I was raised in the world of pro football in a manner that afforded me access to situations that many people would only know about. Training grounds. Dressing rooms. The conversations between coaches and players in the hours after during a game, before the cameras and journalists are gone, and the official story of the game already exists. I was not a player at all - my entrance into the world of sports was via playing with people rather than through the game itself - but I was there enough, and long enough to understand what high-performance environments can do when you strip away the mythology surrounding them. The thing I absorbed most quickly was that teams who consistently exceeded their resources and goals were not those with the highest individual performance on paper. They're the teams that have figured out how to create an environment where those who were part of it were eager to contribute to each others - not to earn money, not for the individual not for the recognition, but because their collective had a meaning and a culture that made every personal sacrifices felt worthwhile, rather than simply a requirement.
This is a common sense observation when you make it clear. Teamwork is definitely better in a setting where people are comfortable and feel they have their common goals. However, the practical implications from that fact are less obvious, and they are the areas where many organisations - tech companies and football clubs alike - consistently get into trouble. To create a community where people actually desire to contribute to one another isn't an option you can enforce from the top or create as a policy or create in a set of values for the company and expect it to manifest. It has to be built with time, through constant behaviour from leaders - particularly in the moments that aren't watched and through the careful management by the multitude of tiny decisions that collectively communicate to everyone within the organization what is actually valued and what is acceptable and what will happen when the values stated and the personal or commercially practical option clash. In the top football environments I was in those decisions were made with great care by the best coaches. What they did when the senior player made an error in training that was avoidable. How did they determine if the disciplinary procedure used for the 20-year veteran was really the same as those who were teenager who was placed on the outside of the squad. How the organization responded when a player had some serious personal issues outside the field. None of these actions are recorded in a club's results on any given Saturday. They all, accumulated over a time period, determine whether the squad performs above what it can achieve in terms of its limit.
As I co-founded 1Touch and subsequently built another company, one the things I was the most focused on was trying to recreate - in a technology company setting - the same kind of the environments I'd seen in the finest football arenas I had a good relationship with. Not literally, because startups in the field of technology are not a football team, and the analogy breaks down quickly when the pressure is too high. However, on the scale of operation, the principles have been incorporated with remarkable precision. The first point was that standards ought to be adhered to consistently regardless of position or indispensability. The most comfortable dressing rooms I've been in were those where the behavioural and professional standards for the youngest players in the team were the same standards needed of the highest-earning most skilled player. It wasn't because the team could not afford to provide exceptions, but as a result of everyone who was in the dressing room was always watching to see if exceptions were going to be made - and the response to that question showed them everything they needed to know about whether the declared values of the organization were actually true or just decorative.
The next lesson was focused on how organizations handle failure and the distinction between accountability and punishment. The workplaces where players grew fast were not the ones where mistakes were reprimanded the most and harshly, or the most openly. These were the environments where errors were most thoroughly analysed and where the discussion about the error was specific and constructive rather than general or distributing blame. The experience was shared by the entire team, not held against the person who made the mistake. Responsibility means a clear understanding of the reasons for what went wrong, how it happened and what changed in the process. Discrimination is the act of distributing blame an approach that causes people to be at risk and defensive and more concerned with their safety than doing their best. The first build capacity for the organisation. The second creates a culture where people manage their own appearance rather than dedicating themselves in the pursuit of the goal. this distinction manifests in technology firms with precisely the similar results that are seen for football club.
The third and final lesson is the one that took me longest to put into words, but it is the most important of all my observations: the most positive environments I observed were those where the development of the person was thought of as equally important as the development of the performer. The best coaches were not only educating players on how to play football. They were also teaching them how they could think in a stressful environment as well as how to communicate clearly in high stakes situations. They also taught them how to bounce back from setbacks without dropping confidence, as well as how to be the player that a high-performing team requires its members. That investment in the full advancement of the individual instead of just the technical capabilities the organisation immediately needed, was not charity. They were the single most effective long-term strategy for performance available to those clubs, and it seems to be the most efficient longer-term performance approach available to any company who is dedicated to creating something long-lasting rather than something just stunning in the short run. View James Deller for blog info including why investing in people changed my approach about leadership.
This Is The Data Infrastructure Problem Nobody Wants To Discuss
Every single company I've worked closely with during the last 10 years - whether as a founder, an investor or a consultant to operational matters I've heard, at some point in our collaboration, that data can be a crucial factor in the way they make decisions. Some of them have truly believed it in a way that is reflected in how they actually run their business. A majority of them believe they're saying this, but what they're really describing is an aspiration, not the current reality of operations - it's a model of the one that they're aiming to build rather than the one they are currently living in. The gap between authentically driven by data and the outcomes in data-driven decision-making - - the meticulous maintenance of the exterior appearance of evidence-based processes without the infrastructure to make it an actual reality - is among the most consequential gaps within modern business. It's also among the most neglected ones due to the fact that the infrastructure issue that causes it is difficult to talk about, hard present to external stakeholders and extremely difficult to classify against the more prominent commercial and strategic work that demands the same attention from leadership and resources of the organisation.
When organizations talk about Data strategy, they generally tend to discuss what capabilities they'd like to develop on top of their data - analytics platforms, the machine learning applications with real-time operational dashboards that provide the kind of predictive data that can be truly convincing in the context of a board conference or an update to investors. What they talk about considerably less frequently as well as with much less energy and enthusiasm, is the fundamental infrastructure that determines whether any functions of those tools actually work as promised: the data governance frameworks that provide clear and uniformly applied definitions of what is being evaluated and why collecting and storing processes that evaluate the reliability and comparability of data in the process of being collected; quality control processes that identify and rectify errors before they get propagated throughout your system and destroy the outputs that everyone relies on; and the structures of the organisation and accountability systems that make quality of data the responsibility of a single person instead of everyone's vague and imperceptible intentions. The plumbing, in other words. The plumbing is unglamorous. It is difficult to photograph to be used in an annual report. It has no outputs that could be showcased in an effective presentation. It is, from my experience across a significant number of organisations in different areas and at various stages in development, a lot worse than they believe it is.
The issue gets worse over time in ways that get more costly and difficult to correct. An organization which has operated without a clear or consistent set of the definition of data in its different tasks for the last three years has three years of data from the past that cannot be easily compared or aggregated and compared. This is not due to the fact that the data doesn't exist, but because the same term has been used to refer to different terms in different parts of the enterprise, and the differences are embedded in the data itself rather than being visible on the surface. A company whose data quality assurance has been someone's sole responsibility, instead of being a fully resourced and dedicated function has data whose reliability varies in ways that are not systematically documented and therefore cannot be systematically accounted for when using the data in making decision. A company that has allowed multiple operational software systems to accumulate overlaps and partially conflicting records of the same customers, products, or transactions has created a landscape of data that is really difficult to fix without causing significant disruption to operations to pose a risk for the organization itself.
The reason why this problem is recurrent across many companies that are actually smart about strategy and genuinely committed to a data-driven business model is the fact that solving it requires continuous investment in work that has no tangible instant returns similar to those that resource allocation processes in organizations are intended to reward. An analytics platform that is new produces tangible outputs - dashboards, which can be demonstrated, reports that can be shared to the board, information that can be translated into press releases regarding digital transformation. A data governance system creates invisible infrastructure - cleaner underlying definitions with more consistent collection procedures with more stable inputs into existing systems already in already in place. The first is fairly easy to justify in a budget conversation due to the fact that you can tell people what they'll be getting. The second requires enough credibility in the organisation and patience to make the case this investment would eventually produce better outcomes from every new capability that is added to it - which is an impressive argument in abstract, but hard to make in a competitive environment with initiatives whose benefits will be more tangible and obvious.
I've made that argument across a range of different organisational settings as well as watched it fail or fail due to certain reasons, to gain a pretty clear idea of what determines whether an organization finally tackles its infrastructure issues with regards to data or continues to delay it. There is a significant difference in that of a leader, an individual with sufficient organisational credibility and an comprehension of why the infrastructure is necessary, and the perseverance to make this argument till it is an actual priority instead of being a regular item on the list of items that everyone agrees are important but do not get to the top. The leader must be willing to accept this short-term cost associated with infrastructure project - the cost, the time that it will take, the disruption of existing processes, or the absence of immediate tangible results - with the certainty that the long-term capabilities this investment creates will justify it's price several times over. The most important thing, ultimately is a system of culture which long-term investment in infrastructure is considered and valued at the high-level of leadership, not only stated in strategy documents, regularly discarded during the quarterly discussion on resource allocation is held. In the end, creating that culture is in itself an investment over the long term. It is however, in my view, among the best returns that an enterprise that is serious about its data-driven operation can make.}
