This first map provides multiple connections of Haas alumni to extant companies. Companies appear if there are two or more Haas alumni as board/management team members in the LinkSV database.

Example 1

Here, we see that two companies have three or more Haas affiliations: Tube Mogul has three management team members from Haas and Delivery Agent has one management team member and two board members from Haas. Exploring further, below is a map of Haas alumni that currently have the title CEO (registrants goto Person Filters Title=CEO and Apply Changes).

Example 2

Here, we see a list of 12 people who are currently CEOs at companies. This could be expanded further by clicking “add to map” for any of the 12 people. Roost CEO Alex Chang was added to the map and then we removed Haas as a target node. You can double-click on any person to pop-up their LinkSV bio.

Example 3

Here, we see Alex Chang’s multiple ties to Juliya Rubin (TotalMove, Roost) and Myles Felsing (Haas, Middlebury).

The next examples are two Cluster Maps, which effectively removes Haas as a target node and highlights other pre-existing relationships amongst its alumni (MinLink=3) map which only depicts triads or greater clusters.

Example 4

Here, note the strong relationship to Accenture (n=8). Note again ties to TubeMogul and Delivery Agent.

The next map is the Haas Cluster Map with School Nodes Collapsed into Links (registrants goto Information window Controls).

Example 5

Here, note two large clusters in the map.

We can specify these clusters from the information window Controls by unchecking Collapse School and checking Collapse Companies, Investors, and Experience, leading us to…

Example 6

Here we see the aforementioned Haas clusters as other university ties, the strongest tie being UC Berkeley (+non-MBA degree, n=32), followed by Stanford (n=9), Cornell (n=8), UC-Davis (n=5). This map can be used to identify potential Haas groups based on common education affiliation. Note how double Berkeley Alumni can be identified as strong School Ties toward potential collaborative efforts. It is surprising to note the high number of ties to Cornell (my old stomping grounds) and the surprising Upstate NY-Bay Area connection.

We hope you can use some of the new features of LinkSViewer 1.3 to your own strategic advantage. Feel free to sign up for a free two-week membership by clicking on Free Trial Registration.

1. What degree is most popular for Harvard alumni on the list?
A. BA/BS
B. MBA
C. MA/MS
D. Ph.D.

2. What degree is most popular for Yale alumni on the list?
A. BA/BS
B. MBA
C. MA/MS
D. Ph.D.

3. In which state do most Yale alumni on the list currently reside?
A. Connecticut
B. New York
C. California
D. Texas

4. What two Universities have the most co-alumni?
A. Harvard and Princeton
B. Harvard and Yale
C. Harvard and Stanford
D. Princeton and Stanford

5. What company has the most Investments (>5% Stake) from list member alumni in the Top 4 Universities?
A. Microsoft
B. Google
C. Gap
D. Berkshire Hathaway

6. What University has the most co-alumni with Harvard University?
A. Columbia
B. Stanford
C. Yale
D. University of Pennsylvania

7. Which University has the most Self made list members in the Finance industry?
A. Harvard
B. Stanford
C. Princeton
D. Yale

8. Which University has the most Inherited and Growing list members in the Oil/Gas industry?
A. Harvard
B. Stanford
C. Princeton
D. Yale

9. What is the state residence for the most Top 4 University list members under the age of 60?
A. New York
B. California
C. Texas
D. Florida

10. What University has the most Self made list members with Wealth over $2 Billion under the age of 50?
A. Harvard
B. Stanford
C. Princeton
D. Yale

Answers:

1. B (Let’s start off easy…still nothing quite like a Harvard MBA - by a large margin)

2. A (Yale is probably less known for its graduate programs than its undergraduate program)

3. D (Don’t mess with Texas; for questions 1-3 considering George W. Bush would have been quite useful)

4. D. (Surprisingly, this is mainly because of Robert, John, & William Fisher (Gap) who all are all alumni of both Princeton and Stanford)

5. C. (See #4, but note that both Charles Schwab and Meg Whitman (eBay) are major investors in Gap - this may be because Gap was started in SF and they all reside in the Bay area)

6. D. (This was a tough one, U Penn had 3 co-alumni (Jamie Dinan, Charles Butt, and Joshua Harris) vs. 2 each for Columbia (Dirk Ziff & Robert Kraft), Stanford (Steve Ballmer & Penny Pritzger), and Yale (Wilbur Ross Jr. & Stephen Schwartzman))

7. A. (This should be of no surprise, given the propensity of Harvard MBAs on Wall Street).

8. D. (All four ties are from the Bass family; again, considering George W. Bush would have helped here)

9. B. (More young people/surfers in California…and the real estate is most expensive)

10. B. (An end of quiz tap in, Stanford by a 5-3 margin over Harvard - Google alone ties with Harvard (Sergey Brin, Larry Page, & Omid Kordestani))

Quark Biotech filed for its IPO on March 30.  The Quark Biotech Relational Map provides some insight into the relations between its current and former management team and board members.  Along the way, I would like to point out some key transition points that will help LinkSViewer users to navigate from simple to complex maps (the opposite of the previous post which demonstrated navigating from complex to simple maps).  First I started with a relatively simple relational map - I searched for Quark Biotech and then filtered in former people.

Quark Biotech Relational Map (Former People Included).  Notes: (1) Board Interlock Ties: Joseph Rubinfeld & Daniel Zurr (Former SuperGen Board Members); (2) Key People Ties: Larry Ellison (Oracle CEO, previous Quark board member).

I clicked on Larry Ellison in LinkSViewer, Add to Map (Under Pink banner in Information Window) to incorporate all of his current and former boards on the below map, and dropped pendants

Quark Biotech Relational Map (Ellison as Person Added to Map). Notes: (1) Ellison Previous Boards (Active Cos.): NetSuite, Pillar Data Systems, Liberate Technologies, Oracle, Apple; (2) Ellison Board Interlocks: Steven Fink (Lawrence Investments) & Jeffrey Henley (Oracle Former Board Chairman).

I clicked on Add to Map under Larry Ellison as Individual Investor (Yellow banner in Information Window) to incorporate all of his current and active individual investments on the below map and dropped pendants.

Quark Biotech Relational Map (Ellison as Investor Added to Map).  Notes: (1) Ellison Investments (Active Cos.): SalesForce.com, SuperGen; (2) Ellison Investment Ties: Igor Sill (Oracle & Salesforce); Daniel Zurr & Joseph Rubinfeld (SuperGen/Quark).

Thus, we see how Larry Ellison connects to Quark as a former board member, but also as an investor in SuperGen.  In this way, we used LinkSViewer to expand existing networks to identify interesting relationships.

Data Domain filed for its IPO on April 4.  The Data Domain Relational Map provides some insight into the co-investment relations between its three investors: Greylock Partners, Sutter Hill Ventures, and NEA.  Along the way, I would like to point out some key transition points that will help LinkSViewer users to navigate from complex to simple maps.  First I started with a relatively complex relational map - I searched for Data Domain and then filtered in current and former people and dropped pendants.

Data Domain Relational Map (Pendants dropped).  Notes (1) Co-Investment Ties: Sutter Hill-Greylock (Trusted Data); NEA-Sutter Hill (QuickLogic, Kovair); and NEA-Greylock (PortAuthority, SiTime, PolyServe, Tabula); (2) People Ties: Geoff Barrall (Trusted Data CEO); Reed Hundt (Former FCC Chair); Aneel Bhusri (Greylock); Scott Sandell (NEA); Ron Codd (PeopleSoft Former CFO); and Michael O’ Donnell (Network Appliance Former Director of Federal Sales); (3) Strong Company Ties: Trusted Data (Geoff Barrall, Greylock, & Sutter Hill); Kovair (Scott Sandell of NEA & Sutter Hill). 

Network Commentary: The active company ties include 4 public companies (QuickLogic, Network Appliance, Adept, & Openwave), 3 active acquired companies (Kovair, PortAuthority, & PolyServe), and 4 private companies (Trusted Data, SiTime, Tabula, & SymphoniQ).  Of particular interest are the 4 public company ties.  There are also three main clusters centered around each VC with seven companies connecting these clusters. These clusters are amplified by Excluding the Target Node in the below map.

Data Domain Relational Map (Exclude Target Node, Pendants dropped).  Notes (1) Here we clearly see the links between investors (PolyServe, SiTime, Tabula, PortAuthority, Kovair, QuickLogic, & Trusted Data); and (2) We can also see the strong relationship between former FCC chairman Reed Hundt with Greylock Partners.

Network Commentary: By removing the target node we are in effect demonstrating how the companies, people, and investors were related to one another before considering Data Domain - are there preexisting ties that bind?  This map illustrates investor clusters on the map by removing the influence of Data Domain on its capital relations.  Moreover, we can now focus in on only the strong-tie companies.  This is performed by increasing the MinLink to 3 from the first map.  The below map only includes those companies with at least 3 ties:

Data Domain Relational Map (Pendants dropped, MinLink=3).  Notes (1) Here we see the strong links between investors: (1) Greylock & NEA are linked by PolyServe via Reed Hundt & Aneel Bhusri; (2) Sutter Hill & NEA are linked by Kovair via Scott Sandell; and (3) Greylock & Sutter Hill are linked by Trusted data via Geoff Barrall.

Network Commentary: By increasing the MinLink to 3 we are in effect illustrating multiple ties between investors and companies on the map - what are the strongest ties that bind?  This map shows only the strongest relationships from the previous maps.  Here we demonstrate the process of taking a complex map and simplifying it to detect only the strongest of relationships (as denoted by the most common ties). 

Data Domain Relational Map (Exclude Target Node, Pendants dropped, MinLink=3).  Here we see a strong-tie circle investors (i.e., each investor has a strong-tie connection to one another).  The fact that each investor has a pre-existing strong tie relation may bode well for Data Domain - relational ties could pave the way for a smooth IPO. 

First let’s look at the networks of the three key board members identified in the previous post: Reid Hoffman, David Sze, and Bill Gurley. Q: What do these board members have in common? The goal here is to identify companies not found in the previous post map - companies that are found in the same circles as the ‘hot companies’ discussed in the last post. Along with the new people we find, all of these companies are potentially interesting, so let’s see what we can dig up.

In the last post we started with a map of company nodes. In this first derivative map we will look at the network formed by the affiliations of those companies - namely, the key board members.

In the map above we see the combined network for our three key board members: Bill Gurley, David Sze, and Reid Hoffman. Some key features to note are the central position of Reid Hoffman as an investor which mirrors his importance as a board member in this network formed around the ‘hottest companies.’ Most of the companies from the previous post appear as well (as is expected). Some new names also appear - Marc Andreessen, Ron Conway, Peter Thiel, and Gil Penchina as angel investors; John Dean, Jed Smith, Keith Rabois, and Brett Bullington as board members, and PayPal as a spawning ground for all of this activity. Some of the new companies we are exposed to include: Softcoin, Marquee, Wink, Vendio Services, Six Apart, Open Table, and Tropos Networks. The next map shows the network for the key angel investors from the map in the previous post.

The second derivative (well, kind of). In the map above we’ve mapped the four key individual investors from the previous post. Just as the first map in this post shows a derivative network of the key board members, this map shows the derivative network of the key angel investors. Looking at this map we see that for our network of the ‘hottest companies’ Bill Gurley and Mike Maples are less integrated. Mike Maples isn’t seen in the board member based map above, and Bill Gurley isn’t seen in the investor based map above, but all of the other key players are present in both maps, as well as Peter Thiel, Keith Rabois, and Marc Andreessen. The other point of interest lies in the new companies introduced, especially those with multiple connections such as the Facebook-Powerset cluster between Peter Thiel and Reid Hoffman. Their common involvement in Facebook negates the interest in Friendster to a great degree, but Powerset is an interesting new inclusion. Similarly, Xoom, Revision3, and Wikia are new companies introduced on this map. The next map shows the network for the key VCs from the map in the previous post.

 

The third derivative (kind of). In the map above we see the co-investments of the four key VC firms identified in the previous post. Along with the ‘hot companies,’ and other companies of interest that we identified from the second map in this post, here we see more companies of interest due to the co-investment relations between our key VCs. It is interesting to note that none of these companies have received funding from more than two of these VCs, which perhaps would have been an indication of a higher level interest or importance in the network of ‘hot companies.’ From this point we could continue to investigate the networks of these other companies - Registered users can do so by clicking through on our maps.There is a tendency in the Valley to fixate on the hottest new thing, and the biggest payoff, but the derivatives of ‘the big ones’ can often lead to a number of extremely successful companies. In any case, the goal of this post was to illustrate alternative viewpoints using network maps (i.e., from the VC, Angel Investor, or Board Member perspective). In this case, derivative networks were used to identify hot company relations. The main premise is that it is not only what you do, but who you are associated with, that helps determine company success. This can be applied to any set of people, companies, or investors in your own area of interest.

Here we see that there are several investors have at least 3 co-investments with Mohr Davidow, but it is difficult to see their relations from the above map.  Because we know by definition that Mohr Davidow is connected to the companies in their map, we can better view their relations by excluding their node from the map.  We now check the Exclude Target Node box below the Legend icon.  The below map alters the previous map even though it contains the same information, with the exception of the Mohr Davidow node.

From the above map you can now discern the relationships between companies and investors for larger maps.   For example, you can see that Accel Partners has 3 active co-investment ties with Mohr Davidow and they are all public companies (FormFactor, Critical Path, & Agile Software).  In the previous map such relations were difficult to gauge.  Of course there are other ways to clarify maps using Filters, zoom, changing font size, and truncating node labels, but the Exclude Target Node feature is an efficient way to view entire maps without losing information.  Try it out.  It is a useful feature. 

This map is interesting because of the multiple board of director ties on the map.  Seth Niemann (Crosspoint), Andrew Verhalen (Matrix), and Kathryn Gould (Foundation) are all VC board representatives.  By appearing on this map, this means that each sits on the board of one other public company: Niemann (Foundry Networks), Verhalen (Turnstone Systems), and Gould (Interwoven).  Thus, the board of directors at ShoreTel all have experience with publicly traded companies.  Two other boad members, Edward Thompson and Charles Kissner, currently sit on the board at SonicWALL. 

I next charted the historical stock prices of the aforementioned related public companies: Interwoven (IWOV), Turnstone Systems (TNST), Foundary Networks (FDRY), and SonicWALL (SNWL).  It should be noted that Turnstone Systems is no longer listed on NASDAQ (now TNST.pk).  Comparing IPO initial performance, I mapped the stock prices for these companies in their early years here.  I then mapped their entire stock prices here.  These pricings tell a cautionary tale.  While, Interwoven, SonicWALL, and Foundary all showed substantial gains after four months or so of their IPO, they declined therefter and are now trading lower than their IPO price.  From these trends, the IPOs were relatively successful early on, but not over the long haul.  This could be explained in large part because these IPOs all occurred in 1999-2000 (before the bubble burst), but present pricings do not reflect full recovery.  Thus, the prospects for ShoreTel, in comparison to its related public companies, seem best after the first few months of its IPO.  Realize that I am not a stock expert, so take my advice with a grain of salt.  Certainly there are other factors that should be considered by analysts in each particular IPO case. 

As a secondary purpose of this post, I offer some tips for LinkSviewer registered users on how to utilize multiple map views of the preceding Relational Map.  These alternative map views can be used to amplify key relationships or simplify complex maps at the click of a button.  Below I provide two examples on how view the preceding Relational Map using the Person-Investor and Company map buttons.

The relationships between board members and their investor ties are illustrated using the Person-Investor Map in LinkSViewer.  One way to further amplify the relations in the map is to Click on the “Exclude target node” box on the Advanced Options Panel (we know by default that ShoreTel is tied to each person and company on the map).  The resultant Person-Investor Map is below:

This map takes out the companies in the map and displays the indirect ties of people to investors. It highlights key people-investor ties in the Relational Map.  The colored links indicate the type of relationship: Blue = Investor to Investor company tie; Grey = Person to Investor company tie; Pink = Person to Person Company tie.  In the above map, note the Grey ties of Neimann, Verhalen, and Gould to their Parent VC Firms.  Note also how Gould has a VC connection to Focus Ventures as well.  The Pink tie from Kissner to Thomson indicates a direct person-to person tie.  Line thickness indicates if strong ties exist - the thicker the line, the stronger the tie. Strong Ties (in this case, at least 3 common public company ties): Matrix-Morgenthaler; Crosspoint-JAFCO; Norwest-Focus; Focus-Foundation. 

The company relationships between these board members can also be illustrated using the Company Map in LinkSViewer and Hiding Yellow Ties in the Advanced Options Window, which excludes Investor-Investor Ties).  The resultant Company Map is below:

This map takes out the people and investors and displays the indirect ties between companies. It highlights the board member ties in the relational map.  The colored links indicate the types of relationships to ShoreTel.  Red links indicate People in common; Orange links indicate People and Investors in common. SonicWALL has a red link because of Kissner-Thompson common board tie.  Foundry Networks, Interwoven, and Turnstone Systems have orange links because of the: (1) Niemann-Crosspoint and Foundry tie; (2) Verhalen-Matrix and Turnstone tie, and (3) Gould-Foundation-Focus and Interwoven ties.  Note that the ShoreTel-Interwoven tie is a thicker line becuase it involves three connections (Gould, Foundation, and Focus), while all of the other lines only indicate two connections.  It is possible that the companies could have ties in this map, which would have made it more interesting, but this does show the nature of the company ties in the Relational Map.  The main purpose of this section was to enlighten users on mulitple map view options.  I encourage users to try new views to help tell their own stories.

(1) Search for the company in LinkSViewer 1.2; (2) Show the relational map; (3) Company filter out (i.e., deselect) private and acquired companies (registered users only); (4) Drop pendants

The result is the relational map for the target company’s public relational network.  Questions to ask: How have related public companies fared at IPO?  Are they successful?  How much experience do the investors and people have in taking companies public?  Let’s now preview the public relational maps for Riverbed and Google.

Riverbed has relations with two public companies: Polycom (Stan Meresman and Accel Partners link) and eHealthInsurance.com (Christopher Schaepe of Lightspeed Ventures).  Polycom has achieved great success (700% increase in stock price over the past 10 years) over the long haul and the jury is still out on eHealthInsurance.com (4% decrease in stock price since its offering three month ago).  The important part here is that the affiliation between Stan Meresman and Accel seems a winning formula.  Check out the below for a comparison of each stock’s historical prices.  

Riverbed Public Company Performance (Yahoo Finance)

Now we turn to the Google public company relational map:

Google has a more complex public company network, than Riverbed.  This is mainly because of the presence of Sequoia Capital and Kleiner Perkins as investors, but also bodes well because of the volume of experience between Sequoia and Kleiner in IPO investments.  Note also the presence of ”heavy hitter” board interlocks (John Hennessy, Al Gore, Arthur Levinson, John Doerr, and Michael Moritz).  Perusing the public companies connected indicates success (Apple, Intuit, Symantec, Cisco, Flextronics, Electronic Arts all at over 500% increase since IPO), but also some relatively unsuccessful IPOs (NeoMagic, Onyx Phamaceuticals, Redback Networks, and Saba).  The below links comparing the successful and unsuccessful IPOs provide some insight in the historical price trends, however.  In general, the successful companies were successful at onset, especially after one year, and steadily increased in price thereafter; the unsuccessful companies were unsuccessful at onset (save Redback), especially after one year. Check out the below links for a comparison of positive and negative performance comparing each stock’s historical prices.  

Google Public Company + Performance (Yahoo Finance)

Google Related Company - Performance (Yahoo Finance)

In summary, the mapping of public companies provides key information that can be used by investors.  By incorporating historical prices among related companies, the investor has a way to gauge the success of connectivity based on actual price indicators.  The goal is to find network connections, identify a positive public trend, and use this information to guide investing.  Given the two cases of Riverbed and Google, there is evidence that success breeds success, although one must incorporate historical trends to further solidify this conclusion.  Certainly, this is a starting point for further investigation and registered LinkSViewer users may want to explore other filters to aid in their IPO analysis.  Pragmatically, I would keep an eye on eHealthInsurance.com (new IPO) and Saba (10% increase over the past year) to see if they exhibit further increases in stock price.  A couple of caveats: (1) dates of IPO may affect trend comparisons because of market volatility at the time of IPO; (2) given the relative paucity in recent IPOs, this trend may be less significant and may need to incorporate successful acquired companies; and (3) relative successes may be driven by company sector/industry versus an overall comparison of all public companies.  In any case, it is clear that the use of visual network analysis provides a new way to predict success of IPO companies. When incorporated with analyst data, it can help guide an investor in choosing (or not choosing) a stock to add to their portfolio.  Look at the relational network, it could be golden!

I was playing around with the network for Kevin Fong, one of the most connected board members in our database when I digressed and began to play with the combined network for two fairly large investors - Mayfield Fund and Foundation Capital. If you click on Kevin’s name (above) you will see a map that shows how Mayfield and Foundation are very centrally located because of the amount of common companies they share with him. Mayfield should be no surprise because he is a general partner there, but it got me to start wondering about what else Mayfield has in common with Foundation…I started a new map by searching for Mayfield and Foundation, and then mapped them together. Now I set the ‘MinLink’ to 1 (a feature in the taskbar, the default setting is 2) and the result was an explosion of information…

Interesting stuff, but unreadable. I decided that I really wanted to look into the management team interlock between their networks of investments. This is the perfect opportunity to make use of the updated tabs in our LinkSViewer tool. If you haven’t used the tool in a while you may not have noticed, but the tabs have been changed to serve like radio presets, creating views that we think serve the interests of the users, and minimizing the time spent applying filters to get to the interesting information.

By clicking on the “Management” tab (5th from the left), LinkSViewer will automatically filter down and display only the management interlock relationships in the network. This change helped a little, but there are still so many management team members involved that the map is cumbersome and unreadable (see this map)… but I’m not interested in all of the management team members, just the ones who connect to more than one of the companies.

Well the ‘MinLink’ is still set at 1, so let’s change that back to 2 by clicking on the “+” icon next to the ‘MinLink’ box. This will filter out any of those management team members on the periphery who don’t have at least 2 links to companies in the map (we’re setting the minimum number of necessary links at 2). Here is the map (click on it to go to the live version):

This is great. I’m getting down to what I really want to see now, but there are still all of those pesky companies that don’t have connections to any of the management team members with at least 2 links in the map. Now I’m going to perform an advanced procedure. The MinLink feature has a way to filter these nodes out as well.

Most of the time the MinLink box has only one number in it. However, if you want to manually insert a comma and add a second number, it can manipulate the map to a greater extent. When just one number is in the MinLink box, it sets the minimum number of necessary links that a node must have to be in the map, but it applies only to the most peripheral set of nodes (the furthest outside - which, in this particular map, can be thought of as the management team members who are on the outside connected to the companies). For the map above, the MinLink is set at “2″. If you enter a comma and a second number, for example setting the MinLink at “2,2″ then we can eliminate those companies with no management team connections. The second number (after the comma) applies to the first degree nodes from the target nodes, or in other words, instead of the most peripheral nodes, it applies to the companies that are 1 degree away from our target nodes of Foundation and Mayfield. So by setting the second number at 2, we are dictating that in this particular map the companies must have at least two links, and just being connected to the target node is not enough. Now the map will be filtered down only to the nodes involved in the management team interlock relationships… check it out:

Now we can see who the management team members hare that connect these two VCs to each other. I think that the large number of common members between the two companies at the top - Packet Design and Precision I/O.

I hope this served to show you some ways to whittle down a big map to a specific point of interest.

GroupScope is proud to announce the release of our LinkSViewer 1.2 product. LinkSViewer 1.2 is a visual network analysis tool that explores relationships between management teams, board members, investors, and companies in the Silicon Valley. It is the first application of the GroupScope network analysis engine, which is the result of research at Cornell University and our current headquarters in Shell Beach, California. LinkSViewer is made possible thanks to our partners at Link Silicon Valley (LinkSV.com), who develop the database used by our network engine. LinkSViewer turns that data into network maps that are easy to read and learn from. What you will discover are indirect relationships that may not be readily apparent without a network perspective. Using LinkSViewer 1.2 users can search, filter, summarize, email, and navigate any map to suit their specific needs.

There are several noteworthy features in our 1.2 product.
o People mapping based on management teams and boards of directors
o Filter and cross filter options for people, investors, and companies
o Advanced search and filter options such as amount and rounds of capital, active/inactive companies, current/former boards & management teams
o In-map legend and filter display for easy use of maps outside of the application
o Map zooming
o Link strength indicators and filters
o QuickSearch feature from any screen
o Add-a-node feature that lets you expand and compare multiple entities
o Person-Investor maps allowing indirect relationship views

We are offering LinkSViewer 1.2 on a trial basis for select users in the VC community. We are also happy to schedule demos in the Bay Area to showcase our map functionality. To obtain a trial password or schedule a demo, contact us at linksviewer@groupscope.com with your request and a little bit about your specific interests - perhaps some sample companies, people, and/or investors that are particularly relevant. Any other feedback is welcome - contact me if you have any other questions. Enjoy, and happy mapping.