The Startup Revolution Series -- Part 1: The Great Transition: Industrial to Information Revolution

-- By Bjoern Lasse Herrmann and Max Marmer

For the past decade or more, Max and I have either heard or experienced endless stories of startup failures. We took as a given that more than 90% of startups go bust instead of bang, but we were also inspired by the amazing success stories — from Salesforce to Google to Kickstarter — that built new industries, created tens of thousands of jobs and transformed society.

And so we asked ourselves one day in the backyard of a house in Atherton: What if that failure rate could be reduced by even a small percent? How much could society benefit if 1% fewer startups failed? 2%? We became bolder. If the code could be cracked on what factors led to more favorable outcomes, could we actually help maximize success rates??

The following series of posts is a detailed look at why, at this unique moment in human history, we firmly believe that nurturing startups is critical to the well-being of our world.

So we reached out to entrepreneurs across the globe, and over the past several years have been overwhelmed by the tens of thousands of people who have shared their data in service to the entire startup community. The findings from our communal efforts have been published in reports, articles and blogs, have been incorporated into the curriculums of hundreds of universities and have been referenced by the Obama Administration, Chancellor Merkel and leaders in dozens of countries.

Then we built benchmarking dashboards to help individual companies, partners and ecosystems make more informed choices, given their unique circumstances and peer groups. We continue to refine Compass Benchmark, Compass Monitor and Compass Ecosystem, and have many releases in process.

Does this mean we’ve achieved our mission? Hardly. For all we’ve achieved as a community, there are always more questions to be asked, more data to be analyzed, more algorithms to be refined. So we continue to chip away at the code of startup success, with a special focus on delivering an updated version of The Startup Ecosystem Report in spring of 2015.

In the meantime, here is a look at the series of posts that will lead up to its release.

As we begin the new year, we wish you the greatest possible success with all your ventures.

— Bjoern Lasse Herrmann, CEO of Compass

The Startup Revolution Series Overview

Part 1: The Great Transition: Industrial to Information Revolution

Part 2: The Decline of the Blue Chip

Part 3: The Rise of the Startup

Part 4: The Critical Role of the Startup Ecosystem

Part 5: Startup Ecosystem Report 2015

Part 1: The Great Transition: Industrial to Information Revolution

By Max Marmer, Compass Co-Founder Emeritus

Have we reached a critical tipping point in the transition between the Industrial and Information Eras? It is always difficult to define a precise moment at which major periods of societal transformation take place, but there is an increasing amount of data that points to a significant decline in businesses founded in the Industrial era and operating on Industrial era principles. At the same time, one can hardly fail to notice the explosive rise of the information age.

If we look at the performance of the types of companies that have sustained the economy for several centuries, we see worrisome trends. The Shift Index, by the Deloitte Center for the Edge, notes a 75% decline in return on asset performance for US companies over the past 45 years, despite increasing labor productivity. At the same time, the success of market leaders appears to be increasingly short lived, with a decline of almost 80% in the length of time an S&P 500 company could expect to remain on that list.

Meanwhile, over the last 15 years, a significant portion of job and economic expansion in the U.S. has come from high-growth technology companies such as Amazon, Google, Salesforce, VMware, Facebook, Twitter, Groupon and Zynga. And while Apple was officially incorporated in 1977, it was the company’s reinvention of itself when Steve Jobs returned to helm in 1997 using the process of what one might call disruptive technology intra-preneurship that led to the later development of the iPhone, iPad and their corresponding app ecosystems. These new product innovations transformed Apple from a struggling organization to the company with largest market cap on the planet — quadrupling its value in just the past five years alone.

Consider this: the entire US GDP is $15 trillion. Collectively, these 9 companies that barely existed a decade and a half ago, have directly created almost a trillion dollars in new wealth. Will the trend of multi-billion dollar tech startups that have a disproportionate effect on the needle of the global economy continue? As we will discuss in these series of blog posts, many signs point to yes. The virtual explosion of startups below the radar is so big, the Economist recently likened it to the Cambrian moment of species evolution.

Humanity doesn't see transitions between eras very often, but when they come, every aspect of society gets reinvented: government, business, finance, education, health, energy, technology, art and science all get upgraded. In fact, most historians would argue there have only been 3 such transitions before: 1. foraging to horticulture 2. horticulture to agriculture 3. agriculture to industrialization. The Industrial Revolution was the last great societal transformation, and the scientific enlightenment that ensued gave rise to modernity. With two billion broadband internet users and billions of smartphones entering circulation, the necessary tools and infrastructure are now in place for the Information Age to burst into full bloom, moving beyond the confines of the technology industry to all aspects of society.

The role of technology entrepreneurship in our global economy is now more important than ever. Increasingly it is becoming clear that technology entrepreneurship will be the primary growth engine of this new economic era. Having gone through a fairly severe dot com boom and bust cycle only fifteen years ago, it is understandable that many people imagine a similar fate for the current tech boom. Rightly or wrongly, it is human nature to look to the past as a way to envision the future. Yet that thinking is also short-sighted. Based on the data we have, the larger context of this epochal transition from the Industrial era to the Information era appears to be a harbinger of long-term exponential wealth creation as the era continues to mature.

But the development from one era to the next requires dangerous periods of transition, where a society can either slide into turmoil or rise to the occasion. We will have to be thoughtful but bold about how we shed our industrial skin — and the institutions, business, jobs, culture and traditions that have come with it.

Change is hard. But if we can adapt, if we can adopt new skills, beliefs and and values appropriate for a new age, we can reap the full benefits of a prosperous and thriving world. The Industrial Revolution brought wealth and prosperity unseen before in the likes of human history. In 1750, the total wealth of the world sat at an estimated $126 billion dollars. Today the world’s wealth is over $70 trillion. It also brought unprecedented advances in education, transportation, medicine and civil rights.

But the hard truth is that what got us here, will no longer take us further. To successfully make the transition to the information era, much of the socioeconomic fabric of society needs to be reinvented for our new era. If we do not adapt and release much our now expiring industrial era mindsets and practices, then the dark days of the 2008 economic recession may return. To avoid this fate, we must let go of the past and engage with the future to ensure that the greatest era in human history is in front of us.

This series will explore what we can do to nurture the flame of progress, keeping the world on a path to greater prosperity by investigating the growth engine of the new Information Economy and harmful Industrial Era patterns we must relinquish.

Together we can lay the groundwork for a successful transition into the new socioeconomic era of the Information Age.

Let’s dig in.


In the spirit of this transition, please help us collect data for the updated Startup Ecosystem Report by filling out our survey.

How to drive dynamic decision-making and action: From fixed to relative performance contracts (Part 1)

by Niels Pflaeging, Founder, BetaCodex Network

Participate in Compass’ Q2-Q3 2014 financial benchmarking study and inform your financial planning and resource allocation decisions.

Join the free Proformative webinarUsing Real-Time Financial Benchmarks to Drive Dynamic Planning, and Real-time Decision-Making” on 11/25/2014 at 11 am PST. 

For decades, organizations of all sizes and from all kinds of industries have curated and perfected management practices such as fixed target setting, target negotiation, planning, budgeting, forecasting, plan-actual variance reporting, incentives-setting, and individual performance appraisal. Now, things are changing: Those practices, usually combined under brands such as Management by Objectives, Merit Pay, or Pay-for-Performance have recently come under fire. If markets and work are becoming ever more dynamic, how can static, annual rituals remain effective and appropriate to improve or even control performance?

Look at companies large and small, and everywhere in the world, and you will find that performance management practices these days are remarkably alike, almost everywhere. That bundle of management practices was popularized between the 1950s and the 1980s, starting with the idea of Management by Objectives, proposed by Peter Drucker in his 1954 book, and into the late 1970s, when Michael Porter elevated the idea of competitive advantage, or strategy, to a quasi-science. Since then, “fixed performance contracts” have become almost omnipresent and are until this day considered the standard for managing performance, and for controlling businesses and people.

Starting with the Beyond Budgeting movement in the late 1990s, some have started to question the idea of the static performance contract: the philosophy of budgeting and setting fixed targets in advance, and then measuring and judging actual performance against those pre-defined objectives. Fixed performance contracts, the critics say, are not only inefficient today. They can only be counter-productive in times when uncertainty and surprise become the norm, and when value-creation becomes more complex, instead of remaining just complicated.

The side effects of “fixed performance contracts” are wide-ranging and dramatic. They range from internal stakeholders gaming performance systems and controls (in reaction to target-setting and bonus compensation), to external stakeholders and CFOs rigging the financial markets (in reaction to earnings guidance and expectation management).

Performance Management: Are we riding a dead horse?

In other words: The performance management practices from the past are broken, and we know it. Uncertainty and complexity have long invalidated planning, forecasting, fixed targets, plan-actual reporting (see illustration 1), and bonus systems. We have outsourced control to markets a long time ago. But instead of letting go of all practices that assume stable, slow-moving, and indeed dull markets, we have continued to optimize and perfect these practices. We have tried to improve a way of managing that has long been straight jackets, or “dead horses.” The very same Peter Drucker once wrote that “90% of what we call management today actually consists of practices that make it hard for people to do their work.”  Today, the challenge for us is not just to recognize that, and its consequences. It is to get off the dead horse.

In dynamic markets and value creation, absolute targets weaken control and create misleading incentives (left), while relative measurement enables transparency and adaptive control rooted in self-organization principles (right).

Illustration 1: How we fool ourselves, using fixed performance contracts: Example of a financial performance indicator

The good news is that the solution, or the alternative to fixed performance contracts, has already been around for quite a while, albeit in a relatively small number of startlingly successful “pioneering” organizations. Even though they may seem new and indeed counter-intuitive to many companies and managers today that have been used to the notion of controlling through fixed performance contacts, some larger companies have used relative performance contracts, exclusively, for a few decades,. As we learned during the case study research journey of the Beyond Budgeting Round Table (of which I was a director for a few years), that started in 1998: There is a whole world beyond budgeting, beyond fixed targets, incentives and variance reporting. We began labeling this alternative “relative performance contracts” in the early 2000s.

Relative performance contracts are based on the assumption that it is unwise to set fixed targets for managers and teams and then to control their behavior and activities in terms of these targets. The implicit agreement is that management's task is to provide a challenging and open work climate within which employee teams agree to aim for continuous performance improvements: managers and employees must use their knowledge and their own common sense to adapt to changing conditions and environments.

Towards the emerging "relative" performance contracts:

Under this performance contract, decisions are not made at the top. Instead, they are distributed, decentralized, and devolved as far out as possible. This type of performance contract increases, not erodes, mutual trust. Increased transparency and higher expectations (compared to competitors or their equivalent) provide a permanent challenge, which either has to be matched to or whose failure will lead to equally transparent consequences. Responsibility for performance and decision-making are gradually shifted away from the center of the organization towards the periphery. Decentralization thus is key to relative performance contracts.

Illustration 2: How to move from fixed to relative performance contacts

Variations of this kind of relative measurement have been used by a few larger companies for decades. An example: In 1971, after severe internal crisis, Swedish bank Handelsbanken began to transform its organizational units into self-managed profit centers with clearly defined customer relationships and highly devolved responsibility for the results. Budgets, fixed targets, quotas, incentives and bonus systems, and indeed also the org chart, and central departments like marketing, product management and risk were abolished. Handelsbanken now has over 10,000 employees and it has consistently been Europe´s most successful bank for more than 42 years, in pretty much any performance indicator you can imagine. This bank´s branch network now consists of more than 700 subsidiaries, legally independent regional banks, and service departments. Autonomy of the bank's branches has been extended continuously since the 1970s. The company's main focus is on branch effectiveness, not on the profitability of individual products.

To monitor performance, Handelsbanken developed a compellingly simple control system within which teams work on the basis of relative performance measurement based on “real world,” not planned, performance data. Success is no longer measured according to negotiated, planned data, but relative improvement as measured using a limited number of key figures. To do this, the bank as a whole compares itself with its closest rivals. Similarly, regional banks assess their performance monthly and in comparison with other regions, and branches are compared with other branches. All targets, performance assessments and reporting systems are thus based on internal or external competition and continuous improvement.

Illustration 3: Ways of measuring, without actual-plan-variances, fixed targets, or plans

This 3-layer continuous ranking system has proved to be highly self-regulating and has required only minor modifications over the course of decades. It does not depend on any annual adjustment, hierarchically integrated planning, or internal negotiation. At the same time, it has dramatically increased internal transparency and responsibility of teams to act as if “the branch is the bank.” Employees are driven not by individual targets or group incentives; rather, the system appeals to employees' need to be valued and recognized for their role in helping the organization succeed.

Other larger, successful companies such as Southwest Airlines, Toyota, W.L. Gore, Guardian Industries, Aldi, dm-drogerie markt, or Egon Zehnder International have developed models similar to the Handelsbanken approach. There are enough examples of pioneering companies to give us the courage to overcome traditional thinking and ways of dealing with performance, Now that competitive benchmark date is becoming widely available, and to organizations of all kinds and sizes, at much lower cost than ever before, we have ever more reasons to search for new ways to measure and improve performance more effectively: using real data, not invented numbers.

Niels Pflaeging is an entrepreneur, management advisor, influencer and speaker. He is founder of the international BetaCodex Network and author of the business bestseller Organize for Complexity, published in 2014. For five years, he was a Director of the Beyond Budgeting Round Table BBRT.  You can download Niels´ white paper “Making Performance Work” here. Get in touch with him through: @NielsPflaeging, or

Compass Raises Fresh Funding and Launches Compass Monitor!

We have two exciting news to share!

1. We raised more than 2 Million in a second round of funding from first institutional Investors including NEA, Profounders and Crosslink and strategic investors including Tom Glocer (ex-CEO of Thomson Reuters), Banca Intesa and Oliver Rothschild joining existing Compass investors, including Steve Blank, Allen Morgan, Roger Krakoff, Rhodium, Erik Jansen and Amir Banifatemi (see full list here: to fund our mission of minimizing business failure by providing automated, crowdsourced benchmarks and industry insights. This totals our investment to date to ~3 Million US Dollars.

See press coverage here:

2. We just launched Compass Monitor that allows companies to securely share selected data with investors, advisors or consultants. Compass Monitor pulls data directly from various data repositories (Google Analytics, Stripe, Quickbooks, etc.) to automate the continuous delivery of selected data. It saves hours of collecting sharing and reviewing data every week for the investor and entrepreneur.

One of our first beta tester Marcin Szelag from Innovation Nest said: "Compass Monitor solves a major problem for investors. On top of that it is easy to use and looks good."

See press coverage here:

If you like our work please help us with sharing the press coverage or tweeting about CompassMonitor. Click here to tweet: Compass increases total funding to $3mil and launches Compass Monitor for Investors and Advisors. 


Are you an engineer or data scientists?

The capital raise will fund the next phase of development to build an automated data refinery attacking complex engineering and data analysis challenges that have never before been solved in concert. Thus, Compass is immediately hiring hiring data scientists, engineers and business analysts. Check

Why should you join?

With a growing wealth of business data easily accessible, we have an unprecedented opportunity to learn about the nature of businesses and their ecosystems at scale. By bringing these new insight and transparency into the global business ecosystem we can fundamentally transform the way businesses are run and interact with each other. The key to success for a business lies in flexible resource allocation to focus on what matter most. The problem; its impossible to reliably interpret business metrics and market signals without reference points and industry insights. Thats what we are providing with Compass at scale - by crowdsourcing business performance data with a simple give-to-get model for businesses; and automating the analysis of the data to avoid expensive analysts.

The Compass (formerly Startup Genome) Tech Startup Salary Survey 2014

Hiring is one of the biggest challenges a company faces. In a recent article by David Smooke, 50 entrepreneurs shared their biggest hiring challenges, most of them expressing concerns around salary, equity and benefits for employees. Figuring out what to pay an early startup employee is difficult. This is a problem that we, at Compass, have faced in our efforts to expand our small team, and is often echoed by most of our users. The prevailing popularity of this challenge made us dig deeper into the issue and we are determined to find an answer by conducting a survey for employee salary and equity in tech startups.

Employers: Click here to take the survey

Tech employees: Click here to take the survey

Salary + Vision + Equity = Compensation. Sam Altman in his blog says, “You should be very frugal with nearly everything in a startup. Compensation for great people is an exception.” But what does an exception mean? “The best people want to work on a mission they believe in, and make money,” says Mark Zuckerberg. What should you pay to people who are onboard with your mission? How do your compensation packages compare to your peers?

With limited resources, startup founders must ensure that they both retain adequate equity and remain competitive in the market. At the same time, they must also compete with other startups that cater to similar markets but have raised huge amounts of funding. This can be even more challenging if you are bootstrapped. For young companies there is a lot of uncertainty each time they make an offer to a new hire.

There are many blog posts that try to formulate a solution for this problem and many founders have shared formulas to determine compensation packages, but companies rarely share specifics in order to maintain their employees’ privacy. There is no comprehensive startup compensation guide out there.

Recently, Buffer published a blog post giving away the formula they use to determine the salary+equity packages of all its employees. But does this formula apply to all companies? And, what do you do till you reach that level of structure in your company that you can use a formula to determine salary or equity?  

In an effort to help companies, from early stage to scale, be more successful with their hiring, we want to make this process more data driven, and provide a guide to the market.

Earlier this year, we conduct a salary survey of startup founders. With participation from more than 11,000 startup founders from across the world, we were able to benchmark what founders in different startup ecosystems pay themselves. The results of this survey were published on many notable websites including The Next Web and Inc.

We are excited to announce that we are conducting a similar survey on tech employee compensation data in order to chart a benchmark of salary and equity of tech startups. All data specific to your company will be excluded from our published results, in order to maintain the privacy of your employees.

You can contribute and help your peers figure out how to effectively compensate their employees by filling out this survey:

Employers: Click here to take the survey

Tech employees: Click here to take the survey

This data will provide you with insight on your compensation versus industry standards. We aim to bring transparency into the global hiring ecosystem by creating a go-to guide for tech companies to help make data driven decisions for tech employee salary and equity.

Thank You,

Bjoern Lasse Herrmann

and the Compass Team

Articles referred to:

Going Public Has Changed Mark Zuckerberg…Finally – Pando Monthly

50 Startup Founders Share Their Biggest Hiring Challenges – Smart Recruiters

Introducing Open Salaries At Buffer – Buffer

How To Hire – Sam Altman

*This survey is for the engineering team of the startups. We will be conducting a survey for non-tech teams of tech startups very soon*

Kicking off the 2014 Startup Ecosystem Report

I am super excited to once again be part of this amazing project to help entrepreneurs worldwide to gain a bigger voice, provide policy makers with better decision-making tools and ultimately expand the global economic impact and job creation driven by startups.

To do this as effectively as possible, we will need the participation of the whole community, and we want to make sure the output is everything you want it to be. Please help us improve the report by filling out the following survey.

Thank you!

Danny Holtschke (@dannyholtschke)

My story: How I joined Compass

While working on my Master Thesis in 2011, I met Bjoern Lasse Herrmann (CEO of Compass) in Maastricht, Netherlands, where he introduced Startup Genome’s findings to a group of students and I was blown away by the power of aggregated data to solve real-world entrepreneurial problems.

But I was young and naive thought the best path to becoming an entrepreneur was to be a consultant, since they seemed to know everything. (#illusion) I found myself so disappointed in my career choice, I quit after three months, flew from Berlin to San Francisco (at my own cost, taking all my own risks) and joined Bjoern, Max and Ertan in Silicon Valley to work on the Startup Ecosystem Report 2012. I wanted to learn from the very best and be immersed in their thinking every day -- and I wasn’t disappointed. I met and absorbed the thinking of tons of entrepreneurs, policy makers, investors and service providers in startup hubs around the globe.

After successfully launching the report in October 2012, I went back to Berlin, proposed to my now wife and started Spotistic. If my days are not filled with guiding the Berlin accelerator Startupbootcamp teams in their journey to market and customer discovery or the Startup Ecosystem Report 2015, I work on StartupGeist - Learn HOW to Start & Better Build a Startup.

- Pic from Startupbootcamp Work in Berlin, 2014 -

And I’ve watched as the last two years have brought major changes, even in my home town of Berlin. Many new accelerators (Hubraum, Google, Microsoft) and incubators have popped up, governmental initiatives for funding have been introduced and successful startups have been launched and exited. The very same holds true for London, Paris, Madrid, Barcelona, Warsaw, Prague, Vienna, Amsterdam, Copenhagen and many many more cities around the globe. Startups are not the ‘new’ kids on the block anymore.

Several factors have lead to an explosion of startups. The Economist (2014) describes this trend as a Cambrian explosion of digital startups, resulting in an amazing variety of services and products that penetrate and change every corner of the economy. Some speak of the "reinvention of capitalism" (Porter & Kramer, 2011). One of the reasons is that the costs for starting a business have dropped enormously. Platforms such as Amazon cloud computing help entrepreneurs host applications for less than a tenth of the original cost. Apple's App Store or Google's Play store allow entrepreneurs to make use of the Internet’s benefits over traditional channels to offer their products and services worldwide. The knowledge to build businesses and products is more democratized than ever and available to anyone who has access to the Internet. That alone increases the number of startups tremendously.

In addition, traditional innovation processes are replaced by new ones (eg slow, linear waterfall methodology by faster, more flexible iterative product development). The Lean Startup movement (Eric Ries, 2011) and Customer Development (Steve Blank, 2010) have played an important role in successfully bringing ideas to market. These new innovation processes and modern tools for business model design (Alexander Osterwalder, 2011) help entrepreneurs to validate potential markets, quickly create prototypes and win paying customers. Today, innovation happens because of startup hubs, networks, clusters and governments have a better understanding of how key stakeholders should work together. For instance, policy makers have come to understand that startups are innovation enabler and job creators in our economies (Kauffman study, 2010).

We are experiencing the Entrepreneurial Enlightenment.

Startup hubs will only mature and increase their economic importance. But to ensure the greatest possible societal benefits from this economic boom, we need the energy, ideas and data of the world’s entrepreneurs to help drive us in the right direction. We invite you to participate in this movement and once we begin collecting data, you can help out in two critical ways.

  1. Contribute your own knowledge and experience to the report

  2. Help spread the word with startups around the globe

You will be helping your fellow entrepreneurs around the globe, and on their behalf, we thank you.


PS: If you’re interested in sponsoring the report, please contact

Compass Monitor Launches Early Access Program

Consultants, investors, accountants and bankers waste half their time chasing and formatting their client’s data, then looking for reference values to pinpoint problems before they can put their expertise to work. For the software businesses they support, this situation is equally imperfect, requiring time-consuming cycles to provide data and leading to less relevant advice and slower access to capital.

Today, Compass announces the first solution designed to give B2B service providers continuous access to key data across a portfolio of clients, along with the relevant benchmarks and industry insights we're known for, launched in a new dashboard product we call Compass Monitor, allowing access to critical information for a portfolio of businesses.

“After launching Compass, we learned many of our biggest referrers were consultants, advisors and investors who found Compass an invaluable tool for serving their many customers,” said Bjoern Lasse Herrmann, CEO of Compass. "So we built the Compass Monitor product to provide an easy way to track a portfolio of businesses. Still, even we were surprised by the level of interest. Before any announcements, we already had 400 companies on the waiting list, including partners from almost every large venture capital, consulting, accounting and market research firm.”

Despite the growth of cloud-based systems, data collection for strategic service providers—including consultants, investors, accountants and bankers—remains a startlingly manual process of emailed spreadsheets, inconsistent formatting and delays. Once received, the data is still missing the context of relevant benchmarks, key to understanding rapidly changing sectors such as software.

Compass Monitor provides advisors with a simple way to access and monitor all of their customers’ performance results in one place, with real-time data collection and standardized formatting. B2B service providers can therefore focus their valuable time creating value rather than trudging through spreadsheets. Customized dynamic benchmarks will be added shortly, allowing advisors to provide more specific and actionable insights than ever before.

Easy data access. Compass integrates with more than 30 common SaaS business platforms—from Quickbooks to Salesforce to Google Analytics. Instead of time-consuming manual data dumps, it only takes a few clicks for a client to set up automated data collection and access. The advisor gets real-time information in the same format across clients, displayed in a dashboard designed to quickly spot issues and opportunities.

“In the cloud computing era, you’d be stunned how time consuming it is to stay on top of performance data,” said Phil Morle, Co-Founder and CEO of Pollenizer Global. "I see Compass Monitor not only as a solution for tracking, but also for board meetings. If we don’t have to reinvent the wheel collecting performance data and debating anecdotal comparisons, we can spend our time focused on strategic opportunities and solutions."

Critical data context. While the first step is to see the data, it can be impossible to interpret effectively without contextually appropriate benchmarks. For a certain type of company at a certain stage of development, how does this growth rate compare to the median of similar companies? Bounce rate? Customer acquisition cost to lifetime value ratio? A few large data firms manually gather data for benchmarks, but these are too expensive, time-delayed and limited in scope to be useful for 99% of advisors. Compass is the number one software business benchmarking engine, with crowdsourced data on more than 30,000 companies, and the ability to provide customized peer groups for highly relevant comparisons.

“Looking at data without the context of benchmarks is like knowing you're driving 100 miles an hour without knowing the speed limit,” said Richard Riedmayr of Emporias Management Consulting. "Compass Monitor will let me be far more effective at helping clients set appropriate goals, identify issues and allocate resources.”  

Service providers who wish to register for the private beta of Compass Monitor can do so at

As always, software businesses can get their own custom business benchmarks at

Are you growing fast enough?

This is a post by Cheyenne Richards, head of marketing for Compass and former VP of Marketing for

Once upon a time there was a brilliant startup founder who hit upon a great idea, built a product, immediately hit exponential growth and went on to become a billionaire icon.

Who was the lucky founder? Facebook’s Zuckerberg? Groupon’s Mason? AirBnB’s Blecharczyk?

The answer is none of the above. This account is a fairy tale, imbued with as much fantasy as a Grimm’s bedtime story, yet arguably a tale that is at least partially responsible for the vast majority of startup failures—via unrealistic expectations.

We can be forgiven for crafting compelling narratives: As humans, our neurobiology demands it. Tens of thousands of years of evolution developed stories into the vehicles by which our brains derive meaning from the world. If the cavemen had shared data around the campfire, things might have turned out differently.

The problem happens when all the soft nuances are shaved off the story and it hardens into myth. Fine distinctions get warped into broad generalizations and real meaning is distilled to a simplified headline. Currently, myths such as these encourage founders to attempt growth before their business is ready, leading as many as 74% of high growth internet startups to fail due to premature scaling.

This number is so large it can initially be challenging to believe, yet one ultimately finds this incredibly common mistake goes a long way to explaining the dismal 90% failure rate of startups. The lower one’s burn rate, the longer one can survive, using every opportunity to pivot as necessary to achieve a fit between product and market. The higher burn rates of startups pushing for scale take away the safety net.

Of course, there is nothing wrong with growth. The primary distinction between a small business and a startup is the expectation of high growth—or as Paul Graham put it in one of his essays: Startup=Growth—but data shows that attempts to scale must be appropriately timed. Serial entrepreneur Jim Pitkow defined the concept very succinctly: “Premature scaling is growth in anticipation of demand instead of demand-driven growth.”

So the billion dollar question—literally—is when is a startup ready to scale? Until recently, founders have had no objective way to know.

Over the 20 years I’ve spent in marketing, one of my most memorable leadership experiences came while working for a startup that eventually achieved a successful IPO. Sitting down one afternoon with the CEO, I thought I knew our data inside and out: customer acquisition cost, lifetime value, retention, spend, headcount. In fact, I was feeling particularly proud that we’d achieved a user growth figure significantly better than prior years. Yet when I mentioned the number he asked the best possible question, a simple one that left me utterly stumped: “Is that good?”

In one of those lightning bolt moments, I realized that all my detailed internal analysis may have been useful for managing our marketing department, but not leading it. I only knew our growth rate was better than last year, but did that put us in the the 90th percentile of our peers or in the 10th? Did I deserve a pat on the back or a kick in the behind? I had the data, but was missing the most important element: context by which to make sense of it.

I was not alone. For mature industries, growth benchmarks are widely available, but for small and medium businesses trying to set targets or plug figures into a business model, finding a good benchmark for growth has been next to impossible.

In place of relevant benchmarks, founders and investors often encounter myths presented as fact: 22% week-on-week growth for Facebook, 20% for Groupon and 17% for AirBnB. What’s extraordinarily difficult to find are the nuances behind those stories. AirBnB founders spent years getting themselves into credit card debt (then selling political-themed cereal to get themselves out) before their storied growth curve began. Groupon was a struggling activism engine that tested coupons as a skunkworks project to keep the lights on before they pivoted to real growth. Facebook was a side project for Zuckerberg who initially accepted ad revenue to offset the $85 per month server space he rented.

Why does myth and uncertainty lead to failure? Founders are consistently under intense pressure to scale, but have few tools beyond their own instincts to decide if they’re ready. Investors want to see a growth curve. The head of sales wants to hire a team of five. Marketing needs more budget to beat AdWords competitors. Without benchmarks to provide an objective perspective, it’s no wonder so many startups scale too fast. But what if founders weren’t blind to their performance relative to peers? What if they could see an abnormally low retention rate that identified a product issue needing to be solved before the big ad campaign began? Or a lower than average close rate pointing to a valid need for more sales staff? Or that peers relying more heavily on PR achieved better results than pay-per-click anyway?

Startups that wait for the right time to scale have much higher rates of both survival and success, whereas those likely to fail overspend on customer acquisition, hiring, product development and several other key metrics before they’re ready.

The graph below demonstrates that those that those who start strongest are not necessarily those who finish strongest. Here we can finally bring in a fairy tale that is valid for comparison: that of the Tortoise and the Hare.

Startup failure rates aren’t just a problem for entrepreneurs or Silicon Valley. The Kauffman Foundation Study showed that net job growth in the US was driven entirely by technology startups. Thus, it is not a stretch to say that if we could improve the success rate of startups by giving founders context about when to scale, the economic future of the country could be significantly improved. Even the globe.

To meet that need, Compass has built a benchmarking engine to allow startup founders to compare themselves to relevant peers, based on multiple criteria. Our mission is no less than to shine the light of transparency into the dark corners of myth and uncertainty, to provide a platform to allow founders and investors to access the critical context they need to make effective strategic decisions. Our 30,000+ CEOs now have a simple tool that helps answer the most fundamental question—“Is that good?”—with real-time benchmarks against a customized group of peers.

Outside the tool, we can provide aggregate figures which are less uniquely relevant, but still provide critical transparency into an otherwise opaque world.

The median user growth rate for startups is 9% per month and those in the 90th percentile hit at least 65.2%.

Having this clear range is a good first step, but to make decisions with figures aggregated from thousands of startups with different customers, business models, products, acquisition channels, user bases and levels of funding would be about as effective as blending all the food in your fridge together and calling it soup. You can forget talking about the nuance of flavors when you’ve got mustard, peanut butter and last week’s burrito in the same bowl.

So here is a more refined breakdown.

User growth by user base

In the graph below, we broke down the growth rates of software businesses by the size of their existing user base and displayed both the median and 90th percentile values. What can we learn from this? First is a 5-10x difference between the median and the fastest growers, which shows significant variation in acceptable results. We can also see some trending, where median growth rates tend to peak around 1000 users but the fastest growers keep getting bigger until at least a million.

User growth by acquisition channel

Here we see data from the ten most popular acquisition channels for startups (listed in order of popularity). Again, we see significant variation from the median to the fastest growers, as well as among channels. 

User growth by funding level

Another interesting perspective on user growth is to look at the data broken out by funding levels. For those who’ve received some level of funding, the following breakdown represents the user growth they are experiencing.

The most heartening thing about this graph is how similar it looks to those above. The median growers are around 9% per month and the fastest growers are 50-60%, showing that plenty of investors are looking at other factors in addition to growth rate when funding companies.

Of course, we are still looking at aggregates. You may be an enterprise software company for whom 10 corporate users generates significant revenue, comparing yourself to a freemium mobile app who needs a million users before they break-even, or vice-versa. What you really want is not data from thousands of startups but the 50-100 that are relevant to you via your customized Compass peer group.

Using Compass, I can finally answer that our growth rate at that previous company was in the 80th percentile of our relevant peer group and 3x the median of our peers, so yes—pretty darned good. I wish I'd had access to that information back when it would have been helpful with decision-making.

Luckily, leaders today have more tools at their disposal. Finally, we can move past the fairy tales and embrace the nuance by providing context to our data. Welcome to the new world of growth: measured through the lens of real-time, relevant benchmarks.

State of SaaS 2014 and its Challenges

by Bjoern Lasse Herrman, CEO of Compass

I recently gave a presentation in front of leaders from many of the SaaS players at The Small Business Web Summit. The feedback was so positive — clearly many people are struggling with the same issues — that I decided to make the presentation available to everyone in the SaaS community.

As a SaaS business ourselves, those of us at Compass are intimately familiar with both the unprecedented opportunities and heavy challenges in our market. But we also have a unique perspective to offer — our own data.

In the 10-15 years since the birth of SaaS as an industry, it’s now been planted firmly in the mainstream of conversation, but it’s disruptive wave is still getting started.

When we look into Compass data we see that nearly half of SaaS startups have received funding, which indicates a significant amount of investment capital being channeled into the category. There’s a clear reason why. Gartner forecasts the SaaS market will grow at 20% through at least 2020, almost 3 times as fast as software overall, and there remains ample opportunity for greater global penetration over time. Salesforce represents the shining star of possibility, consistently growing at more than 30%.

At the same time, at just 17 billion dollars, the SaaS pool is still relatively small and the field is very crowded. While Compass data indicates that half of SaaS companies are profitable, the statistic also measures a push for profitability over growth, often limiting size. Of all SaaS companies in Compass, only 7% achieve even 10,000 users.

The biggest challenge is distribution. Our data shows SaaS companies rely heavily on direct sales — at nearly twice the rates of every other channel, but can afford only modest sales teams of 1 or 2. The vast majority pay nothing for marketing or advertising.

This means many salespeople out there fighting, one by one, client by client, for the same turf. These crowded market challenges are also driving a push away from SMB audiences and into more lucrative enterprise markets. But it is primarily the packaged software industry titans that dominate SaaS revenue — Intuit, Oracle, Adobe, Microsoft, Google, SAP.

One can think of this as a David versus Goliath scenario, except that the David’s are fighting each other. The Goliath’s may not be as nimble, in many cases their products are inferior, but they have the support of an entire distribution ecosystem — from resellers to channel partners to consultants and trainers — who are dependent on the horse they bet on winning.

Enterprises, then, aren’t just larger small businesses. Their needs run far deeper. Any software solution must integrate effectively with multiple legacy systems. Security is a tremendous concern. Training programs must be rolled out. A small business may make decisions for the moment, but enterprises must have confidence in the long-term viability of the vendor.

All of this goes to reinforce the fact that history tells us, sometimes painfully, that the best product does not always win. The best distribution method does.

So returning to the David side of the equation, what can SaaS businesses do to beat the Goliaths?

Target the weaknesses and work together:

Focus on CRM, the fastest growing enterprise market

Specialize in mobile technology that is outside of the core knowledge base of Goliaths

Make liberal use of partnerships, the least expensive growth channel by far

Cross-sell, not just for revenue, but to build distribution networks

Scale fest and build a platform

Band together. Channel partners increase distribution and both scalability and portability attract enterprise buyers.

Alone, the David’s have a hard time competing. Together, they can win.

Compass was founded to bring Moneyball analytics to the 99% of businesses for whom the major information service providers of the world are either too expensive, too slow, irrelevant, or all of the above. We solve these challenges with crowdsourcing. Data from over 30,000 businesses enters into our warehouse through common SaaS business platforms such as Google analytics, Quickbooks, Salesforce and many others. Business leaders feed their own data in and in return get an immediate and reliable perspective about how they are doing on key performance indicators relative to their custom peer group. This allows for instant problem identification and more targeted strategic priorities. You can get your own benchmarks at

What determines founder salary levels?

One week ago, released results from a survey that showed that 73% of startup founders make less than $50k per year and entrepreneurs around the world have been talking about it ever since. To answer some of the many great questions posed, we went back to our data to bring you more answers.

For all data analyzed, current monthly revenue is the greatest predictor of founder salary, with a more than 3.5x difference between the lowest and highest tiers. Until a company makes more than $10k per month in revenue, the average founder salary does not break the $50k mark, and not until the company reaches over $1 million per month in revenue, does the founder salary break $100k. 

This may relate to the all-important burn rate equation. More revenue coming in means more money available to pay back out again without impacting the long-term sustainability of the company. This would tie in closely with Compass’ earlier findings on premature scaling.

One of the most oft-asked questions related to how much a founder’s salary changed by age. We found this is indeed a significant factor in salary, with older founders paying themselves as much as 71% more than younger ones, though the highest salary age range still barely breaks $60,000 per year.

Perhaps even more significant is the fact that 78% of founders are under the age of 40. This may speak to the rigors of entrepreneurship, conflicting family requirements, ageism, technology literacy or a number of other factors we can leave to others to debate. In any case, it may help provide additional perspective on lower salary needs.

Also contrary to the perception of the serial entrepreneur, Compass data found that 67% of founders were working on their first startup, or at least the first in a significant capacity. (Founders were asked to clarify the number of previous startups where they had been one of the first five team members and the company had raised at least $100,000.)

As shown in the graphs above, since founder salary grows by experience level. This is another reason for low average salaries overall.

In the same way Compass found salaries increased by product phase in the previous report, so to do they increase by team size.

And in the same way most founders are working on their first startup, so too are most teams comprised of five or fewer people.

What are your thoughts on founder salaries? What levels seem appropriate to you? We'd love to hear your thoughts and opinions.

Startup and software leaders can also discover their own benchmarks at

73% of Startup Founders Make $50,000 Per Year or Less

Our survey data shows startup founders are living lean, paying themselves low salaries. Even in Silicon Valley, 75% of founders make less than $75,000 per year.

In 2008, Peter Thiel, venture capitalist and co-founder of PayPal, was the first to publicly propose the idea that higher founder salaries are correlated with lower levels of success. The reason is that founders who sacrifice everything for their startup are more dedicated to their idea, set a strong example for their team and have lower burn rates. More than five years since, the debates continues.

Compass analysis has now made publicly available—for the first time—evidence-based confirmation of this strategy’s validity, with data from more than 11,000 global startups.

We received many questions from founders on the subject of salary, due in part to the extensive online opinions, and wanted to provide fact-based answers back to the community. We don’t expect this will end the debate, but will hopefully help focus it with data. Meanwhile, it seems founders are living lean indeed, and that such frugality is likely to accelerate their success. This also ties in closely with to our previous findings on premature scaling.

The data shows the vast majority—73% of founders—pay themselves less than $50,000 per year, whether their company has been funded or not (not including any ownership stake or additional benefits). 

In Silicon Valley, even with the reportedly highest rents in the U.S., 66% of founders pay themselves less than $50,000 per year and a full three quarters make less than $75,000.

Average salaries ranged from a low of $30,208 in India to a high of $72,363 in Australia, and as a ratio to funding ranged from 1.98% in Silicon Valley to 4.8% in Australia.

Below is the breakdown for a number of startup ecosystems.

Survey details: 11,160 founders provided their salary ranges in $USD equivalents. For this particular survey, we did not ask for options or additional benefits. All null values were removed. Averages were estimated based on the midpoint of each range and applied equally to all geographies. All ecosystem breakdowns include responses from at least 75 companies.


Startup and software leaders can discover their own benchmarks at

Last note: this story has created a lot of great debate and we're happy to write a follow-up next week to address the many questions, comments and thoughts we're hearing from all corners, so stay tuned.

This post was updated on 21 January 2013 to use consistent blue graphs rather than multi-colored.