As part of the continued series on startup anti-patterns, we look at the crippling effect of overanalyzing decisions: “Analysis Paralysis.”

First, a story. In 2014, a promising IOT startup in my portfolio (which I won’t name) was working on a revolutionary home security product. The product was cutting edge from an AI standpoint. The founders were technical experts in the space, with significant research capabilities – a team of experienced data scientists who were obsessed with making the perfect product. Every decision—feature prioritization, UI design, pricing model—underwent exhaustive deliberation.

At first, this thorough approach seemed like a strength. Investors admired the team’s commitment to quality, and the startup attracted a talented group of engineers. However, as competitors rapidly iterated and released new features and products, the company was stuck in internal debates and small optimizations. Every feature had to be optimized before launch and ready to scale, delaying releases and updates.

By 2018, the company had a state-of-the-art product—but no real traction. Customers were frustrated with delays in updates to the amazing hardware they bought. Meanwhile, Ring, a competitor with a simpler and cheap solution, captured the market. Ultimately, the company failed not because of poor technology but because they could stop analyzing and optimizing solutions, leading to significant delays.

What It Is

“Analysis Paralysis” is the anti-pattern where startups become so obsessed with making the perfect decision that they fail to make any decision or don’t make decision fast enough. Rather than moving forward with a well-informed but imperfect plan, teams get stuck in endless cycles of research, deliberation, and second-guessing.

Startups are full of uncertainty, and founders often believe that with enough data and discussions, they can eliminate all risk before acting. However, in reality, no amount of analysis can completely eliminate uncertainty. Velocity and momentum often win the startup game – the cost of not making a decision often outweighs the risk of making an imperfect one.

Why It Matters

Startups thrive on speed and iteration. When teams fall into Analysis Paralysis, they risk:

1. Missed Market Opportunities – Startups that hesitate lose out to faster-moving competitors who are willing to launch quickly, learn from customer feedback, and iterate. Very few products are perfect on arrival (read: your startup doesn’t have billions of dollars available to deliver close to perfect product like Apple). Often startups just need to put a stake in the ground, get the product out there, and learn from customers in the real world
2. Wasted Time and Resources – Overanalyzing decisions drains resources that could be better spent executing and testing in real-world conditions. Every day that goes by inches your company one day closer to extinction.
3. Low Team Morale – Employees working in an environment of indecision can become frustrated, disengaged, or even leave, further slowing progress. Obviously, employees want to be heard and bottom-up innovation often wins, but eventually the team wants and needs leaders who can make tough calls and chart a course for the company. If folks won’t see progress in a timely manner they will get frustrated.
4. Investor Skepticism – Venture-backed startups must show progress. If investors see endless discussions without action, they may lose confidence in the leadership.

Diagnosis

To determine if your startup is suffering from Analysis Paralysis, ask yourself the following questions:

Are key decisions frequently delayed due to excessive internal debate? Obviously, you want to leave room for debate, but note everything is and should be debatable.

Does your team frequently revisit past decisions instead of executing? Retros when a major failure happens are okay, but that’s different than consistent and continuous revisiting of decisions made. Sometimes the team just needs to move on.

Are you gathering more and more data but struggling to take action? This could also be an indication that your team is now gather the right data, or maybe the data is “garbage in, garbage out”. this could either be an analytics problem or you might not be asking the right questions. If not, it could be another sign of analysis paralysis.

Do competitors seem to be moving faster while you’re still deciding? This is less about feature parity of chasing the competition, and more about pure execution momentum.

Do team members feel exhausted from constant deliberation with no resolution?
The frustration could be driven by a single, or few, specifical team mates who tend to have hard time moving on, or it could be a cultural indication that your startup is suffering from analysis paralysis.

If the answer to a many of these questions is yes, your team might be suffering from analysis paralysis.

Misdiagnosis

Not all thorough decision-making is bad. The key distinction is whether the analysis is enabling action or preventing it.

For example, in Some industries (such as healthcare – pharma or medical devices) careful regulatory and considerations are required to get a product to market. However, even in these cases, delaying indefinitely is dangerous.

Analysis is key for success. Don’t fall into using the analysis paralysis to “shut down” voices within the company. It’s not just important that employees and stakeholders be heard – it’s critical that they are heard because often they have great insights to bring the table. Even if those insights shouldn’t stop you from moving ahead they might help you refine your strategy and approach.

Refactored Solutions

If your startup is stuck in Analysis Paralysis, consider these steps:

1. Set Decision Deadlines. Establish clear timeframes for making key decisions. When the deadline arrives, make the best choice with the information available and move forward.
2. Use the 70% Rule. Jeff Bezos popularized the idea that decisions should be made with 70% of the information you wish you had. Waiting for 90% or 100% is often too slow.
3. Prioritize Speed Over Perfection. Encourage a bias toward action, and exhibit that yourself as a founder in the company . In most cases, launching a minimally viable version and iterating based on feedback is better than over-engineering upfront.
4. Empower Decision-Makers. Avoid groupthink and endless consensus-seeking. Clearly Delegate authority and trust individuals or small teams to make decisions within their domain. Back your leaders and make sure that the team knows that are making a decision and once it’s made they shouldn’t question those decision until more data is present.

When It Could Help

In some cases, thoughtful deliberation can be valuable:

• High-Stakes Decisions. When a decision is truly irreversible or has major legal, financial, or ethical consequences, careful analysis is warranted. A decision still needs to be made so having a reasonable deadline to achieve the decision could make sense.
• Strategic Inflection Points. If pivoting the company or entering a new market, taking extra time to gather insights can prevent costly mistakes. It’s often okay to “pay” in capital or time to gather data in order to make better decision in the future.

Conclusion

Analysis Paralysis can quietly, over time, kill a startup. Startups win not by avoiding mistakes, but by learning from them quickly and adjusting.

Founders who obsess over perfect decisions often end up making none at all, or at least not as many as they should have. If you find your team stuck in endless deliberation, it’s time to shift gears—because in the startup world, momentum and speed are everything.

As part of the continued series on startup anti-patterns, we look at the perilous pursuit of endless new unknown markets: “Chasing Blue Oceans.”

What It Is

“Chasing Blue Oceans” is the anti-pattern where startups repeatedly seek untapped markets that lack competition but also lack the necessary customer demand or market size to sustain a venture-scale business.

Inspired by the popular business strategy book Blue Ocean Strategy, this anti-pattern emerges when founders prioritize chasing open field opportunities ahead of disrupting well understood categories. In the process founders and team members might be biased and over validate whether that new space is actually worth playing in.

The logic behind the strategy is simple: go where there is no competition. It feels seems and right – why compete with incumbents and other folks i you can, instead, chase a less competitive category. Unlike “Red Oceans” filled with rivals fighting over market share, “Blue Oceans” represent fresh opportunities.

But in reality, these oceans are very often “blue” because there’s no real market to compete over in the first place. Startups that fall into this trap are often visionary but miscalculate the balance between innovation and market reality. They are also risking being “too early” to the market, a well know starup fail point.

Why It Matters

The allure of Blue Oceans can lead to costly distractions, wasted capital, and eventual startup failure. Here’s why:

1. The Market Isn’t Big Enough – The biggest pitfall is misjudging the size of the opportunity. Venture-scale businesses require large and growing markets, but many Blue Oceans are small ponds. If a company can’t find enough paying customers, even the most innovative solution or the best team won’t succeed.
2. Slow or Non-Existent Adoption – Even if a market has potential, it may not be ready for a new solution. Early-stage industries often lack the infrastructure, customer behavior, or urgency to adopt cutting-edge technology, leading to long sales cycles, slow growth, and an inability to scale. No scale = no funding. Companies die because they run out of many, not because they don’t have great directions and ideas.
3. Endless Pivoting Without Progress – Startups chasing Blue Oceans could fall into a pattern of constant pivots, each aimed at discovering a more promising market. Instead of iterating toward product-market fit, they end up on a never-ending quest for an opportunity that may not exist.
4. Lack of Competitive Pressure Can Be a Bad Sign – While competition can be intimidating, it often validates that a real market exists. If no one else is operating in a space, it’s worth asking why. Are you truly ahead of the curve, or is there simply no real business to be built there?

Diagnosis

To determine if your startup is “aimlessly” Chasing Blue Oceans, ask yourself:

• Are there real, paying customers who urgently need your product? If your sales pipeline is full of “interested” but non-committal prospects, your market may not be viable. Also, are those customers growing themselves and are they willing to pay enough for your product to justify the efforts involves and selling, building the product, and servicing those customers
• How many companies have successfully built a business in your space? If the answer is close to zero, there’s a good chance the opportunity is too niche. No competition is bad sign.
• Are you shifting markets every 6–12 months? Frequent pivots in search of a better market are a strong signal that you’re in Blue Ocean territory.
• Does your market have natural adjacencies? Some markets start small but can expand into larger ones. If your Blue Ocean doesn’t naturally lead into a Red Ocean with more opportunity, you may be stuck and should reconsider.

Misdiagnosis

Not all Blue Ocean strategies are bad. Some companies do create entirely new markets—Airbnb, Uber, and Tesla are examples of companies that initially seemed to be chasing obscure opportunities. However, the difference is that these companies had:

1. A clear, pent-up demand for their product. They weren’t just innovating for innovation’s sake; they were solving real problems that customers desperately wanted addressed.
   Further, they were presenting entirely new product that disrupted or out-innovated customers. Tesla built and electric car – a car that at the time didn’t have much demand, but cars in general represent a huge opportunity. AirBnB scaled an existing product (home rentals) to compete with hotels.
2. Mass-market potential. They weren’t building niche solutions; they were creating new behaviors in industries worth billions. Their products seemed niche at first, but took over the red ocean market eventually.
3. The ability to convert skeptics. A common mistake in Blue Ocean thinking is assuming that people will adopt a new behavior without friction. Market creators must have a strategy to drive mainstream adoption.

Refactored Solutions

If you suspect your startup is Chasing Blue Oceans, consider these adjustments:

1. Validate Before Building. Before you commit years of effort, validate that real customers will pay for your product. Conduct interviews, run pilot programs, and test demand in measurable ways.
2. Start in a Red Ocean and Expand. Many successful companies start in competitive markets, prove their value, and then carve out their own niche. Competition often means there’s real demand.
3. Assess Market Timing. Some ideas are great but too early. If infrastructure, regulation, or customer behavior isn’t ready for your solution, you may need to rethink the business model. A pivot might be necessary. Time is money and your company burns cash everyday. You can’t wait forever for the market to mature.
4. Focus on Real Urgencies, Not Hypothetical Ones. Entrepreneurs often get excited about theoretical problems that “should” exist but don’t actually cause enough pain for customers to pay to solve them.
5. Look for Big Adjacencies. If your initial market is small, make sure it has clear expansion opportunities into larger, profitable segments. If that is the case it might make sense to invest in a small blue ocean market, with the clear understanding that this is a temporary workaround that will lead to a big opportunity.

When It Could Help

Despite the risks, Blue Ocean thinking can work when applied strategically. It may be worthwhile when:

• Your solution is truly revolutionary. If you have a breakthrough technology or business model, like OpenAI with generative AI, a Blue Ocean may be justifiable. This is especially true if you have new, foundational technology, that changes the target market.
• You can create network effects. Some markets start small but explode once they reach a critical mass (e.g., social networks, marketplaces, and platforms). If you have clear conviction and data that the Blue Ocean opportunity will become massive (not based on a wild bet) than being the first to open up this opportunity might be a smart thing to do.
• You have the capital to educate the market. If you have the runway to build awareness and shape customer behavior, you might be able to create demand over time. Unfortunately, most startups don’t.

Conclusion

The dream of an uncontested market is enticing, but the reality is often less glamorous. Chasing Blue Oceans without validating market size, demand, and urgency can lead startups down a costly and frustrating path.

Instead of prioritizing open space, founders should prioritize solving big, well-defined problems for real customers. Remember, most successful startups don’t win by avoiding competition—they win by executing better, moving faster, and solving problems that matter at scale.

The unfortunate reality and VC pattern recognition is that disrupting and innovating in a well understood, at scale, market. A red ocean. If often and easier path to building successful scalable startups. Those markets have clear demand and a new technology addressing the existing large market in a completely new way can hit the ground running right away, instead of waiting for the market to show developer, if ever.

First, a story.

In 2012, Twitter launched Vine, a platform that allowed users to create and share six-second looping videos.

Vine quickly gained popularity, becoming a cultural phenomenon and amassing a substantial user base. At its peak in December 2015, Vine had over 200 million active users(!).

However, as competitors like Instagram and Snapchat introduced their own short-form video features, Vine struggled to keep up. Instead of innovating and focusing on its unique strengths, Vine attempted to mimic its competitors’ features. This reactive approach diluted its brand identity and the company lost traction with it’s users. By 2017, Vine was discontinued, serving as a cautionary tale of the perils of chasing the competition.

What It Is

“Chasing the competition” is the anti-pattern where startups reactively adjust their strategy, product, or business model based on competitors’ moves rather than their own well-defined vision, Roadmap, and understanding of customer needs.

Instead of focusing on their unique strengths and market positioning, these companies play an endless game of catch-up, constantly shifting their approach in response to external moves.

Startups fall into this trap for several reasons:

• Fear of Missing Out (FOMO): Seeing competitors gain traction with a feature or model creates panic that they’ll be left behind.
• Investor Pressure: Stakeholders often push startups to replicate competitors’ successes, assuming they must be doing something right.
• Lack of Confidence in Original Strategy: When a startup is unsure of its own value proposition, it looks outward for validation rather than inward or into it’s customer base for conviction.
• Media and Market Hype: Tech media amplifies competitor successes, making founders feel like they must follow suit.

The problem? By the time a startup reacts, the competition has often moved on. Worse, the startup risks alienating its existing customers by failing to deliver what originally made it valuable.

Why It Matters

Chasing the competition can be disastrous for startups. Here’s why:

• Loss of Identity – Startups that constantly shift their strategy can lose their unique value proposition. Customers don’t know what they stand for, leading to weak brand positioning.
• Strategic Drift – The company’s roadmap becomes dictated by external forces rather than internal conviction. This can lead to wasted development cycles and diluted focus.
• Poor Product-Market Fit – Features copied from competitors may not align with the startup’s core user base. This can result in low adoption rates, increased churn, and a confused user experience.
• Inefficient Resource Allocation – Constantly reacting to the market means frequent shifts in development priorities, marketing strategies, and sales approaches. This unpredictability increases operational inefficiencies and burn rate.
• Employee Disillusionment – A startup that continuously pivots in response to competitors can create internal instability. Teams lose confidence in leadership’s vision, and morale declines.

Diagnosis

To determine if your startup is falling into the “chasing the competition” trap, ask yourself:

• Are our product decisions driven by competitor announcements rather than customer feedback?
• Have we pivoted our strategy multiple times and often in response to external moves rather than internal validation?
• Are we sacrificing long-term vision for short-term trends? If so, to what degree?
• Are our employees confused about what our core mission and differentiators are?
• Do we spend more time analyzing competitors than engaging with our own customers?

If the answer is “yes” to multiple questions, your company might be suffering from this anti-pattern.

Misdiagnosis

Not every competitor-inspired move is a mistake. There are valid reasons to take cues from the market, such as:

• Customer-Driven Demand: If your users are clamoring for a feature competitors offer, it probably worth considering.
• Evolving Industry Standards: Some market shifts, such as mobile-first interfaces or AI-driven personalization, become table stakes over time.
• Competitive Benchmarking: Keeping an eye on the competition is healthy, as long as it informs rather than dictates strategy.

The key difference is proactive innovation versus reactive imitation. Are you making changes because they align with your vision, or because you’re afraid of being left behind?

Refactored Solutions

Once diagnosed, here’s how to break free from the competition-chasing cycle:

1. Double Down on Customer Insights – Focus on your users’ needs rather than your competitors’ moves. Conduct regular user research, feedback sessions, and data analysis to validate your direction.
2. Define and Stick to Your North Star – Have a clear long-term vision and resist knee-jerk reactions to market shifts. Your strategy should be based on core principles, not fleeting trends.
3. Develop a Clear Product Roadmap – Plan features and business moves based on long-term value rather than short-term competitive reactions. Make sure each update serves a clear strategic purpose.
4. Limit Competitive Benchmarking – Monitor competitors, but don’t obsess over them. Use them as data points, not roadmaps. Ignore PR and the Media. They often don’t focus on what matters (and sometimes avoid fact checking) and are also naturally gravitate to Selection Bias
5. Empower Your Team to Innovate – Encourage internal ideation rather than external imitation. The best startups continuously create market demand and innovate, rather than just react to market forces.
6. Educate Investors and Stakeholders – If investors push for feature parity with competitors, educate them on why differentiation could be more valuable. Feature parity can eventually lead to a race to the bottom. In started you are actually looking for the opposite, clear differentiation and higher value leading to higher prices and hopefully better margins.
7. Be OK with Not Competing on Every Front – Not every battle is worth fighting. Choose the ones that align with your strengths and ignore the rest. Focus is key.
   
   Here’s one point many early stage founders miss – Startups rarely die because competitors are better or because they run out of money. They die because they lose focus trying to be better at everything instead of being the best at something.

Your biggest threat isn’t your competitor’s bank account. It’s losing sight of who you really serve.

When It Could Help

Are there cases where “chasing the competition” is beneficial? Occasionally, yes.

• When a competitor’s move validates an idea you were already considering. If their success provides proof of concept, it may accelerate your own plans.
• When industry shifts make competitive parity a necessity. If a fundamental technology (e.g., cloud computing, AI, mobile-first) becomes standard, failing to adapt can be risky.
• When entering a mature market where feature expectations are well-defined. In highly competitive industries, some level of parity is expected, though differentiation remains key.

Final Thoughts

Startups succeed by playing their own game, not by reacting to someone else’s. While it’s important to stay informed about the competitive landscape, true success comes from focusing on your vision, your customers, and your strengths—not just keeping up with the latest feature war.

If you’re chasing the competition, stop and ask: What do we stand for? What makes us different? If you can answer those questions with clarity and confidence, you’re on the right path.

First, a blast from the past which some of us might remember.

As a kid growing up in the 80s, I was a movie junkie and rented movies from Blockbuster several times a week. I’d binge-watch the movies I loved (I’ve probably seen the entire James Bond series 20 times). Back in the 80s, Blockbuster was somewhat okay—they had policies around late returns, but those weren’t draconian, and the late fees were manageable. I could pay a reasonable amount of money if I wanted to keep a VHS tape and watch it on repeat.

At some point around the turn of the decade, Blockbuster decided to change its policies. I’m wildly speculating that someone at Blockbuster’s Corporate recognized an opportunity to make a few more bucks from a (probably significant) subset of customers who were late in returning video tapes. Blockbuster decided to charge exorbitant late fees for no real reason.

It was frustrating and kept customers on their toes. The brand image deteriorated. Employee discretion policies regarding charging late fees became increasingly aggressive (the “my dog ate my VHS tape” excuse quickly became frowned upon), not surprisingly, given the incremental revenue lift late returns delivered to the chain. Blockbuster became the one shop on my street I was always trying to avoid.

Unfortunately for Blockbuster, they made the wrong move. Their choice to create significant friction with customers left them completely open to alternatives. We all know how the story ended. Netflix came about and was happy to lend customers DVDs for as long as they wanted to binge. That simple tweak, putting customers first, made a big difference and eventually (among other things, such as streaming and online content piracy) led to Blockbuster’s ultimate demise.

What is it?

It might seem odd, particularly in what feels like a Tech recession (or potentially a broader recession), to talk about the concept of “good vs. bad revenue”. Some of you may be thinking that “Revenue is revenue; all revenue is good!” Unfortunately, that is not always the case.

“Bad revenue” is revenue that comes at the expense of building the long term viability of the business. Below are a few examples of “Bad Revenue”:

• Comes at the expense of the relationship with customers – For instance, a company that hinders their clients’ ability to cancel when they want to or sells something overpriced, taking advantage of the customer’s needs. This could lead to Churn, low NPS scores, and angry clients which can hurt your organization’s reputation.
• Negative or very low contribution margin – The deal with the specific customer is either unprofitable or the margins are significantly lower than those with “good revenue.” The opportunity ends up negatively impacting the company’s financial resources.
• Outside of target audience – Revenue opportunities outside the company’s customer target are more difficult to acquire, and win rates are significantly lower. Even if we win the customers, the ability to create a delighted customer is at risk because the company and product are not set up to win the relationship. Further, those opportunities don’t help your organization learn and evolve.
• “Customer from hell” – Customers who are over-demanding or just plain rude can lead to frustration and churn among the company’s employee base. These customers are unlikely to become an advocate for the business and won’t be good references either.

In contrast, “good revenue” typically generates strong profitability because it is from deals that we know we can support well. The customer is delighted and the product helps them achieve their goals. The customer scores high on NPS scores and is proud to share their delight, serving as an advocate and reference. Engaging with the customer strengthens our collective understanding of our customer’s needs and helps cement our position in the market. It enables us to more easily find and pursue additional deals and revenue.

Why it matters?

Bad revenue can drain the company’s resources and divert management and employee focus toward less productive venues. Good Revenue informs your next decision. Bad Revenue distracts you from it.

Focusing on good revenue could mean that the company probably won’t grow as fast as some of our competitors. However, it does mean that customers will genuinely love the company and want to work with us over a longer period. In the short term, you might miss your goals, but it will be a win in the long term.

Furthermore, bad revenue often comes at the expense of good revenue creating a high opportunity cost. Instead of focusing on the right set of customers, the company’s (often scarce) resources are continuously diverted to energy-draining customer relationships.

Almost every professional has had the unfortunate experience of being stuck in a relationship with a customer who they can’t possibly satisfy. The ongoing frustration could eventually lead to employee dissatisfaction and churn.

Diagnosis

Sadly, too many salespeople are directed by their management to grow revenue at all costs and don’t pay attention to finding opportunities that create “good revenue”. They end up casting a wide net in their prospecting to hit short-term revenue goals, at the expense of the long-term health of the business.

There are several ways to diagnose “Bad revenue” in your organization:

• Profitability is declining, while pricing remains the same – This can be a signal that 1) the company is becoming less efficient, or 2) The company is taking on bad revenue.
• Employ customer profitability analysis – Knowing your average customer profitability and conducting a customer level profitability analysis can help detect relationships which are not making a positive impact on the business. In more mature organizations, this type of analysis should be made on an ongoing basis, or at the minimum at renewals. There are better tools these days to assist with this analysis, such as Lumopath AI (apologizes for the shameless plug to a Recursive Ventures portfolio company).
• NPS scores dropping – Aggregate NPS scores are a great high-level diagnostic tool. Once you spot a negative trend, the trick is to go beyond the aggregate, analyze deviations, and stack-rank customer satisfaction on a per-customer basis. It can be helpful to continuously stack-ranking individual customers and analyzing the bottom quartile of responses. Beyond just better understanding the challenges involving your target market, the exercise can also help understand which types of customers the organization should avoid moving forward.

Misdiagnoses

One common misdiagnosis occurs when companies don’t properly consider “land and expand” opportunities, thus undervaluing the customer relationship. Another form of this is short-term or miscalculations of lifetime value (LTV) of a customer. Instead of considering the long-term potential of the relationship, the company doesn’t properly assess the opportunity and doesn’t end up making the right long-term choice for the business because they think it’s “bad revenue”, but in practice the customer has much more to offer longer term.

Refactored solutions

Once diagnosed, the refactoring of this anti-pattern requires changing the organization’s mindset and approach to sales and customer success. A few ideas on how to refactor best:

• “Firing” customer(s) – If your organization is indeed facing a ‘customer from hell’ or bleeding cash servicing a customer, the easiest solution is to part ways.
• “Improving” Prices – Improving pricing can go both ways. If the customer engagement is not profitable, you can raise prices to achieve the organization’s target profitability goal. Alternatively, if the pricing isn’t sufficiently correlated to the value delivered to the customer, and the customer feels that they are significantly over-paying for the solutions, you could lower the price to help retain the customer for the long term.
• Institute performance-based compensation plans that reflect the overall “health” of a deal – salespeople often get most of their compensation with commissions. Building a scheme that accounts for profitability, Lifetime value, and customer satisfaction goals pushes sales and customer success to prioritize good revenue over “bad” revenue
• Build organizational values seeking “win-win” situations with customers – Win-win situations help build a healthy customer relationship. Obviously, the company needs to strike the right balance and capture value, but avoiding “harvesting” or short-term thinking tactics lead to happy customers, retained over longer periods, and producing higher NPS scores and LTV.
• Embrace Market Research and go-to-market best practices – Start by conducting comprehensive market research to identify your target audience. If possible, avoid diverging from your target audience to focus on the customer you can deliver the most value to first. The company will eventually have to go outside of initial target customer “comfort zone,” but it’s best to avoid doing that early if you have sufficient “runway” with your core target audience.

When it could help?

Sometimes, organizations need revenue badly, and have to accept bad revenue. However, companies should do it with eyes wide open, understanding what they are doing, why they are doing it, and what risks they are taking on.

A few examples in which bad revenue could make a positive, albeit short term, impact:

• Bad revenue could be a necessary evil when the organization needs to fundraise soon (and need to show revenue momentum to investors).
• Related to the previous point, Bad revenue could help contribute to M&A outcomes, with buyer paying a premium for growth or a wider set of customers.
• New market penetration – A company endeavoring into new customer segments and markets might experience a stretch of bad revenue as part of their learning process. This bad revenue could be a necessary evil required to learn the new target market, fine-tune the product offering, or discover the right pricing scheme. If the bad revenue is a means to an end – better understand the market and eventually reaching a good revenue state – it could be an justifiable investment.

First, two stories that highlight two different sides of elephant hunting.

In 2005, Meridio was guaranteed to win a deal worth $15m+. Meridio was a small electronic documents and records management (EDRM) startup whose software ran inside some of the world’s most secure organizations: from banks to oil & gas companies to branches of government and the military. One of its happy customers, the UK Ministry of Defense (MoD), was looking to modernize its infrastructure in a massive IT procurement worth billions. Each of the two integrator consortia shortlisted for the deal had designed Meridio into the solution. It was the largest secure SharePoint deployment in the world at the time: a great proof point of the quality and scalability of Meridio’s software. The future looked bright.

Meridio did win the deal and get the money in the end, but the process nearly killed the company:

• The product roadmap and development prioritization became more complicated.
• Supporting the two fiercely competitive integrator consortia required staffing up teams with semi-duplicated responsibilities: a significant distraction and increase in burn far ahead of revenue.
• Once the MoD deal was awarded to one of the consortia, Meridio had many employees it couldn’t put to productive use quickly. The resulting layoffs impacted culture.

The UK MoD deal was important for Meridio — it influenced the 2007 sale of the company to Autonomy, now part of OpenText — but it was less impactful from a valuation standpoint than the company imagined it’d be. Winning the deal came at the expense of distraction and operational inefficiency, both of which affected growth in other areas of the business. Also, there never was another deal like it.

And now for story #2. In 2014 Life360 hit gold. After 18 months of lengthy negotiations, Life360 landed a $50m investment deal from ADT, the global leader in Home Security, coupled with a strategic joint product development opportunity that could net the company tens of millions of dollars in revenue. The team was dancing on rooftops!

In 2019, long after the commercial deal was dead in the water, Life360 decided to go public early (compared to its peers), and one of the considerations was ADT’s significant position as an investor in the company. Further, after years of development that sucked, at times, half of our engineering team’s bandwidth, the product we launched was discontinued and made no contribution to our business. When the company struck the deal employees were initially very excited. They believed that the organization they were working with would be as devoted to the strategic deal’s success as their small startup was. Three management team changes later, it became clear that the deal, which was one of the highest priority items on Life360 plate, was a pretty low priority for ADT. New execs at the company didn’t feel a real commitment to it, and a Private Equity acquisition coupled with organizational changes didn’t help much either.

Everything is easier in hindsight, but Life360 could have avoided this. Luckily, the deal didn’t end up being a company killer and the other parts of the business helped Life360 cement a great spot as a public company. It’s probably fair to say Life360’s success happened despite the ADT deal, not because of it.

What it is?

“Elephant Hunting” is a buzz term describing the practice of targeting deals with very large customers. For example, hunting an elephant in the context of a startup could be a seed-stage company targeting the likes of Google or AT&T as a customer in a million-dollar deal. These customers can provide large contracts, but they can be hard to catch and require large teams to tackle. With business-to-business (B2B) startups, there’s almost nothing more exciting (or seductive) than hunting and bagging an elephant-sized deal. It can produce huge revenue growth, provide you with highly leverageable customer references, and it’ll excite investors. Once you hunt down an elephant, it can feed many mouths (and egos) at the company for a long time. What could be better?

Be warned: the pursuit of elephants can be a dangerous game. If you fail to “kill the elephant” it might well be the one killing you. Unlike young and dynamic startups, elephants are organizational dinosaurs and striking a deal with an elephant will require your entire team — from sales to engineering — to engage with the elephant at different levels of the organization. This engagement happens over months, sometimes years. Even if you succeed in getting an elephant, you may get less benefit than you expected, as the cases of both Meridio and Life360 demonstrate.

Why it matters?

Elephant hunting can bring your company down on its knees. Here are some perils to be aware of:

• No repeatability. Elephants are hard to catch and often there aren’t enough of them. Meridio never found another UK MoD. Life360 never found another ADT.
  
• Heavy operational burden. When you pursue and, later, land an elephant, it’s tempting to put all your resources into serving them. But this can lead to neglecting other clients and missing out on potential opportunities. Both Meridio and Life360 suffered operationally while selling and, later, servicing their respective elephants. Elephants may demand extended payment terms or lower prices, which can put a strain on a startup’s finances. It’s important to carefully consider the financial implications of taking on an elephant client.
  
• Missed learning opportunities. When you and your team are laser-focused on one client you might be missing the forest from the trees. As a startup, you seek scalable solutions that matter to most potential customers you want to serve. More feedback is better, and getting feedback from just one elephant makes it harder to identify the scalable, repeatable, products that your target audience needs.
  
• Overpromising and underdelivering. In the rush to impress an elephant, startups may make unrealistic promises they can’t keep. This can damage their reputation and lead to the loss of the elephant and future clients. Elephants have tall expectations for products and services delivered, as well as a web of requirements across legal, compliance, cybersecurity, etc. that smaller companies may be incapable of servicing well.
  
• Compromising your identity. When a startup lands an elephant, it’s easy to become absorbed in their world and lose sight of your own identity and values. This can lead to compromises that go against your startup’s mission and culture. Note, for example, how many big tech companies have had to compromise to do business in China.
  
• Losing control. Elephants may have their own demands and expectations that clash with a startup’s way of doing things. This can lead to a loss of control and autonomy, as the startup becomes beholden to the elephant’s whims. On the partner/channel side, this relates to the platform risk anti-pattern. In conclusion, while landing an elephant can be a huge boost for a startup, it’s important to be aware of the perils that come with it. By maintaining a balance, staying true to your values, and carefully considering the operating implications, startups can avoid the dangers of elephant hunting and build sustainable growth.

Diagnosis

Diagnosis is relatively straightforward. Here are a few signals that you might be spending too much time elephant hunting or are getting sucked into the Savannah:

• Are you and your sales team spending most of your time focused on one deal with a big enterprise client? Has this been going on for an extended period?
  
• Are you increasing spend ahead of revenue more than what you’d normally do for just one or two deals?
  
• Is a significant chunk of your engineering team’s bandwidth focused on building custom features for one big customer? Does it feel like this customer is essentially dictating your roadmap for the foreseeable future? Do you find yourself having to promise steep SLAs and help desk hours that you know your existing team can’t support now or in the near future? Startups often do need to stretch to deliver, but if your team feels that servicing the elephants will consume the entire company, they’re probably right.

Misdiagnosis

A common misdiagnosis stems from not fully understand or realizing the scope and bandwidth consumption of Elephants. Often, it’s easy for the team to get excited about big deals and they tend to look the other way. Developing and delivering products to Elephants comes with significant overhead, longer sales cycles, lower win rates, and, often, requirements and standards that don’t make a positive impact on the joint outcome, but suck a lot of time and energy from everybody in the room.

Put together KPIs and tools to help you measure the impact elephant hunting has on your Sales and Engineering teams and make data-based decisions.

If your startup is investor-backed, remember that your job is to grow equity value. Revenue, profits and growth are pieces of how equity value is determined. Ask yourself whether the pursuit or even the winning of an elephant will have a meaningful positive impact on equity value given all the positive and negative externalities.

Refactored solutions

Once diagnosed, the refactoring of this anti-pattern very much depends on the set of challenges and opportunities your company has at hand. A few ideas on how to make the most out of Enterprise customers without consuming your entire (small) organization in the process:

• Try to strike a smaller, multi-phase, deal with the Elephant. That would help both sides build confidence and capabilities to better serve each other.
  
• (Artificially) Limit the resources devoted to elephant hunting. Be ruthless about this with your sales and bizdev folks. They’re likely to gravitate towards elephant hunting — these deals tend to be very exciting.
  
• Continuously measure and analyze how much your team spends on custom work (especially non-repeatable deals and non-productizable work). It might put a strain on your relationship with the Elephant customer, but good Sales and Customer success teams can help strike a balance and set expectations.
  
• Do you have enough slack to sign a deal with an Elephant? One good rule of thumb is assuming that deal will require twice as much resource and time compared to your original expectations. If that’s the case, would you still execute on the deal?

When it could help?

Does this mean you should never try to hunt elephants? No, but it does mean you should think very carefully about it, and be prepared to answer a few questions: 

1. Where does elephant hunting fit in your sales and growth strategy; near vs. longer term; lower-hanging fruit vs. higher up your sales tree?
2. How many elephants are there for you to hunt? Is that a real market niche for your business?
3. Do you have the human resources to hunt and satisfy elephant-sized customers?
4. Do your sales, engineering and customer success people have the skillsets and experience to satisfy this species of customer? 
5. Does your CEO have the bandwidth and skill to take down the elephant? This strategy often demands an inordinate amount of the CEO’s time. Which of the CEO’s other responsibilities might suffer?
6. Does your company have the financial resources to survive and thrive in the face of typically slow decision and purchase cycles? Will investors give you (relatively) cheap cash so that you can wait for the revenue?

For many startups, the transition to spending more time on Elephant hunting is part of the startup journey from childhood to adolescence. If you have good answers to the above questions, a more mature product that is ready to scale, you and your team might be ready to make the move, but tread carefully so you don’t end up being yet another victim on the plains of the Serengeti.

Co-authored with Simeon Simeonov. More startup anti-patterns here – https://blog.simeonov.com/startup-anti-patterns/ 

An anti-pattern is a commonly used process, structure, or pattern of action that, despite initially appearing to be an appropriate and effective response to a problem, has more bad consequences than good ones.

Simeon Simeonov first wrote an introduction to the value of startup anti-patterns back in 2013. To sum it up, it’s hard to pinpoint the exact set of reasons startups succeed, but experienced entrepreneurs and investors have a good sense of what drives startups’ failures.

Startup anti-patterns are all about that — patterns that increase the risks associated with startups (hey, it’s a risky business to begin with). Pursuing an anti-pattern doesn’t mean that your company will die tomorrow or in the next year, but each anti-pattern adds-up and could lead to clouding your focus and hampering your ability to execute.

Together with Itamar Novick from Recursive Ventures, Simeon Simeonov is bringing the Startup anti-pattern series to life. Stay tuned for more in this series as we work through each anti-pattern with tangible examples from our experiences as founders and investors in 100+ startups, and the experiences of guest founders from our portfolio.

Startup Anti-Patterns full list (work in progress…)

Studying repeatable patterns of startup failure (startup anti-patterns) is more useful than studying non-repeatable strategies for startup success.

Top Startup Anti-Patterns:

1. Elephant hunting
2. Ignorance
3. Platform risk
4. If you build it, they will come
5. Bad revenue
6. Chasing the competition
7. Chasing Blue Oceans
8. Analysis paralysis
9. Arrogance
10. Attribution risk
11. Bleeding on the edge
12. Boiling the ocean
13. Bridge to nowhere
14. Changing strategy instead of execution
15. Confirmation bias
16. Confusing activity with results
17. Consulting to product
18. Death by pivot
19. Deathmarch
20. Delayed scaling
21. Demand generation
22. Design by committee
23. Designing for investors
24. Drag
25. Escalation of commitment
26. Escape to the familiar
27. Escapism
28. Featuritis
29. Forward thinking
30. Founderitis
31. Groupthink
32. Hail Mary
33. Ivory tower
34. Lack of focus
35. Lagging indicators
36. Learned helplessness
37. Long feedback cycles
38. Lying to investors
39. Magic salesperson
40. Mentor whiplash
41. Missing your exit
42. Myopic bootstrapping
43. Next round only
44. Not knowing your investors
45. One-off customization
46. Oooh, shiny!
47. Overengineering
48. Overselling
49. Oversteering
50. Platform trap
51. Premature optimization
52. Premature scaling
53. Promiscuity
54. Proof by anecdote
55. Pushing a rope
56. Raising too little
57. Random founders
58. Scapegoat
59. Second class citizens
60. Seed extensions
61. Secrecy
62. Silver bullet
63. Spreadsheet Bingo
64. Stovepipes
65. The one idea entrepreneur
66. Top-down planning
67. Uber pivot
68. Underqualifying
69. Unicorn hunting
70. Unrealistic expectations
71. Warm bodies
72. Weak board
73. Yes man
74. Zombie
75. Outsourcing your architecture (via Alan Neveu)

Note: the list is not “drawn to scale.” Some anti-patterns occur more frequently than others and some are more likely to cause a startup to fail than others.