An MIT student recently created a new type of massively distributed database, one that runs on graphical processors instead of CPUs. Mapd, as it has been called, makes use of the immense computational power available in off-the-shelf graphics cards that can be found in any laptop or PC. Mapd is especially suitable for real-time quering, data analysis, machine learning and data visualization. Mapd is probably only one of many databases that will try new hardware configurations to cater for specific application use cases.
Alternative approaches could focus on large sets of cheap mobile processors, Parallella processors, Raspberry PIs, etc. all stitched together. The idea would be to create massive processing clouds based on cheap specialized hardware that could beat traditional CPU Clouds both in price and performance at least for some specific use cases…
Everybody is hearing Cloud Computing on the television now. Operators will store your contacts in the Cloud. Hosting companies will host your website in the Cloud. Others will store your photos in the Cloud.
However how do you make money with the Cloud?
The first thing is to forget about infrastructure and virtualization. If you are thinking that in 2013, the world needs more IaaS providers then you haven’t seen what is currently on offer (Amazon, Microsoft, Google, Rackspace, Joyent, Verizon/Terramark, IBM, HP, etc.).
So what are alternative strategies:
1) Rocket Internet SaaS Cloning
Your best hope is SaaS and PaaS. The best markets are non-English speaking markets. We have seen an explosion of SaaS in the USA but most have not made it to the rest of the world yet. Only some bigger SaaS solutions (Webex, GoToMeeting, Office 365, etc.) and PaaS platforms (Salesforce, Workday, etc.) are available outside of the US and the UK. However most SaaS and PaaS solutions are currently still English-only. So the quickest solution to make some money is to just copy, translate and paste some successful English-only SaaS product. If you do not know how to copy dotcoms, take a look at how the Rocket Internet team is doing it. Of course you should always be open for those annoying problems everybody has that could use a new innovative solution and as such create your own SaaS.
During the gold rush, be the restaurant, hotel or tool shop. While everybody is looking for the SaaS gold, offer solutions that will save gold diggers time and money. SaaSification allows others to focus on building their SaaS business, not on reinventing for the millionth time a web page, web store, email server, search, CRM, monthly subscription billing, reporting, BI, etc. Instead of a “Use Shopify to create your online store”, it should be “Use <YOUR PRODUCT> to create a SaaS Business”.
3) Mobile & Cloud
Everybody is having, or at least thinking about buying, a Smartphone. However there are very few really good mobile services that fully exploit the Cloud. Yet I can get a shopping list app but most are just glorified to-do lists. None is recommending me where to go and buy based on current promotions and comparison with other buyers. None is helping me find products inside a large supermarket. None is learning from my shopping habits and suggesting items on the list. None is allowing me to take a number at the seafood queue. These are just examples for one mobile + cloud app. Think about any other field and you are sure to find great ideas.
4) Specialized IaaS
I mentioned it before, IaaS is already overcrowded but there is one exception: specialized IaaS. You can focus on specialized hardware, e.g. virtualized GPU, DSP, mobile ARM processors. On network virtualization like SDN and Openflow. Mobile and tablet virtualization. Embedded device virtualization. Machine Learning IaaS. Car Software virtualization.
5) Disruptive Innovations + Cloud
Selling disruptive innovations and offering them as Cloud services. Examples could be 3D printing services, wireless sensor networks / M2M, Big Data, Wearable Tech, Open Source Hardware, etc. The Cloud will lower your costs and give you a global elastically scalable solution.
None of the incumbant telecom providers has put into place any Blue Ocean Strategies. Blue Ocean Strategies have made the Circus, Wine, Gaming, Airline, etc. industries exciting again, so why not apply it to the telecom market. The only telecom players, I know of, that implemented some blue ocean strategies are Free in France, GiffGaff in the UK and Freedompop in the USA. So why not do a Blue Ocean Strategy exercise in this blog post.
Here is my strategy canvas:
Traditional operators focus on charging heavily for calls and SMS although lately more and more packages with free minutes are available. International calls however are still charged extremely expensive. Mobile phones are subsidized up to 24 months and as such you need to stay with them for at least this period. Operators spend a lot of their money investing in the roll out and maintenance of their networks. They also have very complex pricing plans and as such need heavy investments in BSS.
MVNOs try to compete on price and most often do not subsidize mobiles. They do not have their own network as such they do not need to invest in it. They offer less tariff plan options. You are often free to change whenever you want. To make up for not subsidizing mobiles, you can get mobile loans which means you have some sort of permanence.
So how would Blue Ocean Mobile do it differently?
In line with Free’s example, call costs should be eliminated, including international costs. Mobiles should not be subsidized but cheap mobile loans should be offered for those that do not bring their own device [BYOD]. Blue Ocean Mobile should focus on LTE and try to win LTE licenses. However instead of doing heavy investments in installing antennas everywhere, Blue Ocean Mobile should only install antenna’s in those areas where few people live but connectivity is required, e.g. major highways. This is in line with Free’s strategy. However unlike Free, the operator’s network should not be built with unreliable WiFi hotspots. Instead specially designed “Personal Antennas” should be sold to everybody who wants one. What is a personal antenna? A personal antenna is a nanocell LTE antenna. A personal LTE antenna in your home that not only gives service to you but also to neighbours and people close to your home. The idea is that you become a sort of mini-LTE ISP to which others can connect. For every KB that gets transferred through your personal LTE antenna, you will get a revenue share. So it is in people’s interest to put the personal antenna in a place where it can service a lot of people and to have a good backbone Internet connection. People should be able to win back their investment in the Personal Antenna in a few months and make money afterwards. This should allow Blue Ocean Mobile to seriously lower their investment in rolling out an LTE network and to get free mouth-to-mouth advertising. Via a software-defined network [SDN] management system all nanocell LTE antennas are controlled by Blue Ocean Mobile.
Since Blue Ocean Mobile is focusing only on data traffic, it should work together with “over-the-top players” to offer a compelling list of services. Ideally Android Phones and the iPhone will use the data network for calling others instead of a circuit network. Customers should have a full range of BYOD management options so small and medium-sized businesses can easily manage the phones of their employees as well as push enterprise applications towards them.
Blue Ocean Mobile should also try to avoid investment in BSS. Tariff plans should be easy with the customer defining how many free megabytes they want to purchase for a fixed monthly fee and a simple extra charge for overage. So instead of operator defined tariff plans, everybody has a personalized tariff plan that they can adjust every day. Calls and SMS are charged based on data traffic not on per minute charges. VoIP solutions is the standard. Blue Ocean Mobile does not have a circuit network or SS7.
Blue Ocean Mobile is also copying the long tail support from Giff Gaff in which customers give support to other customers and are responsible for marketing. Unlike Giff Gaff not only prepaid but also subscriptions are supported. Like Giff Gaff customers get a revenue share when they participate in support or marketing.
Blue Ocean Mobile’s strategy is just very high-level and still needs in-depth analysis but it is an open invitation for innovative people to start applying Blue Ocean strategies to anything they feel in need of disruption.
Maarten Ectors is a senior executive who is an expert in applying cutting edge technologies (like Cloud, Big Data, M2M, Open Hardware, SDN, etc.) and business innovations to generate new revenues. He is currently looking for new challenges. You can contact him at maarten at telruptive dot com.
In this post I want to show a technique that is an alternative for creating a business case: “Lean Canvas”. Lean Canvas has been proposed by the book: “Running Lean“, that itself is based on “Lean Startup“.
The idea of Lean Canvas is to put what would go into the executive summary of a business case on one page and to forget about writing the rest of the business case. The justification is that writing a business case takes 2 to 3 months and CxOs normally only read the executive summary. So instead of spending 2 to 3 months, you spend hours or days and get it in front of customers to get feedback. With the feedback you can then refine your idea and create a Minimum Valuable Product in the same 2 to 3 months. So instead of having a nice paper report nobody reads, you can start earning money.
The Lean Canvas contains the major customer problems you want to solve. These customer problems need to be important [A painkiller, not a vitamin], shared by many and not have an easy workaround. Customers need to validate them before you start thinking about solutions. Customers are the ideal party to tell you about their problems but not necessarily the best to give you ideas about a solution. Think about Henry Ford’s words: “If I had asked what people wanted they would have said faster horses…”. Most startups focus excessively on the solution and forget that they need to validate a lot more things. After the problem, the second most important part of the Lean Canvas is the customer segment and channel. Who do you want to offer a product to and how to do reach them. Also the unique value proposition is key. The other elements of the Lean Canvas are the unfair advantage [how can I avoid others to just copy my business?], key metrics [how can I measure success?] and last but not least the cost structure [what does it cost to acquire a customer, build a minimum valuable product, etc.?] and revenue streams [how much am I going to charge and what other revenue sources are there]. You can create a Lean Canvas on paper or use a SaaS-version.
So far the theory, now let’s review an example…
The customer problems:
Door keys are a nuisance. You can lose them. You have to give copies to family and friends if you want them to go to your house if you are not there. Do you really want to give the cleaning lady or man a copy? Is my lock safe from burglars?
The mailman or delivery guy comes to my home but often packages do not fit my mailbox.
When people ring my bell, they know when I am not home. That is unsafe.
So what is the solution?
My proposed solution is the iDoor. The iDoor is an intelligent door which you control remotely to decide who accesses, who delivers and who is shut-out. Via a camara and full-duplex audio system, you are able to see who is standing in front of your door and communicate with them. Your smartphone will be your remote door manager. Advanced models could have face recognition and share data with other intelligent doors in the neighbourhood, hence if you are sleeping a siesta and those annoying door to door vendors approach your door they will automatically hear a message to go away and your bell will not function. If a burglar is detected, then the police can be warned. If the postman has a big package then remotely you can open a compartment so they can store the package. If your family comes they can go into the house without problems. Your cleaning lady can as well, as long as it is her normal working hours and she comes alone.
Unique value proposition?
As if you were home 24×7. Busy people will never miss an Amazon package again. Burglars will not know if you are in the garden or not home at all.
Mid-high class house owners.
An existing door manufacturer that targets upper markets should be partnered with. An example could be Hörnmann.
Door sales and door usage.
A complete costing has to be done. TBD.
Door sales and door installation/maintenance services are the primary revenue stream. However door apps and selling anonymous aggregated data could be additional sources.
You can find a quick summary in the following slides as well as some details about the technology components. This example needs customer validation and several areas need quite some more work [e.g. cost, revenue, unfair advantage, etc.]. However I hope the idea is clear.
Maarten Ectors is a senior executive specialised in value innovation: creating new products and generating new revenues based on cutting-edge technologies like Big Data, Cloud, etc. He is currently looking for new challenges. You can contact him at: maarten at telruptive dot com.
I was expecting the announcement a lot sooner. I made some slides about a similar concept some months ago (I called it the iCar) and presented them to one of the largest car parts manufacturer. Unfortunately car manufacturers have been very slow in adopting new innovations. At least one car manufacturer has entered the 21st century. Ford has created OpenXC, an Open Source hardware and software solution to interact with your car. OpenCX = Arduino + Android + Car Interface. Developers will be able to use their Android to read information from the car. You can read the angle of the steering wheel, vehicle speed, location, accelerator pedal position, brake pedal position, engine speed, odo meter (distance travelled), fuel consumed, fuel level, head lamp status, high beam status, ignition status, parking brake status, transmission gear position, turn signal status, etc.
At the moment you are not able to interact with your car unfortunately. It would be good if OpenCX could offer real interaction. Think about the possibilities of:
1) Parental control apps – my teenage child will not be able to drive more than 120km on the highway and 50km in the city center and I can tell them not to go to certain neighbourhoods.
2) Personalization – my car adapts to me. If I am alone in the car the car radio blasts out hits from the 90s, the motor goes into sportive, inside temperature goes to 21, etc. If my family is present, children music, comfort driving, temperature 22.5, etc.
3) Predictive Maintenance – my car tells me that there is a problem, finds the garage that has the spare parts in stock and schedules an appointment based on my calendar’s availability.
These are just one of many ideas. The main thing is that entertainment, personalization and third-party services will get an enormous boost if open hardware, open software and creativity are allowed to enter your car…
Maarten is currently looking for new challenges as a senior executive, expert in value innovation and using cutting edge technologies to generate new revenues. Contact him at maarten at telruptive dot com.
As the inventor and co-founder of Startups@NSN, I was one of the drivers behind a successful incubation program within a large (70K) and complex multinational. We coached global employees into generating hundreds of ideas and converted them into 6 prototypes in 2 months. After customer feedback, 4 commercial products were launched in months of which one won a prestigious international innovation award.
Having gone through the whole process, if given the chance to do it again, I would make some substantial changes.
We overestimated a couple of aspects.
1) Employees have very innovative ideas
2) Employees understand customer’s problems
3) Employees can let go of unproductive products
Several employee ideas were very innovative but the majority were just small changes to existing products. Most corporate employees are good at incremental innovations but have a hard time imagining innovative products on top of unknown technology innovations like Cloud Computing (jan 2010) or M2M (2011).
Also using employees as a substitute for understanding customer needs is not a great idea. Nothing beats real customer contact.
Finally people fall in love with their prototypes too easily. They are blinded and can not understand that their brainchild is an ugly duck instead of a beautiful swan.
So how can you do it better?
My first suggestion would be NOT to start with a technology but to start with the customer. Identifying some real important customer problems before identifying solutions is key.
Secondly, using employee but also external ideas (e.g. Via a competition) to generate minimum viable product requirements on paper should be done before building any prototype. The solution definitions should be reviewed by customers to get early feedback. In addition to solutions also other elements should be evaluated, e.g. Price, customer channel, unique value proposition, customer acquisition costs, etc. A good framework to use is the Lean Canvas.
Only after the customers have validate your lean canvas and minimum valuable product design should you go and build a prototype or even better the minimum valuable product. Launching the product in months and only adding features after the initial product has been successful should lower your initial costs and risk of failure.
If you are looking for ways to launch new innovate products quickly, why don’t we talk (Maarten at telruptive dot com)…
With Big Data in the news all day, you would think that having a lot of high quality data is a guarantee for new revenues. However asking yourself how to generate new revenues from existing data is the wrong question. It is a sub-optimal question because it is like having a hammer and assuming everything else is a nail.
A better question to ask is:”What data insight problems potential customers have that I could solve?” Read more…
If you haven’t heart of Arduino or Raspberry Pi, then you need to get up to speed urgently. Arduino is revolutionizing hardware and gadget innovations. It is a do-it-your-self-hardware-kit that allows you to build complex systems by stacking up components like GPRS/3G, NFC, etc. Raspberry Pi is an ARM GNU/Linux box for $25.
However Kickstarter just funded the next generation of both projects:
The Parallella Super Computer (alternative link) for $99. A 64 Cores computer on a small board for an affordable price and very low power consumption. Imagine stacking a 100 parallella’s in a box. There is already a parallel programming competition set-up.
Both projects are open hardware and open source project, hence expect hobbyists to come up with lots of cool ideas…
Data Scientist is going to be the sexiest job of the 21st century. However do we really need a new army of Data Scientists or is there an alternative? There might be and it is called data democracy.
What is data democracy?
Data democracy allows all people to have access to all data insight. In an enterprise, data democracy is about enabling knowledge workers to share insights. To avoid the construction of data silos. To democratize tools that enable each co-worker to become a data scientist without needing a PhD in statistics, mathematics, etc. Visual tools that allow “Excel-users” to use Neural Networks, Support Vector Machines, Random Forests, etc. to make predictions, to classify or cluster data, etc. But without the need to understand the underlying computer learning algorithms into great detail. A sort of corporate RapidMiner that scales.
At the same time we also need better visualization tools. Everybody should be able to create infographics easily. Tools that allow ordinary people to create stunning data visualizations that go beyond the boring reports.
Finally we need better tools to find and share data insights. We need a “Databook”. A Facebook to easily find the data insight you need. A tool that allows you to distribute your predictions about next quarter’s sales and to compare them with the predictions of others.
In summary, we need the data scientists of this world to focus on making access to data insight available to every knowledge worker. Simplify instead of algorithmify! Enable everybody to be a data scientist…