Why Decades in Technology Has Shaped My Thinking About Teams

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There Is A Hidden Price To Scaling Too Fast: What Founders Typically Learn Too Lately
The mythology about scaling is largely about speed. When you are able to reach the point of product-market compatibility, then add fuel to the fire. Increase the number of employees, expand your market, then raise the next round before the previous one has properly settled. The story rewards the founder, who is always going forward, never stopping to add new employees, always expanding into new verticals prior to it is clear that the business's core has actually stabilized, and before the organization has developed the internal capabilities required to handle the expansion without losing the coherence. I can see where this mythology originates. Under certain conditions of the market and business models, those who grow most quickly wins, and the stories of firms which grew quickly and won are reported more frequently as well as more vividly than stories of those who grew quickly and then broke. However, for every enterprise where aggressive earlier scaling is the optimal strategic option, there's several cases where the speed of scaling can be the primary cause of the issues that ultimately kill the business. And those negative stories aren't getting nearly the same attention as those of the successful cases.
It is important to recognize that the hidden costs associated with growing too fast is not the one that is revealed in the calculation of the burn rate or cash flow projection. It is the one that comes out within six months after, when the organization is past the informal coordination mechanisms which held it together in its early days, but before it's built these formal systems that hold larger organisations together. The gap that exists between informal and formal of the company that it was and the one you're aiming to become is where most growing businesses have a tendency to break. The most evident indication that a company is approaching that point is that it slows down its decision-making while everyone believes that nothing fundamentally has changed. The founder's presence is still present in theory. The team continues to be aligned in theory. The culture remains solid in theory. However, in actual practice, the organisation has grown to a size where the informal communication channels used to transfer crucial information have been clogged and nobody has yet developed the formal channels needed to replace them. Information that once flowed naturally is now continuously managed. Decisions that used to be made swiftly now require alignment across several functions that have never been clearly defined with respect to one another. Accountability that used to be immediate and personal is now scattered and delayed as the organization is beginning to exhibit the signs of a system running at the edge of its coordination capabilities.

None of this is visible in the indicators that entrepreneurs and investors typically follow most attentively. Revenue might still be growing. The acquisition of customers may be trending in the right direction. It is possible that the team is energetic and hardworking. But under the surface, the organisation is developing structural issues that will continue to grow in a quiet manner until they are unable to be ignored - at which point fixing them becomes dramatically more costly and disruptive than it would be if they had been addressed in the past, when the warning signs were subtle rather than glaring. There is a hidden price I am talking about that is not the financial cost of scale, but the long-term cost to the organisation of expanding beyond your infrastructure as well as the cost of putting the infrastructure in it in a reactive way instead of proactively.

Entrepreneurs who are able to navigate this transition in a positive way aren't necessarily those who grow less slowly, though an intentional pace of expansion may be the answer. They are the ones who realize that creating the governance infrastructure of their business is just as important as developing their product and invest in it with the same focus and determination that they bring to product development. This involves doing the tedious job of clarifying roles and decisions and establishing reporting mechanisms that present the information executives require to make sound decisions inventing accountability mechanisms relevant enough to be effective, and thinking carefully about what kind of cultural norms that the organization needs at its current size rather than taking the one that emerged organically when it was smaller. It's not fun. The work will not generate public attention or spark investor interest. It is the work to determine whether the company it is building can achieve the growth you're seeking.

The companies that fail get through this transition successfully will generally not fail very obviously. They deteriorate. They lose their best employees first - the ones who have enough self-awareness to see exactly what's happening within the organization, and enough choices to leave before it gets more serious. Then, they lose customers sometimes in a subtle way, as the performance quietly deteriorates because accountability has become too dispersed and infrequent to recognize problems prior to reaching the customer. Then, they lose momentum and by the time that losing momentum is evident in the numbers when the structural problems become deeply rooted. The cultural damage is massive, and the cost to fix the problem is several orders larger than it would've been if the governance investment could have been made at right time. In the eyes of an organisational structure as a product - something you design mindfully, construct carefully and refine over time as the business grows is among major shifts in mindset the founders can make when they move from the early phase to an actual scale. The founders who master this tend to establish companies capable of reaching their goals. The ones who do not tend to build companies that don't even come close. Take a look at James Deller for more examples including how making investment decisions continues to inform my decisions about what matters.



It's The Data Infrastructure Problem Nobody Wants To Talk About
Every single organization I've collaborated closely with over the past decade and a quarter - whether as an investor, founder or as an operational adviser I've heard from them, at some point during our working relationship, that data can be a crucial factor in the way they make decisions. Certain of them are truly committed to this in a way that is reflected in the way in which the company actually runs. The majority of them think they're really saying that, but what they are describing is an aspiration, not actual operational reality - an idea of the kind of organization they're aiming for in contrast to the reality that they currently exist in. The gap that exists between genuine data-driven decision-making and the results of data-driven decision-making, the meticulous maintenance of what appears to be evidence-based processes without the infrastructure to make it possible - is a single of the most critical gaps that exist that exist in modern-day business. It is also one of the most persistently underaddressed ones partly because the infrastructure problem that causes it isn't a glamorous thing to talk about, hard to prove to stakeholders outside of the company, and enormously difficult to classify against the more obvious strategic and commercial work that competes for the same attention of leaders and resources of the organisation.
When organizations talk about data strategy, they typically tend to focus on what capabilities they'd like to develop on top of your data - the tools for analysis, machine-learning applications operating dashboards in real time with the kinds of predictive insights that are truly compelling in the context of a board conference or an update to investors. What they speak about less often and with a lesser amount of energy and enthusiasm, are the core infrastructure that will determine if all of those capabilities are actually working according to the specifications: the data governance frameworks that establish clear and consistently applied definitions of what's being assessed and how for each measurement; the data collection and storage methods that define the accuracy and comparability of the data being captured; the quality assurance processes that detect and rectify mistakes before they propagate through the system and corrupt the outputs that everyone depends on; the organizational structures and accountability mechanisms that make data quality one's ongoing and explicit responsibility instead of everyone's vague and ineffective plan. The plumbing, in other words. Plumbing is not glamorous. It is difficult to photograph in a report for the year. It doesn't produce any outputs that could be showcased in a convincing presentation. And, in my observations across a broad variety of companies operating in diverse industries and at different stages of development, much worse than the business believes it to be.

The issue continues to grow over time by becoming complicated and costly to reverse. An organisation which has operated using a sloppy or insufficiently defined terminology for data across different functions for three or more years has three years old data that is unable to be effectively aggregated or compared it is not because the data doesn't exist, but because the same term has been used to mean different elements in different parts of the enterprise, and these differences are embedded into the data itself instead being visible on the surface. An organization for which data quality assurance has been the responsibility of a peripheral responsibility rather than having a properly resourced and dedicated function has data whose integrity can be questioned because it is not adequately documented and can't be effectively accounted for when using the data to take decisions. A business that has allowed multiple operational system to accumulate multiple and slightly conflicting accounts of the same products, customers and transactions has an unresolved data landscape that is very difficult to deal with without operational disruption significant enough to create a risk.

The reason this issue continues to be a problem in a lot of organisations who are extremely smart in the field of strategy and totally committed to a data-driven business model is because solving it requires constant investment in work that isn't producing visible short-term returns of the kind that resource allocation processes in organizations are designed to reward. A new analytics platform provides visible outputs - dashboards that can be demonstrated, reports that can be shared with the board of directors, and information that can be translated into press releases about digital transformation. A data governance program creates invisible infrastructures - better underlying definitions and more reliable collection processes as well as more reliable inputs to existing systems in existing. The first one is easy to justify in budget discussions due to the fact that you can tell people what they'll gain. The second one requires sufficient organisational credibility and a willingness to show of how the capital investment is going to eventually result in better outcomes for every feature built on top it. This is an impressive argument in abstract, but can be difficult to compete with initiatives whose benefits will be more tangible and easily visible.

I've argued that case in many different organizational contexts and witnessed it succeed or fail for evident reasons, that I can have a fairly clear view of what factors determine whether an organisation actually tackles the problem of its data infrastructure or continues to delay it. There is a significant difference in one's leader - a particular one with enough organizational credibility with a deep knowledge of the reasons why infrastructure is important, and the determination to continue making arguments until the issue is a genuine priority rather than being a regular item on the list of things that everyone agrees on but which never climb to the top. The leader must be able to pay for this short-term cost associated with infrastructure investment - - the time, the disruption to current processes, and the absence or evidence-based output - with the certainty that the ability it develops will justify the cost several times over. The most important thing, ultimately it is a culture where the long-term investments in infrastructure are highly valued and recognized at the upper levels of management, not simply defined in documents describing strategy and often discarded after the quarterly resource allocation debate occurs. It is, in itself, a long-term investment. However, it is, in my view, one of the best returns that an enterprise who is committed to a data-driven operation could make.}