[Upcoming Virtual Event] Real Talk from the Top
Female leaders are switching jobs at the highest rates we’ve ever seen, and ambitious young women are prepared to do the same. To make meaningful and sustainable progress toward gender equality, companies must go beyond table stakes, understand inequities and develop programs to sponsor women leaders across their organizations.
To celebrate Women’s History Month, we invite you to join a panel discussion led by an Insight Partners Managing Director and three portfolio company CEOs who will share their personal journeys for how they got to where they are in their careers.
What Unicorns Know: The Physics of Scaling for Growth
A ScaleUp company is a vehicle for rapid business growth, whose momentum can be likened to that of a professional NASCAR or Formula 1 race car – where speed is a key determinant of success.
There is a notion for SaaS companies that to get to $100M in 5 years and be valued at $1B (unicorn status), companies need to follow T2D3; that is, they need to triple their revenue growth two times and then double their growth three times. Not all companies will follow this trajectory of growth, and different industries also have varying growth rates. Growth is key for any company to scale effectively, whether it is a startup, ScaleUp, or mature public company.
However, any object moving at a high velocity faces physical forces of resistance that must be overcome to achieve the speed and agility required to win. These restraining forces have business corollaries that act as inhibitors to scale, the net effect of which, if not minimized, can determine whether a company realizes its market potential.
The following four physical forces work against any body in motion, including a fast-growing company: Drag, Inertia, Friction, and Waste.
Drag is the resistance of air against a moving object. Drag in the business context is often present at the strategic level, e.g., adverse indicators such as sluggish market moves, inability to change direction with agility, and company-wide misalignment of strategies and objectives.
A few key questions can help you assess whether your company may be vulnerable to drag:
Does your company have clarity on Where to Play and How to Win?
Do all business operations and functions have supporting strategies aligned to these choices?
Does your company have clearly defined and relevant strategic priorities?
Do all business operations and functions have contributing metrics?
Are cascading goals in place to deploy strategies and achieve metrics?
Inertia is the resistance to any change in the current state of motion. Corporate inertia is often responsible for waning product performance and competitiveness, feature fatigue, and a poor innovation pipeline.
The following questions can help you assess whether your company may be vulnerable to inertia:
Does senior leadership favor experiments over ideas?
Is constant experimentation a required core competency?
Are fresh opportunities and new insights consistently pursued through experimentation?
Do you have a common method for rapid experimentation with customers?
Do you have a standard approach for advancing early experiments toward innovations?
Friction occurs when moving parts rub against each other and is a common cause of slow adoption speed, poor customer experience, retention/renewal difficulty, and undelivered customer outcomes.
The following questions can help you assess whether your company may be vulnerable to friction:
Do customers realize value from your products quickly and effortlessly?
Do you have documented customer jobs-to-be-done for all key customer profiles?
Do you clearly understand the job(s) your customers are trying to do?
Are your products and services aligned to customer/user desired business outcomes?
Do you have a prioritized list of opportunities to improve the customer experience?
Waste is the motion of performing unneeded, unrequested, or unnecessary work or the byproduct of that activity, which restricts value flow.
Waste is perhaps the most prevalent impediment to value. It is present not so much because the work being performed is inefficient but rather because it is ineffective, defined simply as doing the wrong work. As business strategist Peter Drucker once noted, “There is surely nothing quite so useless as doing with great efficiency what should not be done at all.”
Companies in the ScaleUp stage are often fraught with waste simply because growth has outpaced development of the standardized operating processes needed to sustain the business into the future.
Insight Onsite’s work with dozens of ScaleUps reveals that waste most often takes the form of performing work that no one, especially a customer, is asking for or needs.
The following questions can help you assess whether your company may be vulnerable to waste:
Is high priority placed on eliminating all forms of value-destroying waste?
Do key customer value-adding activities optimize quality, cost, speed, and experience?
Do you have standard operating procedures for all key processes?
Is continuous process improvement a company-wide capability?
Do senior leaders actively champion and participate in process optimization?
Typically, most ScaleUps cannot answer the questions above with a resounding “yes!” A new and effective operating framework is often needed to address the unique way restraining forces manifest themselves in rapidly growing software companies. The framework centers on the concept of “lean.”
Lean should be a grand unifying concept encompassing a concerted effort to reduce the momentum-stealing effects of drag, inertia, friction, and waste. While lean methods are the benchmark in manufacturing settings and have been applied with some success to entrepreneurial startups, broad application of lean-based principles to software technology enterprises remains mostly a counterintuitive concept and rare practice.
Ask yourself the questions above, and if you find many apply to your business, read more for how to implement the lean principles of SCALE.
Break Through with These 5 Lean Principles from Unicorn Companies
In 1988, John Krafcik coined the term “lean” in his graduate work at MIT’s International Motor Vehicle Program. His paper, “Triumph of the Lean Production System,” challenged that it was not the location, the culture, or even the technology that determined car manufacturing plant performance. Indeed, the plants that operated with a “lean” production mindset were highly productive, while maintaining high quality. Lean was his way to express what he came to believe in his previous role as a Toyota manufacturing engineer to be the essence of the game-changing Toyota Production System: “an absence of slack in the system, aka waste.” Krafcik famously went on to become CEO of Waymo, the self-driving car company spinout of Google’s parent company, Alphabet.
A key part of Insight Partners’ approach to helping portfolio companies scale has centered on helping leaders eliminate these kinds of organizational impediments, applying the principles of lean thinking in a rather unconventional way: to the operations of software ScaleUps. That work with highly successful “unicorn” companies has led to the development of five foundational principles any company can use to create rapid and lasting growth.
Five lean ScaleUp principles
The term “lean” became popularized as a management philosophy with the 1996 bestseller Lean Thinking by James Womack and Daniel Jones, who led the MIT study during John Krafcik’s graduate work in the late 80s. In 2011, lean gained a resurgence in the tech world with Eric Ries’ The Lean Startup, which focused on helping entrepreneurs test ideas and iterate quickly.
Over the years, lean has evolved and grown to become an organizing principle that engages people in adding the highest possible value for customers across all operations. What makes lean compelling and different as a management philosophy is how that value is created. The lean process is one of addition by subtraction — reducing or removing anything that impedes the free flow of customer-defined value. Amazon calls it “working backwards.”
We have discovered that applying a broader interpretation of lean can be a powerful stance for battling the momentum-stealing effects of drag, inertia, friction, and waste. By keeping Krafcik’s original idea of “zero slack” front and center in efforts to help tech firms scale for growth, we have seen certain themes repeat themselves across various successful scaling companies. Those patterns evolved into a set of guiding principles, which, when adopted, make success more likely. The handy mnemonic to remember is SCALE:
Espirit de Corps
Learn more about using these lean principles for rapid, lasting growth. What a Unicorn Knows is out now!
Principle 1: Strategic Speed
Fighter pilots, professional cyclists, and race car drivers know what geese flying in a V formation know: You can travel faster and farther with half the effort by “drafting” in the slipstreams created by those in front of you. The faster you go, the more energy you save. It’s a virtuous cycle. And the more people in alignment, the bigger the slipstream, so you go even faster. This is the simple physics of momentum, the equation for which is velocity (speed with direction) times mass.
You can apply the concept to your company’s strategies. We call it strategic speed, defined as the optimal speed for swift strategy deployment and decision-making.
To produce a similar effect and create the organizational equivalent of slipstreams requires strategies, priorities, and objectives to be simultaneously linked vertically and horizontally. Mechanisms like Japan’s Hoshin Kanri (“strategy deployment” or “policy management”) and the younger but more well-known Western version, OKRs (objectives and key results), implemented with tools and practices like the lean alignment practice of catchball — essentially the business equivalent of the children’s game of tossing a ball back and forth — help boost strategic speed.
We have observed that ScaleUps achieving company-wide alignment are able to accelerate their growth over 30% more than their peers.
Principle 2: Constant Experimentation
Continuous innovation is a survival need and a competitive must. Without that capability, inertia will act as a speed governor. But innovation cannot be relegated to department status or reserved for the next-level killer app that may never materialize. Doing so is an inertia-producing temptation, but one that can be avoided by making simple, fast, and frugal experimentation an operating norm.
One of the big misperceptions about lean is that it’s all about quality and cost. Those who have spent time embedded in the Toyota culture will delight in correcting you, letting you in on the little-known fact that the Toyota Production System was developed to shorten the time from order to delivery and create a “dash to cash” method without requiring the deep resources of the big U.S. automotive companies. The entire system was evolved through a series of desperate experiments to scale up and grow revenue faster with less.
For high-velocity ScaleUps, creating a steady stream of innovative new product and process concepts that consistently make it to market requires an equally fast, lightweight, high-impact method for carrying out constant experimentation, one that is, unfortunately, missing in most.
Experimentation also isn’t just about product development. Applying agile principles to rolling out a new sales process in one market allows you to test and improve before rolling out globally to your entire organization. As Netflix’s co-founder and first CEO Marc Randolph writes in his 2019 book, That Will Never Work:
“I’ve realized that the key to being successful is not how good your ideas are, it’s how good you are at being able to find quick, cheap, and easy ways to try your ideas.”
Principle 3: Accelerated Value
A failure to understand and align with customers on their desired business outcomes can produce enough downstream friction to produce what every recurring revenue business dreads: churn.
The tendency is to equate the concept of a customer journey with a sales funnel coupled with a monolithic view of the customer, which is wrong. In other words, customer = account is a key source of friction that can ultimately lead to head-scratching when seemingly satisfied customers churn.
At the root of the issue is the difficulty of thinking and operating horizontally in a structurally vertical world. Customers are organized vertically, as are most company support functions, but the customer experience is horizontal. Rather than think like a star quarterback leading a team with set plays being sent in from the sideline (vertical thinking), think like a Formula One pit crew. A horizontally-oriented Formula One team has over 20 people with specific roles so tightly synchronized that they can stabilize the car, change the tires, adjust the aerodynamics, and safely release the car to get back in the race in under two seconds.
Enabling customers to realize value quickly promotes product adoption and positively impacts community spread, customer retention, renewal, and expansion. Ensuring that everyone in your company is aware of how to enable that value quickly, and in a unified fashion, only helps to accelerate your growth through improved customer satisfaction.
Principle 4: Lean Process
Lean as a concept encourages simplicity as the path to speed. It holds that less is best, and that to make more room for what truly matters, eliminate what doesn’t. It’s a subtractive approach to continuously improving and simplifying even the most complicated workflows. It starts with a clearly defined value, then systematically removing everything blocking the path to delivering it. It’s a relentless endeavor, a different way of thinking, and requires a mind shift.
Targeting waste involves using a methodology over 80 years old developed by the U.S. War Department in 1940, who coined the term continuous improvement. The concept was aimed at the effort to convert the American manufacturing base to the war effort. It was then utilized to stabilize war-torn Japan under the leadership of General Douglas MacArthur during the seven-year U.S. occupation. Japan, having scarce resources other than human creative capital, termed it kaizen, meaning “change for better.”
With fast-moving tech ScaleUps, we use an adapted method of traditional continuous improvement called a kaizen blitz, which works best, as it is both faster and more effective.
When applying lean principles within Insight’s portfolio companies, we have been able to achieve a 20-30% improvement in time to value.
Principle 5: Espirit de Corps
You can’t build a Formula One car by yourself, or for that matter, a company. It takes a team and leaders of and within that team to create the kind of environment that enables the first four principles to come to life.
Enter the notion of esprit de corps. French for “group spirit,” esprit de corps figures centrally in military and paramilitary organizations, which are notorious for favoring results-oriented leadership. “Mission first, people always” is the mantra. But social research suggests that for a high-velocity organization like a ScaleUp, a cohesive culture of “people first, mission always” may just be a better approach.
As UCLA social psychologist Matthew Lieberman reveals in his bestselling book, Social: Why Our Brains are Wired to Connect, those viewed as having predominantly strong results focus have only a one-in-seven chance of being viewed as a great leader, while those viewed as having a predominantly social or empathic focus have about the same or slightly less chance. But for those strong in both results and social skills, the likelihood of being seen as a great leader is five times greater.
Leaders of this ilk understand that a people/culture fit is every bit as important as a product/market fit when it comes to scaling for growth. Your star product requires a team of star players to advance it to market and capture maximum value…so much so that Netflix is happy to advertise to all job seekers that they will pay an ill-fitting employee an industry-leading severance of four months’ pay while they search for a star replacement.
What a unicorn knows
A cursory glance at each of the individual principles in the S.C.A.L.E. framework might lead you to ask whether there is anything really new here. That’s fair. What is unique is the lean interpretation of the principle: Well-worn terms like strategy and experimentation take on entirely new meanings when viewed through the lens of lean. What is unique is the synergy created from integrating any one of the individual principles with the other four and pointing the collective model toward the goal of scaling up by leveraging a lean, zero-slack mindset.
Learn more about applying lean principles to scale by reading our book, out now: What A Unicorn Knows.
[Recording] What a Unicorn Knows: 5 Principles for Growth in 2023
With the new pressures of the 2023 economy, founders are looking for ways to scale back while still being able to scale up.
Insight Partners hosted “What a Unicorn Knows: 5 Principles for Growth in 2023” to help SaaS leaders answer:
• What are the implications of the new economy, and how do they impact my business model?
• Which strategies are most important for sustainable growth?
• How do we shift our focus in 2023 and still hit our numbers?
Harnessing their deep expertise in growing B2B SaaS Startups, Insight Partners’ Matthew E. May and Pablo Dominguez will address these questions by applying the five principles from their soon-to-be-released book, What a Unicorn Knows. Join us for a snapshot of how to apply The Unicorn Model™ to your own startup.
Preparing to raise capital in 2023 might feel daunting given the market, but it doesn’t need to be. For great businesses, there are investors (like Insight) who are ready to invest.
Before thinking about raising money, we’re going to assume founders have checked off some of the basics listed below:
Know your specific business needs for the investment. This should be deeper than the amount of money you need to raise. Founders/CEOs seeking funding should have a well-defined business plan that outlines company growth goals, target market, financial projections, and competitive advantage. This helps articulate the value of your business to potential investors and demonstrates an understanding of the industry and market.
Prepare your leadership team. Fundraising takes time away from running the business, which means your leadership team must have the skills, experience, and dedication to execute the business plan and drive the company’s growth. Assemble a team that has a diverse range of skills and expertise needed to achieve the company’s goals.
Have a clear plan for using the funding. Investors want to see a clear plan for how the new funding will be used to drive the company’s growth and generate a return on investment. Be prepared to present a realistic, detailed plan for how the investment will be used to achieve specific milestones and grow the business.
Finally, map the market of potential investors. Asking other entrepreneurs for advice and introductions is a great way to start the fundraising process.
Once these steps are done, you’re ready to begin seriously contemplating your next fundraising partner. Deciding to bring someone new onto your cap table can significantly strengthen your business for the years ahead and inject the capital needed to move from a startup to a scaleup.
Some tips for founders:
Prenup discussions on the second date.
Being prepared with your goals and expectations for raising capital is great, but in today’s market, it’s important to have an open mind and willingness to have a conversation. In the negotiation of final documents, there is always a clear set of rights regarding rules of engagement if things go right — and if things go wrong. While this can feel as off-putting as discussing a prenuptial agreement early in a relationship, it is important all sides understand rights and agreements for all scenarios. Consider your position if things go wrong. What happens when things go wrong is as important as the conditions when things go right.
Consider dilution in addition to valuation.
You’re obviously seeking out capital, but don’t simply fixate on your company’s valuation number or the specific amount of money you want to raise. The more important consideration in the long run will be understanding the percentage of the cap table you are hoping to raise. While value is always important, if you are only raising primary capital you should consider dilution more than the post-money value. For example, if you are hoping to raise $25M at a $125M post (20% dilution), you can offset a 25% price disappointment by lowering the amount of capital raised. You can raise at $80M while limiting the raise to $20M. This is also 20% dilution. The only difference between the two deal structures is $5M on your balance sheet. The point? Valuation matters, obviously. But it’s only one of the variables. You can control the impact of valuation by adjusting the investment amount.
You want a partner that has enough capital to ideally support you through your next few rounds, and ultimately, deliver enough value to scale your business in meaningful ways beyond a sky-high valuation or fundraising amount.
Have conviction in what a new investor can do to add value.
This means two things. Firstly, what does the investor’s investment horizon look like? Do they have the capital and patience to be able to support you long-term? Secondly, how will the investor work with you and your team? It’s critical to know the skillset of your lead investor and ensure that they understand your industry, business, and goals for the years to come.
Besides the financial support of your investor, different firms will have different levels of deeper support available. At Insight, for example, there is a large team set up to support each individual portfolio company, streamlined through a portfolio management function. This ensures impactful, personalized support is delivered when and where it is needed most for each portfolio company.
Most CEOs and founders who choose to work with Insight are particularly excited by having access to Insight Onsite, a team of more than 130 of the software industry’s best operators, dedicated to supporting portfolio companies as they scale up. Understanding what resources different investors have available to you will help you strategically map out your board and partners to best support you at your stage of growth.
Select an investor with a network you can leverage through your journey.
Investors can be incredibly valuable partners and bring a unique perspective to the boardroom. However, being a CEO (or another C-Suite role) at a growing business in today’s climate can be an intimidating and lonely job. Insight’s portfolio of 600+ companies provides CEOs with an unparalleled peer network to lean on and learn from. Having a pool of people who are in your shoes and navigating the same challenges can be one of the most transformational assets for CEOs when building their business.
Insight’s portfolio experience programming is one of the most robust in the industry, made possible because of the global breadth of the portfolio. In 2022 alone, executives accessed nearly 80 intimate digital roundtables and webinars, and over 30 in-person events. Many of Insight’s CEOs choose to participate in the MINDSET CEO Summits, where, alongside their peers, they’re able to dive deep into the leadership and operational challenges they’re facing today and walk away with trusted advice on what to do next. Insight’s portfolio events are all designed to forge strategic connections and actionable tactics.
Raising money can be a challenging process, especially in 2023. But prepared with the proper guidance and expectations, finding the right partner can be transformational to the future of your business.
Six Best Practices for Your First 90 Days as a Data Leader
For newly hired data leaders, the first 90 days are crucial. For existing data leaders, it’s prudent to take a step back at least once a year, think about the business with fresh eyes and ask: What would a new data leader try to address in the next 90 days?
Regardless of title, CxOs of young and established organizations realize their ability to make excellent data-driven decisions is a must to achieve the company’s business goals. In the current resource-stretched climate, the CTO, CIO, or CxO often wears the data leader’s hat. This is especially the case at early-stage companies too small to have this position. But while the role of the data leader is still often shared, a data leader’s acumen and approach for data-driven decisions can be adopted by many leaders to have a significant impact on revenue and growth.
Every enterprise and business case is unique, but today’s data leaders have established a set of best practices to chart the digital pathway to profitability:
Unify data and AI strategies
Cultivate an open data culture
Solve customer problems
Capitalize on early opportunities
Align stakeholders on priorities
Inspire the team
Unify Data and AI Strategies
Young organizations often struggle to create meaningful data strategies. The key is to recognize where emerging trends and company needs intersect, and then create a roadmap to fulfill short- and long-term needs with technology that provides a competitive advantage. The data leader is aware of the importance of aligning data and AI strategies to better serve the organization’s overall mission.
A 2022 survey revealed that over half of the data executives surveyed expect AI to become “critical” to multiple facets of their business by 2025. While most companies expect to adopt AI technologies, many data leaders are looking even further ahead to more advanced forms of artificial intelligence. Techniques such as generative AI — capable of creating rather than simply predicting — has a fast-growing number of use cases.
A sophisticated AI model requires a modern data stack. Companies that can invest in their data infrastructure will be able to more successfully capitalize on emerging AI techniques. A full-stack approach to ETL (extracting, transforming and loading) data, creating data lakes and lakehouses and de-siloing data architectures can give companies a real competitive edge.
Similarly, powerful AI needs DevOps and MLOps tooling to support it. As the role of AI grows within an organization, data leaders will need a more robust foundational toolset if they want to identify which features of their data provide signal (a process known as feature engineering). This also holds true if they want to improve model training, deployment, and monitoring. Additionally, not all MLOps stacks are created equal — AI working with unstructured data requires different pipelines than those working with structured data. The same distinctions exist for generative versus predictive AI.
Today’s data leaders are seeing these AI trends play out in real-time and are adapting their enterprises to take advantage of what AI can offer for data-driven decisions and strategies. This is important not only to promote growth and accelerate innovation but to build resilience during periods of austerity. With the global economy in a period of stagflation (stagnation and inflation), the ability of business leaders to extract value from data could be a deciding factor in how well a company weathers the storm.
Cultivate an Open Data Culture
How a strategy is defined is up to leadership, but how well it is executed is often a function of company culture. Executives are reshaping their organizations to become more data-oriented, but the vast majority still point to culture as the greatest challenge in becoming a data-driven organization.
Successful data leaders hit the ground to build a data-driven culture by identifying stakeholder needs and responding to them with data-driven decisions. Bear in mind that the ultimate stakeholder is the customer. Organizations invest heavily in research to identify who their customers are, what their needs are, and how they differ by region and culture. Expanding these data sources and creating channels where data can be translated into actionable insights is a fundamental part of a data-driven culture.
The organization itself has hurdles to overcome: diversification of customer base, changing business priorities, and infrastructure and scalability concerns. External regulators demand certifications and scrutiny to ensure compliance with standards.
To succeed amid this tangled web of expectations, data leaders have established a practice of identifying objectives that are mission-critical to meet — those actions or failures that could cause a loss of stakeholder confidence.
Solve Customer Problems
Without data, there is no visibility in customer buying patterns, adoption, and behavior. For SaaS companies in particular, identifying a common enterprise data model is foundational to learning about their customers and fulfilling core business responsibilities. This is especially critical in the wake of multiple mergers and acquisitions, when customers may have to deal with multiple quotes, orders, contracts, and invoice formats that don’t match.
At the heart of all data is customer identity data, and your process for customer identity conflict resolution will be key. Unified data models allow businesses to integrate multiple data streams into enterprise resource planning pipelines. How to create and interpret information gleaned from data models might be beyond the technical capabilities of the data leader. However, data gleaned from the data model can provide an easily accessible wealth of information about how well the organization as a whole is able to fulfill customer needs.
Merging these data streams provides much better visibility into customer buying behavior. This includes better insights on lead generation, sales conversions, annual recurring revenue (ARR), customer acquisition cost (CAC), net revenue retention (NRR), and more. More insights allow for better decision-making in every department of the organization. As with software quality and usability for an engineering department, this is a case of operational details determining strategic success. For companies growing through mergers and acquisitions, this is especially important.
Capitalize on Early Opportunities
Understanding where the business’s data organization performs against key performance indicators (KPIs) is an important part of a data leader’s job. Data leaders use a series of self-assessments to understand the strengths and weaknesses of their organization’s data strategy and capabilities. To really deliver value, however, executives often chart a series of phases for their data strategy — the so-called “Crawl, Walk, Run” progression.
As with any “baby steps first” approach, the essential “crawling” phase sees the development of the initial capability by building out the data stack and analysis pipeline. Once a process is in place, leaders can advance to the “walking phase” — fixing the parts of the process that are present but broken. The good news is the switch from walking to running is the easiest, as process fixes eventually become process optimizations.
It’s also important that this process is iterative. At some point, a process can no longer be optimized. In strong data-driven organizations, there is a point at which the team will look for more advanced technology to build, introducing more capabilities than previous optimizations could accomplish. This is also where the data leader’s leadership in building a data-centric culture, their attention to instituting policies for governance and security, and their investment in technologies such as generative AI and MLOps pay off.
This step is important for new data leaders. The average tenure of a data leader is 30 months, significantly shorter than for other executives. Data leader turnover, driven by a gap between expectations and results, often happens because leaders do not seize these early opportunities. This applies equally to data leaders hired to build data departments, and to those hired to make structural architectural changes (especially after a big data breach). Data leaders that fail to deliver demonstrable improvements — both in the department’s operations and overall business impact — struggle to make it past the two-and-a-half-year mark.
Align Stakeholders on Priorities
Balancing a host of competing priorities — investing in emerging tech, building culture, and process optimization — is difficult. Today’s data leaders have adapted by creating a prioritization framework along two axes:
Importance to the business
Difficulty of implementation
Understandably, data leaders often pursue the low-hanging fruit first, consisting of high-priority and low-difficulty items. Although those characteristics seem mutually exclusive, there are changes data leaders can make to secure easy wins. Achieving success for these items can be as simple as instituting transparency policies to keep the board updated on data-driven processes, such as the company’s data privacy and security efforts.
In 2021, less than half of surveyed corporate boards received reports about cybersecurity risks. Another survey revealed progress continued to be slow — only 37% of surveyed board members felt confident that their company was secure. Providing transparency and clear reporting can be on the lower end of the required-effort scale, while it boosts the board’s confidence in the company’s data initiatives and security posture.
Data leaders can use clear reporting to secure buy-in from board members and other stakeholders, demonstrating that their leadership and priorities are leading the company to a better place. Creating this continuous feedback loop helps keep board members, other executives, vice presidents, directors, and even customers, on the same page. It also smooths the way for future initiatives.
Inspire the Team
Finally, every data leader is a team leader. Inspiring the data team to reach new heights provides a force multiplier for growth. Storytelling using data and visuals can serve as a way to lead by example to inspire the team, ultimately changing the company’s trajectory from being a follower to becoming a leader — even a disruptor — in an industry segment.
Investing in technologies like generative AI not only unlocks new capabilities for the company but also provides opportunities for employee growth. It creates better data scientists and engineers.
It also ensures that, as the company grows from early-stage to ScaleUp, the data department remains competitive from a talent standpoint. Data leaders today are capitalizing on the investment in new trends to attract diverse and capable data professionals.
Taking charge of an existing data department — or taking on the role of building one — is a daunting challenge. But data leaders are tackling that challenge with careful prioritization, an eye on the technological horizon, and attention to the intersection of customer problems and business opportunities. They identify low-hanging fruit and communicate their early successes. Make that your plan for your first 90 days, and you’ll be off to what everyone can see is a great start.
8 Tech Investors Share Predictions for 2023
2022 was a busy year for the team at Insight. As hype started to build around the use of AI in our everyday lives, Insight held its first ScaleUp:AI conference, featuring top industry speakers and hosting over 1,700 attendees. The firm also grew the Onsite team — Insight’s dedicated ScaleUp engine of Sales, CS, Product, Marketing, and Talent experts — to over 120 operators to better support portfolio companies, help them focus on metrics that move the needle, and prepare them for whatever comes next.
As we wind down the year, eight of Insight’s Managing Directors share some thoughts about what’s top of mind for tech investors going into 2023.
We’re going to hear a lot more about AI.
If 2022 was the year of crypto, 2023 will be the year of AI truly breaking into the general population’s awareness.
The shift from analytical AI to generative AI
Lonne Jaffe: “Many had been operating under the assumption that manual labor and simpler knowledge work would be most disrupted by AI and automation, but with large foundation models like GPT-3 and DALL-E, we’re seeing AI systems make enormous progress in highly creative tasks like design, programming, music, and creative writing. This will likely continue in 2023 with the release of systems like GPT-4. At the moment, the reliability of these models is still a major challenge — they often hallucinate answers that are false but still ‘speak’ confidently. This kind of unreliability could be problematic for a lot of use cases, like customer service, education, and healthcare. If you don’t already know the answer, it can be hard to tell whether some AI-generated responses are correct.”
Nikhil Sachdev: “We’re moving from analytical AI (analyzing/parsing data and identifying trends and patterns) to generative AI (creating new content or interactions based on patterns). Applications we’re seeing now are benefiting from powerful (often open source) large language models, cheaper computing costs, and established MLOps platforms. These AI applications are starting to overtake human functions and have the potential to augment and disrupt existing entrenched software apps.”
George Mathew: “More of us should be talking about explainability and bias detection as more large language models (LLMs) get to scale and production. We should all be preparing for what opportunities will emerge with a multi-trillion parameter large language model like GPT-4 being released.”
Lonne Jaffe: “It will be very interesting to watch where the value will accrue and where economic moats will be the deepest. Some believe that the economic moats will accrue to the companies building the large foundation models because they require so much time, skill, and infrastructure spend. Others think that the moats will be with the companies fine-tuning the models for specific use cases because of the feedback data demand-side economies of scale. Still others believe that the value will be in the non-AI software that allows the models to integrate with real-world systems. There may even be a layer of value in between the foundation model creation and fine-tuning, requiring a new set of MLOps tools and skills that focus the foundation model for a specific domain, but in a way that is more involved in modifying the internals of the foundation model than needed during the fine-tuning process.”
Moving from AI in infrastructure to AI in applied real-life situations
Lonne Jaffe: “One area where we’re likely going to see continued huge progress in 2023 is in applied computer vision AI in healthcare. The tech is already approaching human ability in domains as varied as polyp detection in colonoscopies, diagnosing gum disease in dentistry, breast cancer screening in a mammogram, etc. This can improve diagnostic accuracy, save physician time, surface candidates who would benefit from clinical trials, and even reshape how the industry works.”
The metrics investors care about in 2023 will shift to retention and efficiency.
“More nailing it, less scaling it.”
Ryan Hinkle, Managing Director: “2023 is about more nailing it, less scaling it. 2023 should be a year where it’s efficiency first, additional costs second. It is really difficult to focus on efficiency when you are adding costs. That is the fundamental pendulum shift: it has abruptly shifted from ‘if you believe it, it will come’ to ‘if you can’t see it, it doesn’t exist.’”
Metrics that matter
Nikhil Sachdev: “Customer NPS is always important, even more so in this environment. (Are you nice to have? Or, I can’t live without you?) NPS flows through all the relevant financial metrics in a business. The more customer value/love you generate, the better your logo growth, pricing power, retention, and efficiency. And goes without saying in this market, it’s no longer growth at all costs. Companies and investors are focused on durable, efficient growth.”
George Mathew: “Gross retention — more than ever, you have to be able to retain customers to stabilize your 2023 growth plans.”
Thomas Krane: “Path to breakeven based on current balance sheet, cash burn as a multiple of net-new ARR.”
AJ Malhotra: “It’s all about how you’re investing to drive efficient growth. My key metrics are about the same: previously, it was all about net-new ARR, and now gross profit matters more. Your true gross (and net) retention becomes very, very important as well — this separates strong companies from weak ones. Cash burn also becomes imperative in this environment.”
Rebecca Liu-Doyle: “In this environment, two things investors are watching especially closely are gross margin and gross retention, both of which are prime leading indicators for steady-state free cash flow potential. In steady state, will this be a 15%+, 25%+, or 50%+ FCF business?”
DevOps will prioritize simplicity.
Michael Yamnitsky comments on the developer perspective: “The great vibe shift of 2023 is a return to simplicity! Back in 2017, it was cool to tinker with the nuts and bolts of Kubernetes, but as of 2022, we’ve reached peak complexity and specialization in cloud infrastructure, and the pendulum is swinging back. Developers want to simplify their stack and ship code faster. To this tune, we’ll see a resurgence of PaaS and other developer-friendly services that eliminate the toil while retaining all the benefits of 10+ years of advances in cloud technology.”
Thomas Krane, Managing Director: “In DevOps, cost pressure will put new pressure on public cloud workload adoptions and reinforce the need to have interoperability between on-premises IT and cloud services. This creates opportunities for new vendors in the space.”
Rust will be all the rage
Additionally, Michael adds: “Rust is all the rage and demand for rust programmers is growing. The performative nature of this programming language makes it a fit for backend-heavy development, particularly in the infrastructure and developer tooling space where performance can be a key differentiator.”
The overall economic environment will be uncertain for a while, but it’s not all bad news.
Ryan Hinkle: “None of us are used to inflation. Inflation hasn’t been a consideration for literally 30 years. Because of inflation, if you aren’t growing 8%, you are shrinking on a real basis. We enter 2023 with a great deal of known issues — inflation being front and center — but no real ability to forecast what comes next. In 2023, we will need to re-evaluate on a quarterly basis or even more frequently, as a year will feel like an eternity. Years make sense as forecast building blocks when things are well-behaved. These are not well-behaved times.”
Nikhil Sachdev: “Market sentiment is as negative as it has been since the Great Recession. We are seeing a combo of inflation, rising rates, cratering multiples, geopolitical turmoil, and de-globalization, which is impacting our supply chains. On top of that, the demand curve is being whipsawed – first as we lap a period of strong pull forward in digital growth driven by the pandemic period, and now budgets and spend tightening. It’s time to go back to basics — focusing on durable growth and building/scaling efficiently are the fundamentals that will enable companies to succeed regardless of the macro. Just remember that things are never as bad as they seem at the bottom and never as good as they seem at the top.”
Thomas Krane: “Companies that largely sell into tech companies with products linked to headcount will see a significant medium-term downdraft in revenue, but there will be a strong recovery on the other side for those that survive.”
Survival of the strongest will drive consolidation
Nikhil Sachdev: “So much of the bad news is out and now baked in the cake that on balance I think equity markets will be more constructive over the next year. I think we’ll see more private tech dealmaking. Growth-stage companies will still need to raise money, maybe at different multiples than before. We are also going to see much more consolidation as companies that can’t or don’t want to continue down the standalone path look to partner with strategics.”
AJ Malhotra: “We’ll see consolidation — lots of companies have raised lots of money, with unsustainable burn rates, cost structures that may not be efficient, and that means some will not be able to raise follow-on rounds and will need to sell. The velocity of fundraising that happened in the tailwinds of Covid from 2021-2022 was a unique moment in time.”
Ryan Hinkle: “Whatever this recession will be, it will really test what is ‘needs to have’ vs. ‘nice to have’ and inform what gross and net retention looks like. We have not had a meaningful downturn since SaaS emerged as a dominant trend in digital transformation.”
There are opportunities in uncertainty
Lonne Jaffe offers several examples of how tech, and AI specifically, could help to alleviate inflationary pressure: “The go-to reaction to inflation is to have Federal Reserve Bank raise interest rates and to slow the economy and raise unemployment. But this comes at a huge cost. Despite the anxiety around robots and automation taking jobs, there can be an opportunity for tech to help alleviate inflationary pressure by increasing efficiencies and making us all more productive. In a similar way as collaboration software helped the economy cope with isolation from the pandemic, this kind of AI-powered efficiency improvement, in a way, could become the unsung hero of this inflationary crisis period.”
George Mathew: “Backoffice sectors like supply chain, procurement, and business process outsourcing all have fundamental opportunities to be transformed by generative AI.”
Thomas Krane: “The cost of cloud services will create opportunities to preserve and even expand on-premises IT.”
Michael Yamnitsky: “One of the positives of continued economic uncertainty going into the new year: the spotlight shifts away from the hype-chasers and storytellers and towards the humble entrepreneur who has been quietly owning their craft.”
Rebecca Liu-Doyle: “Certain categories — like beauty in consumer and automation in enterprise SaaS — have counter-cyclical tailwinds, and this may be their moment to shine.”
AJ Malhotra: “New company formation will increase because of layoffs, and lots of talented folks will have new time on their hands to build something new.”
Hiring might get easier.
George Mathew: “There will be a much more available labor market as hundreds of thousands of tech workers are being laid off at the ‘Big Tech’ firms.”
AJ Malhotra agrees: “Hiring is a big opportunity right now! A lot of good people are in the job market because of layoffs. Hiring may become easier given the talent out there. We have dueling realities — giant tech companies are doing layoffs and hiring freezes, but unemployment is low. We’re still seeing hiring in many industries.”
There’s still a lot to be excited about in tech.
Nikhil Sachdev: “While I acknowledge we are in a peak hype cycle for AI, I think the secular trend is real and feels like we are on the verge of an explosion here. AI will impact horizontal and vertical segments within software.”
Michael Yamnitsky: “I’m excited about WebAssembly. It has the potential to bring unparalleled levels of efficiency and security to computing and transform the way developers organize and collaborate around code. But most importantly, it’s portable — making it a unique fit for the next wave of distributed applications.”
Thomas Krane: “Threat intel will finally get recognition as a critical baseline/foundational priority for a strong cybersecurity stack.”
AJ Malhotra: “It’s easy to be a pessimist but there are a lot of good things happening right now: hybrid work environments are better overall and have provided more flexibility to people, there’s low unemployment. There’s tons of opportunity to do things more productively and more efficiently. Tech dealing with carbon emissions and clean energy transitions, enterprise software selling into financial services, software for the build environment, and tech dedicated to improving healthcare delivery are all exciting areas right now.”
This post was compiled and edited for conciseness and clarity by Jen Jordan.
Pay Transparency is Here to Stay. How Can You Build Salary Ranges in Good Faith?
Pay transparency. It’s a topic on many HR leaders’ minds. With a renewed focus on inequality in pay, many local and state governments are putting laws into place with the intent of positively impacting pay equity for underrepresented groups.
With NYC, California, and other jurisdictions passing pay transparency laws, it’s important for HR leaders to be prepared for how to stay compliant in their organizations.
Start by looking at your internal salary data by job level, function, and geography to identify the median or average salaries.
Avoid publishing salary ranges that are too broad.
Be ready to document and explain the reasoning behind the salary ranges and philosophy to create a truly equitable pay culture at your organization.
Most recently, New York City enacted a pay transparency law requiring employers to state the minimum and maximum salary within job advertisements. The law applies to any company that has at least four employees, one of which is based in NYC. It also impacts any jobs that could be performed in whole or in part in NYC – in other words, postings for remote roles are not exempt.
NYC isn’t the first nor the last jurisdiction to pass such a law. California is close behind, launching a state-wide law effective January 1st, and we anticipate more local and state governments following suit through the next year.
As this trend in pay transparency continues to grow, employers need to rethink how they approach their pay ranges to not only meet the demands of these new laws but also to ensure consistency and equity across their organizations.
So how can organizations create salary ranges in “good faith”?
Leverage data. It’s important first to analyze your internal data. Look at salaries by job level, function, and geography to identify the median or average salaries. You should also leverage external benchmarks through a compensation benchmarking tool. Again, you can examine market data by job level, function, and geography to see how your current range compares to the broader market. As one way to potentially calculate a range in good faith, you can calculate a percent below and above those averages or medians based on geography, experience or education, scope, etc. It’s important to note that you should also proactively identify any employees that may be below your identified range. Once these ranges are shared publicly, you can anticipate employees asking why they fall below or on the lower end of said range.
Try not to make your range too broad. As a workaround, some companies originally tried to state excessively large ranges such as $100,000 to $300,000. However, some local agencies – like the Colorado Department of Labor – are fining a few businesses and issuing hundreds of warnings to businesses with too broad of ranges. Broad ranges also can indicate to a candidate that you lack a transparent culture, which can detract from the overall quality of your applicant pool. If you do have a broader range, you need to ensure you have a good faith reason to do so, such as the role is remote and the salary will be based on a candidate’s geography (e.g., on the higher end of the range if based in NYC) or that the role can be done with varying levels of work experience. Additionally, if an employer has no flexibility in the salary being offered for one particular role, it is ok to make your range smaller.
Document, document, document. To truly build a range in “good faith” you will have to put some forethought into those ranges. If you are able to document and explain why you’ve created a range, it will help you mitigate risk. It also helps ensure that you are truly building a more equitable pay culture at your organization and makes it easier to explain to employees your pay philosophy.
Pay transparency is here to stay. If you have employees in multiple states, it’s better to prepare at large for these laws versus trying to manage multiple processes as more laws come online.
At the end of the day, these laws are meant to close the racial and gender wage gaps and generally remove the stigma around talking about salaries. Preparing now not only ensures you stay compliant but also builds a culture of transparency and equity in your organization.
[Recording] Winning in 2023: Sales KPIs for Sustainable Growth
Prediction: “Efficient growth” will be a buzzy phrase for SaaS startups in 2023 – and for good reason. In the new macroeconomic environment, your business will need to focus on sustainable growth more than ever. An effective way to keep efficiency at the forefront is by heading into next year with the right sales KPIs in mind.
Tune in to hear from Operating Partner Pablo Dominguez (Insight Partners) as he shares his learnings from working directly with hundreds of startups and their go-to-market teams. He is joined by CEOs Jordan Rackie (Keyfactor) and Neha Sampat (Contentstack), for the SaaS leaders’ POVs on successfully balancing the goals of growing sales teams and investors.
(12:30) – How do you optimize sales and marketing spend?
(17:27) – Knowing that CAC efficiency is more important than ever in the current economy, how do you see low touch, product-led sales motion fitting in for B2B SaaS companies?
(20:41) – From a valuation multiple perspective, are there diminishing marginal returns beyond a certain level of efficiency? Should we trade off efficiency for growth beyond a certain number for CAC Payback months?
(23:23) – KPI #2 – Net Revenue Retention (NRR)
(24:20) – How can you use NRR to impact valuation expectations?
(26:42) – What are leading indicators of NRR?
(34:37) – KPI #3 – Quota Attainment
(35:53) – As a CEO how do you work with your CRO/CFO to come up with a realistic revenue target for next year and balanced targets for your sales reps?
(41:33) – As the head of the company, how do you align the goals between your CRO and your CMO?
Disclaimer: Insight Partners is an investor in Contentstack and Keyfactor.
Head of Enterprise Applications: An Often Untapped Orchestrator for Growth and Scale
Many scaleups are seeing the need for a new role to handle daunting internal systems complexity, back-office business systems, integrations, and data.
Hiring a Head of Enterprise Apps and Architecture role in the organization can help scaleups proactively navigate key security and tech process questions while prioritizing growth and innovation.
The most common time to hire this function is in the ScaleUp stage — when a company is at $50-$100M annual revenue.
This role usually reports to a CIO, COO, or CFO.
Boards of directors are seeking digital acceleration from their CxOs and expect enterprise architecture to be orchestrated to enable growth and scale. For ScaleUps already on their digital path, that means transformation of business processes through technology and the deliberate integration of complex digital landscapes. It also means application rationalization to keep operating expenses in check, especially if mergers and acquisitions continue to be part of the growth strategy.
In early-stage companies, many CxOs must also absorb responsibilities for the company’s back-office business technology in addition to their core role. CxOs in these cases can tend to stand up internal business systems in silos while enterprise applications remain poorly integrated with the organization’s IT infrastructure. The repercussions are significant, resulting in low-data quality for internal users to work with, the inability to produce key business KPIs, and ultimately, a poor customer experience. However, there is a solution: The main strategy for dealing with daunting internal systems complexity is to form an enterprise applications and architecture team, responsible for back-office business systems, integrations and data. The head of enterprise applications and architecture thus becomes the master orchestrator of processes and applications for all business units.
Assessing the Need for a Head of Enterprise Apps and Architecture
The need for a master orchestrator was identified in a 2018 survey conducted by threat-assessment company F5. The survey revealed that 38% of the respondents could not name all the applications used by their organization, despite considering 34% of their web applications to be “mission critical.” So how do you determine if your company needs a head of enterprise applications? Below is a simple checklist:
Unmet technology needs. Does the business have capability needs that aren’t supported by current back-office applications? This can happen as the company matures, when the customer base shifts and departments expand their tooling, both to meet demand and to deliver greater value to consumers.
Software ownership. Scaleups often struggle to decide whether to buy off-the-shelf software or to build it themselves. In some cases, it can make more sense to purchase while, for others, an in-house solution works better. Left unchecked, these decisions can result in complex system landscapes.
Architectural vision. Is there a clear internal vision for the company’s business systems architecture? The company should identify which systems add competitive advantage through advanced “best of breed” feature sets and where cost savings can be achieved with mid-market options.
Gaps and overlaps. Which systems offer necessary features and which are redundant? With off-the-shelf enterprise software there will always be gaps in capability, and some redundancies. The problem goes further than unnecessary spending: if different teams use different software to achieve the same objective, progress can be hampered and KPIs can’t be reconciled. Leaders who are dedicated to managing the life cycle of enterprise applications will be able to identify these gaps and overlaps, and make effective rationalization decisions.
Software integration. Are the company’s enterprise applications interoperable? The ability of applications like ERP systems to integrate with sales and marketing eliminates redundancies in capability and provides the functionality enterprises need as they scale. Business leaders have made interoperability a critical part of purchasing decisions, especially as technology needs evolve with the business.
KPIs. Key performance indicators (KPIs) help you understand whether the company’s enterprise systems are delivering required outcomes. If they’re not, then the ScaleUp will likely re-evaluate the organization’s app development and management strategies.
Projects. Perhaps the strongest signal that the company needs a cohesive application strategy – and leadership – is the failure of systems and data projects to deliver on time and/or to offer the expected business capabilities and KPIs.
Scope of the Role
A head of enterprise applications and architecture straddles a wide scope of responsibilities covering the range of tech strategy. Responsibilities include the choice of enterprise platforms for the organizations to adopt, as well as its implementation and testing processes. Improving DevOps and predictable agile delivery also fall under their purview. They are bilingual, well-versed in the languages of business (including SLAs and KPIs) and technology. The head of enterprise applications and architecture connects back-office business technology to core revenue-generating product applications.
The enterprise applications team will oversee most major enterprise software systems, including:
customer relationship management (CRM) systems
marketing automation platforms (MAP)
enterprise resource planning (ERP) suites
human capital management (HCM) tools
enterprise data systems (EDS)
overall integration layer
This team does not need to own every business system, of course. Instead, they focus on those tools that require major investment, integrations or that affect business processes like quote-to-cash or hire-to-retire. These are tools that need to be properly integrated and governed if they are to deliver maximum business impact. ScaleUps are finding that a dedicated enterprise applications team is the optimal way to accomplish this.
As mentioned earlier, a key function of the head of enterprise applications is to navigate the build versus buy decision. While engineering is almost entirely a “build” team (they build the product the company sells), enterprise software leaders often lean towards “buy” in order to optimize cost and deliver the best value. However, some companies do give enterprise applications teams the freedom to build internal tools. As a result, enterprise applications leaders are often well-versed in the intricacies of building, integrating, and deploying software and DevOps.
Timing Based on Growth and Cash Flow
Exactly when a business will need a dedicated enterprise apps team is difficult to predict. Innovation and scale are significant drivers — innovating and investing in digital transformation are top priorities in today’s tech landscape. For most companies, this point arrives as the company transitions from the growth to the ScaleUp phase, typically with between $50 million and $110 million in annual revenue. In later stages, we recommend a CIO, who reports directly to the CEO.
Not all companies manage this transition successfully. Some continue early-stage practices of bringing in consultants to improve processes, but this is a stop-gap measure at best and, when consultants depart, their expertise goes with them. By contrast, organizations with a unified head of enterprise apps and architecture can avoid this churn. This role can serve as a focal point for specific knowledge within the company about business capabilities and managing enterprise applications.
From a cash-flow perspective, companies that struggle to fund and prioritize this role, often have to divest operationally first before they can re-invest strategically, or ask business CxOs to wear a more technical hat.
Many companies that create an enterprise applications team assign it to the CIO’s area of responsibility. In the absence of a CIO, the head of enterprise applications typically reports to the COO or CFO.
The CTO is the least-preferred executive to oversee this critical function. That’s because CTOs need to focus on innovating and driving revenue by building out the core product and finding the right product-market fit.
How does one find qualified IT leaders to occupy this position? The truth is, it can be challenging. Since this is a technical role, the best candidates will have a technical background. IT operations candidates that have only managed networks, desktops or help desks are not good candidates because they lack the business skills needed to speak to sales, marketing and finance executives.
Enterprise applications candidates will have deep experience building software integrations and navigating the complicated web of interoperable enterprise systems. They will also have experience with global implementations, doing configuration or code reviews, and building out proofs of concept for customer relationship management platforms, marketing operations, finance, and accounting systems. Because of the complex nature of the role and the need for outstanding technical, business and interpersonal skills, you can expect to spend at least three months searching for a qualified head of enterprise applications and architecture.
Aligning Business and IT Goals
The ability to unite the company’s business goals with the IT department’s priorities is a unique and critical skill for a head of enterprise architecture to have. That’s because enterprise apps teams serve the entire organization.
That makes this role strategic instead of operational — rather than just managing the status quo, a good head of enterprise architecture will be able to identify areas of business capabilities improvements and drive long-term business value. These skills are part of a wider trend in IT and business leadership – a radical shift from just “keeping the lights on” to planning and driving growth.
The process includes the ability to get stakeholder buy-in, especially for large-scale changes such as introducing new ERP or CRM systems, or a shift to cloud-based architecture. It also requires a solid understanding of the rest of the organization’s pain points. The best candidates for this role have the ability to identify and implement solutions that align with the organization’s business priorities.
Another critical skill set is a thorough knowledge of application security. As the number of applications a company uses increases, so does its security overhead and the risk of a breach. The diversity of applications also makes the task of securing them more complex.
Furthermore, since many of these systems are used by non-technical staff (such as sales, marketing or HR) there’s an increased burden on the enterprise apps team to educate staff on proper security, release management, and control procedures. ERP systems are notorious for vulnerabilities because they are large, complex applications often used by multiple teams. Their size and flexibility mean that different departments often configure them with customizations or plugins.
However, integrating these systems is not the only concern. Most modern enterprise software is based on cloud technology, which makes IT architecture leaders with strong cloud deployment and cloud security awareness an asset. The nature of cloud technology means there is some overlap between the IT-focused enterprise apps role and the infrastructure engineering role responsible for providing DevOps support to core engineering. While both enterprise app teams and infrastructure teams might work on cloud-deployed technology, they are very often different cloud environments to manage. Enterprise apps are usually deployed to dedicated, vendor-owned (and made) cloud platforms. Infrastructure engineers, by contrast, work much closer to the code on platforms that deploy the company’s core product.