What Thinking Like an Operator Sharpened My Thinking on Culture About Value

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Why I Stopped Looking For The Next Deal And Started Inquiring Who's In Charge
There's an era of investor behavior that people instantly recognize regardless of whether they've not given a name to it. It is the version where conversations begin with the deck, quickly moves on towards the numbers, keeps lingering on market size and then ends with a discussion on exit multiples. People inside the company are those who do the actual work on those slides - barely come up. Should they, it is likely to be in the context of headcount projections instead of as individuals with histories, motives, and potential blind spots. affect every decision the organization makes. I've been operating for long enough in this manner to comprehend its the appeal. It's very rigorous. It's very analytical. It feels like you are making a choice based on research rather than on intuition. The issue is that it consistently excludes the single most predictive variable in how a business will perform in the long and medium-term such as the character and strength of the executives who manage it. That exclusion is not accidental. It is the product from frameworks that were crafted to be repeatable, and easily documented, and which therefore favour the things that can be examined and compared to objects that are really important however, they are harder to quantify.
I have learned this through the harrowing process of observation, just as many do, through watching companies with outstanding basic foundations struggle to perform because the leadership team failed to stay together during pressure. I also learned this witnessing businesses with low fundamentals significantly outperform due to their employees were truly exceptional. After many of those lessons I stopped believing figures were doing the heavy lifting for my investment decisions. They weren't. The data was a weak indication of the decisions made by human beings. The accuracy of the decisions relied heavily on who the human beings were and how they operated under stress - under the pressure of a missed quarter, unimportant departures, competitor's move that they hadn't anticipated and a board relationship which was now complicated. Therefore, I changed the way I began every discussion about evaluation. Instead of focusing on market size or revenue forecast I began with what I've come to think of as the"room-wide" question: who actually runs this organization when pressure is on? How do they decide when the data is not accurate and how do they interact with their staff, and what changes to the culture of the organisation when the founder is not present.

None of these questions are in the checklist for investing. All of them, from my experiences, appear to be better prescient of the long-term performance than anything else. It's not a romantic idea of people being valuable. It is a practical observation about how value gets created and destroyed within businesses which are large. Companies don't fall due to poor markets. They fail due to poor decisions made under pressure by employees who were not prepared to take them effectively or because of the cultural dynamic that was not apparent from the outside, but subduedly hindering the organization's ability of retaining talent, maintain control, and adapt for changes that the original plan didn't anticipate. Finding out about these risks earlier - before you've invested capital or before the problems have become more severe, and before the company culture has formed around the incorrect conduct - is really the job of an investment manager who is serious about returns rather than dealing flow. They are not easy to spot if you are spending most of your diligence time on the model.

The shift I am describing is not difficult to explain when you say it in plain language, but it requires a fundamental shift in the nature of the things you regard as evidence. This reorientation isn't as easy as it sounds because it runs directly against those incentive structures common to investment systems. The speed of investment rewards pattern matching at the surface. Competitive deal environments reward confidence over deliberation. The culture of certain investment circles actively discourages what's referred to as soft diligence - the type of meticulous, patient attention to human factors that actually separates good decisions from those that aren't so good over significant time frames. I've been in enough rooms where someone has absconded from a concern regarding leadership chemistry or management culture with the phrase "we can correct that post-close" to see how dangerous this assumption can be. You almost never can. Culture is not a post-close problem. It's an aspect of the pre-commitment process, and if you are not paying attention when you write the cheque there is no diligence - you are doing paperwork and hoping on the bright side.

The things I'm looking for when I'm evaluating the leadership of a company or team, has developed into an extremely specific set of signals. What are the responses of a leader with respect to when they're clearly wrong in a particular area? Do they accept the correction or deny it? How do they speak about their colleagues - do they always redirect credit, and accept accountability or do they take it the opposite way? What does anyone who has worked closely with their colleagues in the past say about the time the conversation has moved beyond the traditional reference check form and becomes more genuine and exploratory? What happens in the business during the times when nobody is looking, when the founder is away and the quarterly goals is not going to be achieved? That is where culture actually is reflected - not in the values that are printed on the walls as well as the mission statement on site, but rather in the normal decisions made by ordinary people when the context is unclear where the easiest thing and the right thing are not the same. Finding companies where these decisions are consistently executed well is, from my experience the most secure path to ensuring that returns are sustained over time. Follow James Deller for blog tips including what making investment decisions confirmed what i suspected about the long game.



A Data Infrastructure Problem Nobody Wants To Talk About
Every company I've dealt closely with over the past 10 years - whether as an investor, founder and/or an operational advisor I've been told, at some point in the relationship, that information is the main factor in how they make their decisions. Some of them actually mean it in a way which has a direct impact on how the company operates. A majority of them believe they mean it, but what they are describing is the aspiration of an actuality that exists in the present - an idea of the kind of organization they are working toward instead of the one that they currently operate in. The gap between truly data-driven decision-making as well as the effectiveness of data-driven decision making - the careful maintenance of the exterior appearance of evidence-based processes without the infrastructure that can make it an actual reality - is among the most crucial gaps in modern business. It's also one of the gaps that remain unaddressed due to the fact that the infrastructure issue behind it is difficult to talk about, difficult to show external stakeholders and incredibly difficult to prioritize against the more visible strategic and commercial work that is competing for the same leadership attention as well as organisational resources.
When companies discuss their data strategy, they typically tend to focus on what they are planning to create on top of your data - the data analytics platform, machine learning applications and the operational dashboards that are real-time or the kinds that offer predictive analysis that sound truly compelling in any board presentation or update to investors. The thing they discuss less frequently and with less energy and enthusiasm, is the fundamental infrastructure which determines whether all of these capabilities work as claimed: the information governance frameworks, which establish clearly and consistently used definitions of what is being measured and why for each measurement; the data collection and storage procedures that establish the credibility and comparability of data to be gathered; the assurance processes that identify and rectify mistakes before they spread throughout the system and corrupt the outputs that all rely upon; the organization's structures and accountability processes that make data quality the explicit and continuous responsibility of each individual rather than a vague and imperceptible intentions. The plumbing, or the. Plumbing is not glamorous. It's difficult to capture to be used in an annual report. It's not able to produce results that can be displayed in an engaging presentation. In my experience across a substantial number of organisations across different areas and at various stages of development. It's a lot worse than what the organization believes it is.

The issue becomes worse as it becomes more difficult and costly to fix. An organization that has been operating with inconsistent or poorly defined terms of data for all its activities for three years, has three years old data that is unable to be effectively compared or aggregated - not because the data isn't available, but because the same terms have been used for different things in different parts of the organisation, and these differences are embedded into the data, rather than appearing on the surface. An organization for which data quality assurance has been someone's personal responsibility, rather than an entrusted and adequately resourced function is one whose data's reliability can be questioned because it is not documented consistently and cannot be fully accounted when the data is used to make decisions. A company that has allowed multiple operational system to accumulate multiple and partial conflicting records on the same customers, products or transactions is a data environment that is real difficult to address without causing significant disruption to operations to present a risk.

The reason this issue persists across organizations who are truly knowledgeable in the field of strategy and totally determined to implement a data-driven strategy is that fixing it requires sustained investment in work that has no tangible gains in the short-term which resource allocation processes are intended to reward. A new analytics platform provides tangible outputs, such as dashboards that can be displayed as well as reports that are shared with the board of directors, and information which can be used to create press releases regarding digital transformation. Data governance programs create an invisible infrastructure with clearer definitions and more consistent collection processes with more stable inputs into system that was already in established. It is the first to argue in a budget meeting because you can show people what they'll receive. The second one requires enough organizational credibility and endurance for convincing people for the investment in infrastructure to, over time, generate better results from each new capability that is added to it. This is a compelling argument in the abstract but it can be difficult to convince in the face of initiatives that have benefits that appear to be immediate, and visible.

I've presented that argument across a range of different organisational settings and watched it perform or fail for certain reasons, to gain a pretty clear idea of the elements that determine whether or not an organization finally tackles their data infrastructure issue or continues to defer it. The difference is almost always the leader, a specific person who has enough credibility in the organization with a deep conviction about why the infrastructure is so important, and sufficient determination to persist in making your case till the infrastructure becomes a genuine priority rather than simply a part of the list of things that everyone is in agreement about but that somehow never quite attain the level of importance. The leader must be willing to take on the short-term cost of the infrastructure investment: the amount of time or disruption to current processes, and the absence of immediate tangible results - and be confident in the capacity that it builds will justify the expense several times over. What's required, at the end of the day the establishment of a culture which investments in long-term infrastructure are recognized and appreciated at the levels of the leadership, and not just articulated in strategy documents and is then systematically relegated to the back burner when the quarterly resource allocation process takes place. It is, in itself an investment over the long term. It's also, in my view, among the best investments that a company that is committed to data-driven operation could make.}