What if You Are a Late Bloomer?

Posted on September 19th, 2017 by Chip Davis

Young software companies seeking growth capital typically look at investor tracksora-capital-approach-advisory-capital-raising-icon record as a variable to consider when determining funding source.  Track record is important, however, it is important for reasons that may not be so obvious.

New fund managers generally aspire to become highly experienced fund managers. To do so, they must perform at levels attractive to their LPs so as to inspire investment in the next fund and the one after that, etc.  LPs are not committed to successive funds and have a wide range of alternatives.

Over the years, we have had deals that required (unexpectedly) multiple rounds of capital (i.e. things were not going according to plan – yes I know, “..you don’t say?”). We have been fortunate enough that many unexpected bets incrementally committed through visceral conviction had positive outcomes allowing us to become “experienced fund managers.”  Sometimes these positive outcomes occurred for reasons we never saw ccompetition-icon-7oming.

When a market suddenly becomes populated with funds promoting the same investment strategy this is when companies seeking funding need to contemplate track record. Why? Because new fund managers want to become experienced fund managers and to do so, they likely have to beat the competition and at significant levels.  So what?

“So what?” needs to be contemplated in the context of the following question…”What if you (i.e. young software company) are a late bloomer?”  This is the question because it impacts how you may be treated by new fund manager hoping to become experienced fund manager.  If you are a late bloomer and other companies in the new fund are not-so-late-bloomers, you have just became a lower priority for incremental capital (which, admittedly, you may or may not need). If you do “need”, you just got squeezed into material financing risk and life just became incredibly complicated. This is so because the inability or unwillingness of your initial capital source to play along significantly is read by potential third-party sources of cash as a sell signal (i.e. they must know something we don’t know). Doesn’t matter what you heard during initial courtship about the long road together, this is the reality of fund management world.




Tracts – Why We Made This Investment

Posted on September 8th, 2017 by Chip Davis




Buying and Selling Oil & Gas Properties – When oil & gas properties change hands, a buyer wants to know that the seller owns what he is selling. A particular property can have multiple simultaneous “owners” each with a different set of conditions/terms under which they share in the value of underlying hydrocarbons.  Sorting through these variables is complicated and requires a substantial amount of manpower to make final determinations of what is real and what is not (i.e. “ownership”).

Over the past twenty years, the workbench for those calculating title has been the spreadsheet. An examiner gathers all the information relevant to a property and begins a process of understanding how a current owner acquired his interest, what that interest is, and how it relates to everyone else who has an interest and their types of interests. Inside of a spreadsheet, an owner’s position may be represented by something like this:


So imagine a piece of property that has 60 owners and 7 different types of economic rights. The result is a very complex collection of formulas all created for a single purpose by one human.

Are You A Software Developer? – I am sometimes asked to give presentations regarding the energy industry & technology.  On occasion, I like to survey the audience asking, “How many of you are software developers?”  The normal showing of hands might be 10% of the audience.  I then like to ask, “How many of you know how to use spreadsheets?” to which maybe 80% raise their hands.  I then accuse that 80% of actually being software developers. Why?

I like to think of Excel (et al) as a very cleverly packaged software development tool.  It has a database, it has a bunch to canned development objects (i.e. formula functions), and it has a palatable user interface for presenting. The reason we likely don’t think of it as “software development” is that a completed work product has a single purpose and generally only its creator can know how to use it (i.e. you can’t go sell it to a lot of people – IT DOESN’T SCALE).

A Large Scale Software Development Project – An oil & gas acquisition regularly involves a lot of acreage representing thousands of “owners” and complex nesting of varying interest types.  When a buyer determines to move on an acquisition, he engages a team of “examiners” each tasked with determining who owns what. Every parcel of land is examined and the work product is assembled by parcel in a spreadsheet.  This may happen hundreds of times for a single acquisition.  Think of there being 100,000 “lines of code.”  All of this occurs under severe time pressure (say 90 days) and the buyer has little recourse (post acquisition) if the conclusions are incorrect (i.e. the software has “bugs”).

To my knowledge, there are very few successful software companies that are able and willing to produce in 90 days a commercially ready application with 100,000 lines of code. The risk to reputation alone is damaging much less the potential financial liability to a customer depending on that code to perform mission critical processes.   The oil & gas industry is doing this every time it makes an acquisition and court cases reveal that the consequences are not trivial when things go bad.

Why We Invested In TractsTracts obviates the need for humans to create formulas in spreadsheets.  A usertracts-slide-4 simply describes to the system a few variables required to characterize “what, when and who” and the system takes off. As the user adds variables, it determines how each “what, when and who” is connected to all others and it builds the “code.”  Using this system, an oil & gas property buyer gets out of the software development business and stops doing what no commercial software company in its right mind would be willing to do.  Easy to scale and freedom from the consequence of extremely expensive “ownership” bugs.   If am spending $100 million to acquire oil & gas interest, it is appealing to me to cut my “examiner time” by $500k and reduce my error rate by $1 million. This is what we see in Tracts.

“Clouds are Forming……” – JPT Reprint

Posted on September 7th, 2017 by Chip Davis

Untitled drawing (1)The upstream energy industry has forever constructed itself to “plan for failure.” This mode of operation has implicit to it a set of expense and capitalization challenges that can inflict serious damage on shareholders in certain circumstances. The advent of cloud-computing has presented the industry with a means to alter its strategy for managing the risk of failure.  This article from the Journal of Petroleum Technology (“JPT”) reflects its take on the changes in industry perceptions and behavior on the use of “cloud.” Our own market observations are similar to those cited by JPT.  While the industry may move relatively slowly compared to others, its movements are, when they occur, gigantic.


What Question are You Trying to Answer?

Posted on August 30th, 2017 by Chip Davis

Rise of the Machines – The past two years have revealed a prolific rise in machine learning and artificial intelligence. Platforms that automate creation of analytical insights are on a very steep evolutionunnamedary curve and the range of subject matters that can be probed with these tools is attracting huge amounts of investment capital.

Many years ago I heard an extremely successful enterprise software sales person make the following observations: (i) a lot of money has been made from “adequate” software, and (ii) most software is bought because it can do “one thing.” It is the second observation that has stuck with me the most.

The Implicit Challenge – The notional allure of artificial intelligence is the initial belief that it can replace non-artificial intelligence (i.e. people). The mechanization of data prep and measurement does displace human tolling, however, measurement requires constant adaptation (a highly-developed human skill).  Where it becomes tricky is when the intelligence requirement pertains to questions oriented toward pre-existing scientific disciplines (e.g. oil & gas exploration and production). By their nature and history, these disciplines want to know specifically how an answer is derived – they will not accept “black box” conclusions.

What artificial intelligence is trying to do is mimic and augment real intelligence.  Machine learning is a scaling technique for taking the best minds (subject matter experts) and imparting their own insights into a system from which all may benefit. The competency of this technique is only as good as the subject matter experts regarding the question at hand. How good are they at answering my particular “scientific” question? What background makes those best minds reliable scientists? When parsed through this lens, the revelation is a certain practical irony:  artificial intelligence all comes down to people.

5 Things Young Software Companies Typically Don’t Know

Posted on August 6th, 2017 by Chip Davis

IMG_0007We hear a lot of pitches from young companies with well developed software capable of solving interesting (high dollar) business problems. There is rarely a solution whose value proposition is so self evident and powerful that it can circumvent typical buying patterns. The danger of most elegant software (at initial commercial release) is its hypnotic distraction from what is required to cause a purchase. In this context, we have listed some opinions and questions for young companies to ponder. In no particular order:

  • If you think you just had a “great meeting” with a prospect, you most likely did not. How do you determine the truth?
  • What it is about the particular business problem of interest that is dragging out your sales cycle and how do you reduce drag?
  • When is a trial the right thing to do for the company?
  • Is your sales force doing too much lead generation and why is this bad?
  • What are the first signs that you should not allow a prospect to become your customer?

Consider these points in earnest and founding shareholders of promising software companies will need less money to evolve and own more stock at exit. Make sure your money source has some answers.

Darwin’s Theories on Software

Posted on March 7th, 2017 by Chip Davis

We occasionally get our hands on business cases prepared internally by companies wanting to purchase enterprise software products. These documents generally include recognizable dialects of business rationale. Software purchase initiatives are generally grounded in some emotional driver obscured by economic rationale. We thought we would share with you some of the unstated reasons we believe are really in play:

“If this works I might get promoted.”
“This will get me home 15 minutes earlier.”
“Everyone else is doing it.”
 “I have been doing it all wrong and this application can be my confessional booth.

A Hidden Cost of Fueling Your Car

Posted on October 18th, 2016 by Chip Davis

A New World for Home Buying

Imagine for a moment you are considering buying a home. When you sit down with the seller, he indicates that he is pretty sure that he owns the entire house but there is a possibility he may not own around 19% of it. You express your concern with this possibility, however, the seller is nonplussed and quickly comments…”If you don’t want it…there are others who do.” You would like to own a home so you don’t walk away.

The compromise you reach with the seller is that he gives you thirty days prior to closing to figure out if he owns the property or not. Based on this you send your guy to the courthouse who sifts through the records and tells you what he thinks about the seller’s ownership status. Your bank then mandates that an attorney looks at the same information and gives you their opinion. Oh…and you can not buy title insurance.

If you were in the business of buying and selling houses of which the seller may not own up to 19%, you would necessarily factor this risk into your business model as a cost of doing business. If you can’t lower your cost of goods, then you find another way to protect your margins.

Oil & Gas

Oil & Gas property transactions are usually negotiated in secrecy and closed subject to very tight time constraints. The protections afforded a buyer in such a deal are, on a relative scale, inexplicably limited in both dollar amount and term. There is very limited time afforded a buyer to make a claim against the seller and you generally can never get a significant percentage of your money back. The “home buying” metaphor above is normal course for oil & gas companies operating in the United States.

What’s the Problem?

The ambiguity of oil & gas rights ownership has a simple root cause:

There are many types of “economic interest in oil & gas” and a single patch of land can concurrently have many dozen “owners.” Over time…the many dozen owners can pass around their varied interests however they see fit.

The formula below was created by an oil & gas attorney to reflect the mineral ownership rights of one party among 67 on a 150 acre parcel of land – for a single type of economic interest.


Before the attorney created this formula he had to understand what formula to create and may have drawn a picture like this:


The spreadsheet from which the above formula was taken required approximately 9,200 cells to cover 150 acres of ownership issues. This spreadsheet revealed 160 unique formulas.

For a company acquiring 25,000 acres, this extrapolates to 1.53 million cells and and 26,666 unique formulas: all done by hand – from one spreadsheet jockey to anotherlet’s not act like there aren’t a lot of errors.

Somewhere in there are errors which negatively impact the cost of being in the oil business. These errors cause the oil company to pay for land they aren’t entitled to use and send royalty checks to payees not entitled to them. It also causes them to spend a lot of money figuring out what went wrong. Imagine a bank that doesn’t know if you have money on deposit or not.

I doubt the oil company’s reaction to the above is…”our mistake…let’s just eat these costs.” There is little doubt in my mind that at least some portion of this error has found its way into my own gas tank. To at least one outsider it seems nothing short of insanity.

A Not-So-Obvious Way to Gather Market Intelligence

Posted on May 2nd, 2016 by Chip Davis

Human Tendencies and The Corporate Organism

No one likes to plan for their own demise and as humans, we are generally hedonists. When things are working well, it is a relief from daily anxiety to direct our attention toward having achieved prosperity. Companies are collections of humans.

For almost every successful new company, there is another that was in a position to make that success its own. Thisimages opportunity lost can be a function of several failings: “We didn’t see this or we misunderstood that.” When companies and board rooms contemplate what’s next, it is many times in the context of their current customer set. Customers are good sounding boards for market feedback; however, what actually happens next (or after that) is not always found through customer dialogues. Customers are only going to discuss “what is next” within certain boundaries (i.e. what they are willing to share, what they think is germane to the listener, what they had for breakfast). It is these boundaries that many times are the raw material for a narrow view of the likely reality of “what’s next.”

I once heard former Secretary of State Condoleezza Rice posit that the eventual demise of so many geopolitical strategies is a failure to establish competent “listening posts.” She was speaking to an audience of technology investors using her career observations as a proxy applicable to the technology company organism. To this technology listener, she meant that most companies don’t establish engines/teams/processes dedicated to considering what technologies might be coming out of left field to undercut strategy and market position. Her eventual point was that many times this results in “opportunity lost” and evolves into something seriously detrimental to shareholder value.

Baby Steps

In the world of software and the Energy Industry, it is very common for the target market to deliberate “build our own.” Software vendors must regularly compete against the prospect’s view that what they envision provides a competitive advantage and needs to be proprietary. I would argue that this mindset sets a course that deprives the prospect of an interesting form of “listening post.” How?

A good software company is a de facto market intelligence-gathering organism. Through the proliferation of product in the market, the software vendor creates neural pathways between companies (prospects) that compete against each other. A software company’s mission is to gather various formsimages-2 of “what’s next” from across the installed base and put that information into code/practice. By examining a software vendor’s product road map and long-term vision, a prospect/customer can develop the sense of what his competition is up to. It is an avenue for detecting and handicapping certain types of market messaging (and your competitor’s priorities around competitive advantage) to which the listener otherwise likely would would never construct any form of foresight.  In his own “buy vs. build” deliberations, the prospect is unknowingly trading away the implicit “listening post” (i.e. buy) for the belief of short-term competitive advantage (i.e. build).

So What Am I Saying?

Obviously this dynamic is not absolute; however, it is very common reality. Many great enterprise software companies have developed successful playbooks based solely on this notion. Does the “listening post” construct always materialize to the favor of the prospect? NO.  But I think I would rather avail myself of the possibility of YES than the probability of opportunity lost.

Explanation of Houston Ventures

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