Innovation

Why Engineers Love the Smart City Works Actuator

So now it’s real! A fantastic Ribbon-cutting and Meet the Cohort event last Friday the 14th for the new Smart City Works Actuator at CIT, next door to our enormo2017-04-14 - SCW - 39 - DSC_9505usly successful and now four-year old cybersecurity accelerator, MACH37 (who also graciously hosted the event). The Governor came to get the 100 or so guests pumped up and glad to be Virginians. Thomas Smith, the Executive Director of the American Society of Civil Engineers spoke about our failing infrastructure and how the Smart City Actuator could play a role 2017-04-14 - SCW - 37 - DSC_9387in helping renew it. There actually was a ribbon, and the Governor was decisive in cutting it (look at the lever arms on those scissors!). And, in addition to civil engineers, we had electrical, mechanical, 2017-04-14 - SCW - 03 - DSC_9517transportation, and an aerospace engineer, computer scientists and data scientists, a materials scientist or two (graphene of course), and probably more. So why do all sorts of engineers love the Smart City Works Actuator? We can turn to the Laws of Physics for answers. Two laws that every engineer learns apply here:

F=ma, where a of course is acceleration,

and the formula for Kinetic energy (energy in action)

Kε=½m(v)**2

Now for our purposes we will let m represent the size of the mentor network, and v represent the volume of innovative companies the accelerator capacity can handle. By starting the Smart City Works Actuator, a has now become 2a, m has become 2m, and v is of course 2v. Substituting in our equations, and letting F represent the amount of fun we are having, any engineer can tell you the results:

2a*2m = 4F …four times the fun!

and

½[2m](2v)**2= 4Kε …four times the energy!!

Yes, its true. Engineers love the Smart City Works Actuator because, together with our MACH37 Accelerator, they can come and have four times the fun and experience four times the energy, all while helping build a better world. Q.E.D.

Of course the way we help Actuate a better world is by helping accelerate our innovative entrepreneurs, and the Smart City Works Actuator has some great ones!

IHT.   You no longer need to be a scientist to know whether your water is 2017-04-14 - SCW - 20 - DSC_9590safe. Using a patented new technology, Integrated Health Technologies’ Sensor BottleTM detects and relays water quality information to your phone to provide you with real-time peace-of-mind that the water you consume is safe to drink.  For cities, these bottles provide a crowd-sourced platform for real-time water quality detection and monitoring of municipal water systems.

UNOMICEDGE.  UNOMICEDGE is a Software Defined Network solution for securely 2017-04-14 - SCW - 51 - DSC_9580connecting the Cloud to devices at Network Edge.  It includes a network Hypervisor that not only enforces network security policies, but develops critical business and operational insights from user and device interactions. Smart cities rely on smart IoT devices at the Network Edge.  UnomicEdge not only reduces the cyber risk of IoT, but can provide valuable intelligence to make businesses and cities run smarter.

InfraccessInfraccess is powering up infrastructure investment by pr2017-04-14 - SCW - 24 - DSC_9570oviding easier access to trusted data so you can more efficiently discover investment opportunities, make quicker, better informed investments, and reduce overall investment risk. The Infraccess web-based workflow platform sources and transforms unstructured information into smart data and proprietary performance indicators to help unlock billions in investment opportunities in infrastructure.

Capital Construction Solutions.  Capital Construction Solutions creates mobile-based 2017-04-14 - SCW - 30 - DSC_9533risk management platforms for improving enterprise-wide accountability and transparency.  With Capital Construction Solutions deployed in the field, companies can immediately turn day-to-day operations into opportunities to reduce corporate liability, mitigate risk, and significantly increase profits.

 

 

PLANITIMPACT.   Design decisions can have significant and long-lasting2017-04-14 - SCW - 27 - DSC_9545 impact on business and environmental costs.  PlanITimpact has created a smart modeling platform to help building professionals better understand and improve performance, including energy, water use, stormwater and transportation, so owners, investors, and communities can better visualize project impacts and returns on investment.

GREATER PLACES.  Cities worldwide are investing in the next generation of buildings, infrastructure, transportation, and technology. But where can you turn to for readily finding the b2017-04-14 - SCW - 28 - DSC_9542est leading-edge solutions in this space?   GreaterPlaces creates a single web-based and mobile platform for bringing together the best ideas, inspirations, and practices for designing and governing cities—a marketplace and tools to connect people seeking ideas, products and services to transform cities worldwide.

Come join them and see what you’re missing!

 

All photos courtesy of Dan Woolley

 

How Do We Know the Actuator is Working? Part 3 – Corporate/University Programs

Follow us @CITOrg or @dihrie or this blog for current information on the new Smart City Actuator.

Parts 1 and 2 of this series looked at methods for measuring the success of commercial and government programs for accelerating innovation. The other major sources of innovation in the U.S. economy are Corporate R&D efforts and University programs. How effective are these sources for driving innovation? It is hard to generalize, given the very large number of both Corporate efforts and University programs and the paucity of data, although the anecdotal data is mixed to negative.

It does seem as though our model of funding leverage and transition probabilities could be adapted to measure success here as well. For this analysis however, alternate data sources provide some quantitative clues that support the anecdotal data. On the Corporate side there are certainly large company innovation success stories. Apple for example has certainly had success with their early mass market personal computer, photo_mac84pand more recently with their mobile devices (iPhone, iPad). One of the more amazing companies in this regard has to be General Electric who, over the last 50 years (based on where their profits originate), has gone from a heavy equipment manufacturer to a financial services company to the current big data company that also happens to be one of the world’s leading manufacturers…and always as a market leader.

But the anecdotal and other data tell a different story. Many accelerator organizations around the country conduct essentially consulting engagements with large Corporations to help them engage tFailureshe innovation ecosystem. Data show that 86% of the original 1955 Fortune 500 companies no longer exist, and that 50% of the Fortune 500 in the year 2000 have also failed. The average life expectancy of all companies is only 12.5 years, and the failure rate seems to be increasing. According to Forbes, the reason “Why U.S. Firms Are Dying: Failure to Innovate

One solution might be for Corporations to invest more in R&D. Alas. <re/code> reports on a clever study from Bernstein Research analyst Toni Sacconaghi that looked at “historical R&D spending figures as a percentage of sales for publicly traded tech companies with market caps of $2 billion”Large Cap Stocks, then tracked their stock performance 5 years later when presumably the research might have paid off. The chart summarizes his data, and concludes that there is “no meaningful relationship between R&D spending and stock performance”. I had a hard time deciphering the chart, so decided to put it in a more graphical form, and insert a few trend lines. The results were actually worse than SaccoCorporate Optimum R&amp;Dnaghi was willing to conclude. Not only is the regression line negative…the more you spend the worse your results…the standard deviation decreases with spending, meaning that the likelihood of a poor result is much higher the more you spend. Looking at this chart as a non-financial person, it is not clear to me why anybody would invest in companies spending more than 20% of sales on R&D. As a side note, something really interesting seems to be happening around a magical number of 7-8% R&D spending, but I haven’t a clue what that might be…ideas welcome!

How about Universities? Many of them have Tech Transfer offices for their research-derived intellectual property (IP), and again there are certainly success stories in MIT/Harvard, Carnegie-Mellon, Stanford and others. Anecdotally however these offices, many based on a traditional licensing model, have overall not been incredibly successful. Two reasons are often given: first, IP transfers much more effectively via people than via paper so licensing models without researcher support are not effective; and, second, some Tech Transfer offices like to value the IP on the basis of research dollars spent, not on market value. As one of my colleagues put it “when I have these discussions the Tech Transfer Office will often tell me the value of the IP is $10M or something; I tell them it’s worth zero unless somebody takes it to market, and we negotiate from there.” Fortunately some of the more forward-looking Universities are starting to migrate towards a shared risk/reward model where the value of IP is set by marketplace outcomes.

Is there an explanation for this phenomenon? One possible answer lies in where the funding for research comes from, and where it goes. Again an obscure chart, this one from NSF.Funding sources After staring at this one for a while what I really wanted to know was net funding flows. For example in Basic Research the Federal Government funds about 60% and only conducts about 10%…where does the other 50% go? Mostly to Universities, which fund 10% and use more than 50% of the Basic Research dollars. OK, easy enough to turn into a graph, where the nodes are the sources, scaled to size by percentage Research fundingof funds sourced, and the graph edges are the net flows, also scaled to size. By applying some awesome powerpoint skills and a garish color scheme, the Basic Research picture looks like this. Half of all research dollars go from the Federal Government to University-based research, with a small additional amount funded by Industry, totaling about 2/3 of all research performed.

Now applying the same analysis to the Development portions of the NSF chart yields the following.Development funding Here, almost ninety percent of all Product Development activity is funded and performed by Industry, with some support from the Federal Government, while Universities are almost invisible. No wonder there is a bit of a disconnect; Universities apparently are not at all focused on commercializing their research, if the funding numbers are to be believed. One last chart provides the summary. Looking at the per capita number of startups based on University-developed IP the numbers have been dropping for a while. More to the point, the numbers are low. For Virginia, for example, these numbers equate to about 20 startups per year. Our cybersecurity accelerator, MACH37, evaluates more than 100 companper capita unievrsity startupsies per year to select a dozen participants just in the area of cybersecurity. Numbers are similar for most venture investors, with only single digit percentages of the number of deals reviewed actually resulting in investment. Thus for Virginia this may equate to one or two investable companies per year, based on University-generated IP. To be fair, this probably underestimates the amount of entrepreneurial activity generated by University programs and proximity, but is probably reasonably accurate in terms of the Institutional success, based at least on the anecdotal evidence.

It is clear now, having looked at innovation and technology transfer across commercial accelerators, the Federal Government, Corporations and Universities that successful innovation is one of those “wicked problems.” While there are successes across each of these domains, there are no magic bullets, no guaranteed approaches for innovation. So, how do we know our Smart City Actuator is working? And, are there ways to make this entire national research enterprise more efficient? We will explore those questions in Part 4 of this series.

Next (Thursday 3/23): How do we know the Actuator is Working? Part 4 – Synthesis and Policy

CTO SmackChat: Technology is not Innovation

First posted 01/08/14 on MACH37.com

In his excellent book “The Idea Factory: Bell Labs and the Great Age of American Innovation”, Jon Gertner quotes Jack Morton, who worked at the Labs on the development of the transistor in the 1940s, saying “[Innovation] is not just the discovery of new phenomena, nor the development of a new product or manufacturing technique, nor the creation of a new market”, but all of these working together to deliver things that make a difference. Or, as one of our investors puts it succinctly: “a business without customers is just a hobby”.

As technologists, we of the nerdly persuasion tend to believe that the tech is the key ingredient in the success of any startup. At MACH37 we talk to a lot of incredibly smart technical people, some with potentially game-changing ideas…but, technology is not innovation. For a startup to deliver products that make a difference it takes a great technical idea, but also someone who knows how to build a business, someone who knows how to turn an idea into a product, and people who can find customers, understand their problems and sell them your idea. Innovation is a team sport.

So, how important is the tech? As we evaluate startups and talk to investors, a large majority consider it essential to have someone with deep technical domain expertise, as well as product development skills, as part of the initial entrepreneurial team. Many of those same people will tell you however that the initial technology contributes maybe only 10% or 20% to the success of the business, that the ability to pivot is critical, that technology almost never creates new market segments. My own rule of thumb is that your going-in idea is always wrong.

Making sense of the contradictions can be maddening…being passionate about your ideas but willing to turn on a dime; knowing what is necessary but not sufficient; being game-changing in a way that’s not too ground-breaking. This is the first of a series of posts to explore these contradictions from the technologist’s point of view. How many features make a product? When do you abandon Rev 1 and start over? When does one product become two? How do you know what customers really want? How far ahead of the market or the product can you be? And once you delegate the product design, and customer interaction and hands-on coding, how do you continue to add value to your organization?

David Ihrie is CTO of MACH37 and has been the lead technical person for six startup companies. He has a BS in EE/CS and an MS in Management specializing in the Management of Technological Innovation, both from MIT.