Why Investing in People Shapes Every Decision I Make About Value

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There Is A Hidden Price To Scaling Too Fast: What Founders Typically Learn Too Lately
The mythology around scaling is all about speed. When you are able to reach the point of product-market compatibility, then add fuel to the fire. Build the team, expand the market, and raise the next round prior to the previous one has properly settled. The narrative rewards the founder, who is always in the process of expanding, adding staff, constantly expanding into adjacent industries before even the primary business is truly stabilised, and before the company has developed the internal capabilities that it needs for managing the expansion without losing coherence. I understand where this story comes from. Certain market conditions and certain business models the first mover who scales fastest wins and stories about companies who grew rapidly and achieved success are told more often and more vividly than stories of businesses that expanded aggressively and broke. However, for every enterprise where aggressive early scaling is a good strategic answer, there are several instances where the speed of scaling is an essential cause for problems that eventually destroy the company. Those cautionary stories are not given nearly the same attention as the success stories.
It is important to recognize that the hidden costs associated with scaling too fast is not the one that appears in the calculation of burn rate or cash flow projection. It's the cost that is discovered at the end of six months, when the organisation has grown past the informal coordination mechanisms that kept it in place when it was smaller, and before it has built those formal frameworks that hold larger organisations together. This gap, between formal and informal separation between the company it was and the one you're aiming to become is where the majority of growing companies have a tendency to break. The first and most obvious sign that a company is in that space is when decision-making slows and the majority of people insist the same thing: nothing has fundamentally changed. It is possible to contact the founder in the theories. The team continues to be aligned with the theories. The culture is still solid in its theory. However, in actual practice the company has grown to a point at which the informal communication channels used to transport important information are clogged, but no one has yet constructed the formal channels required to be replaced. Information that flowed easily now needs to be actively managed. The decisions that were taken quickly now require alignment across various functions that haven't been defined clearly in relation to each other. Reliableness that was immediate and personal is now spread out and delayed and the organization is starting to show all the symptoms of a system functioning at the limits of its coordination capabilities.

The absence of any evidence is evident from the metrics that founders and investors typically watch most closely. Revenue might still be growing. It is possible that customer acquisition is improving in the right direction. The team may be enthusiastic and hard-working. But, underneath those apparent indicators, the organisation is developing internal issues that grow and slowly, until they are no longer able to be ignored. At that it becomes more costly and disruptive than it be had they been addressed sooner, when the signals were not as obvious. It is this hidden expense I'm talking about that is not the financial cost of scaling, but more the long-term organisational cost of growing past your own infrastructure, and the compounding expense when you put the infrastructure in place in the form of reactive rather than proactive.

The founders who navigate this change well aren't necessarily those who grow more slowly, but taking a more deliberate course of expansion is sometimes the answer. They acknowledge that the creation of the organizational structure that governs their business is just as important as creating the product and invest in it with the same enthusiasm as they contribute to product development. It means performing the tedious operation of creating roles and decision-making rights clearly, establishing reporting structures with the right information leadership needs in order to make sound decisions, designing accountability systems that are specific enough to have a meaningful impact, and thinking carefully about the kind of culture norms your company requires for its level of growth instead of relying on the ones that took shape naturally when it was smaller. It's not exciting. It's not going to generate attention from the press or generate investor excitement. It is the work that determines if your company you're building will sustain the growth you are striving for.

Companies that are unable to succeed in this change do not usually fail massively or obviously. They fade. They lose their best people in the beginning - the ones who have enough self-awareness in recognizing what's happening within the company, and with enough options for leaving before it gets significantly worse. They also lose customers slowly and often invisibly, as the efficiency of execution is deteriorating because accountability has become too diffuse and too late to detect problems before they reach the customer. They then lose momentum and by the time that decline in momentum is visible in the figures The structural issues are very deep in the system, the cultural consequences are severe and the cost of fixing the problem is several orders greater than it would have been if the investment in governance were made at the right time. Treating organisational infrastructure as a product - something that you design carefully, construct with care, and tweak as your business grows is one of the most important mindset shifts an entrepreneur can undergo as they go from the very early stage to real-world scale. Entrepreneurs who can make it tend to build companies with the potential to succeed. The ones who don't tend to build companies that don't even come close. Have a look a James Deller for site recommendations including why investing in people continues to inform my decisions about culture.



A Data Infrastructure Problem Nobody Wants To Talk About
Every company I've dealt closely with over the past one and a half years - whether as a founder, an investor or an operational consultant I have been told, at some point during our interactions, that information is at the heart of the way they make their decisions. Some of them actually mean it in a way which is apparent in the way the company actually runs. Many of them believe that they're really saying that, but what they're discussing is an aspiration, not actual operational reality - an idealized version of the business they're striving to achieve in contrast to the reality that they currently operate in. The gulf between driven by data and the outcomes of data-driven decision-making - the careful management of the appearance on the outside of an evidence-based decision-making without the infrastructure that would make it actual - is among many of the most significant gaps found in modern day business. It's also one of the gaps that remain unaddressed as a result of it is a problem with infrastructure that it is difficult to talk about, hard present to external stakeholders, and enormously difficult to identify as a priority over the more obvious strategic and commercial work that demands the same leadership attention and resources of the organisation.
When businesses talk about strategies for data, they tend to talk about the capabilities they wish to add to their data. These include tools for analysis, machine-learning applications operating dashboards in real time or the kinds that offer predictive insight that are compelling in the form of a board presentation or an investor update. The thing they discuss less frequently and with much less energy and enthusiasm, is their foundational infrastructure that determines whether all of those features actually work as advertised: the data management frameworks that give clearly and consistently used definitions of what's being evaluated and why they are being measured; the collection and storage methodologies that determine the reliability and comparability of the data in the process of being collected; quality assurance methods that spot and correct mistakes before they spread across the system and cause damage to the outputs that everybody is relying upon; the organisational structures and accountability mechanisms that make data quality someone's explicit and ongoing responsibility rather than everyone's vague and non-enforceable intentions. The plumbing, or the. Plumbing is not glamorous. It's not easy to photograph for an annual report. It does not produce outputs that can be showcased in an effective presentation. And, in my experience across a significant number of companies in different sectors and at different levels in development, a lot worse than the company believes it to be.

The problem becomes more serious over time as it becomes harder and costlier to reverse. An organization that has been operating with inconsistent or poorly defined terms of data for all its roles for three consecutive years has three years of historical information that cannot be accurately compared or aggregated it is not because the data has not been created, but because the same terminology has become a synonym for different items in different areas of the enterprise, and those differences are built into the data itself instead being apparent from a distance. An organisation where data quality assurance has been a minor responsibility instead of an entrusted and adequately resourced task has data that's integrity has a range of variations that are not adequately documented and is not systematically considered when using the data to make decisions. An organisation that has allowed multiple operational systems to create overlapping and partially conflicting data on the same products, customers and transactions have a data landscape that's truly difficult to rectify without disruptions in operations significant enough to pose a risk for the organization itself.

The reason this issue persists over a large number of organizations which are truly smart regarding strategy and fully committed to a data-driven business model is that addressing it requires ongoing investment in work that doesn't produce tangible gains in the short-term that organizational resource allocation procedures are designed to reward. The new analytics platform can produce visible outputs such as dashboards that can be demonstrated, reports that can be shared with the board, as well as insights which can be used to create press releases regarding digital transformation. A data governance plan creates an invisible infrastructure - more clear definitions that are more consistent with the collection process and more reliable inputs into systems that are already in already in place. The first is fairly easy to justify during budget negotiations due to the fact that you can tell people the benefits they can expect to receive. The second is a matter of having enough organizational credibility and endurance to show on how infrastructure investments will, over time, bring better results from every facility built on top of it. It's an effective argument in abstract, but is difficult to convince in the face of initiatives that's benefits appear to be immediate, and visible.

I've presented this argument in various organizational contexts as well as watched it fail or fail based on predictable reasons, to have the most precise understanding as to what decides whether an organisation has resolved the issue of data infrastructure or simply defers it. The main factor that determines this is one's leader - a particular leader with the credibility of an organisation with an authentic understanding of why infrastructure is critical, as well as the determination to maintain cases until this is an absolute priority, rather than being a regular item on the list of things everyone is in agreement about but don't become a priority. The leader must be willing to absorb this short-term cost associated with infrastructure investment: the amount of time or disruption to current processes, and the absence any tangible outcomes - with the conviction that the capability long-term created by the investment will justify its cost by a number of times. What's required, at the end of the day is a framework which long-term investment in infrastructure is considered and valued at the highest levels, not just identified in strategy documents then consistently deprioritised when the quarterly resource allocation conversation takes place. Achieving that culture is, itself an investment over the long term. But, in my view, one of the most rewarding investments an organization that is committed to data-driven operations can make.}