MINNEAPOLIS — (June 27, 2023) — Flywheel, the leading medical imaging data and AI platform, announces it has raised $54 million in Series D funding. This latest round of funding was co-led by Novalis LifeSciences LLC and NVentures, NVIDIA’s venture capital arm. Microsoft also participated in the round, along with insiders Invenshure, 8VC, Beringea, iSelect, dRx/Novartis, Hewlett Packard Enterprise, Intuitive Ventures, Seraph, and Great North Ventures. Faegre Drinker Biddle & Reath LLP served as counsel to Flywheel in connection with the
financing.

“Flywheel’s products transform healthcare innovation by empowering organizations to efficiently and securely ingest, curate and share medical imaging data for accelerated research and AI development,” said Flywheel CEO Jim Olson.

The funding will fuel Flywheel’s continued growth in its two primary markets, public sector healthcare and pharmaceutical companies, while accelerating expansion in other markets, including providers, payers, system integrators, and software companies seeking to harness the
value of their data for AI development. This latest round of funding will also help Flywheel extend its global reach into key geographies, particularly across Europe.

Marijn Dekkers, chairman and founder of Novalis LifeSciences and former CEO of Bayer AG and Thermo Fisher Scientific Inc., will join the company’s board of directors.

“We are excited to lead this financing round at Flywheel,” said Dekkers. “We believe Flywheel’s unique software solutions enable the smarter use and interpretation of the vast amounts of information associated with large numbers of medical imaging scans. We are particularly excited about the ability of these tools to drive more efficient and faster drug development processes in the biopharma industry.”

“The application of AI has led to the discovery of new drugs, identifying patterns in disease, and improvements in patient care,” said Mohamed “Sid” Siddeek, Head of NVentures, NVIDIA. “Flywheel uses AI to unlock the value within medical imaging data, signaling the continued
benefit of applying AI across the healthcare industry.”

About Flywheel
Flywheel is the pioneering medical imaging data and AI platform powering healthcare innovation through streamlined medical imaging data management, curation and analysis. Flywheel helps organizations turn complex imaging data into analysis-ready datasets for accelerated research
and AI development. Flywheel offers comprehensive solutions for pharma companies, providers, payers, system integrators, AI developers and academic medical centers to get optimum value out of their data assets. Flywheel is an Invenshure-founded company headquartered in Minneapolis, with offices in the Bay Area, St. Louis, and Budapest. For more information on our mission and products, visit www.flywheel.io or follow us on Twitter and LinkedIn.

About Novalis LifeSciences LLC
Novalis LifeSciences is the investment arm of Novalis Capital Partners, a boutique investment and advisory firm for the Life Science industry. With a team of experienced operating executives from the Life Science industry, Novalis funds and advises visionary Life Science entrepreneurs.
For more information visit www.novalislifesciences.com

 

The Rise of Rapid Consumer Detection Technologies: A 2022 Outlook

COVID-19 has sensitized us to the burden of infections, illnesses, hospitalizations, and deaths that can result from living in a globalized world. At the end of 2021, nearly 150 million Americans were estimated to have been infected with COVID. Even for those of us fortunate to have not been infected or symptomatically ill, the nightmare has been around us. And given its high prevalence, the virus has almost certainly affected someone we know.

While the costs and disruptions from COVID are still being tallied – lives lost, schools closed, travel curtailed, offices emptied, and businesses shuttered – numerous start-ups are rising to not only tackle the pandemic but also prevent future ones. 

Their efforts have targeted not only COVID, but also other common sources of infection such as strep and urinary tract infection bacteria. This trend is motivated as much by the emergence of new pathogens as it is opportunities to improve detection speed, sensitivity, specificity, ease of use, and access compared to earlier over-the-counter and at-home tests, or make them available for personal use whereas until now they had been confined to labs. Examples of companies offering these new tests include EverlyWell, Cue, Proov, Poppy, as well as one of our portfolio companies, Allergy Amulet. 

With advances in physical chemistry, the science around rapid, point-of-consumption detection has been advancing quickly. Electronics and electromechanical device innovations are simultaneously enabling detection systems that are more compact and portable. Allergy Amulet’s first product is a consumer device that detects allergenic ingredients in food, helping those with food allergies better determine whether their food is safe. Future applications include toxin, pathogen, and pesticide detection. 

At Great North Ventures, we are excited to support entrepreneurs seeking to make the world healthier and safer. The rise of rapid, simple, point-of-use detection technologies promises just that.

Tech Sector’s Growth has Accelerated

It is no secret that during the pandemic, the tech sector is delivering stronger returns than other sectors.

As examples, underlying the stock prices, Zoom sessions increased from 10M daily in Dec 2019 to 200M daily in March 2020. Daily broadband usage in the US jumped from 13.2GB in March 2020 to 15.3GB in August 2020. Over the 10 years from 2009-19, US e-commerce penetration went from from 5.6 to 27%. E-Books have been flying off e-library shelves. Doctors are seeing patients via e-health. E-ceremonies are delivering graduations, weddings, and birthday events.

Communications, software, biotech, and e-commerce have been among the best performers. On the other hand, non-tech sectors such as airlines, cruise lines, casinos, and automotive, have receded. And in low-growth or stagnant sectors, the tech-enabled disruptors have grown the fastest. For example, in entertainment, witness the growth of streaming media at the expense of cable services. Or in education, witness the growth of e-learning enabled enterprises.


“Dow Jones Industrial Average Compared to NASDAQ Composite” (Data from Yahoo Finance, as of 9.06.20)

Pandemic as Change Agent

Why have Zoom, Twilio, Shopify, and Atlassian become runaway successes? The COVID crisis has boosted them more than most other companies: Zoom for everyone to run businesses, schools, events; Twilio for cloud communications; Shopify to find online growth while controlling one’s destiny compared to selling on Amazon; Atlassian to manage projects; and several others.

As humbling as it is to acknowledge this fact, while venture capital and venture firms are recognized as drivers of digital transformation, the pandemic has been a much bigger factor in driving growth. At Great North Labs we terminated our office lease and deployed reporting methods for our portfolio companies that enable electronic data transfer and analysis. We conducted our own 2020 annual meeting as an e-meeting. In lieu of serving hors d’ouvres at a live event, we used a local startup to send Giftbombs. As much as we have pondered these ideas in times past, the pandemic is motivating this digital transformation.

Where to Invest?

So, in this mix, where should we invest?

Venture capital has the potential of highest value creation of any asset class. All the big tech companies started as venture-funded startups. Imagine if you had invested a few dollars in them when they were young. The negatives of venture investments are that they are not liquid for several years. So, if you can invest and wait, this is a good option. Another key negative is that many investments fail. For this reason, investing as family and friends from a limited pool you have access to is riskier than from vetting across a large pipeline by a venture fund.

It is also true that innovative companies get started at the highest rate during downturns and discontinuities, such as the pandemic crisis we are in now. As a result, more than ever, the world is now teeming with start-ups building solutions to make the world better with high capital efficiency. And they are targeting every sector: healthtech with new drugs and vaccines; supply chains with secure ledgers; insuretech with more tailored insurance; fintech with better access to and management of personal or enterprise capital; foodtech for better food and access; mediatech for pervasive information and media access…you see the picture. Then there are startups enabling these companies: companies enabling training and placement of specialized workers; companies delivering customer service more effectively; companies providing remote accounting, legal, and marketing; and companies training and retraining workers for the future – in product development, customer service, accounting, marketing, demand generation, or anything else.

The world does not need more brick-and-mortar businesses sustained by PPP loans. They can reinforce or repair moats, but we will get better returns from supporting the young innovators. The world needs startups that build value in the post-pandemic world in capital efficient ways, and help the brick-and-mortar incumbents get a new lease on life.

The Decade Ahead

How long will this new wave of startups continue, and what is the period over which their value creation will deliver returns?

The impact of past pandemics – smallpox, yellow fever, bubonic plague – rippled through economies for decades, and caused permanent changes. Among other things, outcomes of past pandemics included industrial equipment for productivity increases to offset population losses, vaccines for health, social safety nets, and new fiscal and monetary policy. Many of these changes have now been part of our lives for decades and in some cases centuries.

In the current pandemic, we have already seen seismic shifts. Post-COVID, the seedlings of Silicon Valley are sprouting at an ever-faster rate in Middle America and many other locations worldwide. At Great North Labs, we believe venture investing and the creation of new enterprises will spawn a new productivity cycle that will permeate economies across the globe over the coming years and decades. In the widespread, tech-enabled economic recovery that we are already seeing, the current venture investment cycle which will seed new startups may well be among the more productive than its recent predecessors.

NOTE: THIS DOES NOT CONSTITUTE AN OFFER OR SOLICITATION WITH RESPECT TO GREAT NORTH FUND INTERESTS IN ANY JURISDICTION IN WHICH SUCH OFFER OR SOLICITATION WOULD BE UNLAWFUL. 

With approximately 500 attendees, uber-founder and CEO Navroop Sahdev and VP Heidi Cuppari conducted the outstanding The Digital Economist Roundtable at the World Economic Forum 2020 at Davos. Great North Labs was invited to the event to discuss the role of venture capital in economic impact, and I shared the fund’s experience and strategy.

Pradip Madan speaking at the World Economic Forum
Pradip Madan speaking at the World Economic Forum 2020.

The strategy starts with Fund I. The plan for Fund I is to invest in roughly 30 companies. We anticipate these portfolio companies will raise a total of ~$200M from co-investments as they grow. With that total and, for example, a 500% return over the life of the fund, we would build ~$1B in market value. By motivating LPs with successful exits to reinvest in subsequent funds, this builds a cycle of growth.

In the course of raising and investing Fund I, we gained valuable experience in developing relationships and aligning incentives. Great North Labs built an ecosystem of 200+ investment partners, 60+ advisors, and developed relationships with universities, regional economic development organizations, government, and innovation catalyst organizations such as Singularity University. To develop local talent, we founded a startup school that educated 200+ on startup entrepreneurship, regularly provide office hours and mentorship to entrepreneurs, and worked with, trained, and hired college students.

Regional entrepreneurs prefer to raise money and grow in their communities, and investors prefer to invest within the region where regional VCs are available. By leveraging our foundational work from Fund I, our second fund could bring 2-3X the co-investment dollars and returns. Over 3-4 decades, this is how investors built fortunes and turned the farm economy of Silicon Valley into one of the world’s most prosperous regions. 

While continuing to lead and co-invest in Seed Stage through B Rounds in Fund I, we will raise Fund II. This will create investing continuity and maintain dealflow, synchronicity with the local ecosystem, and co-investor relations. By creating a cycle of growth and re-investment, our goal is to create prosperity in a similar fashion as Silicon Valley, here in the Upper Midwest.

Over 10,700 venture-backed companies received a combined $136.5 billion in funding in 2019, and the year saw double the exit value of 2018.[i] As stocks, real estate investments, and venture capital reach record highs, what are investors thinking about where to invest?

The answer depends on the type of investor:

Is this a good time for venture investing?

If the economy continues to do well, venture investments will do well. If the economy falters or if there is a stock market correction, this may still be a good time to invest in venture capital.

This is because stock market corrections (and corrections in the real estate market, which usually follows the stock market) follow business cycles, which can last 4-7 years. Venture funds usually invest over a 9-10 year investment cycle (i.e., a 5-6 year investment period followed by a 4-5 year harvest period). A slower business climate or stock market correction ahead could well be bracketed within the life of a new fund. And if needed, with due approvals from the limited partners, venture funds can extend their term to time their exits better.[vi]

Is there benefit in investing in venture funds in down cycles?

Let us look at the dynamics of different asset classes in downturns.

  1. Real estate – During the 2008 financial meltdown, real estate crumbled. As people lost their jobs, renters could not pay their rents, and property owners could not cover their mortgages. As defaults grew, real estate prices dropped. The Case-Shiller index dropped from 195 in 2005 to 116 in 2011.[vii] Considering the leverage of real estate investments, the losses for investors were much higher.
  2. Stocks, ETFs – The stock market similarly took a serious hit. The DJIA dropped 54% from 14,164 to 6,469 over 17 months.
  3. Venture capital – From Q1 2008 to Q1 2009, venture funding fell by 50% nationally to $3.9 billion (Dow Jones Venture Source).

Why did venture capital fare better than real estate or stocks?

First, lean times promote capital efficiency. As is often heard, recessions are the best time to start new companies, which is where early-stage venture capital is focused.

Second, venture capital firms mark up or mark down their investments over their life cycle. However, as actual valuations are pegged only by liquidity events, the real IRR is not known until the investments achieve liquidity. During the holding period, capital-efficient companies, and venture companies that focus on capital efficiency, do well, i.e., are counter-cyclical. They suffer fewer dislocations during downtimes. They can maintain their strategies, continue to do business as usual, and get ahead of those that slow down. Employees of such companies are more secure and loyal. And if needed, high-quality talent not available during good times can be hired, with loyalty that again pays dividends over the long term.

The capital efficiency of the upper Midwest

Companies in the upper Midwest inherently tend to be capital-efficient because there is less capital available. Similarly, smaller funds such as there are in the upper Midwest are inherently more capital-efficient, as they have less to invest.

44% of venture capital flows into Silicon Valley.[viii] This sets the consumption set-point of Silicon Valley companies at much higher burn rates than in regions where availability of venture funds is limited. The relative lack of available capital in other regions, including the upper Midwest, instills caution in spending.

Employee wages

While most other expenses are comparable across the US, with legendary real estate prices, Silicon Valley employees cannot survive at less than Silicon Valley wages.

This is not true in the upper Midwest. Though other expenses are comparable, housing costs may vary from 1/3rd to 1/10th of the Bay Area, enabling much greater capital efficiency for employers. For example, Google employees can buy 5 houses for the price of one by moving to one of Google’s locations across the country.[ix]

Figure 1. The real estate cost advantage of the upper Midwest compares well against not only the most expensive regions in the US, but also against what may be incorrectly perceived as lower-cost overseas regions (e.g., China). Seven cities in China and an equal number of cities in the US are listed above Minneapolis.

Fold? Hold? Or double down?

Not only can capital-efficient companies continue without disruption during slow times, given the lag between investment and market benefit, those that increase their investment can emerge even stronger in a recovery.

Intel applied this counter-intuitive strategy across many recessionary cycles, and invested several billion dollars in down cycles.[x] When their new semiconductor fabrication capacity resulting from these investments came online a few years later, their timing coincided with market rebound. On the other hand, competition (e.g., Atmel, Fairchild, Intersil/GE, IBM, Motorola, Raytheon, and several others) weakened from retrenchment and lost market share. As the industry consolidated during down cycles, Intel gained market share, and cumulatively over several cycles, emerged as its leader.

Some investors may feel that liquidity is useful during a downtime. Others argue against it, as getting out of the game when entrepreneurs are especially capital-efficient has a higher opportunity cost, and to use the Intel analogy, puts the winners further ahead of the losers. According to a prominent Silicon Valley investor, “you got to stay in the game”. At these times there are opportunities to go one step farther and double down.

Are smaller funds better than larger funds?

The statistical odds of a unicorn (company valued at over $1B) are lower than, say, of a ‘deci-corn’ (company valued at over $100M). Larger funds invest larger amounts per deal. To return high multiples, they need unicorns, which are rare. Smaller funds invest smaller amounts and can get the same multiples from ‘deci-corns’, which are much more common.

Advantages for Midwest venture capital

There are other tactics used by, and attributes common to, small Midwest VC’s that safeguard against downturns:

  1. Global investments that require skills available in the upper Midwest. While staying abreast of the latest trends in Silicon Valley to stay competitive, Midwest VC’s can take advantage of expertise available in the upper Midwest to serve global markets. In so doing, they avoid the valuation markups and early-round dilutions of Silicon Valley yet seek global parity in later rounds and exits.
  2. Local investments, global exits. An emphasis on the upper Midwest inherently allows investing at a discount compared to the investments in overheated markets such as Silicon Valley. This roughly translates to a 60% discount in term sheets offered on companies in the Upper Midwest. Global businesses rooted in the upper Midwest still attain exit valuations that correlate with global valuations. Thus, if a down cycle may require 50% markdowns for some Silicon Valley funds, Midwest VC’s can still record a 10% (=60-50%) markup at the bottom of the trough, emerge stronger from uninterrupted progress from investees’ capital efficiency, and exit with a markup brought to parity with global valuations in strong economic times.
  3. Emphasis on product-market fit. With the reduced capital investment now possible in many tech businesses, the barrier to entry has been lowered. Smaller venture funds can adjust criteria to focus investments on product-market fit, early revenue, and early break-even and profitability, instead of being limited by the number of affordable investment options. Nothing demonstrates product-market fit and staying power than paying customers and profit; for customers, employees and investors alike, there is nothing more powerful than profitability. Judicious investment in such businesses and mentorship to focus teams on profitability facilitates survival in lean times.
  4. Operators as investors. Small venture funds are often started by former operators with past successful exits, and the Midwest is no different. Many Midwest VC’s have a history of building profitable businesses the old-fashioned way, a dollar at a time. This experience of running a company, of managing payroll through good times and bad, of knowing the revenue and cost management discipline required to make money operationally and sustainably (i.e., not with short-term financial engineering), is invaluable for VC’s to have. So much so, that even accomplished operators will supplement their teams with experienced industry advisors.
[i] https://pitchbook.com/news/reports/q4-2019-pitchbook-nvca-venture-monitor
[ii] https://www.bizjournals.com/twincities/news/2018/03/15/how-the-leader-of-the-university-of-minnesotas.html
[iii] https://www.wsj.com/articles/robert-f-wallace-named-ceo-of-stanfords-endowment-1427138729
[iv] https://news.yale.edu/2017/10/10/investment-return-113-brings-yale-endowment-value-272-billion
[v] http://www.pionline.com/article/20151014/ONLINE/151019943/university-of-minnesota-endowment-reports-57-fiscal-year-return
[vi] https://www.strictlybusinesslawblog.com/2017/06/29/the-life-cycle-of-a-private-equity-or-venture-capital-fund/
[vii] https://en.wikipedia.org/wiki/Case%E2%80%93Shiller_index
[viii] according to the National Venture Capital Association website
[ix] https://www.cnbc.com/2017/04/07/you-can-buy-multiple-houses-for-the-cost-of-one-near-google-hq.html
[x] https://www.reuters.com/article/us-intel/intel-to-invest-7-billion-in-u-s-as-recession-deepens-idUSTRE5196WR20090210

More than 8,000 venture-backed companies received a combined $85 billion in funding in 2017, representing the highest annual total since 2000.[i] As stocks, real estate investments, and venture capital reach record highs, what are investors thinking about where to invest?
The answer depends on the type of investor:

 
Is this a good time for venture investing?
If the economy continues to do well, venture investments will do well. If the economy falters or if there is a stock market correction, this may still be a good time to invest in venture capital.
This is because stock market corrections (and corrections in the real estate market, which usually follows the stock market) follow business cycles, which can last 4-7 years. Venture funds usually invest over a 9-10 year investment cycle (i.e., a 5-6 year investment period followed by a 4-5 year harvest period). A slower business climate or stock market correction ahead could well be bracketed within the life of a new fund. And if needed, with due approvals from the limited partners, venture funds can extend their term to time their exits better.[vi]
 
Is there benefit in investing in venture funds in down cycles?
Let us look at the dynamics of different asset classes in downturns.

  1. Real estate – During the 2008 financial meltdown, real estate crumbled. As people lost their jobs, renters could not pay their rents, and property owners could not cover their mortgages. As defaults grew, real estate prices dropped. The Case-Shiller index dropped from 195 in 2005 to 116 in 2011.[vii] Considering the leverage of real estate investments, the losses for investors were much higher.
  2. Stocks, ETFs – The stock market similarly took a serious hit. The DJIA dropped 54% from 14,164 to 6,469 over 17 months.
  3. Venture capital – From Q1 2008 to Q1 2009, venture funding fell by 50% nationally to $3.9 billion (Dow Jones Venture Source).

Why did venture capital fare better than real estate or stocks?
First, lean times promote capital efficiency. As is often heard, recessions are the best time to start new companies, which is where early-stage venture capital is focused.
Second, venture capital firms mark up or mark down their investments over their life cycle. However, as actual valuations are pegged only by liquidity events, the real IRR is not known until the investments achieve liquidity. During the holding period, capital-efficient companies, and venture companies that focus on capital efficiency, do well, i.e., are counter-cyclical. They suffer fewer dislocations during downtimes. They can maintain their strategies, continue to do business as usual, and get ahead of those that slow down. Employees of such companies are more secure and loyal. And if needed, high-quality talent not available during good times can be hired, with loyalty that again pays dividends over the long term.
 
The capital efficiency of the upper Midwest
Companies in the upper Midwest inherently tend to be capital-efficient because there is less capital available. Similarly, smaller funds such as there are in the upper Midwest are inherently more capital-efficient, as they have less to invest.
44% of venture capital flows into Silicon Valley.[viii] This sets the consumption set-point of Silicon Valley companies at much higher burn rates than in regions where availability of venture funds is limited. The relative lack of available capital in other regions, including the upper Midwest, instills caution in spending.
 
Employee wages
While most other expenses are comparable across the US, with legendary real estate prices, Silicon Valley employees cannot survive at less than Silicon Valley wages.
This is not true in the upper Midwest. Though other expenses are comparable, housing costs may vary from 1/3rd to 1/10th of the Bay Area, enabling much greater capital efficiency for employers. For example, Google employees can buy 5 houses for the price of one by moving to one of Google’s locations across the country.[ix]

Figure 1. The real estate cost advantage of the upper Midwest compares well against not only the most expensive regions in the US, but also against what may be incorrectly perceived as lower-cost overseas regions (e.g., China). Seven cities in China and an equal number of cities in the US are listed above Minneapolis.
 
Fold? Hold? Or double down?
Not only can capital-efficient companies continue without disruption during slow times, given the lag between investment and market benefit, those that increase their investment can emerge even stronger in a recovery.
Intel applied this counter-intuitive strategy across many recessionary cycles, and invested several billion dollars in down cycles.[x] When their new semiconductor fabrication capacity resulting from these investments came online a few years later, their timing coincided with market rebound. On the other hand, competition (e.g., Atmel, Fairchild, Intersil/GE, IBM, Motorola, Raytheon, and several others) weakened from retrenchment and lost market share. As the industry consolidated during down cycles, Intel gained market share, and cumulatively over several cycles, emerged as its leader.
Some investors may feel that liquidity is useful during a downtime. Others argue against it, as getting out of the game when entrepreneurs are especially capital-efficient has a higher opportunity cost, and to use the Intel analogy, puts the winners further ahead of the losers. According to a prominent Silicon Valley investor, “you got to stay in the game”. At these times there are opportunities to go one step farther and double down.
 
Are smaller funds better than larger funds?
The statistical odds of a unicorn (company valued at over $1B) are lower than, say, of a ‘deci-corn’ (company valued at over $100M). Larger funds invest larger amounts per deal. To return high multiples, they need unicorns, which are rare. Smaller funds invest smaller amounts and can get the same multiples from ‘deci-corns’, which are much more common.
 
Advantages for Midwest venture capital
There are other tactics used by, and attributes common to, small Midwest VC’s that safeguard against downturns:

  1. Global investments that require skills available in the upper Midwest. While staying abreast of the latest trends in Silicon Valley to stay competitive, Midwest VC’s can take advantage of expertise available in the upper Midwest to serve global markets. In so doing, they avoid the valuation markups and early-round dilutions of Silicon Valley yet seek global parity in later rounds and exits.
  2. Local investments, global exits. An emphasis on the upper Midwest inherently allows investing at a discount compared to the investments in overheated markets such as Silicon Valley. This roughly translates to a 60% discount in term sheets offered on companies in the Upper Midwest. Global businesses rooted in the upper Midwest still attain exit valuations that correlate with global valuations. Thus, if a down cycle may require 50% markdowns for some Silicon Valley funds, Midwest VC’s can still record a 10% (=60-50%) markup at the bottom of the trough, emerge stronger from uninterrupted progress from investees’ capital efficiency, and exit with a markup brought to parity with global valuations in strong economic times.
  3. Emphasis on product-market fit. With the reduced capital investment now possible in many tech businesses, the barrier to entry has been lowered. Smaller venture funds can adjust criteria to focus investments on product-market fit, early revenue, and early break-even and profitability, instead of being limited by the number of affordable investment options. Nothing demonstrates product-market fit and staying power than paying customers and profit; for customers, employees and investors alike, there is nothing more powerful than profitability. Judicious investment in such businesses and mentorship to focus teams on profitability facilitates survival in lean times.
  4. Operators as investors. Small venture funds are often started by former operators with past successful exits, and the Midwest is no different. Many Midwest VC’s have a history of building profitable businesses the old-fashioned way, a dollar at a time. This experience of running a company, of managing payroll through good times and bad, of knowing the revenue and cost management discipline required to make money operationally and sustainably (i.e., not with short-term financial engineering), is invaluable for VC’s to have. So much so, that even accomplished operators will supplement their teams with experienced industry advisors.
[i] https://nvca.org/research/research-resources/
[ii] https://www.bizjournals.com/twincities/news/2018/03/15/how-the-leader-of-the-university-of-minnesotas.html
[iii] https://www.wsj.com/articles/robert-f-wallace-named-ceo-of-stanfords-endowment-1427138729
[iv] https://news.yale.edu/2017/10/10/investment-return-113-brings-yale-endowment-value-272-billion
[v] http://www.pionline.com/article/20151014/ONLINE/151019943/university-of-minnesota-endowment-reports-57-fiscal-year-return
[vi] https://www.strictlybusinesslawblog.com/2017/06/29/the-life-cycle-of-a-private-equity-or-venture-capital-fund/
[vii] https://en.wikipedia.org/wiki/Case%E2%80%93Shiller_index
[viii] National Venture Capital Association
[ix] https://www.cnbc.com/2017/04/07/you-can-buy-multiple-houses-for-the-cost-of-one-near-google-hq.html
[x] https://www.reuters.com/article/us-intel/intel-to-invest-7-billion-in-u-s-as-recession-deepens-idUSTRE5196WR20090210

Can the Upper Midwest drive digital innovation in manufacturing and logistics?

Legacy Manufacturing Hubs
Manufacturing and farming ecosystems in the US and around the world have developed around a combination of the following ingredients: raw materials (minerals, crops), energy (electric, hydro, wind, solar), logistics (bays/ports, rivers, roads), talent/labor pools, and viable operating economics. A combination of investment capital, balance sheet leverage, and public policy has provided the needed financial backing to scale up.
In the US, several manufacturing ecosystems have come to exist in different regions over the decades, focusing on aerospace/avionics, automotive, food and farming, healthcare, metals and mining, oil and gas, and semiconductors/electronic components/systems. Upper Midwestern states are prominent in this list. These ecosystems have been using current-generation industrial/process controls systems, heavy equipment, and ERP systems.

Industry Region Anchor Companies
Aerospace/Avionics California McDonnell Douglas, Hughes Aircraft.
Kansas Beechcraft, Cessna.
Washington Boeing.
Automotive Michigan, Indiana, Ohio Chrysler, Ford, GM, Visteon.
North Carolina Borg Warner, Bridgestone, Caterpillar, Continental, Cooper, Daimler, Denso, Freightliner, Goodyear.
South Carolina BMW, Mercedes, Bridgestone, Volvo, Magna.
Food and farming Central Valley, California Del Monte, Dole.
Wine Country, California Gallo, Mondavi, Jackson, J Lohr, Korbel, Rutherford, Sebastiani, Sutter, Wente.
Minnesota Cargill, General Mills, Land O’Lakes, Hormel Foods.
Missouri Monsanto.
Wisconsin Schreiber Foods.
Iowa Rembrandt, Burke, West Liberty.
Idaho Simplot.
Healthcare Minnesota Boston Scientific, Mayo, Medtronic.
Illinois Abbott Labs.
Industrial Equipment Illinois Caterpillar.
Iowa John Deere, Vermeer.
Minnesota Honeywell.
Wisconsin Rockwell Automation.
Metals Pennsylvania, Ohio Bethlehem Steel, U S Steel, USX.
Mining and materials Minnesota 3M.
Oil and gas New Jersey Arco.
Texas Exxon-Mobil, Schlumberger, Valero.
Paper Idaho Boise-Cascade.
Semi-conductors Silicon Valley ICs – Broadcom, Intel, nVidia, Marvell, SanDisk/Western Digital.
IC manufacturing equipment – Applied Materials, LAM Research.
San Diego ICs – Qualcomm.
Idaho ICs – Micron.

 Table 1: US regions, manufacturing ecosystems, and key anchor companies.
Digital Manufacturing – Requirements
In the age of ‘traditional’ manufacturing, the resources needed included:

 
In the age of digital manufacturing, from design to shipping, the following capabilities are important:

 
Advanced technologies useful for these capabilities include:

 
Next-generation digital manufacturing initiatives have taken root in regions where current manufacturing ecosystems have existed. For example, Tesla’s California factory is housed in the earlier NUUMI (General Motors and Toyota) plant in Fremont in Silicon Valley, where the plant was originally set up in 1960 by General Motors due to cheap land, the port of Oakland nearby, and a freight railroad along the Bay. Similarly, SpaceX (Hawthorne, CA) has leveraged design and manufacturing resources originally set up by McDonnell Douglas and Hughes Aircraft in the Los Angeles area near the port of Long Beach.
The Upper Midwest
Considering the extraordinary value creation of companies such as Tesla and SpaceX, there is a significant investment thesis in enabling next-generation manufacturing organizations to arise in the Upper Midwest, where many similar current-generation manufacturing ecosystems already exist.
Given the democratization (i.e., global availability) of some of the new technologies, the presence of global companies such as Google, Amazon, and IBM in most of the major cities in the Upper Midwest, and the significant academic centers across the region; highly-trained resources are available throughout the region to enable advanced digital manufacturing centers of excellence.
The Upper Midwest also has strong attributes to attract and retain relevant labor pools. Table 2 shows the relative desirability of different regions in the US as destinations for STEM workers. The statistics for the Upper Midwest, broadly including the greater Cincinnati, Columbus, Chicago, Denver, Madison, Minneapolis/St. Paul, and Pittsburgh areas, speak for themselves.

Rank (1=Best) Metro Area Total Score Prof Opptys STEM Friendliness Quality of Life
1 Seattle, WA 73.60 2 4 15
2 Boston, MA 71.94 7 1 43
3 Pittsburgh, PA 65.90 12 11 9
4 Austin, TX 65.15 6 8 27
5 Minneapolis/            St. Paul, MN 64.95 19 6 17
6 Madison, WI 64.00 13 16 13
7 Salt Lake City, UT 62.96 9 14 18
8 Springfield, MA 62.80 36 2 7
9 Chicago, IL 60.71 49 13 8
10 Atlanta, GA 60.69 5 27 31
11 Cincinnati, OH 60.51 16 33 14
12 San Francisco Bay Area, CA 60.50 3 7 67
13 Columbus, OH 59.71 33 21 21
14 Denver, CO 57.73 10 24 37
15 San Diego, CA 57.39 59 23 16
16 Sacramento, CA 57.20 44 20 25
17 Colorado Springs, CO 57.00 17 54 20
18 Worcester, MA 56.88 43 3 65
19 Richmond, VA 56.58 8 32 44
20 San Jose, CA 55.79 18 18 53

 Table 2: Desirability of cities in the US for STEM professionals. (Data Source: Richie Bernardo/ WalletHub, “2018’s Best & Worst Metro Areas for STEM Professionals”).
Superimposed with Table 1, Table 2 shows the opportunity for these regions to become magnets for next-generation manufacturing.
What Do the Next-Generation Manufacturing Innovations Look Like?
As a result, disruptive new companies are emerging in these regions, creating the investment opportunity to fund them from early-stage growth to scale-up. These companies are working with the incumbents shown in Table 1 to accelerate their evolution towards advanced digital manufacturing.
Examples of innovative companies focused on manufacturing and transportation in the upper Midwest include:
Proto Labs[i]– Rapid prototyping: allowing quick turnaround manufacturing.
FactoryFix[ii]– Contingent labor for equipment: predictive diagnosis for timely repair with skilled labor and relevant spare parts for better customer experience at lower cost.
Basin Commerce– River transportation: harnessing of shipping capacity on lake and river waterways using barge booking software.
Rambl[iii]- AI: sales call CRM logging and intelligence that analyzes calls for specific criteria and actions to surface insight.
Stemonix– Drug discovery: tissue manufacturing for testing potential side-effects of new drugs for neurological and cardiac diseases.
Aker– Crop management: Use of drones for crop management based on weather databases and image-based diseases detection. 
The Four Legs of the Innovation Stool
Infrastructure, technology, labor, and capital are the four legs of the innovation stool. The Upper Midwest has all of these.
Through new digital manufacturing technologies focused on topline and bottomline benefits, today’s manufacturing ecosystems are ripe for significant new value creation.
At Great North Labs, we are focused on providing early-stage capital to innovators in the Upper Midwest, with an emphasis on next-generation manufacturing. We leverage partners and advisors with market and operating experience in manufacturing. We invest in, and provide guidance and advisory resources to technology startups like FactoryFix that are poised to disrupt the traditional manufacturing and logistics industries in the Midwest.
 
[i] Donald Krantz, Director at Proto Labs, is an advisor to Great North Labs
[ii] FactoryFix is a Great North Labs portfolio company
[iii] Rambl’s co-founders, Mitch Coopet and Brian Bispala, are advisors to Great North Labs

Amazon (mkt cap ~$760B) recently paid more for Whole Foods ($13.7B) than the balance sheets of many mid-market grocers. This frames the obvious question for all grocers: how can your business compete long-term?
This is an especially challenging question for the smaller-cap grocers. Large companies such as Walmart (mkt cap ~$250B) and Target (mkt cap ~$40B) can afford sizable investments. To a lesser degree, the balance sheets of the next tier of grocers, like Kroger (mkt cap ~$21B), also allow them to focus on a couple of key moves and a few smaller initiatives, and to double-down if necessary.
Smaller grocery chains have to look more carefully, however. Except for mergers or sales, their balance sheets are not strong enough to complete large transactions on their own. Nor do they have the operating margin to buy with debt without materially impacting their P&Ls and carrying long-term risk to pay it down, especially if the economy takes a downward turn. With average pre-tax profits of 2% and an annual growth of 0.9% (2012-17), retained earnings can barely meet working capital growth needs, leaving limited capital for innovation.[i]

Mid-Market Innovation

Capital availability aside, the main question still remains: what should mid-market grocers do? To answer this question, let’s break it down into smaller questions and then explore those topics:

1. Without active strategic steps, can mid-market grocers survive over the next 1-2 decades? Do they have to counteract Amazon’s thrust and make similar moves to stay in business? Will they be weaker if they cannot or do not do so?

2. If they act, how should they proceed? Diversify into new markets? Consolidate with other mid-sized grocers? Or try to sell to Amazon, Walmart or Target assuming they are interested?

3. Or, should they build their own path by seeding and growing innovation, and grafting small acquisitions to accelerate growth and achieve scale down these paths?

Long-term Survival

The US grocery retail market stands at $649B today, with 3.4M (1% of the US population) employees across the 66,000+ businesses comprising this industry.[ii]  Given a growing population and the fact that in times good or bad, we all must eat, demand for food is unlikely to go down, though there may be shifts in preferences (e.g., generics v. branded) depending on economic conditions.
In other words, the industry is not small, not consolidated, and not at risk for a decline in demand. Rather, it is large, fragmented, and diverse, with fundamentally stable or growing demand. This makes it difficult for disrupters to disrupt broadly or deeply, and for adaptive innovators, it presents many options.
Evolution favors innovation and adaptability over size and scale, and nature provides useful insight into this Darwinian paradigm. While size and scale produce advantages for certain species, it is no guarantee of future success- it is a sign of successful growth, of successful past innovation. Colossal dinosaurs once dominated the planet, but the reason they rose to prominence, and the only reason their lineage persists in birds is because of adaptive innovations.
With the universal need for food, severe consolidation of grocery chains is unlikely as long as the US economy grows. And with the diversity of ecosystem players, customer preferences, and products, those who innovatively adapt will continue to grow.

Capital: Strength or Weakness?

For over a decade now, Amazon has taken advantage of its strong balance sheets and scale to gain presence in groceries. Given that Amazon’s market cap is roughly twice that of Target’s and Walmart’s combined is a material factor in its choice of strategic weapon: capital. Amazon’s investments related to grocery retailing are approximately $15B.
However, it is incorrect to assume that lots of capital means inevitable success. Many acquisitions simply fail to take root in their new home, no matter how useful the innovation. And companies such as Webvan failed under the weight of their capital because they failed to establish product-market fit incrementally and left no room for adaptive course-correction.

How to Proceed?

If Darwinism tends to prevail, then capital is not an unequivocal advantage, and the existential factor is adaptive growth, not survival.
We believe the multi-part answer is to (1) seed the eco-system for knowledge and initial product-market validation, (2) place 1-2 larger bets (at any given time for focus) based on an understanding of the market forces towards new business models or diversification, then (3) strengthen them to achieve scale, and (4) in parallel, carve out or sunset lines of business with the strongest headwinds to free up cash and focus on growth.
The outcome of such steps can put a mid-market grocer into high-growth business(es) that may not collide directly with Amazon or Walmart, and possibly even set the stage for a valuable acquisition or merger.

Topline Levers

Across these phases – seeding the ecosystem, placing 1-2 larger bets, and achieving scale – the two topline levers are greater share of wallet and new customers. These can come from new products and services.
Products (“SKUs”) such as staples and provisions, non-perishables, and fresh fruits & vegetables, all offer room for expansion. Depending on local demographics, preferences such as branded vs. non-branded, price vs. selection, organic foods, local produce, regional/ethnic items, and specialty items such as liquor and wine, define growth options.
SKU expansion does not require significant capital. Rather it requires a process that allows select experiments to be managed by the grocer, and a much longer ‘tail’ to be ‘self-managed’ by the SKU suppliers, where the grocer only provides limited ‘shelf space’ for a limited time (e.g., in-store endcaps or online kiosks) and charges for the service (and is able to do it without losing money). It is reasonable for SKU suppliers to be willing to pay for more visible use of physical space, differentiated presentation, or better ways to engage customers.
Online shopping enables choice extensions and endless aisles at a modest cost, whereas in-store options can emphasize experience. Demographic understanding of customer needs (healthy foods, organics, specialty foods, local/seasonal produce, etc.) can be assessed through affinity programs and community engagement combined with analytics. Going beyond food and provisions, adjacent businesses such as banking kiosks or medical ‘minute clinics’ can be evaluated in the same way.
Services such as partially- or pre-cooked foods, cellar management (a la VinCellar), produce delivery (a la Instacart or Peapod), meal delivery (a la Blue Apron), in-store eateries, and in-store convenient checkout without PoS lines can also be offered without material investment as vendor or partner offerings from established players and startups.

Bottomline Levers

The main bottomline levers are operational expenses such as rent, labor, and logistics including warehousing and supply chain management (e.g., inventory turns, lower margin items online); and financial items such as cash flow management or cost of debt. Many optimizations for these levers (e.g., robotic warehouses, robotic kitchen management, blockchain-based cold chain tracking, etc.) can also be enabled by partnerships with technology-based startups.

Capital Efficiency

In reviewing the above ideas, it becomes clear that many options are available in capital-efficient ways. Among these options, relationships with venture firms can facilitate access to both topline and bottomline tech-based innovation partners.
We are in an era of Software-as-a-Service (SaaS), which itself mitigates capex. Examples of services include online store builders and marketplaces (e-tail), security, brand/user preference analysis and brand promotion (martech, AI), customer service platforms (chatbots, CRM, KPO), and fleet management (IoT, gig economy apps). As federated web services with APIs, integration of SaaS offerings with the grocer’s enterprise software has become less expensive. With responsive design techniques, consistent desktop and mobile presentations for omni-channel access have become easy. And with integrated dev-ops processes, their deployment and upgrades have become easier as well.
Similarly, the gig economy mitigates capex and opex. Alternatives to home delivery by Whole Foods or Walmart Grocery (earlier known as Walmart-to-Go) can be made available without capex through third parties such as Instacart and Peapod. Federated independent couriers (e.g., Dispatch[iii])provide alternatives (figure 2). Also on the innovation frontier, though groceries are not the prime use case today, third-party drone companies offer drone-based services for commercial payloads of various sizes and type.

Figure 2. Which is better – owned delivery fleets, or independents marshalled with SaaS software? The answer may lie in the clash of medallions vs. Uber.
All of these services become easier to procure through relationships with VC firms that have a high awareness of these start-ups and use cases. The VC community has been quite active in grocery-focused investments. With 100+ investments, ~429 investors, and ~47 exits, grocery-focused VC firms have been active globally. Driving growth through capital-efficient innovation is necessary for mid-market grocers to stay competitive in the industry. Venture firms can provide options for adaptation, intelligence and diversification without billion-dollar expenditures.
[i] http://www.mngrocers.com/index.php/industry/stats
[ii]https://retailowner.com/Benchmarks/Food-and-Beverage-Stores/Supermarkets-Grocery-Stores#290291-profit
[iii] Dispatch is a Great North Labs investment

IoT and Analytics – Organizing the Industrial Internet

 

Figure 1: The third revolution: IoT and Analytics.  [Image credit: General Electric]                               
 
The Evolution of IoT – Where we Came From
The first generation of IoT systems (IoT 1.0) was built mostly with data collected from IP-based sensors by monitoring applications. Whether standalone or embedded in phones, low-cost sensors, compact packaging and distributed power enabled new endpoints and systems. These monitoring applications served needs such as asset tracking, fitness monitoring, mood lighting, physical security, and others.
The second generation (IoT 2.0) leveraged the capabilities of infrastructure tools such as edge gateways, publish-subscribe buses, data warehouses, and API-based integration. The edge gateways allowed IP network segments to connect to sensor bus segments using a diverse set of protocols (e.g., RS-422, RS-485, BACnet, CAN, Fieldbus, Hart, LonWorks, Profibus, Seriplex, Zigbee, Z-wave, and others). The gateways extended the reach of these IoT systems across the many incumbent protocols and enabled the integration of the IP segments with legacy systems. The publish-subscribe buses made data-driven software architectures easier to implement and scale. The data warehouses enabled the integration of structured, semi-structured and unstructured data. The integration APIs enabled ingestion of data at scale. Together, these new building blocks enabled larger-scale IoT applications such as home monitoring, smart metering, power grid management, parking systems, next-generation environmental controls in buildings, windmill farms, warehouse management, etc., with varying degrees of commercial success based on the benefit provided vs. the insertion economics of each use case.
 
Today’s Frontier
With the larger data sets enabled by frameworks such as Hadoop and big data software such as Pivotal, the third generation of IoT systems (IoT 3.0) is integrating analytics for decision-making. These analytic platforms enable the processing and visualization of the IoT data sets. The large data sets and analytic tools identify aberrations with higher levels of confidence (statistical power) and detect ‘signals’ not seen before, they have lower detection thresholds, greater measurement sensitivity, and higher accuracy.
Applications based on these capabilities range from physical security for homes, buildings, and warehouses; to detection of diseases like lung disease, cancer metastases, or cardiac arrhythmias (see the Mayo Clinic and AliveCor’s recent work); and complex chemical analysis as in rare earth element detection. The availability of computing platforms at the ‘edge’ (e.g., gateways) enables distributed/local analysis.
“The Internet of Things is giving rise to a tsunami of data,” said Great North Labs advisor Ben Edwards (founding team member of home automation pioneer SmartThings). “The billions of residential sensors in people’s homes and the personal sensors on their bodies are sources of data of value to each of us, and depending on what we make available to others, to family members for our safety and well-being, to the retailers we buy from, to the health practitioners who take care of us.”
The proliferation of machine learning algorithms with new programming environments such as Python and dataflow libraries such as TensorFlow has opened up a wide range of new applications. These include anomaly-based security alerts, health and fitness monitoring, genomic analysis and biomarker detection for disease prediction, drones, and self-driving cars.
The addition of machine learning libraries to established platforms such as Matlab, R, SAS, and SPSS, is enabling insertion of machine learning into legacy applications.
The availability of these tools in public and private clouds has made their accessibility and deployment even easier.
Together, with supervised and unsupervised learning, the machine learning software is processing data sets with high data dimensionality, like those from mining, voice processing, drone navigation, and self-driving cars.
The integration platforms and IP-based communication are also enabling the integration of the IoT world with the enterprise world, making applications possible across hybrid computing and control environments such as airports, buildings, cargo ships, factories, hospitals, refineries and oil rigs. While this creates security issues for the enterprise as well as control systems, solutions such as micro-segmentation of hybrid systems are beginning to emerge.
 
Tomorrow – The New Startups
With products from companies such as Nvidia, Intel, Qualcomm, Broadcom, and now Google, real-time computing power is becoming available at the edge. With easier integration and low cost, it is becoming embeddable at sensing endpoints for applications such as drones, self-driving cars and trucks, personal walking/talking robots, personal assistants, point-of-care diagnosis, no-POS retail, smart logistics, and smart city applications from parking lots to secure airports and intelligent highways.
 
Adoption Outlook
Beyond analytics and monitoring, this fourth generation of IoT systems will be able to use analytics and machine learning for controls.
What is the outlook for the adoption of these applications? The answer is: it depends. And it is best found through analogies.
How confident do today’s chess masters or masters of the game of Go today feel betting against the machine? IBM’s Deep Blue computer beat chess champion Garry Kasparov in 1997.  And as Great North Labs advisor Mitch Coopet (CEO of AI-focused Aftercode) points out, “Since 2016, Google’s Alpha Go platform has won against several Go masters using improved deep learning techniques.”
Or, when will the day come when your x-ray machine will have better diagnostic accuracy than your radiologist? Ahem, that day is already here.
Or, when will Alexa be able to detect tonal infection to assess mood? Based on indications from Amazon and makers of social robots and AI assistants, sentiment analysis will progressively improve the way machines will interact with humans.
Or, when will we be comfortable with self-driven cars? Completely autonomous navigation in 5-7 years may be unlikely, but it is equally likely that in 20 years, self-navigation will become a required safety feature for new cars.
Given the range of answers above, it is not a matter of if, but when, that real-time control using machine learning will be common. These systems will be able to handle use cases as diverse as (i) detecting rare earth minerals to help navigate the earthmoving equipment towards richer ore in a mining operation, (ii) making real-time sweeps at airports to pinpoint explosives across large masses of people, luggage, and infrastructure, (iii) ensuring that the robots deployed in automotive assembly stay within the extremely tight tolerances of frame construction, and (iv) predicting the failure of a component in a high value CT scanner or remote ATM to dispatch the skilled repairman in a timely way to avoid downtime (a business that Great North Labs has invested in).
 

The Innovation Ecosystem of the Industrial Internet
“Business Insider projects that there will be 55 billion IoT devices operating in the world by 2025, impacting a broad set of industries including automotive, consumer products, electronics, medical devices, and industrial equipment,” notes Great North Labs advisor Robert Bodor (Vice-President and GM, Americas, at Protolabs).
At Great North Labs, with an ambitious vision, we aim to help build the innovation ecosystem of the Industrial Internet visualized by IoT 3.0. This is because we believe the ingredients to build it are uniquely within reach for us.
The three pillars of any tech-enabled disruption are entrepreneurs/developers, adopters/enablers, and capital.

              

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