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Anik Bose (BGV General Partner) shares his perspective on the industrial internet of things (IIOT). Over the past 18 months we have seen a sizeable chunk of our deal flow coming from the IIOT sector. During this time we have also engaged in active dialogue with larger technology firms that are playing an important role in the IIOT eco-system. This blog attempts to synthesize our perspective based on our interactions. Early Days The Industrial Internet of Things is a mega trend that is expected to transform existing businesses and create new ones – see chart below summarizing the research findings from the McKinsey Global Institute report (published in June 2015). 9settings However, we are still in the early days of this transformation and actual deployments have barely scratched the surface. 451 research states that optimizing operations is the most common reason for deploying IIOT solutions, especially amongst manufacturing and utilities enterprises. While enhancing customer targeting is critical for retail, reducing risk is more important for financial and government segments. Security concerns, along with a lack of end-to-end solutions combined with a scarcity of skilled technical resources are currently inhibitors of enterprise IOT adoption. Another data point is that most VC backed company commercial traction in this sector has been at the infrastructure layer – hardware, networking, security and data. Hardware layer (chip) investments include Tessel, Pinoccio, Spark and Arduino. Networking/Cloud infrastructure investments include Ayla Networks, Jasper Networks, Iotera, PubNub and SigFox. Security investments include Mocana, Bastille Networks, Bayshore Networks and Weaved. Data infrastructure investments include Decision IQ, Maana, PingThings and Mnubo. CB Insights has categorized the IIOT into 9 emerging categories – 6 horizontal and 3 vertical ones – see the following chart: CBInsights market map Challenging Traditional VC Models IIOT is challenging the traditional VC model across several dimensions:
  • A key theme of IIOT is transforming existing businesses through operational efficiencies, not just creating new ones. This requires start-ups in this arena to establish collaborative models with incumbents instead of do-it-alone models in order to create and capture value. This will likely result in a bias towards M&A exits rather than billion $ IPO’s.
  • Most traditional VC’s lack domain knowledge around not-so-glamorous IIOT use cases and are therefore unable to provide this value add to start ups. This is another reason for startups to work with VC’s with deep operational experience in this industry as well as collaborate with larger players earlier in the process for product definition and validation.
  • New business models are emerging as VC funded ideas do not need to be just broad and finely tuned (as in other sectors). In fact many IIOT startups are narrowly focused on specific problems and vertical markets. Such a “vertical solution” approach is often outside the comfort zones of most traditional VC’s. Furthermore issues around data privacy and data ownership are creating their own challenges around data monetization for startups.
Increasingly important role of Corporate VC’s Large technology vendors are being strongly influenced by two IIOT vectors: a) How it will impact their existing products, customers and markets; b) What new adjacent market growth opportunities it will create for them. Consequently corporate VC’s are pursuing aggressive IIOT eco-system investments as part of their overall strategies to identify new businesses or identify technologies to transform existing ones. According to a recent CBInsights three out of the top 4 investors in IIOT are corporate VC’s – Intel, Cisco and Qualcomm with True Ventures being the only pure VC firm. A few examples to elaborate on emerging corporate IIOT strategic themes:
  • GE is making investments around building smarter industrial machines and delivering business process improvements to its traditional customer segments such as aviation, rail, healthcare, power and oil and gas through advanced analytics. Key investments include being a founding member of IIC, Predix Industrial data lake development and eco-system investments to seed and identify best of breed IIOT analytics applications.
  • Cisco is focusing its efforts on the theme of intelligent and secure-IIOT infrastructure and is partnering aggressively with industry incumbents like ABB, Honeywell and GE to deliver complete solutions. Key investments include ruggedized industrial networking infrastructure, acquisition of Jasper Networks and investments in PaaS cloud connectivity startups.
  • Intel is touting IIOT as a key driver of its virtuous cycle of growth (data center and memory being the other drivers).   Key investments include IOT SoC chips and investments in IIOT applications and infrastructure to create demand for its chips.
Finally the fragmentation of IIOT tools provides an additional opportunity for larger players like Cisco and GE to play a solution provider or systems integrator role with enterprise customers – e.g. knitting together their own solutions with startup company best of breed technologies. In fact, in many scenarios many startups are being forced to work with large integrators after going through a success proof of concept, where they were able to demonstrate superior capabilities against the same system integrators. Implications for Early Stage Investments To be successful in early stage investing in this sector will require:
  • Startups delivering core solutions instead of technology building blocks alone. BGV portfolio company Intellivision ( a leader in video analytics and smart connected IOT cameras is a good example. The company delivers full video analytics solutions for surveillance and smart connected homes. In an era of robotics, drones and automated vehicles, where a multitude of sensors help in control and maneuverability, computer vision has become a critical technology need. While open source solutions like OpenCV provide a good starting point, accuracy and real time are features one cannot compromise on. IntelliVision has some of the highest accuracy rates and is integrated directly into chipset. In order to win with this strategy, you have to have best-in-class solutions with proven performance metrics.
  • Focus on Analytics and Cybersecurity – the sectors where startups will be best poised to create and capture value. Analytics innovation will be driven two factors: a) Tsunami of MegaData – According to IDC 40% of all data generated by 2020 will be machine generated, yet most companies remain ill prepared to leverage this for competitive advantage; b) Latent Economic Value – McKinsey and ABI estimate that $11.4 trillion will be created from IIOT driven productivity improvements. A big driver of this will be analytics ($25B from Maintenance analytics alone). Innovations in Machine Learning (Neural Networks/Deep Learning) – are beginning to deliver the data science needed to deliver insights from the above. This spans issues such as ability to scale, improved signal to noise ratios, lack of labeled data for training, and the use of deep learning models that adapt as the contextual environment changes. Companies like Predikto ( – Predictive Maintenance for Transportation Verticals along with Sentient ( – AI platform employs deep learning to a number of verticals and Maana ( – Data mining and machine leaning solutions for IOT) are promising early stage companies in this area. Cybersecurity will be the another area of significant value creation opportunity for startups because of two reasons: a) The surface area of attack for IIOT is immense due to factors such as – Cloning of things, malicious substitution of things, eavesdropping attacks, Man-in-the middle attacks during key exchanges, firmware replacement attacks, routing attacks, Privacy threats and extraction of security parameters; b) Security is fast becoming the #1 bottleneck for broader IIOT deployments (451 research findings that the #1 concern inhibiting IIOT deployments amongst enterprises is security). Companies like Bayshore Networks (, Device Authority ( and Bastille Networks ( are good examples of startups in this space.
  • Developing Solutions for Vertical markets – We believe that there will be an emergence of IIOT full stack vertical solutions startups that can deliver solutions required by enterprises instead of having to pursue a DIY strategy with consultants and SI’s. Deep product experience, filling in a gap that is not available within the SI world, is a necessity to win in this market. A common challenge such investments face is questions around the size of the total and serviceable addressable markets (TAM and SAM.) Contrary to a broad approach, startups have to choose a “niche market” that they can dominate. A successful strategy for such full stack vertical solutions startups is to have a viable “bowling alley” strategy ( where they seek a beachhead that will allow them to leverage their success in the initial niche market to attack an adjacent related niche market.
Bowling Alley Source:
  • Partnering with Larger Eco-system Vendors – Finally startups will need to leverage the domain knowledge possessed by strategic partners around IIOT use cases to shape their product and technology development earlier at earlier stages of their life cycle.
  • Cross-border start ups – According to the McKinsey Global Institute report on the Internet of things, “over the next ten years the potential number of IoT uses is likely
to be higher in developing economies. The applications that drive the most value in developing economies differ from those in advanced economies and, in some cases, because there are no legacy technologies to displace, developing economies can “leapfrog” in IoT implementations”. The high volume of estimated installations in developing economies reflects the shift of global economic growth to those areas, which has important implications for companies that compete in IoT equipment and service markets. China will be one of the largest users of IoT systems in factories as well as in other settings. Countries with oil and 
gas operations—among the most important early adopters of IoT—will also be major geographic markets.” Cross-border startups that can address these international market opportunities will be well positioned for success.
Conclusion The IIOT value chain and eco-system is a complex one, this combined with the important role of existing industry incumbents makes for a complex start up value creation and capture journey. Value creation from early stage investing in IIOT will require a different model, one that is more aligned:
  • Around balancing vertical investment bets instead of purely broad horizontal ones
  • With the DNA of corporate partnering required to collaborate with incumbents in the early days to deliver complete enterprise solutions rather than pursuing purely go it alone value building strategies
  • Towards return models with a bias more towards M&A exits than Unicorn IPO exits

Anik Bose and Eric Buatois (General Partners at BGV) share their perspective on securing the Internet of Things. We believe that the intersection of IoT and Security will present a profound opportunity for technology innovation and Venture backed start-ups to create value. This belief is based on several factors.  First the attack area presented by the IoT is immense.  The broad surface area is created by the billions of connected devices and the IoT need for Cloning of Things (for example two cloned devices can still be associated and work together) – this opens up backdoors for all kinds of illegal activity.  Furthermore the IoT opens up opportunities for malicious substitution of things, eavesdropping attacks, man-in-the-middle attacks, firmware replacement attacks and extraction of security parameters to name a few specific threats.  We also know from experience that end points tend to be weak in dealing with security and that IoT devices have constrained resources making the implementation of security at the device level challenging.  As a consequence the economic cost of breaches could be staggering. Securing the IoT presents a unique set of policy challenges since the data and information generated by various IoT applications will be extremely sensitive. Who owns it? How can it be shared? Does it belong to the supplier or the customers? Can the data cross international boundaries (i.e. critical energy grids)? Policies, which do not exist today, will have to be defined, put in place and enforced.  As an example, will data have to be encrypted to move from one data center to another one within the same cloud or between different clouds? The cost and availability of security solutions will also shape the policies. These policies will either rely upon open standards or even generate the creation of new standards. Traditional security is an all IP approach but an all IP approach is unlikely to work because both standards and IoT communications over CoAP are not fully evolved.  802.15.4 defines security procedures but it is still evolving while work within the standards is only focused on end to end security and secure group communications.  So standardization will be a key factor enabling the development of effective security solutions versus ineffective “pieced together” solutions with the help of consulting firms.  Traditional solutions like Sandboxing, signature based detection will not work in an IoT environment.  IoT security solutions will need to manage tradeoffs between performance and security as well as choose between distributed or centralized architectures.  Centralized architectures like Trust Center (Zigbee), 6LBR (Border Router for 6LoWPan) and Central key distribution (KDC) are emerging and are likely to be winners against decentralized mechanisms that require strong P2P mechanisms which are very difficult to implement. While we are still in the early days of IoT adoption there are a few good examples of startup innovation at the intersection of Security and IoT : –       Device Authentication (eg Launchkey) –       RTOS (eg Mocana, Icon Labs and Red Balloon Security), Wireless Sensor Networks (eg Sensalyze acquired by ARM, Dust Networks and Green Pack) –       End to End systems for Key management (eg Dyadic security) and Intrusion detection systems (eg Argus, ScadaFence). These technology segments can address broad application areas and tend to be industry agnostic.  However success in these areas will likely require partnerships with Sensor Vendors in this space. The winning companies are likely to be the one not only creating and or supporting emerging IOT standards but also understanding the critical policies needed to manage, share and exchange critical IOT information. BGV is building key partnerships to source innovation and build companies that will secure the IoT.  These include relationships with IoT focused accelerators, Corporate Partners and University incubators.

Eric Buatois (General Partner at BGV) described in the first part of his blog the creation of a new industrial IOT highway that will remove the friction of connecting, gathering and aggregating data. In this blog he discusses the need for policies to manage cross industry information flow and the emergence of data aggregators in the industrial IoT.  Michael Porter states in his blog – “Smart, connected products raise a new set of strategic choices related to how value is created and captured, how the prodigious amount of new (and sensitive) data they generate is utilized and managed, how relationships with traditional business partners such as channels are redefined, and what role companies should play as industry boundaries are expanded.” ( Currently in the industrial IoT eco system only 1% of the data generated by installed industrial equipment is processed while large Consumer Internet companies process about 70% of the data that is generated. If big data is the result of human interaction with corporate applications and consumer web sites, then similarly the industrial machines will generate a new category of smart data. Large industrial companies such as Siemens, Tyco, GE will use this IOT highway to build specific services using their domain knowledge and by leveraging proprietary algorithms. These services will generate a new data set that will become the basis of novel value creation. This scenario raises an important question – Will this data belong to the equipment vendors i.e. Siemens, GE or the energy utility or hospitals owning the equipment? This raises several policy concerns: what kind of data can be available and to whom and for what purpose? Following the Snowden scandal, the importance for clear public policies to define who owns what data and how that data is protected has come under increasing scrutiny. The massive amounts of data collected by the industrial IoT will create the need for aggregation centers that will process the data locally before centralization. Can this information cross national borders? What kind of encryption and security should be implemented? Third party data aggregators will emerge as independent companies that will on one side protect the information of specific cities, medical centers, public utilities but make it accessible to their suppliers and partners under well-defined policies. In the past a similar trend unfolded in the credit card industry.  When the credit card was launched in 1958, no one forecasted the emergence of new companies performing credit checks, credit scoring, consumer and business data aggregation and payment processing, We are now  using these services on a daily basis without giving them a second thought. Large market segments such as Transportation, Energy generation, Oil & Gas, Manufacturing, Retail, Smart cities, will see a similar transformation with IOT. The information created by the deployment of IOT infrastructure and highway will be aggregated by companies either funded by Venture Capital funding or as spin offs from large industrial corporations. These new companies will benefit from a massive network effect where more data aggregation will generate increasing value. These new data aggregators will have a direct impact on the GDP growth of countries and also be a source of job creation for highly skilled labor. During the next 5 years, we will see an intense co-opetition between large industrial corporations; industry associations, governments and VC backed companies to get access and control to this new source of wealth creation.  But the source of entrepreneurial and software talent to build these data aggregator types of companies is in Silicon Valley.  The key talent that understood, built and monetized the data of the Internet consumers is likely to understand and grasp the opportunities of industrial IOT data aggregation rapidly. BGV is actively involved in identifying investment in industrial IOT as well as establishing pro-active partnerships with industrial corporations to assist in the transformation of the Industrial Internet of Things.

Eric Buatois, BGV General Partner shares his perspective on the opportunities for Venture investing in IoT We are preparing ourselves for a new world where personal devices, cars, glasses, and watches will be connected to the internet for the benefits of the consumer. New smart cities connecting existing infrastructure promise a better environment for consumers. Our new connected homes are envisioned to  automatically secure, and control heating and air conditioning. However all the above emerging market segments demand a fundamentally new consumer behavior.  Such large changes will only occur if large consumer brands invest in creating the demand and providing the right solution at the right price. Large software companies such as Google and Apple are expanding their market footprint acquiring various hardware companies to expand their sensor product portfolio, penetrating deeper in the home and the life of consumers as part of their IoT strategy. To exploit the value creation opportunities presented by the Internet of Things Consumer Internet companies process 70% of the consumer data going through their sites and expect this to increase over time. At the other end of the spectrum large industrial corporations process only 1% of the data generated by their installed industrial equipment.  Furthermore these companies face increasing pressures to increase their top line revenues, grow customer loyalty and adopt new technologies at the risk of being dis intermediated..  Industrial segments such as oil & gas, utilities, manufacturing, commercial and industrial building automation, medical equipment providers and hospitals are facing a revolution where the data and services created around the data captured by their core equipment will generate high shareholder returns. Companies such as General electric, Honeywell, ABB, Siemens, United Technology, Whirlpool, Bosch, Ford, Renault, Volkswagen need to implement a cultural change whereby gathering customer data and selling it as a service will become as important if not more important than delivering superior products.  But corporations in these industries will face difficulties in attracting the top software talent needed to build these solutions. The current lack of trained data scientist and bid/data analytic experts combined with a low-tech brand image put these industrial companies at a disadvantage when it comes to recruiting this “scarce skilled talent.” Therefore it is not surprising to see companies like General Electric, Honeywell, ABB, Siemens, United Technology, and many international Car manufacturers coming to Silicon Valley with the goals of building a business intelligence hub and developing local eco systems.  But will this be enough? Certainly not. Google, Microsoft, Facebook can buy sensors, consumer devices, robot companies and integrate them effectively in their customer value delivery engine. Now, if Honeywell, Siemens, ABB, GE want to acquire innovative software companies the resulting value creation will be disappointing. Why? Because the effective value will reside in the information created through the gathering and processing of data coming from installed equipment. This resulting information has to be shared by players across the value chain of the same industry or even across different industries. Technology has removed the friction of connecting, gathering and aggregating data. Uber has changed the taxi business model leveraging the connectivity platform built by Twilio.   A new generation of integrated connection and information processing platforms will emerge allowing industrial companies to concentrate on their unique algorithm and solution software. They will form a new industrial IOT highway. Despite their top management commitment and significant capital investment, the GE, Siemens, Honeywell of the world will not have the time or talent to build these platforms. These industrial IOT technology companies are likely to emerge in technology hubs such as Silicon Valley. Either local or global these emerging platform companies will create a massive network effect. More connectivity to more and more things combined with a slick mobile user interface will allow more and more applications to emerge increasing the scale of connections and the value of the platform. The complex and lengthy sales cycles experienced by Venture Capitalist who have invested in startups serving the industrial sector will be reduced dramatically incenting them to participate in such companies. Who will perform this industrial IOT App store role? Who will build the necessary wireless and connectivity grid to connect industrial equipment’s?  Technology Start-ups backed by Venture Capitalists!  These companies will start by focusing on a couple of market solutions and ultimately expand horizontally across industries.  Who will benefit in delivering solutions on this new grid? GE, Siemens, ABB, Renault, Honeywell… BGV is actively involved in identifying investment in industrial IOT as well as establishing pro-active partnerships with industrial corporations to assist in the transformation of the Industrial Internet of Things.

Paul Stich, CEO of Appthority shares his perspective on Mobile App Risk Management Mobile devices (smartphones and tablets) are playing an ever increasing and strategic role in today’s corporate environments. Increased employee use of mobile devices, along with the growth of the Bring Your Own App (BYOA) economy, introduces new risks to the enterprise. The average employee has between 50 and 150 mobile apps on their device, with many of those apps capable of accessing and sharing critical and sensitive corporate and personal data. Developers for web based mobile applications are inclined to choose functionality over security when trade-offs must be made.  For example, Ernst & Young (Mobile Device Security) has tested numerous mobile web applications where the password complexity requirements or account lockout features had been reduced or removed entirely. Restrictions on JavaScript or persistent session data have also led developers to place sensitive information and session information within the URL of every request to the server. In addition, network bandwidth limitations may encourage developers to create mobile device-formatted sites that cache additional information from web pages, potentially exposing this information if the device is compromised.  Client based mobile applications need to support different operating systems and SDKs that developers use to create applications.  Each of these platforms has a different security model that affect how developers address security within their own applications. So, what would be considered a mobile app risk?  Here’s an example: Have you ever noticed an app that’s constantly running in the background (that really has no need to do so?) It’s possible that it’s tracking your location and sharing it with outside parties for advertising purposes.
  App developers will often ask for these types of permissions upfront, but unfortunately that’s not always the case; or, the language they use is intentionally vague or deceptive. In the larger context of BYOD (Bring Your Own Device), these types of mobile app behaviors are not only a significant risk to users, but to organizations as well.  Without a fully automated way to check for mobile app risk, it is very challenging for organizations to identify which mobile apps put corporate data at risk versus which apps are benign.  As organizations embrace the productivity and connectivity gains of the mobile workforce, it is important to address the risks commonly found in 3rd party apps on employee devices. Some interesting data about mobile app risk:
  • Surprisingly, iOS apps exhibit more risky behaviors than Android apps (91% of the top 200 iOS apps exhibit at least 1 risky behavior as compared to 83% of the top 200 Android apps)*
  • Free apps are riskier than paid apps: 95% of the top 200 free iOS and Android apps exhibit at least one risky behavior vs 80% of the top 200 paid apps.*
* Source: Appthority App Reputation Report. Appthority was founded on the principle of helping organizations automate the management of mobile app risk, and empower a smarter, safer mobile workforce.  For more on Appthority, please visit