What Operating Through Uncertainty Sharpened My Thinking on Culture About People

Wiki Article

Unexpected Costs Of Scaling Too Fast How Founders Often Learn Too Late
The mythology surrounding scaling is in large part about speed. Once you have a good fit for your product, then add fuel to the fire. Develop the team, increase to market, raise next round prior to the previous one has settled. The story favors those who lead the company by moving forward, always adding numbers, and always expanding into additional verticals even before when the main business of his genuinely stabilized and the company has built the internal capabilities required to be able to manage the expansion with no loss of coherence. I understand where this mythology originates. In certain market conditions and business models, the first mover who scales fastest does genuinely win, and the stories of firms who were aggressive in their growth and ultimately succeeded are told more often and in greater detail than ones about businesses that grew in a hurry and fell. But for every business where aggressive early scaling is a good choice, there's a few where the speed of scaling is the primary cause of the issues that eventually kill the business. These cautionary stories are not given all the attention that the cases of success.
In the end, the cost hidden from scaling too quickly is not the one that is revealed in the burn rate calculation or the cash flow projection. It's what is visible at the end of six months, when the company has gone beyond the coordination mechanisms of informal nature that kept it in place in its early days, and before it has crafted an official structure to keep larger companies together. That gap - between informal and formal separation between the company you were and the business it is expected to become is where the majority of companies that are growing fail to bridge. The first and most obvious sign that a company may be reaching that apex is when decision-making slows even as everyone insists that there has been no fundamental change. There is still a way to reach the founder in the theoretical framework. The team is still united with the theories. The culture is solid in theory. But in practice the organization has gotten to the point that informal channels for communication used to transfer vital information are clogged however, no one has yet set up formal channels to replace them. Information that used to flow effortlessly now must be controlled. The decisions that were made swiftly now require alignment across multiple functions, which have never been clearly defined relative to one another. Accountability that used to be intimate and immediate is now dispersed and delayed The company is beginning to display the signs of a system functioning at the limits of its coordination capacity.

All of this isn't visible in the data that founders and investors generally monitor most closely. Revenue may still be growing. Acquisition of customers could be moving in the right direction. The team may remain eager and enthusiastic. But, underneath those apparent indicators there are internal issues that grow gradually until they can't be ignored - at which point fixing them becomes dramatically more costly and time-consuming than it would be if they had been addressed earlier, when the signals aren't as apparent. What is hidden I am talking about that is not the financial cost of expanding, but the over-the-long term cost of organisational growth that is incurred by growing beyond your current infrastructure and the rising cost of putting it in place reactively rather than proactively.

Entrepreneurs who are able to navigate this change well aren't necessarily the ones who scale more slowly, even though an intentional pace of expansion may be the answer. They are the ones who recognize that creating the management structure of their business is as crucial as creating the product and invest in it with the same intentionality and commitment to the development of their products. This means doing the boring job of assigning roles and responsibilities clearly, creating reporting structures which provide the relevant information the leadership requires be able to make smart decisions, designing accountability systems that are particular enough to be meaningful, and thinking carefully about the kind of culture norms an organization requires at its size and not following the rules that were created naturally when the company was smaller. The work involved isn't exciting. It's not likely to garner press coverage or investor enthusiasm. But it's the job that decides if the business that you're creating can sustain the growth you are seeking.

Businesses that don't achieve this feat do not usually fail massively or clearly. They deteriorate. They lose their most effective employees in the beginning - the ones who have enough self-awareness to see what's going on inside an organization and the options to quit before it becomes more serious. In the next phase, they lose customers sometimes in a subtle way, when the quality of execution is deteriorating because accountability has been made too complex and deferred to find problems before they impact the customer. In the end, they are losing momentum and before the decrease in momentum is apparent in the figures as structural issues become deeply entrenched, the cultural impact is severe, and the cost to fix each is far higher than it might have been if the governance investment were made at the appropriate moment. The idea of treating organisational infrastructure as a product - something you plan cautiously, build meticulously, and continue to refine as the company grows - is one of the most important mental shifts you can make for a founder when they transition from the initial phase to an actual scale. When founders make this change, they tend to build companies that can reach their full potential. People who don't tend to create companies who are a bit too close. Check out James Deller for site recommendations including how working across industries shifted my priorities about character.



The Data Infrastructure Problem Nobody Wants To Discuss
Every organization I've worked closely with during the last decade and a half - whether as an investor, founder or as an operational adviser has informed me, at some point in our working relationship, that data can be a crucial factor in the way they make their decisions. Some of them genuinely mean it in a way which is reflected in how the organization operates. The majority of them think they're genuinely meaning it, but the concept they're proposing is only an aspirational notion rather than an actuality that exists in the present - a version of the organisation that they're aiming to build as opposed to the reality they're currently living in. There is a gap between legitimately decisions based on data and the efficacy of data-driven decisions - the meticulous maintenance of the appearance on the outside of an information-driven operation, without the infrastructure that can make it true - is one of the most serious gaps in the current business. It's also among the ones that is often ignored partially because the infrastructure issue behind it is really not glamorous to talk about, hard to prove to stakeholders outside of the company, and enormously difficult to classify against the more obvious strategic and commercial jobs that vie for the same attention of leaders and organisational resources.
When companies talk about their the strategy for data, they tend to focus on what they are planning to add to their data - the tools for analysis, machine-learning applications for operational dashboards, and real-time data that provide the kind of predictive insight that sound genuinely compelling in the form of a presentation for board members or an investor update. What they talk about less frequently and with a lesser amount of energy and enthusiasm, is their foundational infrastructure that is the determining factor in whether all of those capabilities actually function in the manner they're supposed to: the data management frameworks that give specific and consistent definitions of what is being measured and for what purpose collecting and storing methods that define the accuracy and comparability of the information in the process of being collected; quality assurance processes that catch and correct errors before they get propagated throughout the system, and cause harm to the outputs that everybody is relying upon; the organisational structures and accountability mechanisms that make data quality an ongoing and explicit obligation instead of the general and imperceptible intentions. The plumbing, or the. The plumbing isn't glamorous. It's difficult to photograph to be used in an annual report. The outputs it produces are not ones capable of being presented in an engaging presentation. And it is, in my experience, across a huge variety of companies operating in diverse industries and at different stages of development, significantly worse than the business believes that it is.

The issue continues to grow over time as it becomes harder and costlier to rectify. An organisation that has been operating with poorly or incoherent terminology for data across different functions for three years has three years of historical records that cannot be easily compared or aggregated which is not because the data has not been created, but because the same term has become a synonym for different things in different parts of the organization, and these differences are embedded into the data rather than appearing visible on the surface. An organization where data quality assurance has been the responsibility of a peripheral responsibility rather than being a fully resourced and dedicated task has data that's integrity fluctuates in ways that are not documented properly and cannot be adequately accounted for when the data is used when making decisions. A business that has allowed multiple operational systems to collate overlapping and partly conflicting records of the same customers, products or transactions can create a data environment that is hard to clean up without causing enough disruption that it is a threat to the organisation itself.

The reason that this problem continues to exist across a wide range of organizations that are truly intelligent about strategy and truly dedicated to a data-driven approach to business is because solving it requires sustained investment in work that doesn't produce tangible results in the short term that resource allocation processes in organizations are intended to reward. An analytics platform that is new produces visual outputs: dashboards and reports that are easily demonstrated or reports that could be shared to the board, information that can be translated into press releases on digital transformation. Data governance software creates invisible infrastructure - cleaner underlying definitions and more consistent collection methods as well as more reliable inputs into systems that were already in already in place. This one is fairly simple to justify during a budget discussion because it is easy to show people what they will get. The second needs someone with enough organizational credibility and endurance in order to demonstrate this investment would, over time, improve the outcomes of every ability built on top of it. This is a convincing argument in abstract, but difficult to compete with initiatives that's benefits are more immediate and apparent.

I've argued that case throughout a variety of contexts and seen it succeed or fail due to unpredictability, to have an accurate understanding about what makes an organisation actually tackles the problem of its data infrastructure or defers it. The key difference is usually that of a leader, an individual with sufficient organisational credibility with an authentic understanding of the reason infrastructure is crucial, and enough determination to continue making your case till the infrastructure is an absolute priority, rather than becoming a routine item on the list of things that everyone is in agreement about but do not achieve the status of being a top priority. This leader needs to be able to bear the cost of the infrastructure investment - - the time in the process, the disruptions to processes that are already in place, the absence of a tangible outcome - in the knowledge that the long-term capabilities it develops will justify the expense many times over. What it requires, in the end the establishment of a culture where long-term investment in infrastructure is thought of as a priority and is rewarded at high-level of leadership, not only mentioned in strategic documents, but then consistently deprioritised when the quarterly resource allocation discussions takes place. Achieving that culture is, itself an investment over the long term. But, in my opinion, among the best investments that a company that is serious about its data-driven operations can make.}