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.

Is SaaS such a great business model? – 19 months later.

Unbelievably I went back and read what I wrote in January of 2010 (link) where I compared BMC and Salesforce in terms of comparable companies (revenue speaking), BMC being a more traditional software vendor and Salesforce being the pure SaaS player.

Let’s look at the evolution of those two companies over the last 19 months

01/2010 SalesForce BMC
Market Cap $8.01B $6.84B
EBITDA $145M $633M
Revenue $1.24B $1.8B

Back then I thought that SaaS was not necesseraly the way to go for a startup, although fundamentally, I was seeing a lot of benefits to this model. Now about 19 months later the same table (looking at the last Balance sheet)

09/2011 SalesForce BMC
Market Cap $15.9B $7B
EBITDA $115M $677M
Revenue $1.94B $2.11B

Do you see what I see?? Salesforce doubled its market cap, increased its revenue by almost 30% and is dwarfing BMC.. That said it still has a small EBITDA. In comparison BMC basically stayed the same, with a slight growth and still a nice Earning number.

Salesforce numbers are impressive in terms of growth but scary in terms of earnings so the question remains: Is SaaS such a great business model?

Hell YES! I made one big mistake in my previous analysis and this post is here to correct it. I did not really look at the stage at which the companies were in their growth. Salesforce is a fast growing startup which has one thing in mind: Growth of the top line. On the other hand, BMC has been a stagnant company and is focused on its bottom line. I should not have compared those two companies in the first place because investment decisions are completely different in those two cases.

So why with only 6% of revenue in EBITDA is SaaS a great business model? The answer is simple: It’s the subscription model of SaaS, and it’s the growth.

If your business is using the SaaS model, you will get no big check when you sell your product, in fact it’s the opposite, you get a big cost. If the customer is big enough or if your reached a certain amount of customers on the same infrastructure, you may have to upgrade it, you will have larger server load, memory usage, bandwidth usage and all this will cost you from day one. Of course you will amortize those costs, and if you priced you offer well, you will collect the benefits of this model in the long run. So for Salesforce, a lot of those costs are applied today (R&D, Sales, Marketing, Infrastructure) which eat the margin (reducing the EBITDA).

The growth is the second factor. Growth is costly, you have to hire, you have to invest, you have to discount to win customers, etc. Marc Benioff said today in a keynote that we are trying to hire as many people as he can and the problem he has is that he cannot find enough people! Especially in sales. For a business, if the strategy is growth, where should you put your dollars? As earnings that will be taxed? distributed to shareholder (who will be taxed as well)? Or into your business to make it grow even bigger? Think about $1 of earning. Take out 30% tax. Distribute it, and take another 25%, this dollars is wasted. Now put this dollars in a business that has doubled its market cap in 19 months.. What makes sense now?

The low EBITDA of Salesforce is nowhere near the sign that the SaaS business model is weak, or that the company is not doing well, it’s the opposite. This business is doing very well, demonstrating how powerful the SaaS model can be. Companies using the SaaS as a business model cannot be evaluated as standard software vendor with on-premise solution. If you are considering SaaS for your own business, it should be very clear in your mind. It should also be very clear that transitioning from an on-premise model to a SaaS model is extremely difficult without significant hits on your revenue which is why SAP, Oracle and other big vendors have so much trouble.

Regarding Salesforce, the fun fact is that as soon as the growth starts slowing down, the earnings will explode through the rough relative to revenue. Funny how things work with SaaS.

is SaaS such a great business model?

I have to admit that I love SaaS (Software as a Service), both from a user perspective and from a supplier perspective., and those are the main reasons why:

SaaS is a new way (granted it’s well over 10 years old but new in most people’s mind) to deliver application over the web. Instead of downloading or buying an application and installing it on your own machine or server, you simply connect to a web site and use the application online. What’s the benefit as a user:

Instant access, no install cost. Using a SaaS solution is basically a matter of creating an account. When you use your gmail or Yahoo mail, it’s email using the SaaS model.. You don’t need to buy a machine.

Pay as you go.. Pricing is usually based on a subscription model: If you use the application (assuming it’s not free), you pay a monthly fee, but if you want to stop using it, just stop paying. The investment required is definitely lower than paying an upfront fee for “On-premise” software.

No Maintenance. when you have a software installed in your enterprise, you have to handle it’s maintenance. Upgrade, problems, extension is needed, etc.. With the SaaS model, your supplier takes care of all of it, including Backups. Upgrade are done seamlessly, on a very frequent basis, bugs are solved faster (no need for a big release), storage is usually expandable at will. All this for your monthly subscription.

One version to deal with. If any problem occurs on the application and you have to deal with your suppliers hotline, you won’t hear the usual: “Upgrade to the latest version and call us back”. You are always using the latest version and support is therefore simplified.

From a Supplier stand point the benefits are also great:

Easy to do trials with customers. As the start up cost is close to zero, it’s easy to push your potential customers to try out your software and hopefully convince them that it works for them and that they should subscribe.

The Subscription model allows for recurring incomes that are more predictable and that add up over time. Every new customer will bring an additional revenue to your business which, over time can become very significant and less dependent on sales effort.

Only one version to support. If you think that companies like SAP can maintain something like 10 versions of the same software, imagine the  hassle (and cost) of development, upgrade, testing (Quality Assurance – QA), and training. Dealing with only one version is fundamentally less costly for a supplier.

Easy to up-sale customers with add-ons. Want extra storage, want a Gold Access to certain features? the user can be one click away from those up-sales by making it very convenient for them to buy. SaaS makes it very easy to come up with version pricing, bundle pricing, and get a little closer to the economist dream of one price per user..

I could go on and on about those benefits and the growth of the SaaS market as a whole has been impressive as a consequence. Gartner projected that  “by 2011, 25 percent of new business software will be delivered as SaaS” and IDC projected that “by 2011, this opportunity will reach $14.8 billion, representing a compound annual growth rate (CAGR) of 32%”. Fast growing market (one of the key point for a successful business) so why isn’t everyone taking that route then? What is hidden behind the scene?

People talk about as one of the biggest company to have achieved a sustainable revenue/profit with SaaS. makes almost $1B a year but if we take a closer look at another company with similar size (at least in terms of market cap): BMC, what do we see?

Some rough numbers first:

SalesForce BMC
Market Cap $8.01B $6.84B
EBITDA $145M $633M
Revenue $1.24B $1.8B

If you look at all the benefits from SaaS, a SaaS company should have way larger margins than any other non SaaS company, but the numbers say otherwise:

SalesForce has a profit margin of 5.96% where BMC shoots at 18.29%, the operaintg margin of Salesforce is 8.53% where BMC flies at 27.62%..  (all data come from Yahoo Finance). BMC has been on the market for a lot longer, so the learning curve for Salesforce might not have allowed them to reach an optimum position yet.

Of course I’m not a financial analyst (call to all my friends who are in the finance sector for a quick analysis that I can add here!!) but there is something wrong in this picture.

Here are a few guesses that would surface in their 10K:

Spending on the sales force itself and on marketing effort must be huge at Salesforce. Despite all the benefits of SaaS large company who can bring large revenue with smaller sales force, are still convinced that (for security/control reasons) they are better off having everything internally. There is a huge need to convince decision maker that SaaS IS safe and that you can trust a third party to host your data, secure it and maintain it, better than you can do yourself and for cheaper.

The SaaS market is still very attractive to Small and Medium businesses too, and reaching those companies requires large sales force (or going through resellers), which is costly..

Another explanation is that Saleforce might not follow the SaaS model as much as it wants. What if trying to gain new customers (especially big ones) they break their own rules and start building custom solutions (different versions that need to be maintained separately..). I wouldn’t be surprised to see that happening.. but doing so on a true SaaS architecture makes it a nightmare (and expensive) to maintain and grow.

The SGA of both company could backup those guesses:

Sales Force SGA: 693M (growing steadily with revenue)

BMC SGA: 739M (stable for the last 3 years with a $400M increase in revenue)

When I look at this more closely I realize that SaaS might not be the major success people think int he coming year. It is a good business model that’s for sure, and startups should definitely consider it, but let’s not take things for granted and think that building a SaaS model over an On-Premise model is the recipe for success. I would go even farther than that and say that a company structured to build on-premise solutions can more seasily build a SaaS offer and maitain it as an extra version that the other way around.

Finance people, I am turning to you for comments.. what’s hidden behind those numbers? is SaaS such a great business model?

Startup Analysis: Gliider, can a Browser Plugin have a successful Business Model? – part 1

I recently saw a pitch for a startup called Gliider and was impressed with the product. To make it simple, it’s a Firefox plugin that allows you to store travel information that you find on the web (Hotels, points of interest, Flights, whatever) by a simple drag and drop to the Gliider box. Once you are done, you can print or share you saved stuff.. Usually people will bookmark, print, copy and paste into a word document (at least that’s what I do) which is pretty bad.. Honestly, I really like Gliider.

At the presentation, one of the question after the pitch was: “Do you think this can have a sustainable business model?”. This is what we are going to find out now. I took the liberty to make a few hypothesis of course but I hope to give you an idea of a process that should be applied by every entrepreneurs who wishes to start a business.

First question: How do they make money? They have a “deals tab” in the widget that will send you travel deals (hotels, etc..) according to the saved search. That’s interesting as you can imagine those deals as well targeted.

Second Question: how much do they make per deal sold? That’s an unknown, but they do have a partnership with Expedia (source: Techcrunch) and looking at expedia’s affiliate program, you can easily find that they would make $4 per Flight transaction (which Gliider doesn’t seem to offer yet), and 5.5% to 6% of the transaction on Hotels. That seems pretty high so I’m wondering if it’s the full booking transaction or the gross margin made by expedia (which would be a lot smaller..). Anyway, we’ll stay in wonderland and imagine that it’s the full booking.

A hotel booking can go from something like $60 to an easy $250 (I’m excluding master suits!), for 1 to 5 or 6 nights in general. That ranges the potential gain per room from 5.5% x 1night x $60 = $3.3, to $250 x 6 nights x 6% = $90 commission. Pretty big range and we’ll deal with it. Most probably the transaction commission will fall in the $12 to $20 dollars on average.

Third question: how much do they have to make to be sustainable? That’s along question but I’ll keep it short by just keeping it simple. Gliider is a startup, they are small, probably somewhere around 4 or 5 people, low cost infrastructure, average salary around $90K, a professional web hosting, distribution through Firefox plug-in platform, some benefits (healthcare) and a  little bit of marketing + PR.. Let’s keep it low and say $700K for the year (ok that’s low…). At $700K they can sustain the initial team and maybe improve the business a bit.

Fourth question: For users who have the plugin installed, how many will use the deal section? This is a bit like a CTR (Click Through Rate).. You might play with it after you install it, but then you’ll forget about it until you actually search for your next travel, and out of those they would need to click the Deal tab and see what’s available. I would venture a guess that this number stays in the low %.. Let’s take from 0.5% up to 5% (which would be incredible).

Fifth question: For the users who click on a deal, what would be the conversion rate (user who actually buy after clicking)? This is a classic and I would guess it in the same 0.5% to 6.5% (if the targeting is really great).

Last question: How many Active Users do they need on a monthly basis to make the necessary $700K to be sustainable?

Let’s recap:

  • target revenue: $700K
  • Revenue per transaction: between $12 and $20
  • Users clicking a deal: between 0.5% and 5%
  • Users booking a deal after clicking on it: between 0.5% and 6.5%

We are ready to plug this into Excel and play with the sensitivity parameters:

Those table tell us how many Users of the widget per month they need to have to reach their sustainability:

Ouch… in the best of the best scenario, they would still need to have about 900K users monthly.. and in the worst, 194 million.. That’s a tough call and it brings us to conclude that this model is NOT sustainable (and definitely not interesting for a VC investment). You could do the model yourself and play with different options but honestly, I didn’t find any that would be great…

So the bonus question is: How can they become sustainable? because as entrepreneurs we want to find solutions not just stare at the problem.

I think the post has been long enough for now, but in the next one we’ll talk about ways for Gliider (and probably a lot of other plugins) to reach their goal and succeed.

Any comments are welcome! and by the way: install it and try it, it’s really a good product..

-Antony Passemard