Analysis of Green Markets
We’ve recently started paying attention to the OpenCalais (OC) project by Thomson Reuters. Basically, Sean has a penchant for anything that has “open” in its name…
The project describes itself this way:
Calais is a rapidly growing toolkit of capabilities that allow you to readily incorporate state-of-the-art semantic functionality within your blog, content management system, website or application.
Huh? Translated into human, that means: OC takes information published on the web, identifies people, facts & events, then outputs data that geeks can use. This all happens automatically. With OC output, geeks like us can take it even further to figure out who knows whom, and how. Or, in this case, who acquires whom, who invests in whom and other transactions in the “green energy” markets.
The OC website has a nice “Showcase” function that allows people who have utilized the OC API to post their projects. One of the projects, Who’s Who in the Financial News has developed a listing (spreadsheet) of “Private Equity, Green Energy, Acquisitions and Alternative Investments.” So we grabbed that data and uploaded it to Jute.
The results are very interesting. Part of the intention of this blog post is to find people in the field who can help us interpret the results. If you’re interested, email me and he’ll give you access to the Jute Network Document I used to create this.
So here are the results, and few questions that came up in working with this network. I haven’t bothered to make this a formal report. We’re just feeling it out…
Can we start to extrapolate trends based on a network of relationships? For example, could we identify the next strategic partnership that will be formed based on the existing 2nd and 3rd degree relationships?
Does network proximity indicate corporate strategy? That is to say, does a network that is distant from another network do so intentionally?
What would it take to make this a comprehensive data set? (This is clearly only part of the story…)
What would an investor do with this information?
Getting started: a key for the color-coding of the visualizations
For these visualizations, companies have been "tagged" and color-coded as shown in this index
OIL
companies and tags related to"oil"
"2nd degree" of connections to "oil"
Interesting connections
Why are "oil recovery" and "cement plants" in close proximity to each other?
If you Google “rti international + oil recovery + cement plants” you’ll find that cement can be used to capture CO2 and that the DOE has announced $1.4 billion in projects to capture and store carbon. One company in particular, RTI International has announced major changes in its management team, including a new SVP for “Integrated Value Chain.” (a.k.a. They are building a new network.)
More visualizations of oil networks
"networks within networks" highlighted within the 2nd degree network of oil
VantagePoint Venture Partners is highly connected within the "oil" network
When you start paying attention to the highly connected members of a network, and go learn some more about them at their website, you can see that VantagePoint Venture Partners highlights that:
We were the first large venture capital firm to recognize the opportunity here and have since committed $1 billion for this burgeoning opportunity.
More analysis shows their priorities and their co-investment partners.
a look at VantagePoint Venture Partners' 1st degree network
VantagePoint Venture Partners co-investment network
Whole Network Analysis
A different way to view the data set is to pare it down to only analyze relationships between companies that are “investments” and then identify the best-connected members of the network. You can apply the same analysis to all the relationship types, which is what is documented below.
(Note: use the key at the top of this page to see the color-coding in these visualizations.)
Investments
"Whole network" analysis of "green" investments
M&A
Mergers & Acquisitions within the "green" business world
Collaborations
Collaborations in the "green" business world
Organizations who are drivers in Collaboration
Red circles represent "high traffic nodes" and brown halos represent "power nodes"
Joint Ventures
Notice that most joint ventures--as they appear in this incomplete data set--are among just two partners
Subsidiaries
Alliances
Alliances seem to involve more organizations and to bring in more diverse networks
Looking at the Big Picture
Investments among all relationship types
Investments are dark lines
The dense cluster in the middle gravitates around oil investments
Best-connected member
I ran an analysis of each of the major relationship types and continued to pare the results down by increasing the scale on the “whole network” analysis, which requires that the organization be more connected.
While the visual results are almost irrelevant (they display only one or two results) the list is interesting:
Alliance: GWS Technologies & Praxair, Inc.
Collaboration: OTCBB MNGA, PGE & SSTP Europe
Investments:
Joint Ventures: GWS Technologies
M&A: Cleantech Invest AG
Subsidiary: HSBC Alternative Fund Services & Arotech Corporation
While there is no universal correlation between a position in a network and upcoming activity, I would hypothesize that the organizations that show up on the list above are worth watching if you’re in a related field.
Topic-Specific Visualizations
Wind tree
Solar 3-degree Network
Oil
Natural Gas
Ethanol tree
Electric Car Network
Funding Network
Gallery
We’re offering up all of the visualizations we rendered for this analysis. Some are documented, others are not. If you have questions, just shoot us an email.
