Launching New Business Lines in Startups

Venture capital backed startups are all about creating hyper-growth businesses. There is nearly no valuation upper bound for what we define as a startup as long as the company is sustaining its hockey stick growth trajectory. But what happens after a startup’s existing market is slowly saturated? Startups oftentimes rely on launching new business lines as a way to tap into new markets. This is different from rolling out a new product or feature since the new initiative is often operating as a separate legal entity with different business models. Think of Uber Eats at Uber or Stripe Atlas at Stripe - startups are essentially incubating new startups within themselves. These new lines not only leverage the existing strengths of the parent company, but also actively strengthen the core product offering by developing new channels for customers to gain value from the original product.

I became fascinated by this topic while helping to launch new business lines at Blend. Creating a new business line gives a company the freedom to innovate rapidly in a new market while leveraging existing distribution network and technical infrastructure. With sufficient resources and deliberate execution, there really is no ceiling to what a company can achieve. But companies generally face the hard economic trade-offs on investing in new business lines due to finite resources.

The fundamental challenge for companies to understand is what their competitive advantage is in the new market. Then it branches out into related follow-ups: Could you leverage existing distribution channels efficiently in the new market? How to utilize the current infrastructure for running new experiments economically? What does it mean to build cohesive branding across multiple business lines with underlying connectivity? How do developers build scalable software that is compatible with the current system? By and large, companies may start off deliberating on the following themes when pursuing a new business line:

  1. Advantage: understand your unique competitive advantage in a new market
  2. Cohesion: build a cohesive branding narrative across multiple business lines
  3. Cross-sell: validate the opportunity to sell a new offering to your existing customer base
  4. Experiment: prove the business hypothesis quickly and cheaply
  5. Evolution: build your system as an evolving organism

There really is no one-size-fits-all formula for how to launch a new business line successfully. Even at Blend when two separate business lines are sharing the same overarching objective of making the home-buying process simpler for consumers, we had to reconstruct a new empirical model for each new business. I have seen few cases where we can simply “copy-and-paste” what is working in business line A to business line B without contextual changes. While it is useful to follow a guiding framework for the approaches and strategies, it is unavoidable to keep the execution details loose when dealing with growing business complexity.

There are an abundance of frameworks to cherry pick from, most with detailed explanations available on the Internet: establish a closed feedback loop, measure meaningful key metrics, move quickly and fail fast, talk to customers, build an MVP, and so on. If the new business hypothesis were proven by actual demand, the startup would then focus on scaling the new business mostly as an independent entity, transitioning into a multi-business line company. For internet businesses, it’s worth highlighting the importance of recognizing software systems as an evolving organism. An unusable piece of software is literally useless, regardless how great it is by design. Companies should always evolve their software systems to fit the business needs. It is nearly impossible to design a perfect system architecture at the outset mostly due to the fast changing nature of the business - always build incrementally. The business experiment might begin as a module in the monolith, then migrate out as a single service, and eventually extend and scale up as business-specific multi-services.

Launching a new business line generally has a higher chance of success, compared to launching a startup, because new startups have small runways and usually fewer competitive advantages. Those new lines of businesses are accelerating off the premade rails from the existing business and can spur new directions of growth for the parent company. If a company is capable of sustaining hyper-growth with emerging business lines, I don’t see why innovation would stop even as a company turns “corporate”, as innovation should always be the key driver for startups to create a better society.

Thanks to Jay Palekar and Rinko Shen for sharing their thoughts on the draft.

The Rising Buzz About Fintech

The financial technology sector is gradually resembling the golden age of social media in the 2010s. The social media revolution constituted a continuous wave of hyper-growth startups, now household names including Facebook, LinkedIn, and Twitter. They raised mega financial rounds and exited in temporal proximity. Looking back, these media products entirely changed the perception of digital technology for individuals and businesses. Similar phenomena can now be observed in fintech and will only become more visible as more major liquidity events hit news headlines.

Not only are newcomers introducing new ways for consumers to interact with financial services via technology, incumbents are also investing heavily into utilizing in-house built and third-party software products to win the growing customer expectations. End-users could expect actions from all players in the market: startups are introducing new channels for millennials to manage investments and acquire loans, banks are partnering with software companies to offer a modern digital experience, and even non-financial institutions are launching financial products to control customers’ spending habits. Angela Strange of a16z made a bold prediction stating “nearly every company will drive a significant portion of its revenue from financial services”, which in fact could become a reality given how emergent fintech services are simplifying the steps to create new revenue streams. Payment processing, credit card issuing, white-label compliant software services, one-tap transactions - innovative methods are constantly being reimagined and all that a company has to do is to integrate for pilot. Rising cohorts of fintech unicorns and a seemingly endless stream of private capital to back various initiatives mark the thrilling zeitgeist of this industry.

The Driving Forces of Financial Innovation

In the lending space, there are three key forces pushing for modernized loan processing, states Tim Mayopolous of Blend (also my current affiliation). Consumers, investors, and new market entrants are defining a new set of digital standards in a traditionally paper-driven industry. The kind of frictionless and personalized user experiences that consumers enjoy on Netflix and Amazon would eventually become the ubiquitous expectation in financial services, forcing all players in the lending market to rethink how to incorporate digital solutions.

In fact, zooming out from lending and refocusing on fintech holistically, the same paradigm shift is happening across payment, banking, personal finance, and insurance. Plugging the three key forces into most fintech equations, we see that 1) consumers demand seamless and accessible financial transactions with a few taps on their phones, 2) investors rely on modern data analytics tooling to extract quality insights for decision making, and 3) new market entrants build on top of a maturing fintech infrastructure to reach wider distribution. A whole new generation of financial products were unlocked by smart phones and cloud infrastructure. And the trend shows more aspects of the financial market will be digitalized despite regulatory challenges.

The driving forces of innovation are even provoking the biggest financial institutions to adopt forward-thinking initiatives motivated by the risk of losing market share. Now that fintech startups are challenging incumbents with direct-to-consumer products, incumbents are incentivized to collaborate with fintechs to launch better digital offerings in a shorter amount of time, forcing other legacy players to adapt or to become irrelevant. For instance, an increasing number of banks are partnering with fintechs to provide digital banking solutions to traditional retail customers, all while reducing in-house IT spending. A win-win situation could be achieved when banks leverage efficient digital products to drive additional revenue and fintechs indirectly acquire banks’ customer networks to reach tremendous scale. Whether a fintech is partnering with or challenging incumbents, consumers are the ultimate winner with more innovative, secure, yet simple financial products to pick from.

Innovative Startups in Financial Services

When you fuel an industry with abundant cash and applicable technologies, many valuable companies will be created. This explains why regulatory complexity does not hinder the financial services sector from being dynamically adaptive and ever-changing. So far there are dozens of fintechs reaching unicorn status across the globe. Although most valuations are still speculative, the surge of innovative ideas merging software and financial services is unparalleled. But what innovations are making the giant leaps in financial services? The current landscape of high-growth fintech startups indicates most innovative ideas are manifested in the following ways.

  • New Business Model: Fintechs are introducing new consumer interactions and lowering the barrier of entry by leveraging mobile, data, and cloud infrastructure. A few tweaks in business models, such as zero trading fees and fractional homeownership, could move the needle based on the premise of universal internet access and software automation.
  • Improved Efficiency and Automation: Value creation is straightforward when productivity increases and cost decreases. By harnessing the power of software to automate manual processes, fintechs are putting wealth management on autopilot, reducing time to acquire loans, and simplifying payroll management. Or to say - let software do the work.
  • Emergent Software Infrastructure: Assume the total addressable market of fintechs keeps on growing in the following years, then one of the safest bets an investor could make is perhaps to put money in software building blocks that any other fintechs would need. Whether it is tooling to integrate with banks or become banks, more innovative products will emerge and they are fascinating to learn about.

Among the topics on the next fintech trend, there is a common thread about new startups being built in banking-as-a-service, fintech infrastructure, full-suite fintech apps, and new B2C/B2B marketplaces. A quick Google search will find you numerous predictions about the future of fintech by industry leaders. There are also heated debates about the use of artificial intelligence and blockchains in fintech. No doubts, these emerging technologies have a great potential of disruption and democratizing them is the million dollar question. Ideas like crypto lending platforms are one of a kind in the financial services space, but it could still take years for these emerging applications to become mainstream. However, as it seems there is still plenty of room for disruptive innovations.

The Tech Challenges

Despite being in a drastically different industry, fintechs share a fair amount of technical challenges as software startups in other industries. Great software engineers from Facebook who work on media related problems should have no problems ramping up at Coinbase, a fintech company building a crypto trading platform, and vice versa. This is because the fundamentals of building a large-scale software system are universal. Just to name a few: authentication/authorization, system monitoring, databases management, and network security are challenges found in most software systems designed to scale. Fintech startups are expected to invest significantly into their technical infrastructure to meet the business demands, and it is difficult to cleanly offload development work because of the evolving nature of an application.

If we rule out the fundamental technical issues, there are also many challenges unique to a fintech company. A difficult hurdle to start and scale up a fintech business is the regulation requirements inherent to the financial services industry. If the product fails to comply with the regulation of your concern, the cost could be hard to recover (whether it is financial penalty and prison time). The tricky problem is exactly how to make sure the software complies with the laws 100% of the time. For example, under the TILA-RESPA Integrated Disclosure (TRID) rule, a mortgage lender is required to provide the borrower a form detailing loan fees and limiting fee changes within three days after starting a mortgage application. Any violations could result in fines ranging from $5,000 to $100,000 per day until the issues are mitigated. To satisfy the demand of the legal system, the business would need deliberate software automation combined with manual scrutiny to ensure the product is error-free. The technical complexity naturally grows when the system is expected to be fully compliant under various regulations.

The Uncertainty Ahead

What goes up must come down, especially in speculative valuations. A growing number of growth-stage venture capitalists believe that a retrenchment in the broader private market is looming. Besides the impacts from the macro market, there are also questions around the appropriate valuation methods (ie. using SaaS multiples or book value multiples) for correctly evaluating a late-stage fintech. The general wariness could lead to fewer risk-taking projects for innovation and shrinking market value for fintechs.

Nevertheless, it is an exciting time for the financial services industry. Thousands of startups and banks are launching new initiatives to make the previously cumbersome financial process more transparent and simple. As we move onward in the decade of the 2020s, it wouldn’t be surprising to see more fintechs become household names and bring on game-changing solutions. This technological shift in the financial services sector could and should make people’s financial lives better overall.

Thanks to Mark Goldberg, Rinko Shen, and Rohan Varma for feedback.

Conway's Law and Microservices

Keeping software architecture robust and aligned with business incentives is a tough problem faced by most software companies. As the size of an engineering team grows, its communication cost increases quadratically. This is a result of the growing number of communication links of people as described by Metcalfe’s Law - the number of unique possible links in a network is proportional to the square of the number of participants. Without a clear understanding of how the organization structure affects software development, a company is likely to experience difficulty scaling and iterating once they reach a certain size.

The presented issue does not become significant until launching features or fixing bugs requires a non-negligible amount of overhead. Assume an e-commerce clothing startup is planning to change the pricing of off-season products, but the engineering department is structured so that such an adjustment involves the UI team, the Database team, and the QA team. Once the project is complete, it just happens that they cannot launch the update because the Integration team is attempting to resolve an unrelated email notification issue that is currently blocking the release. Similar scenarios can occur regularly and lead to downstream consequences. In a world where startups succeed by optimizing iteration speed, especially for venture-backed startups, a company is at risk of losing market position if it tolerates expensive development lifecycle.

This leads me to believe that Conway’s Law is perhaps the most important law for modern software businesses.[1] The interrelation between system architecture and organization structure was formalized by Melvin Conway in his paper “How Do Committees Invent” back in 1967. The law states that any organization that designs a system (defined broadly) will produce a design whose structure is a copy of the organization’s communication structure. This generalization on the sociological behavior of system designers has a profound implication: loosely coupled organizations are more likely to produce modular systems with autonomous components bounded by both business and technical context.[2] To empower engineers to develop and maintain software with high productivity, it almost seems inevitable for a company to move towards a paradigm where a team (defined broadly as well) is responsible for the entire lifecycle of a system component, ranging from development to testing to deployment.

It does not mean there is not place for horizontally integrated teams to exist, but tradeoffs are to be made. There is occasionally pressure to horizontalize the teams to ensure consistency across different parts of the system. In a layered architecture, as mentioned in the above example of owning UI and Database teams, you end up with low velocity but high efficiency in terms of code and functionality duplication. This is, by and large, beneficial for maintaining shared utility. The bottom line is a company needs to prioritize iteration speed in a way for loosely coupled teams to succeed, such as creating a hybrid environment to have vertical and horizontal teams coexist in their bounded contexts.

Decision makers at a software company should always keep Conway’s Law in mind. This is to say that a top priority of the leadership team is to create a collaborative structure and low-friction processes that allow its engineers to operate in alignment with business goals. Many of the most renowned tech companies are aware of this issue and invest heavily into refactoring system architecture and restructuring engineering organizations for long-term benefits. But among all standard practices, this investment is most commonly manifested as service-oriented architecture migration. It signals an org-wide shift towards building microservices expected and necessary. Leveraging Docker and Kubernetes to create a flexible and cloud-agnostic service-oriented infrastructure almost becomes an industry-standard practice. In a sense it is like cargo cult science, where some companies do not understand the benefits of microservices but do it anyway (aka. microservice cargo cult). However, knowing that Airbnb, Uber, Tinder, and more all made this transition and it seems to work quite well with their distributed workforce, it is tempting to insert microservice architecture as part of the equation for building fast-growth startups.

In fact, the so-called “microservice cargo cult” actually makes sense theoretically for building an ecosystem of distributed ownership and high scalability for a software company. Conway’s Law validates the reasoning of leveraging microservices to ensure minimal communication friction for rapid prototyping and experimentation. Certain communication limitations of cross-regional engineering teams are also lifted as a result of granting full-cycle service ownership. It is not hard to see why this architecture style becomes the go-to scaling strategy for many San Francisco/Silicon Valley’s hottest companies, but it is also important to understand its costs than keeping more coarse-grained systems.

Applying Conway’s Law and microservices appropriately can create a powerful mechanism for achieving fast and scalable success. Although the duo has their limitations, learning, experimenting, then understanding them is extremely valuable to any software businesses. They are worth serious attention.


  1. There are a couple of laws that greatly influenced the advancement of the tech industry: Moore’s Law, Kryder’s Law, Linus’s Law, and so on. Each offers substantial value in their respective domains for evolving a system and making business decisions, but many relevant questions can be neglected or abstracted away with the abundance of cloud services, open-source frameworks, developer tools available to software businesses nowadays.
  2. Sam Newman discusses a few studies on the topics of organizational structure and software modularity in Chapter 10 of his book Building Microservices, supporting the claim that the organizational structure has significant impact on the system it produces with empirical evidence.

Thanks to Eugene Marinelli, Shahid Cohan, Rohan Varma, and Saad Syed for reviewing the draft.

Unorthodox Methods of Choosing the Right Startup

If you have known me for a while you probably know that I get uncontrollably passionate when it comes to the topic of startups. There is just something intrinsic that is fascinating to me about a group of ambitious people working tirelessly to create a reality closer to their imagination. However, the truth is most startups fail. And this is the exact reason why most people are turned away and choose a steady career instead. If working at Google/Facebook has a higher expected value than joining a startup, why risk working longer hours with lower compensation at a place with so much uncertainty?

There are many reasons why people choose to join a startup: equity, impact, culture, location - you name it. Whatever the incentive is, I believe one’s goal of joining a startup is to find the right fast track to reaching your career objectives compared to taking the alternative paths. It is an opportunity to work on things levels beyond your current credentials. Working at a startup is locally optimal if you are given responsibilities above your market value, but you are mentally eager and intellectually curious to overcome the inevitable hurdles. Therefore, when defining what a “right” startup is for you, it boils down to to one question: can joining this company catapult you towards the success you are looking for?

The startups in consideration need to be able to offer you massive opportunities for personal growth. This growth can come in many forms: building a scalable and reliable video streaming system, leading client negotiation to get a contract signed, launching new products in a niche market with a team of three, and so on. At a company where human resources are limited, you are more likely to get assigned to tasks that you are unqualified for, and it is up to you to rise up to the challenge and deliver value.

An index I often consider for evaluating personal growth is individual I/O (input/output) - input as the amount of information you are learning and output being the value that you are producing. You want to put yourself in an environment with high throughput of this type of I/O.

There are tons of startups out there. You will have to make the call on which one looks promising and can help you get closer to your goal. The younger a company is, the more analysis you will have to do. Here are some thoughts to help you evaluate a startup before signing that offer.

Commit to a mission you truly care about. A young startup is like clay waiting to be molded; no one has a definite answer as to what it will look like eventually. Oftentimes business directions are unclear and management could be messy. You want to believe in the work that your organization is producing, otherwise you are likely to be affected by doubts from time to time.

With that being said, you should pick a mission that you’re passionate about - one that you’ll find yourself thinking about in the shower. Since the structure of a startup is usually flat, your voice would naturally carry more weight, so that your ideas are more valuable to the mission.
People are the most important asset of a company. They are the key ingredient that make or break all other parts of the business. Therefore, you want to identify the people you want to work with, with the goal of becoming a core part of that community.

There are numerous channels to learn about the people affiliated with a company. LinkedIn and Crunchbase are good gateways for collecting information about the founders, team, and investors. Ask yourself whether you see yourself working with these people.

At a Series C or earlier stage startup, you usually have the chance to build a personal connection with the founders and executives. Schedule a phone call or one-on-one with them to get a glimpse of their thoughts about the company’s future.
Work on projects that have a high impact on the business. Your value is correlated to the return on investment of the project that you contribute to. Always talk to your hiring manager beforehand about team assignments and product timelines, and aim to reach agreement in your expectations for one another.

If the startup has a blog, read about their recent work so you have a better sense of what the company is actually working on.
Find a startup with crazy upward trajectory in multiple areas: revenue, headcount, users, new products, market share, etc. You want to be at a startup where things are going to, if not already, grow exponentially. You can usually inquire about these stats from the company once granted an offer.

If the startup has not yet reached the growth stage, but you believe it has great potential, there are many more questions you have to ask before making a logical decision. Has the company already figured out the product market fit? How do they plan to scale given the current state of operation? What can I bring to the table that will help the company accelerate growth?

There are two things you shouldn’t overemphasize on: profitability and funding. Word on the street is telling us blitzscaling trumps everything. Over 80% of 2018 IPOs are unprofitable is the market trend we are observing, so you should have the confidence to join a place with high growth and high burn rate. And speaking of funding, if a company has recently raised a large round of financing, it only tells that the company has a longer runway before having to raise again or reach self-sustainability. Actual growth stats should be weighted more in your analysis than the amount the company has in the bank account. So remember that these numbers do not tell the whole story.
You get rich by owning things. Calculate what percentage of the company you are going to own. Negotiate for higher equity if you can. Even if the stocks could be worthless, equity is always a better motive for personal growth than cash is. (a16z has a great intro explaining how stock options works if you are new to this subject - link)
Last but not least, join a startup where you would enjoy working. If you are going to spend most of your time on weekdays, and possibly weekends, at a fledgling startup, you want to make sure that you can sense the joy of being there, otherwise burnout is hard to avoid. What kind of culture did you feel during onsite? If you are going to disrupt an industry, you might as well have some fun doing it.

The described method is purely derived from my personal philosophy and experience, as the word “right” varies per individual. I do hope that this essay can at least serve as a guideline to help you make a decision, or get you start thinking about joining a company you would not have considered before. If you are looking for a place to start, below is a list of accredited resources on high potential startups:

Thanks to Aleksander Bello, Rohan Varma, Rinko Shen, and Austin Poore for reading the draft and giving feedback on my writing.