Case Study: Building an Emerging Market Model

BUILDING AN EMERGING MARKET MODEL | 2

“The kind of market-size forecasts that come out of even the most highly respected firms—the ones that get quoted in the press as showing the bright and promising future for some new technology or product—are, by necessity, rooted in multiple assumptions.”1

– Geoffrey A. Moore, Crossing the Chasm


INTRODUCTION

An advantage of working in a well-established market is that detailed analyst reports—with

market size, growth rate, competitive landscape, etc.—are readily available from highly

regarded firms. At the other end of the spectrum, new disruptive and discontinuous

innovations may present a “low-data situation” where, according to Geoffrey A. Moore,

“informed intuition, rather than analytical reason, is the most trustworthy decision making tool.”2

I’ve worked in both situations, but the majority of my corporate and consulting experience is

in markets between the two extremes: A new market that is 1) a result of a new segment

emerging within a larger established market, 2) the convergence of two technologies to form

a new category, or 3) a combination of these two situations.

Examples include Micro-Fuel Cells (the convergence of portable power and fuel cell

technology), Transaction Anomaly Detection (user behavior monitoring emerging as a

security software technology for online authentication), and a Laboratory Information

Management System for Next-Generation DNA Sequencing (the application of data

management software for basic and applied genomics research).


THE PURPOSE OF AN EMERGING MARKET MODEL

An emerging market model can help you persuade key parties that your company is viable.

Investors – Venture capitalists and other investors want to know where your company

fits within their portfolios (is there potential synergy, but not competition, between

your company and others), and they want some degree of confidence that there is

growth potential sufficient to provide a desired return on their investment.

Analysts – Inclusion in a report from a major analyst firm, such as Gartner, is the

"Holy Grail" for many technology startups. However, if you don't fit one of the pre-

existing categories, you have to convince the analyst firm to create a new technology

category. At a minimum, that will require presentation of a credible market model that

includes the market size, growth rate and competitive landscape.

Employees – Many emerging-market companies begin with an entrepreneur’s idea; not

a well-developed business plan. Early on, the entrepreneur can recruit like-minded

employees. As the company grows, a market model can be helpful in recruiting more

pragmatic employees who want to better understand the company’s risk-reward profile.

And a market model can help show employees that business goals are realistic and

achievable, and that the company is successfully progressing towards its goals.


BUILDING AN EMERGING MARKET MODEL

The most recent market model I’ve developed is for laboratory information management

system (LIMS) software to support next-generation sequencing (NGS) for basic and applied

genomics research. The methodology is based on best practices and personal experience.

The case study information is specific to the emerging market segment. I have used actual

information where it is publicly available, and I’ve omitted or altered proprietary information

to preserve confidentiality.

The market model was initially developed in late 2010 and early 2011, and was periodically

updated throughout 2011 and into early 2012. It was used for several purposes including:

• Securing $2.5M in short-term debt financing, and raising $8M in equity funding.

• Identifying the target market (core labs), and developing a go-to-market strategy.

• Aligning all departments and employees across the company.

The graphic on page 6 shows the framework for developing the market model. It started

with a wide-angle view of the scientific software market and zoomed into the emerging NGS

LIMS market model by analyzing market intelligence from the global LIMS market and

global NGS instrument/laboratory market and combining it with proprietary knowledge.


EMERGING MARKET MODEL DEVELOPMENT FRAMEWORK

Scientific Software Market

LIMS Market

NGS Market

Proprietary Knowledge

NGS LIMS Market


CASE STUDY | GENOMICS LIMS EMERGING MARKET


GLOBAL SCIENTIFIC SOFTWARE MARKET

The global scientific software served available market (SAM) is about $2.2B with a

15% CAGR. Bioinformatics is the largest segment with the fastest growth rate.

Sources: Atrium Research, ELN Edition IV, 2009; Kalorama Information, Informatics in Drug Discovery: The Evolving Information Technology Market, 2005; ARC Advisory Group, Laboratory Information Management Systems, 2009; Business Insights, The Global Bioinformatics Market, 2009

!

Software Segments

SAM CAGR

Bioinformatics $1,099M 30%

LIMS $410M 4%

Cheminformatics $300M 0%

LIOC $200M 0%

ELN $110M 20%

In-silico Modeling

$90M -4%

TOTAL $2,209M 15%

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GLOBAL LIMS MARKET – SIZE

The global LIMS market is over $400M, and growing at about 3.5% annually to over

$450M by 2013.

Source: Global LIMS market size, ARC Advisory Group, Feb 2009

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GLOBAL LIMS MARKET – APPLICATION SEGMENTATION

The pie chart shows the global LIMS market by major application focus. Large molecule life

sciences (biology) applications are 6% of the total, or about $26M.

Source: Worldwide Survey of LIMS Users, Strategic Directions International Inc., Feb 2009


AN EXPLOSION OF GENOMIC DATA

In 1990, The Human Genome Project ignited a technological race in gene sequencing. High-throughput sequencing technologies are driving data generation and cost improvements at a rate even greater than Moore’s Law.3

!It took more than a decade and an estimated cost of $3 billion to publish the first draft of the human genome in 2000. Just over 10 years later, businesses are competing to sequence an individual’s entire genome in a matter of weeks for about $10,000.4

!The 1000 Genomes Project, the first large project to capitalize on next-generation sequencing technologies, deposited twice as much raw sequencing data into the GenBank archives in its first six months of operation as had been deposited into GenBank in the 30 years since its inception.5


NEXT-GENERATION SEQUENCING MARKET

The incredible improvements in speed and cost are driving large-scale adoption of next-generation sequencing (NGS) instruments by genomics labs—from 200 in 2007 to an estimated 1,900 in 2010 and over 5,000 by 2013.6

!Organizations are confronting the reality that new sequencing instruments running at capacity can generate more information in a single year than the total deposited in GenBank at the beginning of 2008.7

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DATA MANAGEMENT IS A MAJOR HURDLE TO NGS ADOPTION

In turn, industry analysis that once focused on the costs of sequencing genome data now focus on the challenges of managing it. Research by J.P. Morgan in May 2010 determined that 63% of NGS laboratory directors surveyed said that data storage, data management and informatics are the biggest hurdles to expanding next-generation sequencing.8

Biggest Hurdles %

Data management/informatics/storage 63%

General cost 17%

Sample prep/workflow 13%

DNA sample access 13%

Funding 10%

Quality and reproducibility 7%

Regulatory/legal constraints 7%

Capacity/access to more sequencers 7%


DATA MANAGEMENT SOFTWARE IS A TOP PRIORITY

Research by William Blair & Company in January 2011 determined that software and data management support is a top-three priority in selecting an NGS platform.9


NEXT-GENERATION GENOMICS LABS – LOCATION

About 73% of NGS labs are in North America, 18% in Europe and 9% in Asia-Pacific.

Source: William Blair & Company, LLC, survey, January 2011


NEXT-GENERATION GENOMICS LABS – NUMBER OF INSTRUMENTS

There are about 1,200 global NGS labs with the following breakdown in the number of instruments per lab.



NEXT-GENERATION GENOMICS LABS – FUNCTION

43% of NGS labs are individual (PI) academic labs and 41% are core labs.



NEXT-GENERATION GENOMICS CORES – LOCATION

About 66% of core labs are in North America, 20% in Europe and 12% in Asia-Pacific.

Source: Genome Technology, survey, March 2010


NEXT-GENERATION GENOMICS CORE LABS – OWNERSHIP

44% of core labs are academic, 38% are biopharma and 8% are government.



NEXT-GENERATION GENOMICS CORE LABS – CLINICAL

About 11% of core labs are CLIA certified and 85% are not.



PROPRIETARY KNOWLEDGE

One benefit of working in a small emerging market is that initial sales are often in the tens progressing to the hundreds, and the number of competitors is relatively small. It is feasible to obtain highly accurate and complete market-size and market-share information from your own win-loss intelligence.

Because there are relatively few competitors in the early stage of an emerging market, your company is likely to be aware of and involved in almost all competitive purchase decisions. Therefore, it is possible to support a market-size and market-share model with specific account name and price paid data from your win-loss analysis.

Because the emerging NGS LIMS market is being driven by the need to manage the explosion of data from NGS instruments (page 13), the NGS LIMS adoption curve should resemble the NGS instrument adoption curve (page 12), adjusted for multiple instrument purchases by individual labs (page 16).

The emerging market for NGS LIMS was constructed using adjusted actual market-size data from 2008 through 2010, and extrapolating that trend over the three-year period from 2011 through 2013, in line with laboratory adoption of NGS instruments.


NGS LIMS MARKET MODEL FORMULA

The formula for estimating the annual served available market (SAM) size for NGS LIMS for the years 2011, 2012 and 2013 is:

IB x ASPIB x 0.20 + NL x ASPNL

Where:

IB = installed base of NGS LIMS from prior years

ASPIB = average sales price of NGS LIMS installed base

0.20 = average annual cost of maintenance and support

NL = projected number of labs purchasing NGS LIMS in the calendar year

ASPNL = projected average sales price of NGS LIMS purchased in the calendar year


NGS LIMS EMERGING MARKET MODEL – MARKET SIZE

Applying actual data in $US for years 2008 through 2010 and estimated data using the formula on the previous page for years 2011 through 2013 produces the following market-size chart (the $US units have been removed for confidentiality).

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NGS LIMS EMERGING MARKET MODEL – MARKET SHARE

Applying actual data in $US for years 2008 through 2010 and estimated data assuming a 5% annual increase in market share for years 2011 through 2013 produces the following market-share (red) chart (the $US units have been removed for confidentiality).

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NGS LIMS EMERGING MARKET MODEL – SMELL TEST

As the quote at the beginning of this case study indicates, even market-size forecasts from highly respected firms are rooted in multiple assumptions. Therefore, the test of your market model is its consistency with known information and relevant market trends. Here are some essential “smell tests” that the model must pass.

The “S” Curve – The growth curve for a new market resembles a skewed s as market adoption progresses from a few high-priced sales during early adoption (base of the S), through accelerated mainstream market adoption (sharp ascending slope in the middle of the S), followed by a sharp decrease due to slowing sales and falling prices (leveling at the top of the S). Beware of the mythical parabolic curve (e.g., dotcom or housing booms), with an underlying assumption that the growth rate will not decline and prices will not fall.

Known Data and Trend Consistency – The pie chart on page 9 shows life sciences is 17% of the total LIMS market, and only 6% ($26M) is large molecule (biology). While NGS LIMS is the fastest growing segment of biology LIMS, in 2010 it was still less than the $26M total. And projected market size and growth is consistent with actual market-size data from 2008 through 2010 and the NGS instrument/lab (LIMS market driver) projected growth rate from 2011 through 2013.


NGS LIMS COMPETITIVE LANDSCAPE

The NGS LIMS landscape is composed of four competitive categories:

Category A – Companies that develop LIMS software specifically for genomics laboratory research, with a software product offering supplemented by a custom services group.

Category B – Companies that develop LIMS software specifically for genomics laboratory research exclusively through custom consulting.

Category C – Companies that develop LIMS software for large multidiscipline (different biology-based and chemistry-based analytical labs) enterprise applications. These competitors are rarely encountered outside of large research institutions that want a single LIMS vendor to serve multiple labs across the entire enterprise.

Category D – A custom LIMS developed as an application layer to an existing data-management software platform by laboratory personnel. This is most often encountered in academic labs where doctoral candidates and post-doctoral research assistants with some programming experience can be employed at very low cost.


NGS LIMS COMPETITIVE LANDSCAPE – RELATIVE MARKET SHARE

The pie chart shows relative market share for the three commercial vendor categories. In-house development is excluded because cost cannot be accurately determined. However, about 30% to 40% of academic opportunities are lost to in-house development.

85%

10% 5%

A B C


NGS LIMS COMPETITIVE LANDSCAPE – RELATIVE CAPABILITIES

The matrix shows the three categories of commercial software developers (in-house not shown), and their respective size (size of circle represents relative annual revenue) and capabilities relative to multi-purpose enterprise LIMS and NGS LIMS.


NGS LIMS COMPETITIVE LANDSCAPE – RELATIVE THREAT

While the large enterprise LIMS vendors (C) have significant capability, they have shown little interest in the NGS market, but this could change as market size increases. Custom NGS LIMS vendors (B) lack the capability to pose a significant threat. For now, the fight for market supremacy is among the dedicated NGS LIMS product vendors (A).


CONCLUSION

This case study describes the methodology used to develop the emerging market model. All publicly available data are displayed as they were in the actual market model. The market-size and market-share data have been omitted for confidentially, and the individual competitors have been grouped into categories, for the same reason (in the actual market model, seven individual companies were profiled).

As previously noted, the market model was initially developed in late 2010 and early 2011,

and was instrumental in several activities and events, including:

• Securing $2.5M in short-term debt financing in Q1 2011.

• Raising $8M in equity funding in Q3 of 2011.

• Identifying the primary market (core labs) and developing a go-to-market strategy.

• Explaining the focus on the NGS market to the board and employees.

• Aligning all departments and employees across the company with the NGS focus.

• 15 articles and interviews in target media between February 2011 and January 2012.


ABOUT THE AUTHOR

Bruce Pharr lives in the San Francisco Bay Area with his wife and son. He umpires little league baseball games, hikes in the Santa Cruz Mountains, eats good food, drinks good wine, reads, and indulges a passion for the arts.

As a marketing executive, he has a track record of increasing enterprise value by developing and executing successful product and marketing strategies, and by managing technological and organizational change. He developed the emerging market model described herein while serving as Vice President of Products and Marketing at GenoLogics Life Sciences Software.

He has held lead marketing positions at several private and public corporations, and he founded and led a technology marketing consulting firm, for over a decade, with clients ranging from startups to Fortune 500 corporations.


ENDNOTES

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!1 Geoffrey A. Moore, Crossing the Chasm: Marketing and Selling Disruptive Products to Mainstream Customers (Collins Business Essentials, 2006), 91. 2 Ibid, 92. 3 Stein, L. D. The case for cloud computing in genome informatics. Genome Biology 2010, 11, 207. 4 Batley, J.; Edwards, D. Genome sequences data: Management, storage, and visualization. BioTechniques 2009, 46, 333-336. 5 Stein, L. D. The case for cloud computing in genome informatics. Genome Biology 2010, 11, 207. 6 Third Quarter 2010 Earnings Conference Call, Caliper Life Sciences, October 2010, 16. 7 Holt, R. and Jones, S. The new paradigm of flow cell sequencing. Genome Research 2010, 18 (6). 8 J.P Morgan Equity Research. Next Gen Sequencing Survey, May 2010, 11. 9 William Blair & Company, LLC, Next-Generation Sequencing Survey, January 2011, Figure 24, 27. !

Case Study: Building an Emerging Market Model

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