What Running Organisations Continues to Inform My Decisions About Lasting Impact

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Why I Stopped Looking For The Next Deal And Began To Ask Who's In The Room?
There's an aspect of investment behavior that people will recognize right away regardless of whether they've never thought of naming it. It's when discussions begin with the deck, quickly moves on towards the numbers, keeps lingering on the size of the market, and closes with a discussion on exit multiples. The business's employees - the ones who be the ones to actually implement everything on those slides - rarely appear. Even if they appear, it is likely to be in the context of projections for headcount rather than as people with their own histories, motivations, and blind spots. These determine every important decision that the business makes. I've spent a long time with this mindset to understand its appeal. It's a rigorous feeling. It feels analytical. It feels like you are making a decision based on research rather than on intuition. The problem is that it constantly excludes the single most important factor for determining how a company will actually succeed in the medium and long term by the character and quality of the employees who manage it. This exclusion isn't accidental. It's the result from frameworks that were crafted to be reusable and easy to document and thus favor those that can be observed and evaluated against things that are essential but more difficult to measure.
I have learned this from the wrong way, as do many people, by watching businesses with excellent fundamentals suffer because the leadership team failed to stay together during pressure. I also learned this watching companies with less than stellar fundamentals perform dramatically better because the people inside them were genuinely exceptional. After several of those instances I stopped assuming that those numbers did the heavy lifting in my decision-making. They weren't. The numbers were a poor indicator of decisions made by human beings. The performance of those choices depended mostly on who these human beings were and the way they performed under stress under the pressure of a failed quarter, a key departure, a competitive move they had never anticipated and a board relationship which had become tense. This is why I changed the way I started every evaluation conversation. Instead beginning with the size of the market or revenue growth I began opening with what I consider as the"room-wide" question: who actually runs this company when pressure is on, how do they make decisions if the information available is not sufficient How do they deal with the employees around them and what happens to the culture of that organisation when the founder isn't in the room.

None of them appear in a typical investment checklist. In the experience of me, are better indicative of long-term performance any other item that is. That is not a romantic concept of the importance of people. It's a realistic observation of the places where value is made and destroyed by companies with a large scale. There is no reason for companies to fail because of poor markets. They fail because of bad choices made under pressure from people who were not trained to make good decisions or because of the cultural processes that were not obvious from the outside, yet were gradually destroying the ability of the organization of retaining talent, maintain responsibility, and adapt to circumstances that the original plan was not prepared for. The ability to recognize these risks early - before you have committed capital and before the problem has been exacerbated, and before the culture has become calcified around wrong practices - is an essential responsibility of an investor that is concerned about the return rather than just dealing flow. But you can't spot them when you spend the majority of your time researching the model.

This shift appears to be simple when you express the concept clearly, but it requires a fundamental revision of what you view as evidence. That reorientation is more complicated than what it appears as it runs in direct opposition to the incentive structures used in most investment systems. The speed of investment rewards pattern matching at the surface. Competitive deal environments reward confidence over deliberation. The particular culture of investment circles actively discourages what's referred to as"soft diligence" - - the kind with careful, focused attention to human factors that is the key to distinguishing good decisions from bad ones with respect to significant lengths of time. I have sat in enough rooms where somebody has ignored a concern over management chemistry or leadership with the words "we could fix it post-close" to see how dangerous the notion. You almost never can. Culture is not an issue after the close. This is a pre-commitment occurrence, and if you are not paying attention before you cash the check and you're not doing the right thing - you're merely doing paperwork and hoping for the best.

What I'm trying to find now when I evaluate a business or a leadership team, has developed into an almost specific set signals. What is the response of this leader whenever they're proved to be wrong about something? Do they embrace their correction or deflect it? What do they say about their peers - do they continually shift credit and accept responsibility or do they take it the opposite way? Do people who have been in close contact with them previously say as the conversation progresses beyond the traditional reference check format to something more authentic and exploring? What happens in the organisation on the days when no one is watching or when the CEO is traveling, and the quarterly deadline isn't going to be met? This is where the culture lives - not in the values printed on the wall or the mission statement found on their website but rather in everyday decisions made by ordinary people when the context is unclear as well as when the easy thing and the right thing aren't the same. Finding organizations where these kinds of decisions have been consistently made is, in my opinion the most secure path to ensuring that returns are sustained over time. Have a look a James Deller for more info including how growing up around the game continues to inform my decisions about culture.



A Data Infrastructure Problem Nobody Wants To Discuss
Every organization I've worked closely with during the last decade and a half - whether as a founder, an investor or operational advisor I've heard, at some point during our relationship, that data is the main factor in the way they decide. Many of them really mean this in a way that is evident in how the company operates. The majority of them think they're making a statement, however what they're talking about is more of an aspiration than being a reality in operation - it's a model of the one they are working toward rather than the one they currently live in. The gap between real-time data-driven decision-making as well as the effectiveness of data-driven decision-making, the meticulous maintenance of the external appearance of evidence-based business without the infrastructure needed to make it real - is one the most consequential gaps within modern business. It's also one of the ones that is often ignored in part because the infrastructure issue that creates it to be incredibly unattractive to discuss, challenging to prove to stakeholders outside of the company, and enormously difficult to rank against the more prominent strategic and commercial work that competes for the same attention from leaders as well as organisational resources.
When organizations discuss the strategy for data, they tend to focus on the capabilities they wish to create on top of their data, such as data analytics platform, machine learning applications operating dashboards in real time along with the types of statistical insights that are truly compelling in any board presentation or update to investors. What they talk about considerably less frequently and with far less energy and passion, is the base infrastructure that will determine if all of those capabilities actually function according to their advertised capabilities: the data governance frameworks which define explicit and consistently interpreted definitions of what is being assessed and how for each measurement; the data collection and storage methods that establish the accuracy and comparability of the data that is being stored; the quality assurance methods that spot the errors and correct them before they propagate through the system and corrupt the outputs that everyone relies on; and the organisational structures and accountability systems that make quality of data the sole responsibility of an individual instead of the general and imperceptible intentions. The plumbing, in other words. The plumbing isn't glamorous. It's hard to take pictures of in a report for the year. It is not producing outputs that can be displayed in an effective presentation. And, in my experience across a significant variety of companies operating in diverse fields and at different stages of development, much worse than the organization believes that it is.

The issue gets worse over time as it becomes more difficult and costly to fix. An organisation which has operated in a way that is inconsistent or not well-defined the definition of data in its different activities for three years, has three years of historical data that are unable to be easily compared or aggregated it is not because the data is not there, but because the same terminology has been used for different things in different areas of the organization, and the distinctions are embedded within the data instead of being apparent from a distance. A business whose quality assurance was a subordinate responsibility and not a dedicated and properly resourced function has data whose integrity varies in ways that are not documented in a systematic manner and can't be properly accounted for when the data is used for making decisions. A company that allows multiple operational systems to collect overlapping and partially contradicting records of the same products, customers and transactions have the data landscape impossible to eliminate without significant disruptions to the operation to put the company at risk.

The reason this problem persists across a wide range of organizations who are extremely smart about strategy and truly focused on data-driven operational excellence is because addressing it requires continuous investment in work that will not yield visible, short-term returns of the kind that resource allocation processes in organizations are intended to reward. A new analytics platform produces visible outputs - dashboards that are easily demonstrated or reports that could be shared with the board and also insights which can be used to create press releases on digital transformation. A data governance program produces invisible infrastructure - cleaner underlying definitions and more reliable collection processes that are more reliable in integrating into systems that are already in already in place. The first is simple to justify in a budget conversation because you can show people what they'll get. Second, you need someone who has enough organisational credibility and perseverance to convince people that an infrastructure project will eventually yield better results from each capacity that is built upon it. This is a compelling argument in the abstract but a difficult one to prevail against initiatives that have benefits that are more immediate and more obvious.

I have made that case throughout a variety of contexts and witnessed it succeed or fail for reason that is predictable, to have a fairly clear view of what will determine if an organisation has resolved the issue of data infrastructure or continues to delay it. It is generally the leader, a specific individual who has the organizational credibility and a clear awareness of the reason why infrastructure is vital, and enough perseverance to push cases until this is an absolute priority, rather than becoming a routine item on the list of things that everyone acknowledges are important but that somehow never quite rise to the top. That leader has to be willing to absorb the immediate cost of the infrastructure investment – the time in the process, the disruptions to existing processes, and the lack of immediately demonstrable output - and be confident that the capability long-term it builds will justify the price several times over. What is required, ultimately to be a system where the long-term investments in infrastructure are appreciated and celebrated at the levels of the leadership, and not just articulated in strategy documents and regularly discarded during the quarterly resource allocation discussion is held. The creation of that culture is, in itself an investment for the future. However, it is, in my opinion, among the best returns that an enterprise that is serious about its data-driven operations can make.}