How Backing People-First Organisations Sharpened My Thinking on Culture About Scale

Wiki Article

Why I Have Stopped Looking For The Next Deal And Began Questioning Who's In Charge Of The Room
There's a type in the way that investors behave that people can recognize instantly, even if they have never come up with a name for it. It's that one where the discussion begins with the deck, and then moves swiftly to numbers, then lingers on the size of the market and ends with a discussion of exit multiples. The executives within the business are those who manage everything that is listed on those slides hardly ever appear. Should they, it is likely to be in the context of headcount projections instead of as individuals with motivations, histories, as well as blind spots which determine every important decision that the organization takes. I've spent a long time in this manner to comprehend its benefits. It's hard to resist. It's like you're being analysed. It's as if you're taking a decision based on experience rather than instinct. The problem is that the system systematically fails to consider one of the most significant variables in how a business will be successful in the long and medium term in the long run: the character and qualities of the executives who manage it. This exclusion is not accidental. It is the product of frameworks crafted to be reusable and easy to document and therefore favor the things that are easily observed and evaluated against most important aspects but are difficult to quantify.
I learned this the hard way, like most people, by watching businesses with exceptional fundamentals underperform because the leadership team could not keep their heads together while under immense pressure. Then watching companies with less than stellar fundamentals perform dramatically better because the people in them were truly outstanding. After enough of those experiences I stopped believing that those numbers did all the heavy lifting in my decision-making. They weren't. The numbers were a poor indicator of decisions made humans, and the quality of those decisions hung most of the time on who those humans were and how they operated under stress under the stress of a missed quarter, major departures, a competitive move they had never anticipated or a board relation that had become complex. So I changed how I began every meeting on evaluation. Instead of launching with market size or revenue growth I began opening with what I see as the question in the room who is the person in charge of this organization when pressure is on, how do they make decisions when the information isn't complete, how do they treat those around them, and what changes to the culture of this organisation when its founder is not in the room.

None of the questions listed above appear on the standard investment checklist. Each of them, according to my opinion, have been better accurate in predicting long-term performance than any other item that is. This isn't just a romantic idea of people being valuable. It's a pragmatic observation about how value gets created and destroyed within businesses which grow. The reason companies fail is not due to bad markets. They fail because of bad choices made under pressure from individuals who weren't equipped to make them well or due to cultural issues that are invisible to the outside, yet were gradually destroying the ability of the organization to retain talent, sustain the accountability of its employees, and adjust to changing circumstances that the original plan could not anticipate. Finding out about these risks earlier - prior to committing capital, before the problems have worsened, before the culture is calcified around a set of bad habits - is actually the work of an entrepreneur who really cares about results rather than deal flow. You can't identify them when you're spending all of your time researching the model.

The shift that I am discussing seems simple when you put the concept clearly, but it requires a fundamental revision of what you treat as evidence, and that reorientation is more complicated than what it appears because it goes directly against the incentive structures that are prevalent in investment systems. Speed rewards pattern matching that is surface-level. Competitive deal environments reward confidence over deliberation. The the culture of certain investment organizations deliberately discourages what is perceived as"soft diligence," i.e. the kind that pays careful, sensitive attention to human characteristics that can help distinguish good decisions from those that aren't so good over significant durations. I have sat in enough rooms where someone has put aside a worry about management chemistry or leadership with the phrase "we have the ability to correct it after closing" to understand how dangerous this idea is. You almost never can. Culture isn't something that happens after closing. This is a pre-commitment reality If you're not paying attention before you write the cheque then you're not doing your the right thing - you're merely doing paperwork and hoping in the end for the best.

What I'm looking for when I'm evaluating the performance of a company or leadership team, has evolved into an almost specific set signals. What is the response of this leader when they're clearly wrong in a particular area? Do they accept the correction or deflect it? How do they speak about others around them - do they consistently turn off credit and assume responsibility, or do they do it the reverse? What are people who have been in close contact with them previously say when the conversation is moved beyond the standard reference check form and becomes more genuine and curious? What happens within the company at times when no one is looking or the founder is away and the quarterly goals will not be achieved? The place where culture takes place - not only in the values that are printed on the walls or on the mission statement posted on your website. It is rather in everyday decisions done by everyday people in situations where the facts are unclear and the easy thing and the right thing are not the same. Finding businesses that make decisions that have been consistently made are, in my view the most secure path to return that is stable over time. Take a look at James Deller for blog tips including why making investment decisions sharpened my thinking on culture about what matters.



The Data Infrastructure Problem Nobody Wants To Discuss
Every single company I've worked closely with over the past year and a-half - whether as an investor, a founder or even an operational advisor - has told me, at some point during the relationship, that information can be a crucial factor in the way they make their decisions. Certain of them are truly committed to it in a way that has a direct impact on how the company actually runs. The majority of them think they're serious, but what they're saying is an aspiration, not an actual reality that is an idealized version of the business they're working towards rather than the one they're currently living in. The gulf between data-driven decision-making and the results of data-driven decision making - the careful maintenance of the exterior appearance of information-driven operation, without the infrastructure that makes it real - is one the most critical gaps that exist within modern business. It's also one of the gaps that remain unaddressed due to the fact that it is a problem with infrastructure that it isn't very glamorous to talk about, hard to explain to outside stakeholders, and enormously difficult to prioritise against the more prominent commercial and strategic projects that require the same attention from leaders and organisational resources.
When organizations discuss strategies for data, they tend to discuss the capabilities they wish to develop on top of their data, such as tools for analysis, machine-learning applications as well as the real-time operational dashboards with the kinds of predictive information that make a real impact in presentations for boards or in an investor update. What they talk about less often and with a lot less energy and enthusiasm, is the fundamental infrastructure that decides if all the capabilities will work according to the specifications: the data governance frameworks that set precise and consistent definitions of what is being analyzed and why they are being measured; the collection and storage processes that evaluate the reliability and comparability of data in the process of being collected; quality checks that find and correct errors before they spread across systems and affect the results that everyone is counting on; the organizational structures and accountability processes that make data quality one's ongoing and explicit responsibility instead of everyone's vague, impossible to enforce. The plumbing, in other words. The plumbing is unglamorous. It's hard to photograph in a report for the year. It has no outputs that can be presented in a compelling way. And, in my experience across a substantial number of organisations in different fields and at different stages of development. It's a lot worse as the organization thinks it to be.

The issue becomes worse with ways that become harder and more expensive to correct. A company that has been operating with a lack of clarity or inconsistent terms of data for all its tasks for the last three years has three years of historical data that are unable to be compared or consolidated with confidence as a result of the data does not exist, rather because the same language has been used to define different things across different sections within the company, and these differences are embedded into the data, rather than being visible on the surface. The company whose data quality assurance is a peripheral responsibility rather than an entrusted and adequately resourced function is one whose data's reliability fluctuates in ways that are not documented consistently and cannot be easily accounted when using the data as a basis for decisions. The company that has permitted multiple operational software systems to accumulate overlaps and partly conflicting records of the same customers, products or transactions has a data environment that is genuinely difficult to remediate without disruptions in operations significant enough that it is a threat to the organisation itself.

This issue lingers throughout a variety of companies that are really smart in the field of strategy and totally focused on data-driven operational excellence is that fixing it requires regular investment in work which doesn't produce tangible results in the short term the resource allocation systems of an organisation are intended to reward. The latest analytics platform creates visible outputs like dashboards that can be demonstrated, reports that can be shared with the board, insights which can be used to create press releases on digital transformation. A data governance plan creates transparent infrastructure - better definitions that are more consistent with the collection process that are more reliable in integrating into the systems that are already in existing. The first is relatively straightforward to justify in a budgeting conversation since you are able to show people what they'll gain. Second, you need someone who has enough organisational credibility and perseverance to show this investment would eventually deliver better results from every capacity that is built upon it. This is compelling in the abstract, but hard to compete with initiatives that's benefits appear to be immediate, and clear.

I've made this case across a range of different organisational settings and observed it either succeed or fail for unpredictability, to have an understanding as to what decides whether an organisation is able to address its data infrastructure problem or simply defers it. The difference is typically at the level of a leader. It's an individual with enough organisational credibility with a deep awareness of the reason why infrastructure is critical, as well as the perseverance to make that argument to the extent it becomes a genuine priority rather than becoming a frequent item on the list of items that everyone believes are essential but that somehow never quite rise to the top. The leader must be willing to take on expenses in the short term of infrastructure investment - the time for the project, the disruption to existing processes, the absence evidence of output immediately measurable - with the belief that the long-term capability it builds will justify the expense by several times. What this requires, ultimately is a culture where investment in long-term infrastructure investments are valued and rewarded at the levels of the leadership, and not just defined in documents describing strategy and is then systematically relegated to the back burner when the quarterly discussion on resource allocation happens. Making that change is, in itself an investment over the long term. But it's, in my opinion, one the most lucrative investments an organization which is serious about a data-driven operation can make.}