Internet of Things Landscape Beyond Things

As I am looking at the different facets of the Internet of Things, I realize that there are a million ways to slice and dice it’s different components. It is clearly a complex ecosystem and the amount of buzz generated around IoT is a clear demonstration of that fact. Similarly to my previous post around the IoT protocols stack I wanted to attempt to draft a view of the landscape but this time beyond the things and communication layers. I wanted to have a focus around the application side of things where I believe most of the value lays. So let’s show that. Here is my view of the IoT landscape and I’ll talk about the different bricks right after:



Following a strong message pitched by around the fact that behind every device is a customer, this is where I started: The connected customers on the left.

It all starts with connected devices, and you will find in there chip manufacturing, and connection protocols like Bluetooth, wifi, etc.. Not the focus of this blog but definitely important. The following bucket to look at is to the right of the connected devices: The communication buckets where you will find a lot of the protocols I described in my previous post. But there is where the interesting part begins.

DATA END POINTS. I have create a bucket for this as it many players actually only play there. The features found in this bucket are around pub/sub architectures and protocols for high volume communications for millions of devices, but also intelligence. I believe that intelligence at the Data end point level is extremely important as it will avoid the overload of totally useless information coming from the devices. The end point should be capable of creating a first level of triage of the information coming in: What’s expected? what’s normal? what is NOT normal? The end point should be able to generate alerts in near real-time to the customer support bucket (below) or to applications through the development platform (above). The better at assessing data in real time, the less dumb data will be added to the data store (to the right). Another important element of the data end point, is authentication and security that can be handle there. The end point should be able to know (authenticate) the devices and customers behind the devices as well as make sure that communication are secured (encrypted) and no one can send data or commands in a malicious way.

BIG DATA STORE. This is where the raw data will go in. I do believe that if the data end point has done its job right, not everything needs to be stored. Maybe only aggregate data is store like “the device has been on for 24hours” instead of thousands of “I’m alive” data points. That said, there is a balance between pure raw data and not enough data. The value of a big data store is to be able to query and work through that data via learning algorithms, and pattern detection algorithms. Those algorithms love to have tons of data as they become better and better with it. There again, the intelligence is key to determine predictive outcomes. This is the holy grail of the industrial internet by the way: predicting when things are going to fail in order to reduce unplanned maintenance. You will notice that the diagram connects the big data store to applications (above) and customer support (below) as this data is key to provide insights to agents in call centers (of in the field) as well as provide input, bi-directionally, to applications. Maintenance history, upgrades, etc, should feed back from specialized application into the big data store as well.

ASSET MANAGEMENT. There is data generated by the devices, but there is data about the devices. A device needs to come online for the first time and declare itself through a provisioning system before it can send data. The devices have owners, serial numbers, a history of their creation, maybe even all the way to the CAD designs and specifications. It is made of parts that can be assembled, upgraded, etc. It has a cost, to sell of to built. It can be optimized in a way or another. All that information about customers’ assets will be kept in that system. An advanced asset management and asset optimization system is a critical piece of the landscape where a lot of value can be generated.

DEVELOPMENT PLATFORM. On top of the data and assets, can sit a development platform. From simple cloud based OS to full fledge application development platform, you will find a entire ecosystem just in that bucket. Anything that allows others to create applications linked to the data or to connect to the device (via the data end points bus). Those platform have to provide all the brick of security, authentication, licensing and provisioning management, workflows and business processed, etc.

CUSTOM APPLICATIONS. Either through an ecosystem of ISV or by customers themselves, applications can be developed on top of the platform to consume data and manipulate / control devices. Applications can be virtualized for certain industries (smart home, smart cities, industrial internet, healthcare, etc..) each having their own market to go after. I think there is still a lot of work and opportunities in that bucket where most certain 70% of the value chain will reside at some point. Note that those applications will connect back to the customer via the web, through any type of device (mobile, tablet, desktop) including the device itself.

CUSTOMER SERVICE AND SUPPORT. Going back to the bottom part of the diagram, you may know that I am a big fan of the service use case of the IoT. I believe it is one of the big opportunities that this trend provides: to offers outstanding customer service thanks to the data generated by connected devices. From intelligent routing of alerts coming from the data end points in real time, or from the data store asynchronously, to knowledge management, entitlements, RMA, and then multi-channel communication with the customer, a good customer service operation will empower agents by tying device data and related intelligence to the customers themselves.

FIELD SERVICE. Interestingly the field service use case is very big in customer support. It’s not because machines are connected that there is never a need to physically go see them. Repairs, maintenance, refill, physical upgrades, all those still have to be performed by a field technician. I think what has changed is that now that devices are connected, the field service technician can be much more efficient than before. Accessing the entire history of the devices, its usage and failure patterns, knowing everything about the parts needed and planning for preventive maintenance are all very cost effective tasks that will drive significant returns to companies using connected devices. I even think that it will drive more field service needs than before, but it will be done is a more efficient way. Instead of incurring a huge cost of a failure, a company can have a much smaller cost of more efficient technicians.

SALES AND MARKETING PROCESSES. Even if support is definitely a big use case for IoT, the extension into sales and marketing is undeniable. A cartridge is low in your printer: that’s a lead. You don’t drive your car very much: that’s a lead. You go in certain places very often: that’s a lead. Opportunities are all over the place for up-sell, cross-sell, proactive marketing, in-context marketing, etc. I think this will come a bit later as the infrastructure need to be in place for it to be realized fully but it will come and it will be big.

ANALYTICS & INSIGHTS. I could not have a diagram without this piece. Understanding the data through smart visualization is critical to efficient decision making. Seeing trends and patterns and being able to generate reports and dashboards conveniently for every level of the organization are constant asked from any company I talk to. Bringing together, Device data, support data and sales data into single dashboard has tremendous power that many company will take advantage of.

I hope that this view of the IoT landscape brings some clarity to some of you. I would love to get feedback about it to make it better. Why I built this initially was to understand where we wanted to play as a company and I think it has been helpful to segment the market and the players we have been talking to.

Enjoy and share.




The Internet of Things Protocol stack – from sensors to business value

There is no doubt that we are entering a new era.. An era that will change the world more than the Internet did 15/20 years ago. This era is the Internet of Things, or IoT. John Chambers, the CEO of Cisco is going on a crusade to tell the world about and is driving many conversation with his potential $19T in economical impact from efficiency gains to pure economical growth. I have personally never seen a number that big, and it’s starting today.

Granted connecting objects is not something new, we have had connected machine for more than 15 years. Axeda, one of the leading solution providers in connected machine, has been in business since 2001! What has changed is that now: 1- it’s becoming cheap to connect machines to the internet. Very cheap. Hardware is affordable and even open source: Raspberry Pi announced it’s 2M unit sales in November 2013! Knowing that they compete with Arduino, Mbed and others, I am astounded by the cheer volume of supposedly “hardware enthusiasts”. This not a hobbyist game anymore, it’s everywhere. I personally played around with an Mbed and a Spark Core using Cloud based backend from Xively. It’s so easy, it amazed me and got my imagination going on a few projects.

But where is the catch? I’ll be honest: Standardization. The IoT landscape is a mess! Too many protocols, too many wannabe standards, too many revolutions. It will calm down and consolidate but for now it’s creating more mess with every new device that comes out on the market.

I’ve decided to give a try at describing that mess through a protocol stack that I’m hoping to be useful for others. My goal was not to be exhaustive in anyway, I don’t even think it’s possible. But I hope that I captured the most common protocols that people encounter on in a day in the life of an guy in IoT.

IoT protocols stack


[Note: This diagram has been updated based on comments and feedback received since Jan 29]

What I found important in this stack was to add a Business value layer, because what’s the point of connecting devices if in the end there is no business value.

Some will find similarities with the ISO stack (Link layer, Transport, Session, etc..) and there are some, but I wasn’t particularly trying to map to it. It just happens that the ISO stack is foundational to the Internet and as a consequence in the DNA of everything Internet.

Protocols you will find in there:

Connectivity layer: What kind of physical connectors you can find. RJ45 (the physical connector, usually for Ethernet), PLC, RS-232, RS-485, ModBus, USB (as a connector type, not the communication protocol), SPI, ODB2 (in Cars), and Wireless (no connector!). You will sometimes find gateways that will convert any of those physical connectors into wireless.

Link Protocol: How do those device actually send the data. Ethernet 802.3, Wifi 802.11a/b/g/n, BlueTooth, BLE, Dash 7, ZigBee, RFid, GSM, 6LoWPAN, 802.14.5e. The last two are really focused on the IoT use case. I have put ZigBee here only but I am well aware that ZigBee covers a large portion of the entire stack. To avoid too many redundancy, I had to make a decision on where it would fit best.

Transport: IPv4 and IPv6. I also added 6LoWPAN and RPL despite the fact that they are both based on Ipv6. The IPv6 has been a long time coming and was supposed to be adopted by everyone 10 years ago, but now with the projection of having 50 Billions devices connected in 2020 (according to Gartner), we have to go to IPv6! What was interesting is that I haven’t found much of anything beside the IP protocol out there which proves the dominance it has acquired through the rise of the Internet.

Session / Communication: This section is an interesting bunch with a lot of new protocols that have been build for super high volumes and large networks of things. The most famous right now is MQTT, a subscribe and publish protocol that is used by Facebook for its mobile app. You will also find CoAP (kind of a REST Based protocol but much more efficient than its HTTP counterpart), DDS, XMPP and AMQP that are all well suited for IoT and will map different use cases. One will still find older protocols like FTP, Telnet and SSH, but even though they are working very well, they are resource intensive, power intensive, and do not fit well with the low power, unreliable bandwidth of the IoT realm.

Data Aggregation / Processing: This is where it gets really interesting. When device send data, lots of data, you need an end point to do something with it. Be it processing it in real time (with Storm), but at minimum getting the data and sending it somewhere else at very large scale, which Kafka is a great example of. Other solution exists like RapidMQ, Scribe, Plume, Luxun, Fluentd (although more on the translation to JSON side)

Data Storage / Retrieval: The realm of Big Data backend and NoSQL solutions. Hadoop, HBase, MongoDB and Cassandra dominate the field. There are others, like the google AppEngine,  but I may add them later on if they start appearing more in IoT use cases.

Business Model: This is a new addition fro, the initial post. This layer is trying to capture the fact that business value and business processes always rely on an underlying business model. Open or Closed, Integrated or platform, direct sales or indirect, cloud based or on-premise (or private cloud), on-demand pricing, etc.

Business Value: I’ve split it in three. One part if around Device Management, the provisioning, registration, firmware management, remote access, but also the product and asset structure as well as Security (tremendously important, especially as we just went through the first massive Connected Devices attack just a couple of weeks ago. The second section is to highlight the birth or transformation of Service for smart devices, Marketing for owners of smart devices and the impact on manufacturing those smart devices.  Finally, the analytics piece shows how much technology could be applied to the data gathered, With machine learning algorithms, data mining, and all the insights and visualization that can be derived from it.

With such a representation of the most common protocols, the need for consolidation really becomes obvious, the IoT cannot keep going with so many protocols if the dream of having any devices talk to other devices in a fully connected world wants to come true. In any case, it’s fascinating.

Building your App in the Cloud or not is a business decision better made early…

Having worked at for several years now, I have been immersed in the world of Cloud and I have witnessed first hand how an enterprise class application could scale in such an environment. It has been fascinating all along and that experience has been truly put to use as I have been dealing with ISV (Independent Software Vendors) partners in the last few months for Salesforce.

As I talk to CEOs and CTOs of those ISV who want to work with us, the question of the architectural choice they have made comes every single time: Is your offering Cloud based or on-premise? Is it truly Multi-tenant or more of a shared hosted solution? What I came to realize through those conversations is that the choice those companies made early on is definitely something that is very impactful to their business and that once it is made, it is extremely hard to change. That difficulty can have huge consequences on your ability to scale, your ability to innovate, your ability to lead and even your ability to exit!

As a consequence, I would like to write a piece of advice, or at least a bit of guidance to all  of you, early entrepreneurs, who are thinking about building software: Should you go Cloud or not, and if so what type of Cloud offering should you pursue? What I hope from this post is that you will realize that this decision should not be taken lightly and should definitely not be an afterthought, but above all, it should be made early.

Cloud, Multi-tenant, On-premise.. What is all this??

Let’s quickly recap what Cloud, multi-tenant or on-premise mean (I’ll stay very high level here):

  • A Cloud application does not live on your customers infrastructure(usually). The customer connects to your application via a basic Web Browser. Most of the time those solutions are sold on a subscription basis.
  • An On-Premise solution usually lives on the customers infrastructure. The customer owns servers and potentially spaces in data centers to run the software. Usually those solutions are sold through a one time license and some yearly maintenance fee that gives access to upgrades and patches.

Cloud based solution can have (roughly) two flavors: Hosted or Multi-tenant.

  • A Hosted solution usually means that despite the fact that the customer accesses your solution through the Web and has a subscription service they pay, the application lives in its own container called “instance”. Each customer has its own instance with its own engine and Database. There is literally a virtual separation between each customers instance.
  • A multi-tenant solution usually means that the Database as well as the application is unique and access for each customer is controlled through some meta-data layer. Everything is shared and security is ensured at the query level rather than at the virtual infrastructure level.

So what are the implications of each of those solutions for an early startup?

Let’s assume you start with an on-premise solution

Let’s say you start on-premise (just like many of the enterprise solution providers out there started many years ago). Here is how your business will go:

  1. Your sales representative will be compensated on the licenses they sell. Usually those up-front licensing costs are high: the customer “Buys” the software. That’s usually pretty attractive when you start because:
  2. You get more upfront cash which can fuel your growth
  3. You don’t have to have a security conversation with your customers which will ask where the data resides and how secure it is, etc.. so sells are a bit easier.
  4. You will have happy sales guys because they will get high bonuses

So it all starts pretty well, but then as your business grows, this is what happens:

Your customers are not upgrading which means you have to maintain several versions of your software which drives your support and development costs up. You have to release patches for several versions and you have to train your support crew on several versions.. this could quickly become a nightmare. So to reduce this cost you revert to a fewer releases which drives down your ability to innovate fast, react to new market trends and lead ahead of the competition as you cannot afford to manage too many versions and at the same time and you cannot force your customers to upgrade.

You realize that the new hardware that a customer has added to their machine is causing issue so you have to handle hardware specific patches, or your virtual machine provider has released a patch that is also causing problems with your application but that only happened for a subset of your customers..

Your sales guys constantly have find new customers because your revenue is dependent mostly on this one-time licensing fee that you charge and if they don’t get new deals they don’t get the nice bonuses they use to have.

Some prospects are worried about the seasonality of their business and how quickly they can scale up and down and also deploy mobile apps.. Well with your on-premise solutions Mobile access is not that simple as your customers need to open their Firewalls to give access to the servers that host your App. And by the way, they also need to integrate with other solutions, and some of them are Cloud based, so do you offer some kind of standardized platform where partners can create those hooks?

As a business owner you look at this, you look at your costs, you look at the market trend and the growth of the Cloud and you decide that it’s time for you to start providing a Cloud based solution..

This is where things really start breaking.

From on-premise to cloud: the equivalent of a pivot, but harder!

Your sales force has been trained to pitch the value of on-premise versus cloud and all your customers have bought into this vision. Now you have to go tell them that Cloud is better! If you don’t, you will have to manage yet another version of your offering and increase your costs even more.

Of course, you don’t want to re-code everything as multi-tenant, it would take you months if not years as the architecture are fundamentally different. Your developers would be frustrated and your customers may not have the patience. You may even loose the precious lead you had on your competition in terms of product features. Multi-tenant is a no-go, so you decided to go hosted.

Going hosted is easy enough, you basically take the on-premise App you have, hopefully you had a web browser front-end instead of a desktop application (if not you are really in trouble), and you put it in your own infrastructure.. You change your licensing model to be subscription based and you are good to go: You have a nice Cloud bases solution.

Well it’s not that easy..

First, you still had to spend an ungodly amount of cash to build or rent your datacenter in the meantime though. You will have to swallow that as the revenue of a Cloud based offering are also much more progressive, no big one-time fee here.

Second, your sales guys won’t like this and will always sell the on-premise version if they can. They will come in a deal leading with Cloud, start pitching and revert to the on-premise every time. Maybe you mitigate this with two different sales units, one for Cloud solutions and one for on-premise, but you will rapidly enter a turf war internally. I have seen this over and over. That means your cloud solutions will have a very hard time picking up.

The maintenance of the hosted solution is also going to be the same nightmare as it was for the on-premise.. When you upgrade you have to go through each instance individually and upgrade them one by one. The problem is that your customers will always tell you that it’s not a good time and it takes weeks if not months to upgrade everyone. By that time you may already have a new version available.

Going hosted you haven’t solved anything.. you made it worth. You have sales that don’t want to sell your stuff, you have support and maintenance nightmares and you lost your innovative power.

Let’s continue the story. You are resourceful and with your strong leadership you have been able to change the culture of your company and everyone is behind you now.. your hosted solution has taken off and you have an opportunity to exit with one of the leading firm in the Cloud.

Looking at an exit? Tough luck…

The company (fictional) that is looking at your business was attracted by you because of your Cloud offering. Their IT is looking at your architecture and realized that you host many instances of your solution.. There is nothing multi-tenant and basically the integration story will be almost impossible as everything will have to be re-written to be compatible with multi-tenant. Your support organization will be cut drastically as well as you have way to many and all your customer base will have to be migrated as heavy costs which means there is a good chance of attrition. How do you think the acquiring company will feel about your business? not so sexy anymore. Of course it can happen, but what multiple will you get?

So what about multi-tenant then?

Very quickly, multi-tenant means you ARE Cloud. You develop 1 version, you maintain 1 version, you upgrade everyone at once, you are nimble and innovative and you will crush your competition. Your sales will be trained on 1 message, compensated on 1 model, and customers will grow with you, making you a very good target for a beautiful exit.

One element often forgotten about hosted versus multi-tenant is that a hosted solution will never be able to grow your customer base in the SMB market if that is what you plan on doing (either as a start or if you want to go down market later). Spinning up a new instance and maintaining that instance for a customer with 2 seats will definitely not be worth the time. A Multi-tenant architecture on the other hand, doesn’t care if you are 1 or 10,000, the cost of deploying and maintaining each customer comes down to a cost per seat (roughly). Small business are subject to the same level of quality and care as the big customers and your overall level of service is much higher.

Summary: choose wisely and choose early… (my advice: choose multi-tenant!)

I took a very simplistic approach to the story, but hopefully you now have a better understanding of what it could mean to start with the wrong architecture. Going on-premise may be simple, or even hosted to start with, but the consequences on the growth of your company, the costs, the innovation and flexibility you will have to adapt to a rapidly changing market and the ability to exit may be really impacted and depending on your business strategy and goals could even be detrimental.

I truly believe in the Cloud but I also truly believe in multi-tenant. There are many different ways to architect your solution with some hybrid solutions but always keep in mind the maintenance costs they will generate assuming customers will not upgrade if they can avoid it.. Some customers are very sensitive to cloud solutions like in the banking industry but salesforce has proven that with the right security, the right message and with enough benefits, even the banks will follow you.

Is the VC industry in trouble?

I had a discussion with an entrepreneur the other day regarding how VCs now look at deals to invest. I already talked about the fact that VC are not a solution, but rather a means to achieve the scale you need to get to with your startup.

One guys ones told me: “Look at this startup, they have VC funding, that means they are successful”. As much as I can disagree with that, the latest data I’ve read reinforces even more my feeling about what a VC can achieve for your startup.

The Cambridge Associates LLC release a study on the return of the VC asset class compared to other types of assets like Private Equity and Public Markets. We are going through a very interesting time as the returns from the bubble era are starting to disappear from the overall 10 years returns for the funds (10 years.. already!!). That means that we are starting to see how VC returns really are in a normal (though tough) market and the picture doesn’t look good:

8.4% return over 10 years for VCs and 8.3% for PE, it still looks significant but the return for VC in the last 9 years is actually -6%!!..

In 2 quarters ( as we get closer to the end of 2010) the full effect of the bubble should have disappeared completely and we should expect those numbers to get a lot lower if not negative.

What does it mean for startups that need such funding?

Well, you’d better choose the VC you work with very carefully because only a handful of them actually are successful. Getting money from any VC just won’t make it. The model is proving to be broken somehow and we might see a pretty big shift in the VC industry as a whole.

Startups need to get back to basics, building a service or offer that actually has great value for their customers and that can be sold. They need to build their product with whatever resources they have (which will take longer). Most important they should focus on the value to customers instead of focusing on how much money they can raise. In the long run, the payoff will certainly be way better. Funding is a means.. not an end.. Getting VC funding can fuel your growth (or simply make impossible) but it’s nowhere near a success.

Some interesting articles on the subject:

What about the Team?

As I was reading my previous post about how good the picture needs to be for an entrepreneur, I realized that I totally overlooked the team. This was not intentional as the Team is definitely very important but I have a certain view about that.. My feeling is that VC would love to have a business with a great team: Knowledgeable people, outstanding track record of success, etc.. But what you realize is that when you start working with a VC it’s for years (hopefully), and the VCs will try to have either people that are the cream of the crop for the job, OR former buddies they worked with in the past and who have been successful in the post. You should not under-estimate the fact that Affinity will play a enormous role in the choice of the team (for you and the VC). I’m not blaming them for that, would you not rather work with people you have already worked with and who have been successful rather than having to bet on a  new team?

The only advice I could have is certainly to find a someone who already had a successful startup at a key role in your team.. or be ready to hire a CEO (from the list provided by the VC ;-)) Additionally, make sure you REALLY get along with your teammates and open up issues as fast as possible. It’s easy to change things at the beginning of a company, but as time passes, things get harder..

A few myths about VC funding

I met an entrepreneur who filed a patent for a pretty interesting technology and he was willing to get some funding for his business. He came to me as I was participating in panel for the launch of the UC Berkeley Business plan competition 2010. He was very convincing about his technology and really felt that his idea could get funded quickly.

After his first presentation to a VC firm that turned him down we had a long conversation about the most probable reasons why he had been turned down. This is when I realized that some people (probably more that I think) actually have a misperception of VC funding. The influence of the Bubble era pre-2001 are still deeply rooted in many people’s mind,making them think they can get funding with “just an idea”, but the scares of the burst after 2001, are also deeply rooted in the VC’s mind.

Here are a few myths about VC funding that I think should be well understood by wannabe entrepreneurs:
A good technology is enough for a VC: Technology is good but not sufficient. A VC firm is here to invest and make fast returns on their investments. A company at the technology stage has a lot of work to go by to prove the market opportunity, define a business model and acquire customers. A VC would rather invest a bit later in a proven business than earlier in a technology.
VC have so much money they’ll finance everything: It is true that VC do have a lot of money and they do need to invest it. But make no mistakes, VC bet on big wins for most of their investments. A big bet is a Google, a VMWare or similar company for which the return is astronomical. Out of 10 companies in which a VC invest, One will be a big win, 2 or 3 will make money and the rest might barely make it or lose money. (BACKUP WITH NUMBERS) If you think about the fact that all of those were thought to be potential big wins, imagine how much a VC can be wrong.. Just a little less wrong that others (hopefully).
Asking for a low amount is equivalent to low risk for a VC: I have seen a incredible amount of entrepreneurs taking that stand: asking for $100K, or $250K to make the VC feel it’s so low that they are not taking much risk. This attitude clearly shows that the entrepreneur doesn’t understand how  a VC works. There is two component when looking at how a VC works in terms of investment decision. To make it brief:
If a VC has several millions to invest and a very limited number of partners to take care of their portfolio. if a $300M fund invest in $250K deals they will need to find and finance 1200 deals.. knowing that most of the time those VCs have 2 to 10 general partners, is their something wrong in the equation? VC are willing to invest from $5M to $30M or more in one venture if the return is good enough. A few deals a year is perfect for each General Partner and their is no time for very small deals.
if your venture requires only a few hundred thousands dollars to start and explode to the level a VC is interested in, it certainly means that their is a very low barrier to entry and competition will be very quick to come by and hinder the growth. Some competitive edge must be present to explain how you can produce so much value with such a little amount of cash to start with. I’m not saying it is impossible, but it’s doubtful.
Any VC will do for my Venture: This is a very common mistakes made by Entrepreneurs as they pitch to VCs. A VC is here not only for the money they invest, but for the network they provide, their experience, and their capacity to execute a good exit. The Track record of previous funds and of the general partners as well as the composition of the VC’s portfolio are very important in choosing the VC you want to work with. I might be naive, but I feel that a VC-Venture deal has to be a match for both sides otherwise it is doomed to fail. Pick your VC carefully because if it makes sense for you to work with them, the reciprocal might very well be true.

I’m digging up some numbers and will post them very shortly..

Wannabe Entrepreneurs, does the picture look good?

I was reading a post on a friend’s blog ( about the mind set of an entrepreneur and realized that what he was pointing at as arguments not to start a business was partially flawed. I agree with the fact that if we could get all the data the analyze a venture’s success in advance, most of the time we wouldn’t start those businesses but the flaw in the argument resides in the fact that most of the time, those analysis are close to impossible to make. Sensitivity on Pricing based on what evidence? your product is not even sold yet. Of course you could survey a few potential customers and get an idea, but until you start getting money in your bank account, you have no real proof that your ricing is the right one. Your market sizing is similar in that a lot of entrepreneur will rely on a Gartner research, or on Forrester research to get those big billions of dollars market, but knowing in advance who your perfect customer is, and predict how well you are going to be able to sell them is clearly an illusion. What I’m saying here is that the art of forecasting and sizing stays an art, and their is very rarely hard proof that you forecasts are right or wrong. As a consequence, entrepreneurs won’t decide to start a business based on evidence that it cannot work, but more relying on the fact that the picture “looks good” when gathering as much data as possible.

So what is a picture that “looks good”?
A big market: clearly the bigger the market the easiest it will be to find some place for your venture. just a matter of sheer size.. The Travel industry for example is over $300B dollars annually. It could be considered easier to make $50M to $100M in a market of that size than in a $200M market.
A fast growing market: It’s easier to grow with a market than inside a market. Their is less competition for market share and the demand is growing which helps keeping prices high and preserve margins.
A real problem: That would be the key to a successful business.. Solving a problem that is painful, costly, visible, well known.. It’s even better if it’s a direct problem for you customer. Costly server and datacenter maintenance have pushed companies to use SaaS (Software as a Service) solutions. It was a direct cost (high cost I should say) reduction. On the other end, global warming has an indirect effect on people, and the immediate value of solving that problem is harder to defend in the short term. Who is the most impacted today by global warming? That’s who should be targeted by company that have solutions (if any) to solve the problem. A consequence of the real problem is that customers would be willing to pay for it. to many product (especially on the web) think they cannot charge and that it will bring more traffic if they don’t. This might be true but I would rather have 1 customers that pay me $1, than 10 customers that don’t pay me at all.. both could be used in a pricing strategy though!
A cheaper, faster, better solution: It’s often the case that the problem you are solving already has a solution, albeit a bad one. Switching costs are often a big forgotten component of many wannabe entrepreneurs and status quo has a very powerful force. The venture should have a cheaper product (to compensate the switching cost), it should be faster if a matter of performance is implied (although it could be faster to deploy… ie SaaS), and better. Better does not necessarily mean more features, more integration, etc.. but could be better suited for need. Why is it that Barracuda antiSpam solutions when they came out were so successful with a product that was clearly not as efficient as a Sophos PMX and Open Source alternatives? it was easy to install, easy to upgrade, was cheap and replaceable, and was doing an “OK” job. It’s was better for many companies where spam was an issue but not a tremendous one.

Some other points could be added to the picture:
A good business model: The choice of business model is extremely important and can make or break a venture. As an example, your product could be a technology that you license or a full blown product. One of the other is completely different in cost structure and financial forecast. “Implicit Interfaces” (winner of the UC Berkeley Bplan competition 2008) has a good technology for shopping visually based of commonality between products. they started deploying the technology with which was a perfect fit and suddenly changed their business model to a standalone site that they would control. I’m hoping they are successful but I strongly doubt that the shift in business model was the right move..
Connections / industry experience. Having the right network in the industry you are dealing with can greatly speed up development of your business. When Marc Benioff started, he had a tremendous experience at Oracle, as a VP of sales (TO VERIFY). What a great position to start a company like salesforce. This is why the team is very important when the venture starts.
A Patent: I was hesitant to put that in the picture because of the cynical point of view I have about patents for entrepreneurs. The problem with patents is that you need to defend them against infringement. Imagine you come up with a great technology, you file a patent and try to start a business. Now Microsoft, Google or what ever big corporation infringes the patent.. What money are you going to use to fight the multimillion dollars law fees they have available against you for many years? Those companies can drain you out quicker than you can think. The movie (MOVIE ABOUT WIPERS) was a great story but I wouldn’t make it an evidence that it works every time.
A good understanding of the competition: The more you can know on the competition the better. How much revenue do they make, how fast did they grow, how many customers, what segments of the market are they targeting, what’s their roadmap, who’s in the team, who funded them, could they copy/modify their product to look like you etc.. Your competition can bring a lot of data point for your own forecast. Competition can also force your pricing in a direction or another and your sensitivity analysis could potentially be more accurate. I often hear entrepreneurs pitching their idea and saying that their is no competition on their market. If that is really the case, they should wonder why, and think about switching costs and status quo as their competition. Those two are tough..

I’ll conclude by saying that evidences of a good opportunity are hard to gather in a precise way. Writing a Business Plan is a way to ensure that you have dug as much as you can into what you can know and see if the picture “looks good” or not. Experience helps a lot, so getting feedbacks from other entrepreneurs is critical in the process. they will raise some good questions and allow you to refine your search for the right opportunity.

So why are entrepreneurs still starting all those ventures? is it because of a leap of faith or something else? I think that is going to be the subject of my next post..