Trends – RMK Scale Ventures

Rise of deep tech startups in Japan – Norihiko Isawa

March 21, 2019
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Although the news was inconspicuous at the time in Japan, it was indeed remarkable that Airbus Ventures participated as a lead investor in the $7.3 million Series A round for Infostellar, a Tokyo-based satellite antenna sharing platform in September 2017. The financing was substantially the first lead investment by a venture capital arm of a prestigious European multinational corporation in the Japanese startup history.

In addition to Infostellar, Airbus Ventures participated in the $11 million Series A round for Trillium Secure, a presently Sunnyvale-headquartered cyber security technology startup originally established in Tokyo. The financing led by JAFCO Japan, one of the largest VC firms in the country, in July 2018 is another funding round which involved a venture capital arm of an eminent European MNC, Deutsche Bahn Digital Ventures this time.

The recent two investments above imply a newly emerging omen that European capital has gradually started to go towards Japan. However, contrary to the large market sizes of and trading volumes between Europe and Japan, both a number and amount of bilateral investments are still small for the time being. Major reasons behind this limited interaction are considered to be the low visibility of Japanese startups and a lack of necessary information for investment examination in Europe. Therefore, this article principally aims at introducing the latest ecosystem and rising deep tech startups in Japan to MNCs and VC firms in Europe.

Overview of the Recent Japanese Startup Ecosystem

The global top 8 VC investment markets in 2017 from top to bottom are the United States ($71.9 billion), China ($40.0 billion), the United Kingdom ($5.8 billion), Israel ($3.9 billion), Germany ($2.9 billion), Japan ($2.5 billion), France ($2.4 billion) and Sweden ($1.7 billion). So, in terms of a VC investment amount, Japan is ranked 6th in the world, behind Germany and ahead of France.

The VC investment amounts in Japan rapidly increased after the inception of the new economic growth policy “Abenomics” installed by the Abe Administration in 2013. The quantitative easing policy increased the amount of capital in the market and encouraged private-sector investment, resulting in the dramatic change in VC investment from $0.8 billion in 2013 to $2.5 billion in 2017 with a CAGR of 35.1%.

Unlike other countries, there is a notable characteristic in Japan that corporations, instead of VC firms or institutional investors, have been the principal player in the market. Indeed, shares of VC investment amounts by players in 2017 from top to bottom are corporations (41.0%), financial institutions (16.1%), independent VC firms (14.8%), governmental agencies and universities (12.5%) and others (15.7%).

A major reason behind this characteristic is the large amount of retained earnings as cash and deposits within Japanese corporations. The overall amounts of cash and deposits within Japanese corporations have continuously increased from $1.4 trillion in 2008 to $2.2 trillion in 2017. And the richest Japanese corporations such as Toyota, Sony and Mitsubishi have as much cash and deposits as the US “Tech Giants” such as Apple, Microsoft and Alphabet do.

Large corporations also play an important role as Limited Partnership investors or sponsors of major VC funds. For example, the LP investors of World Innovation Lab, or WiL for short, the largest and most prestigious VC firm in Japan, are 28 leading corporations in major industries ranging from automobile and TMT to transportation and financial services. In addition to WiL, the lead LP investors of Global Brain, another VC giant, include large corporations such as KDDI, a major mobile operator, and Mitsui Fudosan, the largest real estate developer.

Large corporations strategically invest in VC funds in order to search for promising startups as potential business partners, especially those in frontier domains. In the past couple of years, investment in deep tech startups has significantly increased.

Rise of Deep Tech Startups in Japan

VC investments in deep tech fields such as but not limited to autonomous driving, robotics and UAVs dramatically increased in 2017. Comparing numbers of VC investments in the top 50 largest financing rounds, they are 3, 18 and 9 in 2016, 2017 and 2018, respectively. ispace, a space resource exploration company, raised $90 million, the largest financing in the Japanese startup history, from large corporations such as Japan Airlines, KDDI, Suzuki Motor, Dentsu and Konica Minolta as well as VC funds such as Mirai Creation Fund, the CVC of Toyota. In addition to ispace, GROOVE X, a consumer robot developer, raised a significant amount of approximately $40 million, mostly owing to the fame of its founder Mr. Hayashi, the product manager of Pepper at Softbank.

Autonomous driving is a core field of deep tech which recently attracts a large amount of investment. Indeed, Preferred Networks, an AI for-IoT startup spun-out from the University of Tokyo, has raised $130 million in total until now, and its lead investor is Toyota which subsequently funded $8.2 million and $95 million in 2015 and 2017, respectively. The company is notable for its brilliant founders; they are among the most intelligent researchers in the field of AI and participated in the prominent International Collegiate Programming Contest by the Association for Computing Machinery. Preferred Networks has developed big data analysis infrastructures and deep learning frameworks, and now focuses on development of deep learning technologies for IoT. In this context, Toyota Research Institute, Toyota’s AI laboratory, partnered with Preferred Networks in 2017 to co-develop AI for autonomous vehicles.

Another notable deep tech startup is Tier IV, a Nagoya University-origin startup established in 2013 which develops and provides corporations with Autoware, open source software for autonomous driving, and other hardware necessary for demonstration experiments. Tier IV has partnered with NVIDIA and intends to become a global de-facto standard in the field of autonomous driving software, through the distribution of Autoware for free. The company has raised over $25 million in total from large corporations such as KDDI, Sony, Yamaha and Aisan Technology, a surveying technology company. KDDI, Aisan Technology and Tier IV started a demonstration project of autonomous driving in February 2019.

In the field of Urban Air Mobility, a hoverbike developer A.L.I. Technologies is remarkable. The startup was established in 2016 by students from the famed Department of Aeronautics and Astronautics at the University of Tokyo. It has been funded by Drone Fund, a fund dedidicated to investments in UAVs, and itself in turn invests in drone startups to construct a technology portfolio of drone-related IPs. The startup now develops a hoverbike called Speeder and relevant traffic control systems for UAVs.

In addition to large corporations, it is funded by KSK Angel Fund, a family office of Keisuke Honda, a Japanese professional football player who once played for VVV-Venlo, AC Milan and CSKA Moscow in Europe.

There exist several reasons why deep tech startups have successfully raised vast amounts of capital from and partnered with large corporations.

In short, there is a clear win-win collaboration opportunity between large corporations and startups. Large corporations have for long focused their in-house R&D activities on strategic themes which are directly related to their core businesses, in order to increase the ROI/ Return on Investment and other efficiency indices. Therefore, they have hardly been able to deal with frontier technologies which are far from their existing businesses, resulting in a lack of innovations from Japanese corporations. This inconvenient mechanism in corporate R&D activities has produced motives for large corporations to search deep tech startups as their co-development partners. Since Japanese high-tech corporations require frontier technologies which cannot be developed in-house, startups spun-out from universities which usually have more advanced technologies become their main targets.

In general, technologies in leading universities are considered to be 10 to 20 years more advanced than technologies in large corporations. However, deep tech startups spun-out from universities tend to lack know-how and capabilities to commercialize. Therefore, they are motivated to collaborate with and look for corporations which can support them to transform their technologies into viable products and services.

Thus, the clear win-win collaboration opportunity has led to the recent tide of deep tech investments and corporate venturing.

Global Expansion by Japanese Deep Tech Startups

It is remarkable that some Japanese deep tech startups are already open to global. For example, ispace has an office in Luxemburg with 12 staffs. In addition, Rapyuta Robotics, a developer of cloud-connected low-cost multi-robot systems for security and inspection, is a spun-out venture from ETH Zurich. Furthermore, Xtreme-D, a developer of plug-in computing for next generation high-performance computing, has already opened an office in Silicon Valley, with the cooperation of WiL. Tier IV has also opened an office in Silicon Valley. One of the co-founders of Ascent Robotics, a startup for automation algorithms, is from the United States.

As already mentioned, Infostellar and Trillium Secure have been funded by Airbus and Deutsche Bahn. In addition to the two, Floadia Corporation and Cerebrex, which are both semiconductor startups, have been funded by UMC Capital, the CVC arm of UMC, the world’s second largest semiconductor foundry based in Taiwan. There only exist a few examples of such globally-funded startups, but they indicate an omen that their followers will appear soon.

In terms of hiring, some deep tech startups are comprised of multinational teams. Startups such as Ascent Robotics actively recruit staffs, especially engineers, globally and their job descriptions are prepared in English.

Potential Collaborations between European MNCs and Japanese Deep Tech Startups

As described above, Japanese deep tech startups have rapidly gained power for the last couple of years, through constant capital injection from and co-development with large corporations. At the same time, European MNCs such as Airbus and Deutsche Bahn have also reached and invested in some Japanese deep tech startups. These recent trends indicate that there exist further potentials of collaborations between Europe and Japan; Japanese deep tech startups could be relevant business partners and promising investees for European high-tech MNCs. This hypothesis is backed by four reasons.

Firstly, quite a few Japanese deep tech startups are ventures spun-out from leading universities, and thus their technologies are foremost of its kind and generally more advanced than those in large corporations which themselves are front-runners in the world. This means that Japanese deep tech startups are worth partnering in terms of technology acquisition for European high-tech MNCs.

Secondly, European and Japanese large corporations have similar organizational cultures and behaviors. For example, conservative senses of values, relatively slow and bureaucratic decision-making processes and high quality standards can be seen in both European and Japanese large corporations. This means that Japanese deep tech startups which have been co-working and therefore are now familiar with cultures and behaviors of Japanese large corporations could easily adapt to those of European ones. From the viewpoint of European high-tech MNCs, hurdles to collaborate with Japanese deep tech startups are fairly low now.

Thirdly, economic and trade relationships between Europe and Japan are expected to strengthen due to the Agreement between the European Union and Japan for an Economic Partnership which just came into effect on February 1 st, 2019. The EPA will further encourage trade of goods and services and investment between the two parties. In addition to the national-level policies, the Tokyo Metropolitan Government has been promoting global expansions of startups based in Tokyo, through the X-Hub program in which selected startups are able to receive business support from mentors such as venture capitalists and seed accelerators in partner countries. Indeed, Tier IV and Ascent Robotics have been selected as startups of the Germany onward program.

Lastly, Japanese deep tech startups have recently been more open to the global market but do not have proper business partners in Europe. This means that there exist white spaces for European high-tech MNCs to become their business partners.

The rise of deep tech startups in Japan (and why European companies should take note)

Open Source Software – Investable Business Model or Not? – Natallia Chykina

March 11, 2019
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Open-source software (OSS) is a catalyst for growth and change in the IT industry, and one can’t overestimate its importance to the sector. Quoting Mike Olson, co-founder of Cloudera, “No dominant platform-level software infrastructure has emerged in the last ten years in closed-source, proprietary form.”

Apart from independent OSS projects, an increasing number of companies, including the blue chips, are opening their source code to the public. They start by distributing their internally developed products for free, giving rise to widespread frameworks and libraries that later become an industry standard (e.g., React, Flow, Angular, Kubernetes, TensorFlow, V8, to name a few).

Adding to this momentum, there has been a surge in venture capital dollars being invested into the sector in recent years. Several high profile funding rounds have been completed, with multimillion dollar valuations emerging (Chart 1).

But are these valuations justified? And more importantly, can the business perform, both growth-wise and profitability-wise, as venture capitalists expect? OSS companies typically monetize with a business model based around providing support and consulting services. How well does this model translate to the traditional VC growth model? Is the OSS space in a VC-driven bubble?

In this article, I assess the questions above, and find that the traditional monetization model for OSS companies based on providing support and consulting services doesn’t seem to lend itself well to the venture capital growth model, and that OSS companies likely need to switch their pricing and business models in order to justify their valuations.

OSS Monetization Models

By definition, open source software is free. This of course generates obvious advantages to consumers, and in fact, a 2008 study by The Standish Group estimates that “free open source software is [saving consumers] $60 billion [per year in IT costs].”

While providing free software is obviously good for consumers, it still costs money to develop. Very few companies are able to live on donations and sponsorships. And with fierce competition from proprietary software vendors, growing R&D costs, and ever-increasing marketing requirements, providing a “free” product necessitates a sustainable path to market success.

As a result of the above, a commonly seen structure related to OSS projects is the following: A “parent” commercial company that is the key contributor to the OSS project provides support to users, maintains the product, and defines the product strategy.

Latched on to this are the monetization strategies, the most common being the following:

Extra charge for enterprise services, support, and consulting. The classic model targeted at large enterprise clients with sophisticated needs. Examples: MySQL, Red Hat, Hortonworks, DataStax
Freemium. (advanced features/products/add-ons) A custom licensed product on top of the OSS might generate a lavish revenue stream, but it requires a lot of R&D costs and time to build. Example: Cloudera, which provides the basic version for free and charges the customers for Cloudera Enterprise
SaaS/PaaS business model: The modern way to monetize the OSS products that assumes centrally hosting the software and shifting its maintenance costs to the provider. Examples: Elastic, GitHub, Databricks, SugarCRM

Historically, the vast majority of OSS projects have pursued the first monetization strategy (support and consulting), but at their core, all of these models allow a company to earn money on their “bread and butter” and feed the development team as needed.

Influx of VC Dollars

An interesting recent development has been the huge inflows of VC/PE money into the industry. Going back to 2004, only nine firms producing OSS had raised venture funding, but by 2015, that number had exploded to 110, raising over $7 billion from venture capital funds (chart 2).

Underpinning this development is the large addressable market that OSS companies benefit from. Akin to other “platform” plays, OSS allows companies (in theory) to rapidly expand their customer base, with the idea that at some point in the future they can leverage this growth by beginning to tack-on appropriate monetization models in order to start translating their customer base into revenue, and profits.

At the same time, we’re also seeing an increasing number of reports about potential IPOs in the sector. Several OSS commercial companies, some of them unicorns with $1B+ valuations, have been rumored to be mulling a public markets debut (MongoDB, Cloudera, MapR, Alfresco, Automattic, Canonical, etc.).

With this in mind, the obvious question is whether the OSS model works from a financial standpoint, particularly for VC and PE investors. After all, the venture funding model necessitates rapid growth in order to comply with their 7-10 year fund life cycle. And with a product that is at its core free, it remains to be seen whether OSS companies can pin down the correct monetization model to justify the number of dollars invested into the space.

Answering this question is hard, mainly because most of these companies are private and therefore do not disclose their financial performance. Usually, the only sources of information that can be relied upon are the estimates of industry experts and management interviews where unaudited key performance metrics are sometimes disclosed.

Nevertheless, in this article, I take a look at the evidence from the only two public OSS companies in the market, Red Hat and Hortonworks, and use their publicly available information to try and assess the more general question of whether the OSS model makes sense for VC investors.

Case Study 1: Red Hat

Red Hat is an example of a commercial company that pioneered the open source business model. Founded in 1993 and going public in 1999 right before the Dot Com Bubble, they achieved the 8th biggest first-day gain in share price in the history of Wall Street at that time.

At the time of their IPO, Red Hat was not a profitable company, but since then has managed to post solid financial results, as detailed in Table 1.

Instead of chasing multifold annual growth, Red Hat has followed the “boring” path of gradually building a sustainable business. Over the last ten years, the company increased its revenues tenfold from $200 million to $2 billion with no significant change in operating and net income margins. G&A and marketing expenses never exceeded 50% of revenue (Chart 3).

The above indicates therefore that OSS companies do have a chance to build sustainable and profitable business models. Red Hat’s approach of focusing primarily on offering support and consulting services has delivered gradual but steady growth, and the company is hardly facing any funding or solvency problems, posting decent profitability metrics when compared to peers.

However, what is clear from the Red Hat case study is that such a strategy can take time—many years, in fact. While this is a perfectly reasonable situation for most companies, the issue is that it doesn’t sit well with venture capital funds who, by the very nature of their business model, require far more rapid growth profiles.

More troubling than that, for venture capital investors, is that the OSS model may in and of itself not allow for the type of growth that such funds require. As the founder of MySQL Marten Mickos put it, MySQL’s goal was “to turn the $10 billion a year database business into a $1 billion one.”

In other words, the open source approach limits the market size from the get-go by making the company focus only on enterprise customers who are able to pay for support, and foregoing revenue from a long tail of SME and retail clients. That may help explain the company’s less than exciting stock price performance post-IPO (Chart 4).

If such a conclusion were true, this would spell trouble for those OSS companies that have raised significant amounts of VC dollars along with the funds that have invested in them.

Case Study 2: Hortonworks

To further assess our overarching question of OSS’s viability as a venture capital investment, I took a look at another public OSS company: Hortonworks.

The Hadoop vendors’ market is an interesting one because it is completely built around the “open core” idea (another comparable market being the NoSQL databases space with MongoDB, Datastax, and Couchbase OSS).

All three of the largest Hadoop vendors—Cloudera, Hortonworks, and MapR—are based on essentially the same OSS stack (with some specific differences) but interestingly have different monetization models. In particular, Hortonworks—the only public company among them—is the only player that provides all of its software for free and charges only for support, consulting, and training services.

At first glance, Hortonworks’ post-IPO path appears to differ considerably from Red Hat’s in that it seems to be a story of a rapid growth and success. The company was founded in 2011, tripled its revenue every year for three consecutive years, and went public in 2014.

Immediate reception in the public markets was strong, with the stock popping 65% in the first few days of trading. Nevertheless, the company’s story since IPO has turned decisively sour. In January 2016, the company was forced to access the public markets again for a secondary public offering, a move that prompted a 60% share price fall within a month (Chart 5).

Underpinning all this is that fact that despite top-line growth, the company continues to incur substantial, and growing, operating losses. It’s evident from the financial statements that its operating performance has worsened over time, mainly because of operating expenses growing faster than revenue leading to increasing losses as a percent of revenue (Table 2).

Among all of the periods in question, Hortonworks spent more on sales and marketing than it earns in revenue. Adding to that, the company incurred significant R&D and G&A as well (Table 2).

On average, Hortonworks is burning around $100 million cash per year (less than its operating loss because of stock-based compensation expenses and changes in deferred revenue booked on the Balance Sheet). This amount is very significant when compared to its $630 million market capitalization and circa $350 million raised from investors so far. Of course, the company can still raise debt (which it did, in November 2016, to the tune of a $30 million loan from SVB), but there’s a natural limit to how often it can tap the debt markets.

All of this might of course be justified if the marketing expense served an important purpose. One such purpose could be the company’s need to diversify its customer base. In fact, when Hortonworks first launched, the company was heavily reliant on a few major clients (Yahoo and Microsoft, the latter accounting for 37% of revenues in 2013). This has now changed, and by 2016, the company reported 1000 customers.

But again, even if this were to have been the reason, one cannot ignore the costs required to achieve this. After all, marketing expenses increased eightfold between 2013 and 2015. And how valuable are the clients that Hortonworks has acquired? Unfortunately, the company reports little information on the makeup of its client base, so it’s hard to assess other important metrics such as client “stickyness”. But in a competitive OSS market where “rival developers could build the same tools—and make them free—essentially stripping the value from the proprietary software,” strong doubts loom.

With all this in mind, returning to our original question of whether the OSS model makes for good VC investments, while the Hortonworks growth story certainly seems to counter Red Hat’s—and therefore sustain the idea that such investments can work from a VC standpoint—I remain skeptical. Hortonworks seems to be chasing market share at exorbitant and unsustainable costs. And while this conclusion is based on only two companies in the space, it is enough to raise serious doubts about the overall model’s fit for VC.

Why are VCs Investing in OSS Companies?

Given the above, it seems questionable that OSS companies make for good VC investments. So with this in mind, why do venture capital funds continue to invest in such companies?

Good Fit for a Strategic Acquisition

Apart from going public and growing organically, an OSS company may find a strategic buyer to provide a good exit opportunity for its early stage investors. And in fact, the sector has seen several high profile acquisitions over the years (Table 3).

What makes an OSS company a good target? In general, the underlying strategic rationale for an acquisition might be as follows:

Getting access to the client base. Sun is reported to have been motivated by this when it acquired MySQL. They wanted to access the SME market and cross-sell other products to smaller clients. Simply forking the product or developing a competing technology internally wouldn’t deliver the customer base and would have made Sun incur additional customer acquisition costs.
Getting control over the product. The ability to influence further development of the product is a crucial factor for a strategic buyer. This allows it to build and expand its own product offering based on the acquired products without worrying about sudden substantial changes in it. Example: Red Hat acquiring Ansible, KVM, Gluster, Inktank (Ceph), and many more
Entering adjacent markets. Acquiring open source companies in adjacent market segments, again, allows a company to expand the product offering, which makes vendor lock-in easier, and scales the business further. Example: Citrix acquiring XenSource
Acquiring the team. This is more relevant for smaller and younger projects than for larger, more well-established ones, but is worth mentioning.

What about the financial rationale? The standard transaction multiples valuation approach completely breaks apart when it comes to the OSS market. Multiples reach 20x and even 50x price/sales, and are therefore largely irrelevant, leading to the obvious conclusion that such deals are not financially but strategically motivated, and that the financial health of the target is more of a “nice to have.”

With this in mind, would a strategy of investing in OSS companies with the eventual aim of a strategic sale make sense? After all, there seems to be a decent track-record to go off of.

My assessment is that this strategy on its own is not enough. Pursuing such an approach from the start is risky—there are not enough exits in the history of OSS to justify the risks.

A Better Monetization Model: SaaS

While the promise of a lucrative strategic sale may be enough to motivate VC funds to put money to work in the space, as discussed above, it remains a risky path. As such, it feels like the rationale for such investments must be reliant on other factors as well. One such factor could be returning to basics: building profitable companies.

But as we have seen in the case studies above, this strategy doesn’t seem to be working out so well, certainly not within the timeframes required for VC investors. Nevertheless, it is important to point out that both Red Hat and Hortonworks primarily focus on monetizing through offering support and consulting services. As such, it would be wrong to dismiss OSS monetization prospects altogether. More likely, monetization models focused on support and consulting are inappropriate, but others may work better.

In fact, the SaaS business model might be the answer. As per Peter Levine’s analysis, “by packaging open source into a service, […] companies can monetize open source with a far more robust and flexible model, encouraging innovation and ongoing investment in software development.”

Why is SaaS a better model for OSS? There are several reasons for this, most of which are applicable not only to OSS SaaS, but to SaaS in general.

First, SaaS opens the market for the long tail of SME clients. Smaller companies usually don’t need enterprise support and on-premises installation, but may already have sophisticated needs from a technology standpoint. As a result, it’s easier for them to purchase a SaaS product and pay a relatively low price for using it.

Citing MongoDB’s VP of Strategy, Kelly Stirman, “Where we have a suite of management technologies as a cloud service, that is geared for people that we are never going to talk to and it’s at a very attractive price point—$39 a server, a month. It allows us to go after this long tail of the market that isn’t Fortune 500 companies, necessarily.”

Second, SaaS scales well. SaaS creates economies of scale for clients by allowing them to save money on infrastructure and operations through aggregation of resources and a combination and centralization of customer requirements, which improves manageability.

This, therefore, makes it an attractive model for clients who, as a result, will be more willing to lock themselves into monthly payment plans in order to reap the benefits of the service.

Finally, SaaS businesses are more difficult to replicate. In the traditional OSS model, everyone has access to the source code, so the support and consulting business model hardly has protection for the incumbent from new market entrants.

In the SaaS OSS case, the investment required for building the infrastructure upon which clients rely is fairly onerous. This, therefore, builds bigger barriers to entry, and makes it more difficult for competitors who lack the same amount of funding to replicate the offering.

Success Stories for OSS with SaaS

Importantly, OSS SaaS companies can be financially viable on their own. GitHub is a good example of this.

Founded in 2008, GitHub was able to bootstrap the business for four years without any external funding. The company has reportedly always been cash-flow positive (except for 2015) and generated estimated revenues of $100 million in 2016. In 2012, they accepted $100 million in funding from Andreessen Horowitz and later in 2015, $250 million from Sequoia with an implied $2 billion valuation.

Another well-known successful OSS company is DataBricks, which provides commercial support for Apache Spark, but—more importantly—allows its customers to run Spark in the cloud. The company has raised $100 million from Andreessen Horowitz, Data Collective, and NEA. Unfortunately, we don’t have a lot of insight into their profitability, but they are reported to be performing strongly and had more than 500 companies using the technology as of 2015 already.

Generally, many OSS companies are in one way or another gradually drifting towards the SaaS model or other types of cloud offerings. For instance, Red Hat is moving to PaaS over support and consulting, as evidenced by OpenShift and the acquisition of AnsibleWorks.

Different ways of mixing support and consulting with SaaS are common too. We, unfortunately, don’t have detailed statistics on Elastic’s on-premises vs. cloud installation product offering, but we can see from the presentation of its closest competitor Splunk that their SaaS offering is gaining scale: Its share in revenue is expected to triple by 2020 (chart 6).

Investable Business Model or Not?

To conclude, while recent years have seen an influx of venture capital dollars poured into OSS companies, there are strong doubts that such investments make sense if the monetization models being used remain focused on the traditional support and consulting model. Such a model can work (as seen in the Red Hat case study) but cannot scale at the pace required by VC investors.

Of course, VC funds may always hope for a lucrative strategic exit, and there have been several examples of such transactions. But relying on this alone is not enough. OSS companies need to innovate around monetization strategies in order to build profitable and fast-growing companies.

The most plausible answer to this conundrum may come from switching to SaaS as a business model. SaaS allows one to tap into a longer-tail of SME clients and improve margins through better product offerings. Quoting Peter Levine again, “Cloud and SaaS adoption is accelerating at an order of magnitude faster than on-premise deployments, and open source has been the enabler of this transformation. Beyond SaaS, I would expect there to be future models for open source monetization, which is great for the industry”.

Whatever ends up happening, the sheer amount of venture investment into OSS companies means that smarter monetization strategies will be needed to keep the open source dream alive

Source : https://www.toptal.com/finance/venture-capital-consultants/open-source-software-investable-business-model-or-not

Money Out of Nowhere: How Internet Marketplaces Unlock Economic Wealth – Bill Gurley

March 1, 2019
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In 1776, Adam Smith released his magnum opus, An Inquiry into the Nature and Causes of the Wealth of Nations, in which he outlined his fundamental economic theories. Front and center in the book — in fact in Book 1, Chapter 1 — is his realization of the productivity improvements made possible through the “Division of Labour”:

It is the great multiplication of the production of all the different arts, in consequence of the division of labour, which occasions, in a well-governed society, that universal opulence which extends itself to the lowest ranks of the people. Every workman has a great quantity of his own work to dispose of beyond what he himself has occasion for; and every other workman being exactly in the same situation, he is enabled to exchange a great quantity of his own goods for a great quantity, or, what comes to the same thing, for the price of a great quantity of theirs. He supplies them abundantly with what they have occasion for, and they accommodate him as amply with what he has occasion for, and a general plenty diffuses itself through all the different ranks of society.

Smith identified that when men and women specialize their skills, and also importantly “trade” with one another, the end result is a rise in productivity and standard of living for everyone. In 1817, David Ricardo published On the Principles of Political Economy and Taxation where he expanded upon Smith’s work in developing the theory of Comparative Advantage. What Ricardo proved mathematically, is that if one country has simply a comparative advantage (not even an absolute one), it still is in everyone’s best interest to embrace specialization and free trade. In the end, everyone ends up in a better place.

There are two key requirements for these mechanisms to take force. First and foremost, you need free and open trade. It is quite bizarre to see modern day politicians throw caution to the wind and ignore these fundamental tenants of economic science. Time and time again, the fact patterns show that when countries open borders and freely trade, the end result is increased economic prosperity. The second, and less discussed, requirement is for the two parties that should trade to be aware of one another’s goods or services. Unfortunately, either information asymmetry or physical distances and the resulting distribution costs can both cut against the economic advantages that would otherwise arise for all.

Fortunately, the rise of the Internet, and specifically Internet marketplace models, act as accelerants to the productivity benefits of the division of labour AND comparative advantage by reducing information asymmetry and increasing the likelihood of a perfect match with regard to the exchange of goods or services. In his 2005 book, The World Is Flat, Thomas Friedman recognizes that the Internet has the ability to create a “level playing field” for all participants, and one where geographic distances become less relevant. The core reason that Internet marketplaces are so powerful is because in connecting economic traders that would otherwise not be connected, they unlock economic wealth that otherwise would not exist. In other words, they literally create “money out of nowhere.”

EXCHANGE OF GOODS MARKETPLACES

Any discussion of Internet marketplaces begins with the first quintessential marketplace, ebay(*). Pierre Omidyarfounded AuctionWeb in September of 1995, and its rise to fame is legendary. What started as a web site to trade laser pointers and Beanie Babies (the Pez dispenser start is quite literally a legend), today enables transactions of approximately $100B per year. Over its twenty-plus year lifetime, just over one trillion dollars in goods have traded hands across eBay’s servers. These transactions, and the profits realized by the sellers, were truly “unlocked” by eBay’s matching and auction services.

In 1999, Jack Ma created Alibaba, a Chinese-based B2B marketplace for connecting small and medium enterprise with potential export opportunities. Four years later, in May of 2003, they launched Taobao Marketplace, Alibaba’s answer to eBay. By aggressively launching a free to use service, Alibaba’s Taobao quickly became the leading person-to-person trading site in China. In 2018, Taobao GMV (Gross Merchandise Value) was a staggering RMB2,689 billion, which equates to $428 billion in US dollars.

There have been many other successful goods marketplaces that have launched post eBay & Taobao — all providing a similar service of matching those who own or produce goods with a distributed set of buyers who are particularly interested in what they have to offer. In many cases, a deeper focus on a particular category or vertical allows these marketplaces to distinguish themselves from broader marketplaces like eBay.

In 2000, Eric Baker and Jeff Fluhr founded StubHub, a secondary ticket exchange marketplace. The company was acquired by ebay in January 2007. In its most recent quarter, StubHub’s GMV reached $1.4B, and for the entire year 2018, StubHub had GMV of $4.8B.
Launched in 2005, Etsy is a leading marketplaces for the exchange of vintage and handmade items. In its most recent quarter, the company processed the exchange of $923 million of sales, which equates to a $3.6B annual GMV.
Founded by Michael Bruno in Paris in 2001, 1stdibs(*) is the world’s largest online marketplace for luxury one-of-a-kind antiques, high-end modern furniture, vintage fashion, jewelry, and fine art. In November 2011, David Rosenblatt took over as CEO and has been scaling the company ever since. Over the past few years dealers, galleries, and makers have matched billions of dollars in merchandise to trade buyers and consumer buyers on the platform.
Poshmark was founded by Manish Chandra in 2011. The website, which is an exchange for new and used clothing, has been remarkably successful. Over 4 million sellers have earned over $1 billion transacting on the site.
Julie Wainwright founded The Real Real in 2011. The company is an online marketplace for authenticated luxury consignment. In 2017, the company reported sales of over $500 million.
In 2015, Eddy Lu and Daishin Sugano launched GOAT, a marketplace for the exchange of sneakers. Despite this narrow focus, the company has been remarkably successful. The estimated annual GMV of GOAT and its leading competitor Stock X is already over $1B per year (on a combined basis).

SHARING ECONOMY MARKETPLACES

With the launch of Airbnb in 2008 and Uber(*) in 2009, these two companies established a new category of marketplaces known as the “sharing economy.” Homes and automobiles are the two most expensive items that people own, and in many cases the ability to own the asset is made possible through debt — mortgages on houses and car loans or leases for automobiles. Despite this financial exposure, for many people these assets are materially underutilized. Many extra rooms and second homes are vacant most of the year, and the average car is used less than 5% of the time. Sharing economy marketplaces allow owners to “unlock” earning opportunities from these underutilized assets.

Airbnb was founded by Joe Gebbia and Brian Chesky in 2008. Today there are over 5 million Airbnb listings in 81,000 cities. Over two million people stay in an Airbnb each night. In November of this year, the company announced that it had achieved “substantially” more than $1B in revenue in the third quarter. Assuming a marketplace rake of something like 11%, this would imply gross room revenue of over $9B for the quarter — which would be $36B annualized. As the company is still growing, we can easily guess that in 2019-2020 time frame, Airbnb will be delivering around $50B per year to home-owners who were previously sitting on highly underutilized assets. This is a major “unlocking.”

When Garrett Camp and Travis Kalanick founded Uber in 2009, they hatched the industry now known as ride-sharing. Today over 3 million people around the world use their time and their underutilized automobiles to generate extra income. Without the proper technology to match people who wanted a ride with people who could provide that service, taxi and chauffeur companies were drastically underserving the potential market. As an example, we estimate that ride-sharing revenues in San Francisco are well north of 10X what taxis and black cars were providing prior to the launch of ride-sharing. These numbers will go even higher as people increasingly forgo the notion of car ownership altogether. We estimate that the global GMV for ride sharing was over $100B in 2018 (including Uber, Didi, Grab, Lyft, Yandex, etc) and still growing handsomely. Assuming a 20% rake, this equates to over $80B that went into the hands of ride-sharing drivers in a single year — and this is an industry that did not exist 10 years ago. The matching made possible with today’s GPS and Internet-enabled smart phones is a massive unlocking of wealth and value.

While it is a lesser known category, using your own backyard and home to host dog guests as an alternative to a kennel is a large and growing business. Once again, this is an asset against which the marginal cost to host a dog is near zero. By combining their time with this otherwise unused asset, dog sitters are able to offer a service that is quite compelling for consumers. Rover.com (*) in Seattle, which was founded by Greg Gottesman and Aaron Easterly in 2011, is the leading player in this market. (Benchmark is an investor in Rover through a merger with DogVacay in 2017). You may be surprised to learn that this is already a massive industry. In less than a decade since the company started, Rover has already paid out of half a billion dollars to hosts that participate on the platform.

EXCHANGE OF LABOR MARKETPLACES

While not as well known as the goods exchanges or sharing economy marketplaces, there is a growing and exciting increase in the number of marketplaces that help match specifically skilled labor with key opportunities to monetize their skills. The most noteworthy of these is likely Upwork(*), a company that formed from the merger of Elance and Odesk. Upwork is a global freelancing platform where businesses and independent professionals can connect and collaborate remotely. Popular categories include web developers, mobile developers, designers, writers, and accountants. In the 12 months ended June 30, 2018, the Upwork platform enabled $1.56 billion of GSV (gross services revenue) across 2.0 million projects between approximately 375,000 freelancers and 475,000 clients in over 180 countries. These labor matches represent the exact “world is flat” reality outlined in Friedman’s book.

Other noteworthy and emerging labor marketplaces:

HackerOne(*) is the leading global marketplace that coordinates the world’s largest corporate “bug bounty” programs with a network of the world’s leading hackers. The company was founded in 2012 by Michiel Prins, Jobert Abma, Alex Rice and Merijn Terheggen, and today serves the needs of over 1,000 corporate bug bounty programs. On top of that, the HackerOne network of over 300,000 hackers (adding 600 more each day) has resolved over 100K confirmed vulnerabilities which resulted in over $46 million in awards to these individuals. There is an obvious network effect at work when you bring together the world’s leading programs and the world’s leading hackers on a single platform. The Fortune 500 is quickly learning that having a bug bounty program is an essential step in fighting cyber crime, and that HackerOne is the best place to host their program.
Wyzant is a leading Chicago-based marketplace that connects tutors with students around the country. The company was founded by Andrew Geant and Mike Weishuhn in 2005. The company has over 80,000 tutors on its platform and has paid out over $300 million to these professionals. The company started matching students with tutors for in-person sessions, but increasingly these are done “virtually” over the Internet.
Stitch Fix (*) is a leading provider of personalized clothing services that was founded by Katrina Lake in 2011. While the company is not primarily a marketplace, each order is hand-curated by a work-at-home “stylist” who works part-time on their own schedule from the comfort of their own home. Stitch Fix’s algorithms match the perfect stylist with each and every customer to help ensure the optimal outcome for each client. As of the end of 2018, Stitch Fix has paid out well over $100 million to their stylists.
Swing Education was founded in 2015 with the objective of creating a marketplace for substitute teachers. While it is still early in the company’s journey, they have already established themselves as the leader in the U.S. market. Swing is now at over 1,200 school partners and has filled over 115,000 teacher absence days. They have helped 2,000 substitute teachers get in the classroom in 2018, including 400 educators who earned permits, which Swing willingly financed. While it seems obvious in retrospect, having all substitutes on a single platform creates massive efficiency in a market where previously every single school had to keep their own list and make last minute calls when they had vacancies. And their subs just have to deal with one Swing setup process to get access to subbing opportunities at dozens of local schools and districts.
RigUp was founded by Xuan Yong and Mike Witte in Austin, Texas in March of 2014. RigUp is a leading labor marketplace focused on the oilfield services industry. “The company’s platform offers a large network of qualified, insured and compliant contractors and service providers across all upstream, midstream and downstream operations in every oil and gas basin, enabling companies to hire quickly, track contractor compliance, and minimize administrative work.” According to the company, GMV for 2017 was an impressive $150 million, followed by an astounding $600 million in 2018. Often, investors miss out on vertically focused companies like RigUp as they find themselves overly anxious about TAM (total available market). As you can see, that can be a big mistake.
VIPKid, which was founded in 2013 by Cindy Mi, is a truly amazing story. The idea is simple and simultaneously brilliant. VIPKid links students in China who want to learn English with native English speaking tutors in the United States and Canada. All sessions are done over the Internet, once again epitomizing Friedman’s very flat world. In November of 2018, the company reported having 60,000 teachers contracted to teach over 500,000 students. Many people believe the company is now well north of a US$1B run rate, which implies that around $1B will pass hands from Chinese parents to western teachers in 2019. That is quite a bit of supplemental income for U.S.-based teachers.

These vertical labor marketplaces are to LinkedIn what companies like Zillow, Expedia, and GrubHub are to Google search. Through a deeper understanding of a particular vertical, a much richer perspective on the quality and differentiation of the participants, and the enablement of transactions — you create an evolved service that has much more value to both sides of the transaction. And for those professionals participating in these markets, your reputation on the vertical service matters way more than your profile on LinkedIn.

NEW EMERGING MARKETPLACES

Having been a fortunate investor in many of the previously mentioned companies (*), Benchmark remains extremely excited about future marketplace opportunities that will unlock wealth on the Internet. Here are an example of two such companies that we have funded in the past few years.

The New York Times describes Hipcamp as “The Sharing Economy Visits the Backcountry.” Hipcamp(*) was founded in 2013 by Alyssa Ravasio as an engine to search across the dozens and dozens of State and National park websites for campsite availability. As Hipcamp gained traction with campers, landowners with land near many of the National and State parks started to reach out to Hipcamp asking if they could list their land on Hipcamp too. Hipcamp now offers access to more than 350k campsites across public and private land, and their most active private land hosts make over $100,000 per year hosting campers. This is a pretty amazing value proposition for both land owners and campers. If you are a rural landowner, here is a way to create “money out of nowhere” with very little capital expenditures. And if you are a camper, what could be better than to camp at a unique, bespoke campsite in your favorite location.

Instawork(*) is an on-demand staffing app for gig workers (professionals) and hospitality businesses (partners). These working professionals seek economic freedom and a better life, and Instawork gives them both — an opportunity to work as much as they like, but on their own terms with regard to when and where. On the business partner side, small business owners/managers/chefs do not have access to reliable sources to help them with talent sourcing and high turnover, and products like LinkedIn are more focused on white-collar workers. Instawork was cofounded by Sumir Meghani in San Franciso and was a member of the 2015 Y-Combinator class. 2018 was a break-out year for Instawork with 10X revenue growth and 12X growth in Professionals on the platform. The average Instawork Professional is highly engaged on the platform, and typically opens the Instawork app ten times a day. This results in 97% of gigs being matched in less than 24 hours — which is powerfully important to both sides of the network. Also noteworthy, the Professionals on Instawork average 150% of minimum wage, significantly higher than many other labor marketplaces. This higher income allows Instawork Professionals like Jose, to begin to accomplish their dreams.

THE POWER OF THESE PLATFORMS

As you can see, these numerous marketplaces are a direct extension of the productivity enhancers first uncovered by Adam Smith and David Ricardo. Free trade, specialization, and comparative advantage are all enhanced when we can increase the matching of supply and demand of goods and services as well as eliminate inefficiency and waste caused by misinformation or distance. As a result, productivity naturally improves.

Specific benefits of global internet marketplaces:

1. Increase wealth distribution (all examples)
2. Unlock wasted potential of assets (Uber, AirBNB, Rover, and Hipcamp)
3. Better match of specific workers with specific opportunities (Upwork, WyzAnt, RigUp, VIPKid, Instawork)
4. Make specific assets reachable and findable (Ebay, Etsy, 1stDibs, Poshmark, GOAT)
5. Allow for increased specialization (Etsy, Upwork, RigUp)
6. Enhance supplemental labor opportunities (Uber, Stitch Fix, SwingEducation, Instawork, VIPKid), where the worker is in control of when and where they work
7. Reduces forfeiture by enhancing utilization (mortgages, car loans, etc) (Uber, AirBnb, Rover, Hipcamp)

Source : http://abovethecrowd.com/2019/02/27/money-out-of-nowhere-how-internet-marketplaces-unlock-economic-wealth/

How The CIO Role Must Change Due To Digital Transformation – Peter Bendor

January 31, 2019
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Digital transformation is sweeping through businesses, giving rise to new to new business models, new and different constraints, and presenting a need for more focused organizational attention and resources in a new way. It is also upending the C-suite, bringing in new corporate titles and functions such as the Chief Security Officer emerge, Chief Digital Officer and Chief Data Officer. These new roles seemingly pose an existential threat to existing roles – for example, the CIO.

As companies invent new business models through digital transformation and bring new organizations into being, they do more than cover new ground. They also carve new roles out of existing organizations (the CIO organization, for instance). Other digital threats potentially affect the CIO role:

Recognition that digital transformation now makes technology THE business, rather than technology supporting the business; therefore, IT and CIO roles are much more vital to growth in sales.
Competing through new digital models and digital platforms, focusing on redefining the customer experience and employee experience to create and deliver new value.

At Everest Group, we investigated the question of “Will the role of the CIO go away?” As a result of that investigation, we come back strongly with “no.” In fact, here’s happening to the role of the CIO: the CIO charter is changing and thus changing – but strengthening – the role.

Reasons For Changes In The CIO Charter

The focus of the CIO charter is increasingly changing – matching the new corporate charter for competitive repositioning. The prior focus was on the plumbing (infrastructure, ensuring applications are maintained and in compliance, etc.). Although those functions remain, the new charter focuses on building out and operating the new digital platforms and new digital operating models that are reshaping the competitive landscape.

The reason the CIO role is changing with the new corporate charter is that, in most organizations, the CIO is the only function that has these necessary capabilities for digital transformation:

Breadth of vision that sees the entire organization and all its workings
Depth of resources and ability to drive transformation projects and apply technology across silos, functions and divisions.

Digital transformation inevitably forces new operating models that have no respect for traditional organizations that are functional. Digital platforms and digital operating models collapse marketing and operations, for instance, spanning across these functions and groups to achieve a superb end-to-end for customer experience.

The new models force much tighter integration and often a realignment of organizations. The CIO organization and its breadth of vision and depth of resources to drive the transformation and support the new operating model that inevitably emerges from transformation.

How The CIO Role Must Change For The New Charter

Meeting the goals of the new charter for the CIO role will not come without CIOs changing their organizations and, in many cases, changing personally. To seizing the opportunities in the new charter, as well as shaping it, requires substantial change in (a) modernizing the IT, (b) the orientation and mind-set of the IT organization, and (c) changing the organizational structure.

To support digital transformation agendas, CIOs face a set of journeys in which they need to dramatically modernize their traditional functions. They first must think about their relationship with the business. To meet the needs of the business in a much more intimate, proactive, deeper way requires more investment and organizations with deeper industry domain knowledge and relationships. They need to move talent from remote centers back onshore to be close to the business so that they can better understand in a deeper way what the needs are and act on those quickly.

Second, the IT operating model needs to change from its historical structures so that it can deliver a seamless operating environment. The waterfall structures that still permeate IT need to change into a DevOps model with persistent teams that don’t change, teams that sit close to the business. IT also needs to accelerate the company’s journey to automation and cloud.

One thing companies quickly find about operating models is that they can’t get to a well-functioning DevOps team without migrating to a cloud-based infrastructure basis. And they can’t get to a cloud-based infrastructure basis without transforming their network and network operations model.

To meet the new charter, the CIO organization also needs to change in the following aspects:

Change its mind-set
Ensure deeper business knowledge
Increase agility and speed

The modernizations I mentioned above then call into question the historical organizational structure of IT with functions such as network, infrastructure, security, apps development, apps maintenance, etc. In the new digital charter, these functions inevitably start to collapse into pods or functions aligned by business services.

As I’ve described above, substantial organizational technology and organizational change is required within the CIO’s organization to live up the new mandate. I can’t overemphasize the fact that the change is substantial nor overemphasize the need. In upcoming blog posts, I’ll further discuss the CIO’s role in reorienting the charter from plumbing to transformation and supporting the new digital operating models.

Source : https://www.forbes.com/sites/peterbendorsamuel/2019/01/30/how-the-cio-role-must-change-due-to-digital-transformation/#24f9952f68be

Digital Transformation of Business and Society: Challenges and Opportunities by 2020 – Frank Diana

January 4, 2019
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At a recent KPMG Robotic Innovations event, Futurist and friend Gerd Leonhard delivered a keynote titled “The Digital Transformation of Business and Society: Challenges and Opportunities by 2020”. I highly recommend viewing the Video of his presentation. As Gerd describes, he is a Futurist focused on foresight and observations — not predicting the future. We are at a point in history where every company needs a Gerd Leonhard. For many of the reasons presented in the video, future thinking is rapidly growing in importance. As Gerd so rightly points out, we are still vastly under-estimating the sheer velocity of change.

With regard to future thinking, Gerd used my future scenario slide to describe both the exponential and combinatorial nature of future scenarios — not only do we need to think exponentially, but we also need to think in a combinatorial manner. Gerd mentioned Tesla as a company that really knows how to do this.

He then described our current pivot point of exponential change: a point in history where humanity will change more in the next twenty years than in the previous 300. With that as a backdrop, he encouraged the audience to look five years into the future and spend 3 to 5% of their time focused on foresight. He quoted Peter Drucker (“In times of change the greatest danger is to act with yesterday’s logic”) and stated that leaders must shift from a focus on what is, to a focus on what could be. Gerd added that “wait and see” means “wait and die” (love that by the way). He urged leaders to focus on 2020 and build a plan to participate in that future, emphasizing the question is no longer what-if, but what-when. We are entering an era where the impossible is doable, and the headline for that era is: exponential, convergent, combinatorial, and inter-dependent — words that should be a key part of the leadership lexicon going forward. Here are some snapshots from his presentation:

Because of exponential progression, it is difficult to imagine the world in 5 years, and although the industrial era was impactful, it will not compare to what lies ahead. The danger of vastly under-estimating the sheer velocity of change is real. For example, in just three months, the projection for the number of autonomous vehicles sold in 2035 went from 100 million to 1.5 billion
Six years ago Gerd advised a German auto company about the driverless car and the implications of a sharing economy — and they laughed. Think of what’s happened in just six years — can’t imagine anyone is laughing now. He witnessed something similar as a veteran of the music business where he tried to guide the industry through digital disruption; an industry that shifted from selling $20 CDs to making a fraction of a penny per play. Gerd’s experience in the music business is a lesson we should learn from: you can’t stop people who see value from extracting that value. Protectionist behavior did not work, as the industry lost 71% of their revenue in 12 years. Streaming music will be huge, but the winners are not traditional players. The winners are Spotify, Apple, Facebook, Google, etc. This scenario likely plays out across every industry, as new businesses are emerging, but traditional companies are not running them. Gerd stressed that we can’t let this happen across these other industries
Anything that can be automated will be automated: truck drivers and pilots go away, as robots don’t need unions. There is just too much to be gained not to automate. For example, 60% of the cost in the system could be eliminated by interconnecting logistics, possibly realized via a Logistics Internet as described by economist Jeremy Rifkin. But the drive towards automation will have unintended consequences and some science fiction scenarios could play out. Humanity and technology are indeed intertwining, but technology does not have ethics. A self-driving car would need ethics, as we make difficult decisions while driving all the time. How does a car decide to hit a frog versus swerving and hitting a mother and her child? Speaking of science fiction scenarios, Gerd predicts that when these things come together, humans and machines will have converged:

Gerd has been using the term “Hellven” to represent the two paths technology can take. Is it 90% heaven and 10% hell (unintended consequences), or can this equation flip? He asks the question: Where are we trying to go with this? He used the real example of Drones used to benefit society (heaven), but people buying guns to shoot them down (hell). As we pursue exponential technologies, we must do it in a way that avoids negative consequences. Will we allow humanity to move down a path where by 2030, we will all be human-machine hybrids? Will hacking drive chaos, as hackers gain control of a vehicle? A recent Jeep recall of 1.4 million jeeps underscores the possibility. A world of super intelligence requires super humanity — technology does not have ethics, but society depends on it. Is this Ray Kurzweil vision what we want?

Is society truly ready for human-machine hybrids, or even advancements like the driverless car that may be closer to realization? Gerd used a very effective Video to make the point
Followers of my Blog know I’m a big believer in the coming shift to value ecosystems. Gerd described this as a move away from Egosystems, where large companies are running large things, to interdependent Ecosystems. I’ve talked about the blurring of industry boundaries and the movement towards ecosystems. We may ultimately move away from the industry construct and end up with a handful of ecosystems like: mobility, shelter, resources, wellness, growth, money, maker, and comfort
Our kids will live to 90 or 100 as the default. We are gaining 8 hours of longevity per day — one third of a year per year. Genetic engineering is likely to eradicate disease, impacting longevity and global population. DNA editing is becoming a real possibility in the next 10 years, and at least 50 Silicon Valley companies are focused on ending aging and eliminating death. One such company is Human Longevity Inc., which was co-founded by Peter Diamandis of Singularity University. Gerd used a quote from Peter to help the audience understand the motivation: “Today there are six to seven trillion dollars a year spent on healthcare, half of which goes to people over the age of 65. In addition, people over the age of 65 hold something on the order of $60 trillion in wealth. And the question is what would people pay for an extra 10, 20, 30, 40 years of healthy life. It’s a huge opportunity”
Gerd described the growing need to focus on the right side of our brain. He believes that algorithms can only go so far. Our right brain characteristics cannot be replicated by an algorithm, making a human-algorithm combination — or humarithm as Gerd calls it — a better path. The right brain characteristics that grow in importance and drive future hiring profiles are:

Google is on the way to becoming the global operating system — an Artificial Intelligence enterprise. In the future, you won’t search, because as a digital assistant, Google will already know what you want. Gerd quotes Ray Kurzweil in saying that by 2027, the capacity of one computer will equal that of the human brain — at which point we shift from an artificial narrow intelligence, to an artificial general intelligence. In thinking about AI, Gerd flips the paradigm to IA or intelligent Assistant. For example, Schwab already has an intelligent portfolio. He indicated that every bank is investing in intelligent portfolios that deal with simple investments that robots can handle. This leads to a 50% replacement of financial advisors by robots and AI
This intelligent assistant race has just begun, as Siri, Google Now, Facebook MoneyPenny, and Amazon Echo vie for intelligent assistant positioning. Intelligent assistants could eliminate the need for actual assistants in five years, and creep into countless scenarios over time. Police departments are already capable of determining who is likely to commit a crime in the next month, and there are examples of police taking preventative measures. Augmentation adds another dimension, as an officer wearing glasses can identify you upon seeing you and have your records displayed in front of them. There are over 100 companies focused on augmentation, and a number of intelligent assistant examples surrounding IBM Watson; the most discussed being the effectiveness of doctor assistance. An intelligent assistant is the likely first role in the autonomous vehicle transition, as cars step in to provide a number of valuable services without completely taking over. There are countless Examples emerging
Gerd took two polls during his keynote. Here is the first: how do you feel about the rise of intelligent digital assistants? Answers 1 and 2 below received the lion share of the votes

Collectively, automation, robotics, intelligent assistants, and artificial intelligence will reframe business, commerce, culture, and society. This is perhaps the key take away from a discussion like this. We are at an inflection point where reframing begins to drive real structural change. How many leaders are ready for true structural change?
Gerd likes to refer to the 7-ations: Digitization, De-Materialization, Automation, Virtualization, Optimization, Augmentation, and Robotization. Consequences of the exponential and combinatorial growth of these seven include dependency, job displacement, and abundance. Whereas these seven are tools for dramatic cost reduction, they also lead to abundance. Examples are everywhere, from the 16 million songs available through Spotify, to the 3D printed cars that require only 50 parts. As supply exceeds demand in category after category, we reach abundance. As Gerd put it, in five years’ time, genome sequencing will be cheaper than flushing the toilet and abundant energy will be available by 2035 (2015 will be the first year that a major oil company will leave the oil business to enter the abundance of the renewable business). Other things to consider regarding abundance:

Efficiency and business improvement is a path not a destination. Gerd estimates that total efficiency will be reached in 5 to 10 years, creating value through productivity gains along the way. However, after total efficiency is met, value comes from purpose. Purpose-driven companies have an aspirational purpose that aims to transform the planet; referred to as a massive transformative purpose in a recent book on exponential organizations. When you consider the value that the millennial generation places on purpose, it is clear that successful organizations must excel at both technology and humanity. If we allow technology to trump humanity, business would have no purpose
In the first phase, the value lies in the automation itself (productivity, cost savings). In the second phase, the value lies in those things that cannot be automated. Anything that is human about your company cannot be automated: purpose, design, and brand become more powerful. Companies must invent new things that are only possible because of automation
Technological unemployment is real this time — and exponential. Gerd talked to a recent study by the Economist that describes how robotics and artificial intelligence will increasingly be used in place of humans to perform repetitive tasks. On the other side of the spectrum is a demand for better customer service and greater skills in innovation driven by globalization and falling barriers to market entry. Therefore, creativity and social intelligence will become crucial differentiators for many businesses; jobs will increasingly demand skills in creative problem-solving and constructive interaction with others
Gerd described a basic income guarantee that may be necessary if some of these unemployment scenarios play out. Something like this is already on the ballot in Switzerland, and it is not the first time this has been talked about:

In the world of automation, experience becomes extremely valuable — and you can’t, nor should attempt to — automate experiences. We clearly see an intense focus on customer experience, and we had a great discussion on the topic on an August 26th Game Changers broadcast. Innovation is critical to both the service economy and experience economy. Gerd used a visual to describe the progression of economic value:

Source: B. Joseph Pine II and James Gilmore: The Experience Economy

Gerd used a second poll to sense how people would feel about humans becoming artificially intelligent. Here again, the audience leaned towards the first two possible answers:

Gerd then summarized the session as follows:

The future is exponential, combinatorial, and interdependent: the sooner we can adjust our thinking (lateral) the better we will be at designing our future.

My take: Gerd hits on a key point. Leaders must think differently. There is very little in a leader’s collective experience that can guide them through the type of change ahead — it requires us all to think differently

When looking at AI, consider trying IA first (intelligent assistance / augmentation).

My take: These considerations allow us to create the future in a way that avoids unintended consequences. Technology as a supplement, not a replacement

Efficiency and cost reduction based on automation, AI/IA and Robotization are good stories but not the final destination: we need to go beyond the 7-ations and inevitable abundance to create new value that cannot be easily automated.

My take: Future thinking is critical for us to be effective here. We have to have a sense as to where all of this is heading, if we are to effectively create new sources of value

We won’t just need better algorithms — we also need stronger humarithms i.e. values, ethics, standards, principles and social contracts.

My take: Gerd is an evangelist for creating our future in a way that avoids hellish outcomes — and kudos to him for being that voice

“The best way to predict the future is to create it” (Alan Kay).

My Take: our context when we think about the future puts it years away, and that is just not the case anymore. What we think will take ten years is likely to happen in two. We can’t create the future if we don’t focus on it through an exponential lens

Source : https://medium.com/@frankdiana/digital-transformation-of-business-and-society-5d9286e39dbf

Robots for Rent – Why RaaS Works – RIA

December 21, 2018
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Renting robots as temp labor? Not a new idea. But it’s certainly one that is gaining followers.

Rising labor shortages, tightly contested global markets, and growing interest in automation are tightening the screws on traditional business models. A broader spectrum of users are seeking flexible automation solutions. More suppliers are adopting new-age rental or lease options to satisfy the demand. Some are mature companies answering the call, others are startups blazing a path for the rest of the industry. Robotics as a Service (RaaS) is an emerging trend whose time has come.

Steel Collar Associates may have been ahead of its time when RIA spoke with its owner in 2013 about his “Humanoids for Hire” – aka Yaskawa dual-arm robots for rent. Already several years into his venture at the time, Bill Higgins was having little success contracting out his robo-employees. Back then, industry was barely warming up to the idea of cage-free robots rubbing elbows with their human coworkers. Now every major robot manufacturer has a collaborative robot on its roster. And a slew of startups have joined the fray.

Just like human-robot collaboration is helping democratize robotics, RaaS will help bring robots to the masses. And cobots aren’t the only robots for rent.

Whether you have a short-term need, want to try before you buy, forgo a capital expenditure, or lower your cost of entry to robotic automation, RaaS is worth a closer look. It’s robots on demand, when and where you want them.

An out-of-the-box collaborative robot solution on wheels is easy to redeploy as production needs change. A rental option further enhances ROI. (Courtesy of READY Robotics)

Robots on Demand
Out-of-the-box solutions like those offered by READY Robotics, which are easy to use and easy to deploy, are making RaaS a reality. Your next, or perhaps first, robotic solution may be a Johnny-on-the-spot – on wheels.

“The TaskMate is a ready-to-use, on-demand robot worker that is specifically designed to come out of its shipping crate ready to be deployed to the production line,” says READY Robotics CEO Ben Gibbs, noting that manufacturers without the time to undertake custom robot integration are looking for an out-of-the box automation solution. Rental options make the foray easier.

“Time is their most precious resource. They want something like the TaskMate that is essentially ready to go out of the box,” says Gibbs. “They may have to do a little fixturing or put together a parts presentation hopper. Besides that, it’s something they can deploy pretty quickly. We’re driving towards providing a solution that’s as easy to use as your personal computer.”

The system consists of a collaborative robot arm mounted on a stand with casters, so you can wheel it into position anywhere on the production floor. The ease of portability makes it ideal for high-mix, low-volume production where it can be quickly relocated to different manufacturing cells. Nicknamed the “Swiss Army Knife” of robots, the TaskMate performs a variety of automation tasks from machine tending to pick-and-place applications, to parts inspection.

The TaskMate comes in two varieties, the 5-kg payload R5 and 10-kg payload R10 (pictured). Both systems use robot arms from collaborative robot maker Universal Robots. The UR arm is equipped with a force sensor and a universal interface called the TEACHMATE that allows different robot grippers to be hot-swapped onto the end of the arm. Supported end effector brands include SCHUNK, Robotiq and Piab.

Contributing to the system’s ease of use is READY’s proprietary operating system, the FORGE/OS software. A simple flowchart interface (pictured) controls the robot arm, end-of-arm tooling and other peripherals. No coding is required.

For those tasks requiring a higher payload, reach, or cycle time than is capable with the power-and-force limiting cobot included with the TaskMate R5 and R10 systems, READY also offers its FORGE controller (formerly called the TaskMate Kit). Running the intuitive FORGE/OS software, the controller provides the same easy programming interface but is designed as a standalone system for ABB, FANUC, UR and Yaskawa robots.

“For example, if you plug the FORGE controller into a FANUC robot, you no longer have to program in Karel (the robot OEM’s proprietary programming language),” explains Gibbs. “On the teach pendant, you can use FORGE/OS to program the robot directly, so you have the same programming experience on the controller as you do on the TaskMate.

Intuitive software interface with a flowchart design and compatibility with multiple robot brands makes programming easier and faster. (Courtesy of READY Robotics)

“We started primarily with smaller six degree-of-freedom robot arms, like the FANUC LR Mate and GP7 from Yaskawa,” continues Gibbs. “We have started to integrate some of the larger robots as well, like the FANUC M-710iC/50. Ultimately, we’re driving toward a ubiquitous programming experience regardless of what robot arm or robot manufacturer you’re using.”

In the Cloud
A common element in the RaaS rental model is cloud robotics. READY offers customers the ability to remotely monitor the TaskMate or other robotic systems hooked up to the FORGE controller.

“We can set them up with alerts, so when the production cycle is completed or the robot enters an unexpected error state, they can receive an email notifying the floor manager or line operator to check the system,” says Gibbs.

You can also save and back up programs to the cloud, and deploy them from one robot to another. If an operator were to inadvertently lose a program, rather than rewrite it from scratch, you can just drop the backup version from the cloud onto the system and be up and running again in minutes.

The TaskMate systems and FORGE controller are available for both purchase and rental.

“We provide a menu to our customers of how they might want to consume our products and services,” says Gibbs. “That may be all the way from a traditional CapEx (capital expenditure) purchase if they want to buy one of our TaskMates upfront, to the other end of the spectrum where they can rent the system with no contract for however long or short of a duration they want.”

For an additional charge, READY can manage the entire asset for the customer.

“We set it up, we program it, and we remotely monitor it to make sure it’s maximizing its uptime. We can come in and tweak the program if it’s running into unexpected errors. All of the systems are equipped with cell modems, so they can update the software over the air. We handle all of the maintenance or it’s handled by our channel partners.”

No-Term Rental
Gibbs says flexibility is the biggest advantage to their rental option. READY offers a 3-month trial rental. But customers are not required to keep it for that full term.

“We have a no-term rental. That’s even more appealing because it can come entirely out of your OpEx (operating expenditure) budget. Instead of going through a lengthy CapEx approval process, we’ve had some customers just run their corporate credit card, because the rental is below their approval level for an OpEx purchase. They can easily set up the system and use it for a few months. That alone provides them with a much stronger justification for moving forward with CapEx if they want, or just continue to expand their rental.

“At the end of the first month, if they decide that it’s not working out, just like any incompetent worker, they can fire it and send it back.”

If the customer chooses to continue renting, Gibbs says it’s more cost-effective to sign a contract. This reduces the risk for everyone, so there’s usually a financial incentive.

“The primary way we differentiate ourselves is that we offer that no-term rental with a fixed monthly fee, which allows these factories to capture the traditional value of automation. We don’t have a meter running that says you ran it 22 hours this day, so you owe us for 22 hours of work. We encourage them to run it as long as they want. The expectation is the longer you run it, the cheaper it should be.”

Flexibility for High-Mix, Low-Volume
READY’s target customers range from small job shops to large multinationals and Fortune 500 companies.

“Attwood is a great example of the type of high-mix, low-volume production environment where the flexibility of the TaskMate really shines,” says Gibbs.

Attwood Marine in Lowell, Michigan, is one of the world’s largest producers of boat parts, accessories and supplies. If it’s on your boat, there’s a good chance this century-old company made it. They make thousands of different parts, but cater to a relatively small marine market. The challenges of high-mix, low-volume production in a highly competitive market had them looking for an automation solution.

The flexibility of the TaskMate to quickly deploy and redeploy depending on Attwood’s short- or long-term needs was a deciding factor. With only a couple hundred employees and no dedicated robotics programmer on staff, the customer appreciates the FORGE software’s ease of use. Plus the ability to rent the system plays to the seasonal nature of Attwood’s business and lowers the cost of their first foray into robotic automation.

Attwood has deployed the TaskMate R10 to a half-dozen cells on the production floor performing CNC machine tending, pick-and-place tasks like palletizing, loading/unloading conveyors and case packing, and even repetitive testing. You need to actuate a switch or pull a cord 250,000 times? That’s a job for flexible automation.

By deploying one robot system to multiple production cells, Attwood was able to spread their ROI across multiple product lines and realize up to a 30 percent reduction in overall manufacturing costs. Watch the TaskMate on the job at Attwood Marine.

Small to midsized businesses aren’t the only ones benefiting. Large multinationals like tools manufacturer Stanley Black & Decker use the TaskMate R10 for machine tending CNC lathes.

“Multinationals may have robot programmers on staff, but usually not enough of them,” says Gibbs. “Automation engineers are in high demand and very difficult to come by. Any technology that makes it faster and easier for people to set up robots is a tremendous value. Even with large multinationals, some like to be asset-light and do a rental, but everyone loves the ease of programming we offer through FORGE.”

Forged in the Lab
READY’s portable plug-and-play solution is a technology spinoff from Professor Greg Hager’s research in human-machine collaborative systems at Johns Hopkins University. Gibbs, an alumnus, was working in the university’s technology ventures office helping researchers like Prof. Hager develop commercialization strategies for their new technologies. Hager, along with Gibbs, and fellow alum CTO Kelleher Guerin cofounded the startup in October 2015. Another cofounder, Drew Greenblatt, President of Marlin Steel Wire Products (an SME in the Know), offered up his nearby Baltimore, Maryland-based custom metal forms factory as a prototype test site for the TaskMate. The system was officially launched in July 2017.

Prof. Hager is now an advisor to the company. Distinguished robotics researcher, Henrik Christensen, is Chairman of the Board of Advisors. In December 2017, the startup secured $15 million in Series A funding led by Drive Capital.

READY maintains an office in Baltimore, while its headquarters is in Columbus, Ohio. They are a FANUC Authorized System Integrator. Gibbs says they are in the process of building a channel partner network of integrators and distributors to support future growth.

Pay As You Go
Business models under the RaaS umbrella vary widely, and are evolving. Startups like Hirebotics and Kindred leverage cloud robotics more intensely to monitor robot uptime, collect data, and enhance performance using AI. They charge by the hour, or even by the second. You pay for only what you use. Each service model has its advantages.

Some RaaS advocates offer subscription-based models. Some took a page from the sharing economy. Think Airbnb, Lyft, TaskRabbit, Poshmark. Share an abode, a car or clothes. Skip the overhead, the infrastructure and the long-term commitment. Pay as you go for a robot on the run.

Mobile Robots for Hire
Autonomous mobile robots (AMRs) are no strangers to the RaaS model, either. RIA members Aethon and Savioke lease their mobile robots for various applications in healthcare, hospitality and manufacturing. Startup inVia Robotics offers a subscription-based RaaS solution for its warehouse “Picker” robots.

Autonomous mobile robot navigates production floors to transport pallets and heavy loads via the most efficient route, while safely maneuvering around people and other obstacles. (Courtesy of Mobile Industrial Robots A/S) We first explored the emergence of AMRs in the Always-On Supply Chain. It’s startling how much the logistics robot market has changed in just a couple of years. Since then, prototypes and beta deployments have turned into full product lines with significant investor funding. Major users like DHL, Walmart and Kroger, not to mention early adopter Amazon, are doubling down on their mobile fleets.

After triple-digit revenue growth in Europe, Mobile Industrial Robots (MiR) was just breaking onto the North American scene two years ago. Now, as they celebrate comparable growth on this side of the pond, MiR prepares to launch a new lease program in January.

MiR is another prodigy of Denmark’s booming robotics cluster. They join Danish cousin Universal Robots on the list of Teradyne’s smart robotics acquisitions. Odense must have the Midas touch.

Go Big or Go Home
Responding to customer demands for larger payloads, MiR introduced its 500-kg mobile platform at Automatica in June. The MiR500 (pictured) comes with a pallet transport system that automatically lifts pallets off a rack and delivers them autonomously. Watch it in action on the production floor of this agricultural machine manufacturer.

“Everybody we deal with today is making a big push to eliminate forklift traffic from the inner aisleways of production lines,” says Ed Mullen, Vice President of Sales – Americas for MiR in Holbrook, New York. “That’s really driving the whole launch of the MiR500. We’ve gone through some epic growth here in my division.”

Mullen’s division is responsible for supporting MiR’s extensive distributor network in all markets between Canada and Brazil. Right now, the Americas account for about a third of the global business.

“We’re seeing applications in industrial automation, warehouses and distribution centers,” says Mullen. “Electronics, semiconductor and a lot of the tier automotive companies, like Faurecia, Visteon and Magna, have all invested in our platforms and are scaling the business. We see this being implemented across all industries, which is really adding to our excitement.”

Lease Options
Although Mullen says they’ve seen tremendous success with the current buy model, MiR is trying to make it even easier to work with this emerging technology. That drove them to the RaaS model.

“We think a leasing option will allow companies that are still trying to understand the use cases for the technology to get in quicker, and then slowly scale the business up as they learn how to apply it and what the sweet spots are for autonomous mobile robots. The lease option is intended to reduce the cost of entry. Today it’s mainly the bigger multinationals that are buying, but we believe by providing options for lower entry points, this will make the use cases in the small-to-midsized companies come to light.”

He says a third-party company will handle all the leases. MiR’s distributor network will engage with the third-party company to put together lease programs for customers.

MiR has also implemented a Preferred System Integrator (PSI) program to augment the existing network of distribution partners. Two and a half years ago, it was mainly large companies investing in these mobile platforms. They were purchasing in volumes of one to five robots. Today, they’re seeing investments of 20, 30, or even more than 50 robots.

“When you get into these bigger deployments, it’s more critical to have companies that are equipped to handle them. Our distribution partners are set up as a sales channel. Although most of them have integration capabilities, they don’t want to invest in deploying hundreds of robots at one time. They rather hand that off to a company that’s able to properly support large-scale deployments.”

Over the last couple of years, MiR had been focused on bringing more efficiency to the manufacturing process; not necessarily replacing existing AGVs and forklifts.

“For example, you have a guy that gets paid a healthy salary to sit in front of a machine tool and use his skills to do a certain task. That’s what makes the company money. But when he has to get up and carry a tray of parts to the next phase in the production cycle, that’s inefficient. That’s what we’ve been focusing on, at least with our MiR100 and MiR200 (pictured).”

Autonomous mobile robot efficiently transports finished product to the inspection area, freeing up employees for more high-value tasks at this custom plastic injection molder. (Courtesy of Mobile Industrial Robots A/S)

Technologies, an Indiana-based company specializing in custom plastic injection molding and mold tooling. The mobile robot loops the shop floor, autonomously transporting finished product from the presses to quality inspection. This frees up personnel for more high-value tasks and eliminates material flow bottlenecks.

“With the new MiR500, we’re going after heavier loads and palletizer loads. That’s replacing standard AGVs and forklifts. We’re also starting to see big conveyor companies like Simplimatic Automation and FlexLink move to a more flexible type of platform with autonomous mobile robots.

“Parallel to the hardware is our software. A key part of our company is the way we develop the software, the way we allow people to interface with the product. We’re continuously making it more intuitive and easier to use.”

MiR offers two software packages, the operating system that comes with the robot and the fleet management software that manages two or more robots. The latter is not a requirement, but Mullen says most companies are investing in it to get additional functionality when interfacing with their enterprise system. The newest fleet system is moving to a cloud-based option.

Hardware and software updates are all handled through MiR’s distribution channel and Mullen doesn’t think any of that will change under the lease option.

“The support model will stay the same. Our distributors are all trained on hardware updates, preventative maintenance and troubleshooting. I firmly believe the major component to our success today is our distribution model.”

Mullen says he’s looking forward to new products coming out in 2019. MiR is also hiring. They expect to double their employee count in the Americas and globally.

High-Tech, Short-Term Need
It’s many of these feisty startups that we’re seeing adopt nontraditional models like RaaS. But stalwarts are coming on board, too.

On-demand material handling robots come in all sizes, payloads and reaches for rental by the week. (Courtesy of RobotWorx) Established in 1992, RobotWorx is part of SCOTT Technology Ltd., a century-old New Zealand-based company specializing in automated production, robotics and process machinery. RobotWorx joined the SCOTT family of international companies in 2014 and recently completed a rigorous audit process to become an RIA Certified Robot Integrator.

RobotWorx buys, reconditions and sells used robots, along with maintaining an inventory of new robotic systems and offering full robot integration and training services. Rentals are nothing new to them. They’ve been renting robots for several years, before it was a trend. But in response to the upswing in industry requests of late, RobotWorx rolled out a major push on their rental program this past spring.

“We’ve done a lot with the TV and film industry,” says Tom Fischer, Operations Manager for RobotWorx in Marion, Ohio. “If you’ve seen the latest AT&T commercial, there are blue and orange robots in it. We rented those out for a week.”

Dubbed “Bruce” and “Linda” on strips of tape along their outstretched arms, these brightly colored robots have a starring role in this AT&T Business commercial promoting Edge-to-Edge Intelligence? solutions. Fischer says companies in this industry usually select a particular size of robot, typically either a long-reach or large-payload material handling robot, like the Yaskawa Motoman long-reach robots in this AT&T commercial.

Ever wonder if the robots in commercials are just there for effect? It turns out, not always. Fischer says these are fully functioning robots. AT&T’s ad agency must have a robot wrangler off camera to keep Bruce and Linda in line. However, the other robots in the background are the result of TV magic.

“We basically just sent them the robots,” says Fischer. “They did what they wanted to do with them and then sent them back.”

For quick gigs like this commercial, or maybe a movie cameo or even a tradeshow display, rental robots make sense. But how do you know when it’s better to rent or buy?

“We’ll do a cost analysis with the customer,” says Fischer. “We have an ROI calculator on our website if they want to see what their long-term commitment capital investment would be. (Check out RIA’s Robot ROI Calculator). We also look at it from the standpoint that if they have a long-term contract with somebody, their return on investment is going to be a lot better with a purchase. If they think they’re only going to use the robot for six months, it doesn’t make sense for them to buy it.”

Rent-A-Cell
RobotWorx rents robots by the week, month or year. A week is the minimum, but there’s no long-term commitment required. A rental includes a robot, the robot controller, teach pendant and end-of-arm tooling (EOAT). Robot brands available include ABB, FANUC, KUKA, Universal Robots, and Yaskawa Motoman.

They also rent entire ready-to-ship robot cells for welding or material handling. The most popular systems are the RWZero (pictured) and RW950 cells.

Self-contained, ready-to-ship robotic welding cell accelerates uptime whether you buy or rent it. (Courtesy of RobotWorx)

“The RWZero cell is very basic,” says Fischer. “You have a widget and you need 5,000 of them. Rent this cell and you have a production line instantly.”

The RW950 is more portable. Fisher calls it a “pallet platform.” The robot, controller, operator station and workpiece positioner all share a common base, which is basically a large steel structure that can be moved around with a forklift whenever needed. See the RW950 Welding Workcell in action.

“We’ve done a lot of the small weld cells,” he says. “We always have a couple on hand so we can supply those on demand. We’ve done larger material handling cells, as well.

“We have a third-party company that does the financing if you need it. A lot of people just end up paying it upfront. If they were to purchase the robot after they’ve rented it, we apply that towards the purchase as well.”

Fischer says 20 percent of the rental price is credited to the purchase if a customer decides to keep the robot. All the robots and robotic cells are up to date on maintenance before they leave the RobotWorx floor and shouldn’t require any major maintenance for at least a year. He says most customers end up buying the robot if their rental period exceeds a year.

Time is not always the deciding factor under the RaaS model. As robotic systems become easier to deploy and redeploy, the idea of robots as a service will gain more permanence as a long-term solution. In the future, robotics in our workplaces and homes will be as ubiquitous as the Internet. In the meantime, we’ll keep our eyes on RaaS as it gets ready for primetime

Source : https://www.robotics.org/content-detail.cfm/Industrial-Robotics-Industry-Insights/Robots-for-Rent-Why-RaaS-Works/content_id/7665

Ten Signs You’re Headed for Trouble in 2019 – ITL

December 12, 2018
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gartner-hype

Many of you have seen the Gartner Hype Cycle curve. When a hot technology appears, it gets hyped and hyped until one day enough people become impatient, and sentiment turns against the technology. It then heads into what Gartner calls the Trough of Disillusionment. Eventually, the technology finds its role – often a major one – in the market.

The idea has always struck me as rather obvious (I described the curve to reporter colleagues on the tech beat at the Wall Street Journal years before I ever saw the Gartner chart), but Gartner popularized the notion, which is why it’s known as the Gartner Hype Cycle rather than, say, the Carroll Hype Cycle. Gartner is to be commended, because technologies can be plotted on the curve, and, drawing on history, their futures can be predicted with some confidence.

On the Carroll…er, Gartner Hype Cycle, the idea of technology-driven innovation in insurance seems to be heading into the Trough of Disillusionment (great name) among incumbents. A Lemonade or Trov hasn’t taken over the world. Big Tech is coming to insurance but not really here yet for most insurers. Industry executives seem to have read everything they care to about AI, blockchain, etc., and are starting to describe plans for small-bore improvements rather than truly innovative ones. Not total disillusionment, but headed in that direction.

Which brings me to the warning signs for 2019.

The slide into the Trough of Disillusionment creates real opportunities because prices of insurtechs will start to settle back toward reality. In any case, technologies keep maturing, no matter how we feel about them, so the day of reckoning in the market creeps closer all the time, and the slide toward disillusionment is the last opportunity for companies to position themselves before a host of technologies and startups will shake the insurance market.

If I’m right, 2019 may well be the last chance for insurance industry incumbents to start taking advantage of the opportunities presented by insurtech, or lose out to nimbler competitors. In that spirit, my colleagues and I at ITL pulled some thoughts together for incumbents on:

10 Signs You’re Headed for Trouble in 2019

You set up an innovation fund and think that means you’re innovative.
Your innovations focus on cutting expenses, to the exclusion of all else, and – worse – you reward executives based on those cuts.
You say your legacy IT systems are what is preventing you from innovating.
You say your defensive culture is preventing you from innovating.
You practice “innovation tourism,” going to Silicon Valley and assuming magic dust will wear off on you. (Related warning sign: You have a ping pong table and coffee bar and think they signify creativity.)
You have 6,000 ideas but can’t figure out how to turn one into a product.
You can’t name 20 insurtechs that operate in your strategic domain or adjacent ones.
You aren’t starting to move your operations into the cloud.
You don’t have significant diversity in your management team and board, in terms of gender, race, age and nationality.
You can’t quantify and measure how you’re doing on your innovation journey and hope you’re improving.

Bonus warning sign: You make television commercials criticizing innovative companies.

In “The Sun Also Rises,” a character is asked how he went bankrupt. “Two ways,” he says, “gradually, then suddenly.” We’re still in the “gradually” part of innovation driven by insurtech, but “suddenly” is coming. I suggest insurance industry incumbents view 2019 and warning signs like these as a last warning to get moving and avoid innovation bankruptcy.

Source : http://blog.insurancethoughtleadership.com/blog/ten-signs-youre-headed-for-trouble-in-2019

Data-driven transformation of the life sciences industry – RockHealth

December 11, 2018
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Digital health innovation continues moving full-force in transforming the business of healthcare. For pharma and medtech companies in particular, this ongoing shift has pushed them to identify ways to create value for patients beyond the drugs themselves. From new partnerships between digital health and life science companies to revamped commercial models, collecting and extracting insights from data is at the core of these growth opportunities. But navigating the rapidly evolving terrain is no simple task.

To help these companies effectively incorporate and utilize digital health tools, Rock Health partner ZS Associates draws on over 30 years of industry expertise to guide them through the complex digital health landscape. We chatted with Principal Pete Masloski to discuss how he works with clients to help identify, develop, and commercialize digital health solutions within their core businesses—and where he sees patients benefiting the most as a result.

Note: This interview has been lightly edited for clarity.

Where does ZS see the promise of data- and analytics-enabled digital health tools leading to in the next five years, 10 years, and beyond?

Data and analytics will play a central role in the digital health industry’s growth over the next five to ten years. Startups are able to capture larger, novel sets of data in a way that large life science companies historically have not been able to. As a result, consumers will be better informed about their health choices; physicians will have more visibility into what treatment options work best for whom under what circumstances; health plans will have a better understanding of treatment choices; and pharmaceutical and medical device companies will be able to strategically determine which products and services to build.

We see personalized medicine, driven by genomics and targeted therapies, rapidly expanding over the next few years. Pharmaceutical discovery and development will also transition to become more digitally enabled. The ability to match patients with clinical trials and improve the patient experience will result in lower costs, faster completion, and more targeted therapies. The increase in real-world evidence will be used to demonstrate the efficacy of therapeutics and devices in different populations, which assures payers and providers that outcomes from studies can be replicated in the real world.

How is digital health helping life sciences companies innovate their commercial models? What is the role of data and analytics in these new models?

The pharmaceutical industry continues to face a number of challenges, including the increasingly competitive markets, growing biosimilar competition, and overall scrutiny on pricing. We’ve seen excitement around solutions that integrate drugs with meaningful outcomes and solutions that address gaps in care delivery and promote medication adherence.

Solving these problems creates new business model opportunities for the industry through fresh revenue sources and ways of structuring agreements with customers. For example, risk-based contracts with health plans, employers, or integrated delivery networks (IDNs) become more feasible when you can demonstrate increased likelihood of better outcomes for more patients. We see this coming to fruition when pharma companies integrate comprehensive digital adherence solutions focused on patient behavior change around a specific drug, as in Healthprize’s partnership with Boehringer Ingelheim. In medtech, digital health tools can both differentiate core products and create new profitable software or services businesses. Integrating data collection technology and connectivity into devices and adding software-enabled services can support a move from traditional equipment sales to pay-per-use. This allows customers to access the new equipment technology without paying a large sum up front—and ensures manufacturers will have a more predictable ongoing source of revenue.

That said, data and analytics remain at the core of these new models. In some cases, such as remote monitoring, the data itself is the heart of the solution; in others, the data collected helps establish effectiveness and value as a baseline for measuring impact. Digital ambulatory blood pressure monitors capture an individual’s complete blood pressure profile throughout the day, which provides a previously unavailable and reliable “baseline.” Because in-office only readings may be skewed by “white coat hypertension,” or stress-induced blood pressure readings, having a more comprehensive look at this data can lead to deeper understandings of user behaviors or conditions. Continuous blood pressure readings can help with diagnoses of stress-related drivers of blood pressure spikes, for example. These insights become the catalyst for life science companies’ new product offerings and go-to-market strategies.

What are some examples of how data sets gathered from partnerships with digital health companies can be leveraged to uncover new value for patients and address their unmet needs?

As digital health companies achieve a certain degree of scale, their expansive data sets become more valuable because of the insights that can be harnessed to improve outcomes and business decisions. Companies like 23andMe, for example, have focused on leveraging their data for research into targeted therapies. Flatiron Health is another great example of a startup that created a foundational platform (EMR) whose clinical data from diverse sources (e.g., laboratories, research repositories, and payer networks) became so highly valued in cancer therapy development that Roche acquired it earlier this year for close to $2B.

It’s exciting to think about the wide array of digital health solutions and the actionable insight that can be gleaned from them. One reason partnerships are important for the industry is few innovators who are collecting data have the capabilities and resources to fully capitalize on its use on their own. Pharma companies and startups must work together to achieve all of this at scale. Earlier this year, Fitbit announced a new partnership with Google to make the data collected from its devices available to doctors. Google’s API can directly link heart rate and fitness activity to the EMR, allowing doctors to easily review and analyze larger amounts of data. This increase in visibility provides physicians with more insight into how patients are doing in between visits, and therefore can also help with decision pathways.

Another example announced earlier this year is a partnership between Evidation Health and Tidepool, who are conducting a new research study, called the T1D Sleep Pilot, to study real-world data from Type 1 diabetics. With Evidation’s data platform and Tidepool’s device-agnostic consumer software, the goal is to better understand the dynamics of sleep and diabetes by studying data from glucose monitors, insulin pumps, and sleep and activity trackers. The data collected from sleep and activity trackers in particular allows us to better understand possible correlations between specific chronic conditions, like diabetes, and the impact of sleep—which in the past has been challenging to monitor. These additional insights provide a more comprehensive understanding of a patient’s condition and can lead to changes in treatment decisions—and ultimately, better outcomes.

How do you assess the quality and reliability of the data generated by digital health companies? What standards are you measuring them against?

Data quality management (DQM) is the way in which leading companies evaluate the quality and reliability of data sources. ISO 9000’s definition of quality is “the degree to which a set of inherent characteristics fulfills requirements.” At ZS, we have a very robust DQM methodology, and our definition goes beyond the basics to include both the accuracy and the value of the data. Factors such as accuracy and absence of errors, and fulfilling specifications (business rules, designs, etc.), are foundational, but in our experience it’s most important to also include an assessment of value, completeness, and lack of bias because often these factors can lead to misleading or inaccurate insights from analysis of that data.

However, it’s not easy assessing the value of a new data source, which presents an entirely different set of challenges. One very important one is the actual interpretation of the data that’s being collected. How do you know when someone is shaking their phone or Fitbit to inflate their steps, or how do you interpret that the device has been taken off and it’s not tracking activity? How do you account for that and go beyond the data to understand what is really happening? As we get more experience with IOT devices and algorithms get smarter, we will get better at interpreting what these devices are collecting and be more forgiving of underlying data quality.

What are the ethical implications or issues (such as data ownership, privacy, and bias) you’ve encountered thus far, or anticipate encountering in the near future?

The ethical stewardship and protection of personal health data are just as essential for the long-term sustainability of the digital health industry as the data itself. The key question is, how can the industry realize the full value from this data without crossing the line? Protecting personal data in an increasingly digitized world—where we’ve largely become apathetic to the ubiquitous “terms and conditions” agreements—is a non-negotiable. How digital health and life science companies collect, manage, and protect users’ information will remain a big concern.

There are also ethical issues around what the data that is captured is used for. Companies need to carefully establish how to appropriately leverage the data without crossing the line. For example, using de-identified data for research purposes with the goal of improving products or services is aligned with creating a better experience for the patient, as opposed to leveraging the data for targeted marketing purposes.

Companies also face the issue of potential biases that may emerge when introducing AI and machine learning into decision-making processes around treatment or access to care. Statistical models are only as good as the data that are used to train them. Companies introducing these models need to test datasets and their AI model outputs to ensure gaps are eliminated from training data, the algorithms don’t learn to introduce bias, and they establish a process for evaluating bias as the models continue to learn and evolve.

Source : https://rockhealth.com/the-data-driven-transformation-of-the-life-sciences-industry-a-qa-with-zs-associates-pete-masloski/

When, which … Design Thinking, Lean, Design Sprint, Agile? – Geert Claes

December 3, 2018
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Confusion galore!

A lot of people are — understandably so — very confused when it comes to innovation methodologies, frameworks, and techniques. Questions like: “When should we use Design Thinking?”, “What is the purpose of a Design Sprint?”, “Is Lean Startup just for startups?”, “Where does Agile fit in?”, “What happens after the <some methodology> phase?” are all very common questions.

(How) does it all connect?

When browsing the Internet for answers, one notices quickly that others too are struggling to understand how it all works together.

Gartner (as well as numerous others) tried to visualise how methodologies like Design Thinking, Lean, Design Sprint and Agile flow nicely from one to the next. Most of these visualisations have a number of nicely coloured and connected circles, but for me they seem to miss the mark. The place where one methodology flows into the next is very debatable, because there are too many similar techniques and there is just too much overlap.

The innovation spectrum

It probably makes more sense to just look at Design Thinking, Lean, Design Sprint & Agile as a bunch of tools and techniques in one’s toolbox, rather than argue for one over the other, because they can all add value somewhere on the innovation spectrum.

Innovation initiatives can range from exploring an abstract problem space, to experimenting with a number of solutions, before continuously improving a very concrete solution in a specific market space.

Business model

An aspect which often seems to be omitted, is the business model maturity axis. For established products as well as adjacent ones (think McKinsey’s Horizon 1 and 2), the business models are often very well understood. For startups and disruptive innovations within an established business however, the business model will need to be validated through experiments.

Methodologies

Design Thinking

Design Thinking really shines when we need to better understand the problem space and identify the early adopters. There are various flavors of design thinking, but they all sort of follow the double-diamond flow. Simplistically the first diamond starts by diverging and gathering lots of insights through talking to our target stakeholders, followed by converging through clustering these insights and identifying key pain-points, problems or jobs to be done. The second diamond starts by a diverging exercise to ideate a large number of potential solutions before prototyping and testing the most promising ideas. Design Thinking is mainly focussed on qualitative rather than quantitative insights.

Lean Startup

The slight difference with Design Thinking is that the entrepreneur (or intrapreneur) often already has a good understanding of the problem space. Lean considers everything to be a hypothesis or assumption until validated …so even that good understanding of the problem space is just an assumption. Lean tends to starts by specifying your assumptions on a customer focussed (lean) canvas and then prioritizing and validating the assumptions according to highest risk for the entire product. The process to validate assumptions is creating an experiment (build), testing it (measure) and learn whether our assumption or hypothesis still stands. Lean uses qualitative insights early on but later forces you to define actionable quantitative data to measure how effective the solution addresses the problem and whether the growth strategy is on track. The “Get out of the building” phrase is often associated with Lean Startup, but the same principle of reaching out the customers obviously also counts for Design Thinking (… and Design Sprint … and Agile).

Design Sprint

It appears that the Google Venture-style Design Sprint method could have its roots from a technique described in the Lean UX book. The key strength of a Design Sprint is to share insights, ideate, prototype and test a concept all in a 5-day sprint. Given the short timeframe, Design Sprints only focus on part of the solution, but it’s an excellent way to learn really quickly if you are on the right track or not.

Agile

Just like dealing with the uncertainty of our problem, solution and market assumptions, agile development is a great way to cope with uncertainty in product development. No need to specify every detail of a product up-front, because here too there are plenty of assumptions and uncertainty. Agile is a great way to build-measure-learn and validate assumptions whilst creating a Minimum Viable Product in Lean Startup parlance. We should define and prioritize a backlog of value to be delivered and work in short sprints, delivering and testing the value as part of each sprint.

Conclusion

Probably not really the answer you were looking for, but there is no clear rule on when to start where. There is also no obvious handover point because there is just too much overlap, and this significant overlap could be the explanation of why some people claim methodology <x> is better than <y>.

Anyhow, most innovation methodologies can add great value and it’s really up to the team to decide where to start and when to apply which methods and techniques. The common ground most can agree with, is to avoid falling in love with your own solution and listen to qualitative as well as quantitative customer feedback.

Some great books: Creative Confidence, Lean Startup, Running Lean, Sprint, Dual Transformation, Lean UX, Lean Enterprise, Scaling Lean … and a nice video on Innovation@50x

Update: minor update in the innovation canvas, moving the top axis of problem-solution-market to the side

Source : https://medium.com/@geertwlclaes/when-which-design-thinking-lean-design-sprint-agile-a4614fa778b9

What Do Investors Need to Know About the Future of LED Grow Light Technology – Agfund

November 30, 2018
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The horticultural lighting market is growing, and growing rapidly. According to a September press release from Report Linker, a market research firm specializing in agribusiness, the horticultural lighting market is estimated grow from a $2.43 billion market this year to $6.21 billion in 2023.

One of the key factors driving current market sector growth is increased development of LED grow light technology. LEDs (light emitting diodes) were first developed in the 1950s as a smaller and longer-lasting source of light compared to the traditional incandescent light bulb invented by Thomas Edison in 1879.

LEDs last longer, give off less heat, and are more efficient converting energy to light compared to other types of lights, all features that can result in higher yields and profits for indoor growers.

But until recently, LEDs were only used to grow plants indoors experimentally, largely because the cost was still too high for commercial businesses. Many commercial growers still use HID (High Intensity Discharge) lights such as High Pressure Sodium, Metal Halide, and Ceramic Metal Halide; all lights that have a high power output but are less durable than LED lights, generate far more heat, and have less customizable light spectra.

Today, LEDs are fast becoming the dominant horticultural lighting solution. This is due primarily to the one-million fold decrease in fabrication cost of semiconductor chips used to make LED lights since 1954.

For investors more familiar with field-based agriculture, it can certainly be a minefield to know where LED lighting technology for horticulture is going in the future. Although it is no longer the “early days” of LED technology development, current trends are still shaping the future of LED technology.

So what does the intelligent agtech investor need to know about the current state and future of LED grow light technology?

I interviewed Jeff Mastin, director of R&D at Total Grow LED Lighting, to discuss what the future of LED grow light technology for agriculture looks like, and how investors can use current trends to their advantage in the future.

What is your background – how did you get involved in grow light technology at Total Grow?

The company behind TotalGrow is called Venntis Technologies. Venntis has, and still does, specialize in integrating touch-sensing semiconductor technologies into applications.

Most people don’t realize LEDs are semiconductors; you can also use them for touch-sensing technologies, so there’s a strong bridge to agricultural LED technology.

Some of the biggest technical challenges in utilizing LEDs effectively for agriculture include LED glaring, shadowing and color separation.

We have used our expertise in touch-sensing LEDs to expand into horticultural LEDs, and we have developed technology that addresses the above challenges better, giving better control over the spectrum that the LED makes and the directional output of the light in a way that a standard LED by itself can’t do.

My personal background is in biology. When TotalGrow started exploring the horticultural world, that’s where being a biologist was a natural fit to take a lead on the science and the research side of the development process for the product; that was about 7 years ago now.

If you were going to distill your technical focus into trends that you’re seeing in the horticultural lighting space, what are the main trends to keep an eye on?

The horticultural lighting industry is really becoming revolutionized because of LEDs. Less than 10 years ago, LEDs in the horticultural world were mainly a research tool and a novelty.

In the past, they were not efficient enough and they were definitely not affordable enough yet to really consider them an economical general commercial light source.

But that is very quickly changing. The efficiencies are going up and prices down and they are really right now hitting the tipping point where for a lot of applications, but definitely not all applications, the LED world is starting to take over horticulture and indoor agriculture.

How do you view the translation of those trends into actionable points? For investors or technology developers in the agriculture technology space, how do they make sure that the LED light technology they are investing in isn’t going to be obsolete in a year or two?

With LEDs, the key question is still cost-efficiency, and there’s only so far the technology can improve.

Why? There are physical limitations. You can’t make a 100% efficient product that turns every bit of electricity into photons of light. At this point, the efficiency level of the top of line LEDs are up over 50%.

Can we ever get up to 70 or 80%? Probably not any time soon with an end-product, not one that’s going to be affordable and economical generally speaking.

So to answer your question, it’s not a category where you’re going to say, “well this is obsolete, I can get something three times better now.” The performance improvements will be more marginal in the future.

Ten years from now the cost will be cheaper. But that again doesn’t make current LED technologies obsolete. In terms of that fear, I don’t think people have to worry about current LED light technologies becoming obsolete.

In a large commercial vertical farming set up, what is the ballpark cost of horticultural LEDs currently?

To give just an order of magnitude sort of number, you’re probably going to be someplace in the $30 per square foot number for lights for a large facility. It can be half that or it can be double that.

That’s just talking within the realm of common vertical farming plants like greens and herbs, or other plants similar in size and lighting needs.

If you start talking about tomatoes or medicinal plants, then the ability to use higher light levels and have the plants make good use of it skyrockets. You can go four times higher with some of those other plants, and for good reason.

**What type of horticultural lighting applications are LEDs still not the best solution for now and in the foreseeable future?**

There are at least 3 areas where LEDs still may not make sense now and in the near future.

First, if the LED lights are not used often enough. The more hours per year the lights are used, the more quickly they return on their investment from power savings and reduced maintenance. Some applications only need a few weeks of lighting per year, which makes a cheaper solution appropriate.

Second, in some greenhouse applications, LED’s may not be the best choice for some time to come. Cheaper lights like high-pressure sodium have more of a role in greenhouses where hours of use are less and higher hang heights are possible. (Many greenhouses will still benefit strongly from LEDs, but the economics and other considerations make it important to consider both options in greenhouses.)

Lastly, some plants are not the best in vertical farming styles of growing where LEDs have their most drastic advantages. At least at this point it is not common to attempt to grow larger fruiting plants like tomatoes or cucumbers totally indoors, though when attempted that is still more practical with LEDs than legacy lights.

Source : https://agfundernews.com/what-do-investors-need-to-know-about-the-future-of-led-grow-light-technology.html/

Category: Trends