, you go with a simple business model and you test everything“. But lately, cloud computing makes the cost of production much less costly, lean management allows teams to run tests faster and all these references (blogs, books etc.) give a prior knowledge to anyone that starts up; so starting a digital business is more easy than ever before. So, most of us can do simple things easily nowadays, but the ones that can handle complexity (or get lucky) faster will succeed.

Overall, simplicity should hide complexity and make something look magical. My position is this:

If you cannot raise money fast and launch a business based on a simple idea even faster, invest some serious time and start reading books that will allow you to build the proper business complexity that will give you a strategic advantage.

Do you want to start building an interesting, innovative business model? Read the “Ten types of innovation“.

Do you want to handle complexity in business? Read the “Design thinking for strategic innovation“.

Photos by: Unsplash

The Epilogue of Moodeet, 1.5 year after the end

Moodeet has been archived since 2014, after 2.5 years of operations, and this is my epilogue 1.5 year after the end of that venture. I needed some time to be able to share that experience publicly, and I think this is the right time to do it, just before launching my second try in the world of startups.

It all started with a very common question back in 2011… why couldn’t we build a better social network than Facebook? Being young and naïve might seem the perfect combination to join the world of startups, but then everything else is f***d up…

Finding a friend who accepts the challenge and starts working with you is a bless and a curse; together with Michael Petychakis we started exploring different ideas. After some weeks of brainstorming, we came up with a simple idea: why not expressing simply with emoticons, to say directly what we feel for things around us. Then people will understand what each other means through their social media posts, and there will be no need of special sentiment analysis and NLP systems  to understand what people say, like on Twitter. We needed “only” one think: someone to build a nice application, fast; we had the logic, the rules, the scenarios and we could build the backend. But we hadn’t developed an end user application before.

Me and Michael in TEDx Academy 20112
Michael and me in TEDx Academy 2012

Then I made the first mistake: I just contacted the first guys I had in mind, who I sympathized (I still do) but I hadn’t collaborated with them before to know their skills and their state of mind. They liked the idea, they joined equally in the team, and we started a phase of exploration for the perfect idea, as they did have their own ones too. So we discussed every idea, but we ended up with the more complete and mature idea: Moodit, which would become Moodeet (mood+tweet) because the domain was not available.

So I started reading books about startups (i.e. this was one of the best choices I have ever made). And we started looking for the best technological stack. And we found a designer among various propositions. And we started building our vision: an application where you choose anything around you (place, product, event, other people etc. coming from other services), and you put your mood on it. And I built a mobile application on that idea, ugly, huge in size (20MB) and laggy; I had learned also AppAccelerator in those early months, to build the app “faster”. We applied to some competitions, we won some of them, and we booked some tickets for SV; we knew that we were far away from investing, but we had to start networking and SV was the perfect place for that.

An initial list of the books I ordered to read
An initial list of the books I ordered to read

There in SV we started realizing the problems of our idea… They “didn’t get the concept”, it was “too complicated”. They wanted something simpler (I love and hate Americans for that). So we came back in Greece , and we “sacrificed” our summer to change everything, building from scratch. We needed a new idea. But we would also present Moodeet on TEDx Academy 2012 and we had to show an application: the perfect product launch! In the while the designer was part of our team, because “the design must be part of the business and technical team”.

Walking around San Fran
Walking around San Fran

As you may guess, again nothing went according to the plan. One member of our team “couldn’t make it what he promised “, and we voted to outsource it to another developer; thus a new member joined our team before even launch (6 in total). He would do it in one moth (it took him 4 to build an incomplete prototype). So, we created a nice story and we presented it in TEDx. After months of tensions, when a member of the team left because “he couldn’t perform”, we launched the first application on the App Store on February 2013; how anxious it was for me that users might not like it… Then I realized everything I had read about a unwanted product: at the end you don’t care how crappie it is,  as nobody likes it or uses it…

Presenting Moodeet in TEDx Academy 2012
Presenting Moodeet in TEDx Academy 2012
The Moodeet team in TEDx Academy 2012
The Moodeet team in TEDx Academy 2012

Still we didn’t  quit, we started collecting feedback. We were lean, even if we didn’t have the required money. We designed a new version with the feedback in mind, and it was fantastic in mockups, so we started implementing it again. But we betted on our skills only, we didn’t have any cash left, and we reached the burnout point sooner: we wanted to be Lean when we didn’t have the financial resources to support ourselves. Soon the team wanted funding to “work for Moodeet exclusively”. And we started seeking for a fund, on a social media application with 2,000 users, in Greece… you can imagine the outcome, nobody wanted to invest in a social application. So, the team continued to burnout, while milestones were even harder to reach. Deeply inside everyone knew that we were tired.

Then a new option came up: we had been selected in the final 10 teams in i-Bank competition by NBG and we had been offered full scholarships for the iMBA of AUEB. Based on theory MBAs are not for startups, but I knew that I lacked some basic knowledge in financial and economics (at least)… so decided to join and follow a dream I always had, to move into business. I haven’t regret it, I still believe that an entrepreneur should have a holistic view of doing business and an MBA program is perfect for that. On the other hand, my sleeping hours were reduced, the day was full. I was tired and anxious, but still it was one of the best periods of my life.

As you may guess again, the team went apart 4 months later. I was too tired to discuss for the third time what went wrong and try to fix it, and I quitted my role of leading the rest of the team. After two months we stopped working on Moodeet; The team couldn’t continue working as it was already tired as well, even nobody else had expressed it openly before. It took me some months to understand that I was trying to continue something that was broken for some time.

To summarize, it was the best period of my life in a professional level. I read some of the most influential books in my life, I met may interesting people, I met investors for the first time and then I realized how they think and how they behave, I travelled a lot, I was the owner of myself and my life, I fought my fears to present publicly, I faced many other fears in general,  I inspired people who believed in me, I felt sorry for arguing with people that I previously was friend with. I collected experiences even if I didn’t collect any money. I was close to lose one of my best friends. But I learned each team member expects different things from a startup, that not everyone has the same energy, visions, expectations and risk-ignorance as me.

I do collect all these memories and I continue my ride to the world of entrepreneurship wiser and stronger… for the next step (to be continued).

Note: This blog post is a documentation of facts from my perspective. I have analyzed the situation, I have learned many lessons and I have ended up with my outcomes on what we did right and what we did wrong. Still the reasons that Moodeet did not find the tipping point of success are multiple and complex, so an enumeration of them would still be my personal opinion. The way I highlight parts of a 2.5-years period is quite subjective already; I only want to remind to anyone who wants to start his own venture how difficult such a process is, but still I will call him to accept that challenge definitely!

RE.WORK: The Future Technology Summit in London on September 24th-25th, 2015

RE.WORK: The Future Technology Summit in London on September 24th-25th, 2015

On 24th-25th of September we attended the RE.WORK Future Technology Summit in London, in order to collect feedback on the technical trends and the entrepreneurial activities in one of the biggest hubs in Europe (the agenda is available here). The goal of this post is to present what was the whole event about and what is the latest technical progress, trying to link it on the same time with our work in FutureEnterprise.


In FutureEnterprise we released a roadmap of the major technological trends that are expected to affect future enterprises, from the perspective of the company. The main components are visible in the figure below. The idea is that these trends are orchestrated, together with new business models (i.e. innovations), in order to allow an enterprise create better capacities and build a competitive advantage, even a new business stream in the digital economy. As long as the presentations will be available, this blog will try to see the presentations in the scope of this framework and discuss what is missing or not.


Overall had 8 main sessions, which we will go through. The general idea was to show what is happening in UK around specific industries and domains, thus a sense of locality was in the air:

  1. Future Connected Cities & The Smart Home (Day 1)
  2. Smart Textiles & Materials
  3. Smart Robots & Applications
  4. Innovation in Healthcare & Advanced Neuroscience
  5. Startup Session: Shaping Tomorrow (Day 2)
  6. A New Source of Energy
  7. Artificial Intelligence Applications
  8. Biomedicine

Future Connected Cities & The Smart Home

The speakers mainly described the future city and home (as the title says) but focused on different dimensions. The FutureEnterprise framework covered all of them; the first talked about sensors and networks in the city of London, with emphasis on how a city can become connected, smart, and offer sensors as infrastructure to other vertical businesses. Visualization on big data coming from sensors and social media around London was another case, where a digital lab from UCL (i.e. Centre for Advanced Spatial Analysis) tried to handle data coming from the London Underground, sensors and help the city of London take better decisions. Then the session talked about smart homes, where trust among companies and users must be established to integrate such services. Last but not least, Jaguar & Land Rover discussed how initially Virtual Reality (VR) has been used since 2008 in their labs to design engines, and how Augmented Reality is used now in product design, to reduce costs; it is impressive to hear that AR and 3D model rendering generate models of high quality that construction cannot implement because of limitations on materials, and their efforts to become fully a digital factory, to reduce costs and speed up their production.

In a whole, everyone works on a basic level, trying to digitize infrastructures and systems, to start building additional intelligence over these systems; the problems in smart cities and homes are practical and need great engineering skills and management capabilities to overcome. Industries and authorities in London seem to work already in that direction.

Smart Textiles & Materials

I joined this session rather skeptical, but I was quietly impressed; Wearable devices are quite a hype and smart materials is something quite immature yet to lay my hopes in this session. But I was impressed! CuteCircuit presented their view on wearable clothes, which I would definitely not wear, but showed that innovation may not be mainstream in the beginning; they focused on high-end customers, celebrities and performers, in order to create wearable clothes with integrated LEDs, connectivity with server, no visible batteries and cables and capabilities of showing messages on the clothes. U2 and Katy Perry are some of their clients, while the have lately presence in New York fashion shows. On the other hand, University of Stuttgart presented how they build (public at the moment) constructions of high design and look, based on bioengineering patterns and techniques, using robots as builders, minimum material footprint and results generated from algorithms; future constructions may be inspired by nature and use less, stronger materials.


Overall, before attending this session I was skeptical on how these trends would be integrated. The answer is “go niche, reach high-end markets, find funds and needs, and then work to make technology mainstream“. That was a good hint for everyone working in this area (i.e. this is also a nice hint for 3D printing). Also, industrial design looks to be highly integrated with digital technologies, this is something companies in traditional industries should consider.

Smart Robots & Applications

This session had three different trends presenting: flying drones, exoskeletons and swarm robotics. Again the presentations were specialized in use cases and no general technologies or platforms were presented. This is a growing area that tries to find practices. Drones try to find applications, overcome energy and policies, and develop specific industrial design characteristics (i.e. integrated privacy policy, additional components to protect by the environment etc.); one case for indoor security and another concept to plan roofs in cities with seeds were presented but they were quite premature. Exoskeleton as a means for medical recovery was quite interesting as well, while applications of swarm robotics on nano-bionics is an interesting area, where future medicines will be nano-robots to fight deceases, like cancer cells.

To summarize, this session was very specialized and had less practical results to show; it has many limitations from policies, laws and ethical issues, and needs heavy investments to grow and show mature results. Nevertheless smart, collaborative robots are an interesting aspect of future life, where new industries pop up and traditional ones will be disrupted.

Innovation in Healthcare & Advanced Neuroscience

Even if I have basic knowledge on biology and medicine, with many friends in the industry, I might be too skeptical on such applications because I don’t consider doctors as engineers. It is my fault definitely, as this session showed basic research on many medical aspects. Some projects focus on social innovation based on sharing medical data, to increase public health, or reverse innovation in developing worlds to provide cheap healthcare on underdeveloped areas based on cheap, affordable solutions. At the end, interfaces on the brain and visualizations of the brain activity were presented.

This session made the idea of quantified self a bit more complicated, as all this technological progress has serious ethical and legal issues. For that reason my estimation is that it has to follow specialized solutions, like wearable devices have shown, where people with illnesses or disabilities will use them to recover. Public policies are also needed to build trust on medical data, and recover the spying scandals that NSA and MI6 lately involved in; only then patients will be willing to participate in large-scale projects, share sensitive data and improve public health systems. Thus, healthcare was the least applied research area of the whole conference, more are expected in the future.

Startup Session: Shaping Tomorrow

This session emphasized more in 3D printing, a hype that tries to find its location in a market. The interesting part was to see how 3D printing starts finding applications in specific industries, to provide personalized services. Orthopedics was the most interesting case, where solutions customize on patients’ anatomy while they can also become nicely aesthetic, fashionable accessories; people in treatment need an empathetic design. Thus, again industrial design became core dimension of 3D printing.

The best presentation was related to designing easily 3D models with less effort; Gravity Sketch presented their software to design 3D models without the need of complex software, something that may make 3D printing mainstream faster. Their interesting positioning was that 3D printing for 3D models downloaded from web markets is another channel for typical consumption, and only if customers learn to design their solutions there is a disrupted market.

A New Source of Energy

As an electrical and computer engineer I was surprised by this session; I had left for some years the area of energy since I graduated my university, and I though we will discuss for strictly engineering topics in the energy sector. All the sessions were quite interesting, maybe better presented than in reality in a matter of energy efficiency, but definitely interesting solutions that combined social and industrial design as well. Pavegen, a pavement tile that recovers energy from footprints is a growing company with many design problems overcome, University of Perugia showed a computational, logic gate with less energy needs than typical silicon circuits, Buffalo Grid showed a social innovation scheme for charging mobile phones in India, and Solar Team Eindhoven presented an energy-positive solar car for a family (i.e. having 4 seats) and challenging the energy model that Tesla and Toyota want to push to the market.

Generally, this session showed that technologies in energy production, delivery and storage have improved the latest years, in order to build (theoretically) sustainable alternatives to traditional energy models. It is a matter of business model innovations, engineering improvements, investment policies and legal framework to support more sustainable business models in energy.

Artificial Intelligence Applications

Unfortunately, highly disappointed by this session, I have to say. Face recognition with night vision for mobile devices as a Kickstarter project is interesting, yet has many ethical issues and less applications, at least as presented; I have to admit it was a great engineering achievement nevertheless. Building a general AI for gaming was so out of the scope of the whole conference, or I missed something from the presentation.

Not much to say for this session, maybe the Deep Learning summit in the next room had more to say on that topic. On the other hand, AI was integrated in various solutionsalready presented, like robotic swarms, drones and smart constructions. At the end, AI may become an interesting feature and prerequisite in any digital solution, not a core offering in many solutions.


I never got it why nanobionics and swarms were separated from this section. Thus, in that sessions there were smarter medicines to edit human RNA and cure cancer, again interfaces with the human brain and some (rather incomprehensive) ideas about personalized medicine based on avatars; the idea of sharing health data for a better public, health system might be more relevant or another view of the same idea.

Biomedicine engineering has many steps to do still, it  needs heavy investing schemes, governmental support and a parallel development of a strong legal framework and policies. It is the hope of humanity for the future, Google X also work on that direction, but at least the session show little progress.

This is an article collaboratively written in a FutureEnterprise blog post.


Customer Feedback – Privacy on Systems with Personal Data

In CloudTeams we are working on a problem that every startup has: finding early adopters, give them the prototype and get useful, meaningful feedback. The best approach for us is to build trust with customers, give them rewards for participating, but also to secure their privacy.

For these reasons in CloudTeams we though of using “personas”, like many software engineering and marketing teams do, in order to represent similar customer segments and also secure customers’ privacy. Users’ quantitative data will be covered under aggregations and data abstractions, that will let customers match with the proper software team but will not reveal their identity.

We have started releasing some initial prototypes, and more things will be announced soon. For more details on how we do this, go to my relevant CloudTeams blog post.

Personal Cloud – Lessons Learned from OPENi

It is indeed some time since OPENi  has finished, and I think it is time to evaluate the results, in a matter of business and technological outcomes.

The OPENi team in the final review (July 2015)
The OPENi team in the final review (July 2015)

Before going deeper on the results, a brief description might be needed  of what OPENi is all about (or you just didn’t follow the link above). OPENi was an EU funded project in the area of cloud computing, and its goal was to create a personal cloud for each one of us, in order to become masters of our data and then choose who uses them and who doesn’t. In other words, everyone would have his own “personal Facebook“. It is still the ultimate dream for every European officer, in many cases citizen also, to break the chains from the “bad guy who sells our data for ads” and get independent. I am also in favor of such an utopia, we have to see how we can get there; and OPENi was an important lesson in that direction.

Then the difficulties started and the dream of  a personal cloude was put into challenge. First of all, users do love their applications and the services they already use, and they won’t stop using them in favor of any new platform. Additionally,  it was not possible for the project partners to both experiment on new staff and also build a competitor for every single service coming from Silicon Valley. For that reason, the first decision was to create an interoperable layer that connects the personal cloud with a set of the most popular services; thus users would have access on the services they own and they could orchestrate their data easily, until the personal cloud (aka “Cloudlet”) was quite mature to make them independent from any business solution. We indeed studied how this layer would me as scalable as possible, and how it would be easily extendable. We did work on what Facebook starter (and then stopped), and described what a Graph API should be; and we described it for other services outside social networking as well, like e-commerce or activity tracking applications. We followed API standards that started popping up, and we proposed a collaborative tool to allow developers build and maintain their APIs. This is what my lab and my team worked 100% on. But then the problems started: platforms started changing API versions, like Facebook, and even “destroy” endpoints with desired resources. Other services don’t like to give any API to developers, because they would challenge their business models; for example Amazon loves to rent  infrastructure to other developers, but it hates to give any information to developers about their products, prices, shopping lists or purposes. It was a time that everyone wanted to build a platform and build a community of developers, and then suddenly they changed their mind (maybe Microsoft still tries to bring developers in Windows Phone 🙂 ).

But problems didn’t stop there. People in the Internet are spoiled with all these free services, they don’t understand that actually “they are the product” sold to advertisers. Of course their data individually have no meaning, but it is questionable if users would enjoy better or worse services if they paid. So, then it was the other challenge: how can we convince people to pay to host their data, even if they own them? The idea was to build on Raspberry Pi and let users run the Cloudlet as hardware whenever they like. But questions arose: who is willing to pay to buy a Cloudlet? How much technically savvy should they be to setup such an early-stage concept? How could they make it to have the available bandwidth to access information from their mobile devices, for data they have at their home under a common internet line? Who owns this device? How many should they have? Is it power-efficient? The answer to all these questions was that there is no-one  who is not hacker or hobbyist that may be interested to run a server at home. Ask Owncloud or Diaspora how they feel about it. For all these reasons we decided to design a decentralized architecture; a service provider would host a farm of Cloudlets, without having any access right on users data, and people would pay for that service. Alternatively, we created a networking service, and the old business model “free for ads” would be enabled, with one big difference: there would be multiple players, and all of them would be operating under the same standards and protocols, thus they can be interconnected across different farms.

At the end, unless new technologies arrive, or a personal cloud is delivered together with the proper hardware (e.g. a hard disk with easy-to-use interfaces and high-end design that would be nice-to-have at home, the decentralized (and not the federated) approach seems more logical. But still someone has to convince the service provider to invest on such a project. Then another question arises: who trusts a telecommunication carrier or a government to become a service provider to host their personal data…?