A founder asked me recently if there were any trends in professional services across public SaaS companies. I had examined the gross margins
and share of revenue from professional services
about 3 years ago. Professional services are consulting fees software companies charge to customers for software configuration, customization and education. What has changed over the past 3 years?
First, we have more comprehensive data set, since many more companies have gone public. Second, many newer software companies generate substantial fractions of their revenue from PS. Appian is close to 50%; Pegasystems is at 37%; Horton is at 24%; Mulesoft at 20%.
In the past, companies with higher professional services components to their revenue have been valued less highly because PS revenue isn’t recurring and is lower margin than software revenue.
In addition, the gross margins from professional services look different than three years ago. The variance is much higher. One
Continue reading "How the Economics of Professional Services Have Changed in Software"
Last week, Elastic filed their S-1 to go public
. Elastic is a Dutch company founded in 2012. Just five years later, the company generated $159.9M in revenue. Elastic commercializes open source software called the Elastic Stack, a set of different products that enable users to search and store data in many different sources and formats. This software is used for application search, website search, enterprise search, application performance monitoring, and analytics for business and security data.
To put this company’s exceptional success in context, I plotted their metrics alongside Mulesoft, another enormously successful open source company that Cisco acquired the day before their IPO for $6.5B. In the charts that follow, I have plotted Elastic’s metrics the two years before their IPO, marked as -2 and -1. I have plotted Mulesoft’s metrics from 2015 and 2016, which was -3 and -2 years before IPO, but the companies were
Continue reading "Elastic S-1 Analysis – Another Open Source Monster"
consumer internet shift from intent to attentino consumerization of it means the biggest platform companies will also have a shift to attention
The power to transcend paradigms: disruption The mindset (goals, structures and rules): culture The goal of the system: mission The power to evolve the structure: organizational growth; self-organization; moving fast Rules of the system: how to engage inside and outside the company Structure of information flows: Positive feedback loops http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/
Advances in machine learning are transforming the software world. One of the most exciting applications of machine learning is speech recognition and natural language processing. After researching the space for more than a year, we are thrilled to announce our investment in and partnership with Chorus, a pioneer in speech analysis for sales.
Chorus has a unique technology that enables it to listen to inside sales phone calls, and provide real-time feedback to salespeople while they are speaking on the phone.
.— title: Building A Money Machine layout: post excerpt: Successful startups are money machines: they ingest a dollar of investment and produce more than a dollar in revenue. There are three steps to build a money machine:
Find or create a product many people will use. Convince customers to buy the product. Mechanize the two processes above, reducing costs and increasing profitability to finance growth. Startups repeat these three steps many times during their lifespans.
Baumol cost disease explains the increase in salaries without productivity gain. In a classic example created by the former Princeton professor who taught luminaries like Burton Malkiel, the number of people required to play a Beethoven symphony today is equal to the number hundred years ago. But the wages of a classical violinist have increased despite no productivity gain.
Baumol also cites this phenomenon in nursing. But, from the cursory research on nursing salaries, I found this isn’t true in g3452ffy1that field.
.— title: How to succeed despite your every effort to fail layout: post excerpt:
Startups are discovery teams - they venture into the abyss, like Shackleton, aspiring to cross the Antarctic, plant a flag and live to tell the tale. Because every expedition is unique, no one knows what will work: product features, marketing tactics, sales pitches, fundraising stories. Nor can the team fully anticipate the precipices and risks: competitive, legal, hiring, market timing and management risks.
Alex, I just sent him a note. I will forward you his response