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How to prepare for M&A, your most likely exit avenue
Despite the plentiful headlines about mega billion-dollar M&A transactions, record IPOs and the rapid growth of SPACs, small deals will continue to be the most likely exit for the vast majority of tech startups. In the over 30 years I’ve worked on M&A at White & Case, Barclays and my current firm Ascento Capital, I have seen too many startups that are not prepared for an exit via a merger or sale. This article will provide specific recommendations on how to prepare your startup for M&A.
While it is good to strive for a billion-dollar-plus sale, a successful IPO or a SPAC deal, it is practical to prepare your startup for a smaller transaction.
Global M&A hit record highs in the second quarter with a total deal value of $1.5 trillion, but smaller transactions vastly outnumber mega billion-dollar deals. The U.S. saw a total of 16,672 deals in the year ended June 31, but only 583, or 3% of that number, were valued at more than a billion dollars (FactSet). The IPO market is healthy again, but M&A still represents 88% of exits: So far this year, there were 503 IPOs and 5,203 deals, according to the CB Insights Q2 2021 State of Venture Report. After the SEC announced in early April that it was considering new guidance on SPAC IPOs, the rate of new SPAC issuances fell by around 90%.
While it is good to strive for a billion-dollar-plus sale, a successful IPO or a SPAC deal, it is practical to prepare your startup for a smaller transaction.
Here are a few recommendations that will prepare your startup for an M&A exit:
Track M&A in your subsector
Set up an alert on Google News for M&A activity in your subsector. For example, if your startup is in the IoT subsector, search for “IoT acqui” and this will pick up news stories on acquisitions in the IoT space. Save the search so you can go to Google News on a regular basis. Also track your closest competitors on Google News, particularly to see who is selling their company.
Prepare a list of likely acquirers
Prepare a list of the companies or firms most likely to buy your startup. This list should include domestic and international companies, businesses in non-tech industries, private equity firms and their portfolio companies, as well as VC-backed companies. Track these likely acquirers on Google News as well.
Consider executing a parallel track
Consider approaching the top 10 likely acquirers when you are raising the next round of capital. If your startup gets M&A offers and VC term sheets at the same time, this will provide your board of directors choices on the path ahead. Knowing the M&A activity in your startup’s subsector and the 10 most likely acquirers will impress VCs and increase the chances of being funded.
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Pro tips from the team behind Kickstarter’s most funded app
Here at memoryOS, we have a saying we repeat often: “Most of the Kickstarter happens before the actual Kickstarter.”
Preparation is the key. But even if you understand that most of the work is done in advance, you should still prepare yourself for some sleepless nights after the launch date. The usual startup mantra will apply to your crowdfunding campaign just as well: Measure, analyze and adjust along the way.
As you may know, crowdfunding fits some B2C products better than it does others. So to give you our product context here, memoryOS is a gamified app that teaches memorization skills with the help of virtual mind palaces and interactive microlessons taught by our co-founder, two-time World Memory Champion, Jonas von Essen.
Image Credits: memoryOS (opens in a new window)
Before becoming the most funded app on Kickstarter and getting it 6,400% funded (and carrying it further to the Indiegogo platform right after), we spent countless hours researching down the rabbit hole of crowdfunding tips and tricks. We also had calls with several top-tier crowdfunding project creators who were kind enough to answer our questions and share bits of knowledge from their experience.
We’re sharing our approach (and secrets) to building a successful crowdfunding campaign because we know just how tough it can be to launch your own product. So here is a complete 10-step guide:
Find a unique idea
You should have a unique idea for a product that would solve at least one problem for your target audience. The proven approach is to set two major hypotheses right at the start and then work on getting them tested:
- Does your product work and solve the problem as intended, and is it better than what’s out there? This is usually referred to as the “proof of concept” stage.
- Are there enough people who are willing to pay for your product for you to build a sustainable business?
You will need to build a base prototype to test the first hypothesis and, if it works, you can then work on turning it into an MVP or a short demo version for your future commercial product. You can then get people to test it for free and prepay for the full version.
Getting people to actually back their interest with their wallet means you already have customers, not merely enthusiasts, and it significantly increases the chances of a successful project.
Yes, it’s important that you get people to pay a minimum reservation deposit at this point and receive their commitment to pay the remaining amount for the full product later on. Getting people to actually back their interest with their wallet means you already have customers, not merely enthusiasts, and it significantly increases the chances of a successful project.
Get user feedback
As soon as you have something to test, conduct short surveys to better understand your customers by gathering and analyzing the reasons why and for what purpose(s) they would want your product.
Here at memoryOS, we called the first couple thousand of our leads and had many insightful conversations to help us connect to our audience on a more personal and emotional level.
Once you have a demo or prototype for the users to test, make sure to add a feedback form right at the end of their experience (or gather feedback using Google Forms for surveys, or via email inquiries).
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These simple metrics will tell you if your startup is ready to scale
Finding go-to-market fit (GTM) is a pivotal moment for a startup. It means you’ve found a repeatable formula for finding and winning lead that can be written into a repeatable GTM playbook. But before you scale up your sales and marketing, you should check the metrics to make sure you’re ready.
So, how do you know when your startup is ready to scale? I’ll help you answer this using numbers you can calculate on a napkin.
You have to consider three metrics — gross churn rate, the magic number and gross margin. With these, you can measure the health and profitability of your business. By combining them into a simple equation, you can get your LTV:CAC ratio (long-term customer value to customer acquisition cost), which is a measure of your business’ long-term financial outlook. If the LTV:CAC is over 3, you’re ready to scale.
Whatever your particular business, it’s worth spending some time with these metrics to find realistic targets that will push LTV:CAC over 3. Otherwise, you might be in danger of running off a cliff.
Let’s unpack the three basic metrics:
Gross churn rate (GCR) is a measure of product-market fit (PMF). GCR is the percentage of recurring revenue lost from customers that didn’t renew. It answers the question: Do your customers stay with you? If your customers don’t stick with you, you haven’t found PMF.
GCR = Lost monthly recurring revenue / Total MRR.
Example: At the beginning of March, the company brought in $60,000 in MRR. By the end of the month, $15,000 worth of contracts didn’t renew.
GCR = $15,000 / $60,000 = 0.25, or 25% GCR.
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Dear Sophie: Should we look to Canada to retain international talent?
Here’s another edition of “Dear Sophie,” the advice column that answers immigration-related questions about working at technology companies.
“Your questions are vital to the spread of knowledge that allows people all over the world to rise above borders and pursue their dreams,” says Sophie Alcorn, a Silicon Valley immigration attorney. “Whether you’re in people ops, a founder or seeking a job in Silicon Valley, I would love to answer your questions in my next column.”
Extra Crunch members receive access to weekly “Dear Sophie” columns; use promo code ALCORN to purchase a one- or two-year subscription for 50% off.
Dear Sophie,
I handle people ops as a consultant at several different tech startups. Many have employees on OPT or STEM OPT who didn’t get selected in this year’s H-1B lottery.
The companies want to retain these individuals, but they’re running out of options. Some companies will try again in next year’s H-1B lottery, even though they face long odds, particularly if the H-1B lottery becomes a wage-based selection process next year.
Others are looking into O-1A visas, but find that many employees don’t yet have the experience to meet the qualifications. Should we look at Canada?
— Specialist in Silicon Valley
Dear Specialist,
That’s what we’re all about — finding creative immigration solutions to help U.S. employers attract and retain international talent and help international talent reach their dreams of living and working in the United States.
I’ve written a lot on how U.S. tech startups can keep their international team members in the United States. One strategy is to help the startup employees become qualified for O-1As. Another is to obtain unlimited H-1B visas without the lottery through nonprofit programs affiliated with universities. Sometimes candidates return to school for master’s degrees that offer a work option called CPT, or curricular practical training.
Image Credits: Joanna Buniak / Sophie Alcorn (opens in a new window)
But sometimes, companies end up deciding to move some of their international talent to Canada to work remotely. Recently, Marc Pavlopoulos and I discussed how to help U.S. employers and international talent on my podcast. Through his two companies, Syndesus and Path to Canada, Pavlopoulos helps both U.S. tech employers and international tech talent when their employees or they themselves run out of immigration options in the United States. He most often assists U.S. tech employers when their current or prospective employees are not selected in the H-1B lottery.
Through Syndesus, a Canada-based remote employer — also known as a professional employment organization (PEO) — Pavlopoulos helps U.S. employers retain international tech workers who either no longer have visa or green card options that will enable them to remain in the United States or those who were born in India and are fed up by the decades-long wait for a U.S. green card. U.S. employers that don’t have an office in Canada can relocate these workers to Canada with the help of Syndesus, which employs these tech workers on behalf of the U.S. company, sponsoring them for a Canadian Global Talent Stream work visa.
Syndesus also helps U.S. tech startups without a presence in Canada find Canadian tech workers and employ them on the startup’s behalf. As an employer of record, Syndesus handles payroll, HR, healthcare, stock options and any issues related to Canadian employment law.
Pavlopoulos’ other company, Path to Canada, currently focuses on connecting international engineers and other tech talent working in the U.S. — including those whose OPT or STEM OPT has run out — who cannot remain in the U.S. find employment in Canada, either at a Canadian company or at the Canadian office of a U.S. company. These employees get a Global Talent Stream work visa and eventually permanent residence in Canada. Pavlopoulos intends to expand Path to Canada to help tech talent from around the world live and work in Canada.
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How we built an AI unicorn in 6 years
Today, Tractable is worth $1 billion. Our AI is used by millions of people across the world to recover faster from road accidents, and it also helps recycle as many cars as Tesla puts on the road.
And yet six years ago, Tractable was just me and Raz (Razvan Ranca, CTO), two college grads coding in a basement. Here’s how we did it, and what we learned along the way.
Build upon a fresh technological breakthrough
In 2013, I was fortunate to get into artificial intelligence (more specifically, deep learning) six months before it blew up internationally. It started when I took a course on Coursera called “Machine learning with neural networks” by Geoffrey Hinton. It was like being love struck. Back then, to me AI was science fiction, like “The Terminator.”
Narrowly focusing on a branch of applied science that was undergoing a paradigm shift which hadn’t yet reached the business world changed everything.
But an article in the tech press said the academic field was amid a resurgence. As a result of 100x larger training data sets and 100x higher compute power becoming available by reprogramming GPUs (graphics cards), a huge leap in predictive performance had been attained in image classification a year earlier. This meant computers were starting to be able to understand what’s in an image — like humans do.
The next step was getting this technology into the real world. While at university — Imperial College London — teaming up with much more skilled people, we built a plant recognition app with deep learning. We walked our professor through Hyde Park, watching him take photos of flowers with the app and laughing from joy as the AI recognized the right plant species. This had previously been impossible.
I started spending every spare moment on image classification with deep learning. Still, no one was talking about it in the news — even Imperial’s computer vision lab wasn’t yet on it! I felt like I was in on a revolutionary secret.
Looking back, narrowly focusing on a branch of applied science undergoing a breakthrough paradigm shift that hadn’t yet reached the business world changed everything.
Search for complementary co-founders who will become your best friends
I’d previously been rejected from Entrepreneur First (EF), one of the world’s best incubators, for not knowing anything about tech. Having changed that, I applied again.
The last interview was a hackathon, where I met Raz. He was doing machine learning research at Cambridge, had topped EF’s technical test, and published papers on reconstructing shredded documents and on poker bots that could detect bluffs. His bare-bones webpage read: “I seek data-driven solutions to currently intractable problems.” Now that had a ring to it (and where we’d get the name for Tractable).
That hackathon, we coded all night. The morning after, he and I knew something special was happening between us. We moved in together and would spend years side by side, 24/7, from waking up to Pantera in the morning to coding marathons at night.
But we also wouldn’t have got where we are without Adrien (Cohen, president), who joined as our third co-founder right after our seed round. Adrien had previously co-founded Lazada, an online supermarket in South East Asia like Amazon and Alibaba, which sold to Alibaba for $1.5 billion. Adrien would teach us how to build a business, inspire trust and hire world-class talent.
Find potential customers early so you can work out market fit
Tractable started at EF with a head start — a paying customer. Our first use case was … plastic pipe welds.
It was as glamorous as it sounds. Pipes that carry water and natural gas to your home are made of plastic. They’re connected by welds (melt the two plastic ends, connect them, let them cool down and solidify again as one). Image classification AI could visually check people’s weld setups to ensure good quality. Most of all, it was real-world value for breakthrough AI.
And yet in the end, they — our only paying customer — stopped working with us, just as we were raising our first round of funding. That was rough. Luckily, the number of pipe weld inspections was too small a market to interest investors, so we explored other use cases — utilities, geology, dermatology and medical imaging.
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Founders: How well do you really understand seed-stage financing?
I’ve fundraised a lot. Tactically, fundraising is a skill like any other. You get better the more you do it. But practicing gets you nowhere if you don’t have a strong foundation in understanding a fundraising round’s core components.
As a founder, you will understand less than investors when it comes to fundraising. For investors, negotiating with founders is their full-time job. For founders, fundraising is just a small part of building a business. Understanding the basics of venture financing can help founders raise on better terms.
We’ll cover:
- How financing works: SAFEs versus equity rounds.
- How much to raise.
- How to arrive at your valuation.
How financing works: SAFEs versus equity rounds
As a founder, you will understand less than investors when it comes to fundraising.
Venture financing takes place in rounds. The first stage is the pre-seed or seed round, then a Series A, then a Series B, then a Series C and so on. You can continue to raise funding until the company is profitable, gets acquired or goes public.
We will focus here on seed-stage funding — your very first funding round.
SAFEs
Post-money SAFEs are the most common way to raise funding. These documents are used by Y Combinator, angel investors and most early-stage funds. You should raise on post-money SAFEs using standard documents created by YC. Standard documents have consistent terms that have been drafted to be fair to both investors and founders.
By using the standard post-money SAFE, your negotiation can focus on the two terms that matter:
- Principal: The amount you want to raise per investor.
- Valuation cap: The value of your business.
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In an increasingly hot biotech market, protecting IP is key
After a record year for biotech investment in 2020 — during which the industry saw $28.5 billion invested across 1,073 deals — the market for new innovations remains strong. What’s more, these innovations are increasingly coming to market by way of early-stage startups and/or their scientific founders from academia.
In 2018, for instance, U.S. campuses conducted $79 billion worth of sponsored research, much of it thanks to the federal government. That number spiked amid the pandemic and could increase even more if President Biden’s infrastructure plan, which includes $180 billion to enhance R&D efforts, passes.
Since 1996, 14,000 startups have licensed technology out of those universities, and 67% of licenses were taken by startups or small companies. Meanwhile, the median step-up from seed to Series A is now 2x — higher than all other stages, suggesting that biotech startups are continuing to attract investment at earlier stages.
When it comes to protecting IP, early and consistent communication with investors, tech transfer offices and advisers can make all the difference.
For biotech startups and their founders, these headwinds signal immense promise. But initial funding is only one part of a long journey that (ideally) ends with bringing a product to market. Along the way, founders will need to procure additional investments, develop strategic partnerships and stave off competition. All of which starts by protecting the fundamental asset of any biotech company: its intellectual property.
Here are three key considerations for startups and founders as they get started.
Start with an option agreement
Most early-stage biotechnology starts in a university lab. Then, a disclosure is made with the university’s tech transfer office and a patent is filed with the hopes that the product can be taken out into the market (by, for instance, a new startup). More often than not, the vehicle to do this is a licensing agreement.
A licensing agreement is important because it shows investors the company has exclusive access to the technology in question. This in turn allows them to attract the investments required to truly grow the company: hire a team, build strategic partnerships and conduct additional studies.
But that doesn’t mean jumping right to a full-blown licensing agreement is the best way to start. An option agreement is often the better move.
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Build a digital ops toolbox to streamline business processes with hyperautomation
Reliance on a single technology as a lifeline is a futile battle now. When simple automation no longer does the trick, delivering end-to-end automation needs a combination of complementary technologies that can give a facelift to business processes: the digital operations toolbox.
According to a McKinsey survey, enterprises that have likely been successful with digital transformation efforts adopted sophisticated technologies such as artificial intelligence, Internet of Things or machine learning. Enterprises can achieve hyperautomation with the digital ops toolbox, the hub for your digital operations.
The hyperautomation market is burgeoning: Analysts predict that by 2025, it will reach around $860 billion.
The toolbox is a synchronous medley of intelligent business process management (iBPM), robotic process automation (RPA), process mining, low code, artificial intelligence (AI), machine learning (ML) and a rules engine. The technologies can be optimally combined to achieve the organization’s key performance indicator (KPI) through hyperautomation.
The hyperautomation market is burgeoning: Analysts predict that by 2025, it will reach around $860 billion. Let’s see why.
The purpose of a digital ops toolbox
The toolbox, the treasure chest of technologies it is, helps with three crucial aspects: process automation, orchestration and intelligence.
Process automation: A hyperautomation mindset introduces the world of “automating anything that can be,” whether that’s a process or a task. If something can be handled by bots or other technologies, it should be.
Orchestration: Hyperautomation, per se, adds an orchestration layer to simple automation. Technologies like intelligent business process management orchestrate the entire process.
Intelligence: Machines can automate repetitive tasks, but they lack the decision-making capabilities of humans. And, to achieve a perfect harmony where machines are made to “think and act,” or attain cognitive skills, we need AI. Combining AI, ML and natural language processing algorithms with analytics propels simple automation to become more cognitive. Instead of just following if-then rules, the technologies help gather insights from the data. The decision-making capabilities enable bots to make decisions.
Simple automation versus hyperautomation
Here’s a story of evolving from simple automation to hyperautomation with an example: an order-to-cash process.
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Where is suptech heading?
Technology plays a huge role in nearly every aspect of financial services today. As the world moved online, tools and infrastructure to help people manage their money and make payments have burgeoned the world over in the past decade.
With much of the finance world now leveraging technology to conduct business, predict trends and deliver services, financial services regulators are also developing new technologies to monitor markets, supervise financial institutions and conduct other administrative activities. The emergence of purpose-built technologies to facilitate regulator oversight has, over the past few years, garnered its own moniker of supervisory technology, or suptech.
Interest in suptech is proliferating across the globe thanks to a diverse set of prudential and conduct regulators. A sampling of regulators developing suptech include the FDIC, CFPB, FINRA and Federal Reserve in the U.S.; the U.K.’s FCA and Bank of England; the National Bank of Rwanda in Africa; as well as the ASIC, HKMA and MAS in Asia. Several “super regulators” are also engaged in suptech efforts such as the Bank of International Settlements, the Financial Stability Board and the World Bank.
The strides in suptech demonstrate that creative thinking coupled with experimentation and scalable, easily accessible technologies are jump-starting a new approach to regulation.
In this post, we’ll examine a few core suptech use cases, consider its future and explore the challenges facing regulators as the market matures. The uses are diverse, so we’ll focus on three key areas: regulatory reporting, machine-readable regulation, and market and conduct oversight.
A quick general note: Nearly every financial services regulator is engaged in some type of suptech activity and the use cases discussed in this article are intended as a sample, not a comprehensive list.
But what exactly is suptech?
As a preliminary matter, we should quickly survey a few definitions of suptech to frame our understanding. Both the World Bank and BIS have offered definitions that provide useful outlines for this discussion. The World Bank states that suptech “refers to the use of technology to facilitate and enhance supervisory processes from the perspective of supervisory authorities.” It’s a little circular, but helpful.
The BIS defines suptech as “the use of technology for regulatory, supervisory and oversight purposes.” This is a similarly loose definition that describes the broader scope better.
Regardless of differences on the margins, the “sup” in these suptech definitions acknowledges the primacy of the idea that regulators’ objectives are to oversee the conduct, structure, and health of the financial system. Suptech technologies facilitate related regulatory supervision and enforcement processes.
Regulatory reporting
Regulatory reporting refers to a broad swath of activities such as financial firms providing trading data to regulatory authorities and regulators’ analysis of financial data or corporate information to determine the projected health or potential risks facing an institution or the market.
The MAS and FDIC are incorporating transactional and financial data reported by firms as a means to assess their financial viability. The MAS, in conjunction with BIS, has run tech sprints soliciting new ideas relating to regulatory reporting, while the FDIC has “a regulatory reporting solution that would allow ‘on-demand’ monitoring of banks as opposed to being constrained by ‘point-in-time’ reporting. This project is particularly targeted at smaller, community banks that provide only aggregated data on their financial health on a quarterly basis.”
The HKMA recently outlined its three-year plan for the development of suptech, which includes developing an approach to “network analysis.” The HKMA will analyze reporting data related to corporate shareholding and financial exposure to bring them “to life as network diagrams, so that the relationships between different entities become more apparent. Greater transparency of the connections and dependencies between banks and their customers will enable HKMA supervisors to detect early warning signals within the entire credit network.”
These reporting initiatives touch on a theme regulators have continuously struggled with: How to regulate markets and firms based on a reactive approach to historical data. Regulation and enforcement are often retrospective activities — examining past behavior and data to decide how to sanction an organization or develop a regulatory framework to govern a particular type of activity or financial product. This can result in an approach to regulation too rooted in past failures, which might lack the flexibility to anticipate or adapt to emerging risks or financial products.
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Here are 3 things you should do with your stock options
There’s a reason startup compensation packages usually include equity, or stock options. For one, it’s a way for startups to remain competitive in the job market and attract top talent. But it’s also a way to reward those employees who join early and give them a tangible reason to stay incentivized to grow the company.
The problem is that while many employees do understand that their equity compensation could mean a big payday in the future — and, in 2021, that’s more likely than ever — they don’t often understand the inevitable complexities of their stock options. That puts employees at risk of not getting the most value after an IPO or, worse, losing them.
If you’ve ever been confused about your equity, or haven’t thought much about it, you’re not alone. That’s why I’m going to share three things all employees joining a startup should do with their equity:
Understand how to value your equity — and when it can change
While many startups are getting better at proactively communicating the value of your equity package upfront, some are still figuring out the best way to do it. That’s because, unlike the more straightforward number of a salary, stock options are more nuanced — they’re a living, breathing type of compensation.
The most important pieces of information to pay attention to are your 409A valuation, your strike price, the type of options you were granted and the preferred share price.
The 409A valuation is based on your company’s valuation. This is also referred to as the fair market value (FMV). The 409A valuation can, and does, often change — they have to be updated at least once a year by a third-party valuator in order to meet tax rules. The 409A also changes during a fundraising event. Investors involved in the funding round determine how they value the company and are given options, at that valuation, in exchange for cash.
The most important pieces of information to pay attention to are your 409A valuation, your strike price, the type of options you were granted and the preferred share price.
Since the company has now been valued higher, the 409A changes for everyone. It’s also possible for the 409A to go down if, for any reason, the company is now valued at a lower amount. This is known as a “down round.” Airbnb had a notable down round during the pandemic, though it eventually recovered and went public.
Your strike price is the price at which you can buy your stock options (also known as exercising). Yes, buy. You are given the option to buy them, which is why they are called stock options. But know that your strike price will likely never change. However, if you’re ever given more stock options (perhaps as a future bonus), this would be a separate grant and the strike price could be different. Companies are legally required to issue stock options at the most recent 409A price (or higher).
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