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How does growth come about? Scaling challenges and management options

 
 
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By Stelios Kavadias, Margaret Thatcher Professor of Enterprise Studies in Innovation and Growth, Co-Director of Cambridge Judge Entrepreneurship Centre and Jeremy Hutchison-Krupat, Senior Lecturer in Innovation and Operations Management, Director of Master of Studies in Entrepreneurship.

Key takeaways:

  • The problem of scalability often hides in the operational detail of a venture’s business models and processes
  • Two major challenges for scalability relate to the choice of how much variation should be served and the lack of standardisation and professionalisation of the operational processes
  • Standardisation and professionalisation are not always about more rigidity but also about smart operational design

Starting-up is sexy. It is exciting. Real and digital ink is spent on articles that advise on the challenges of starting-up, finding the right product-market fit, pivoting sufficiently and effectively, and eventually reaching sales and revenues. All these are useful perspectives, and they provide a meaningful guide for the initial stages of an entrepreneurial journey. They also tend to create false expectations, creating the illusion that starting-up a new venture is the most difficult step, once a venture gets traction, a rosy world with multi-million pound deals lies ahead. Unfortunately, reality trumps expectations here. Going from 1 to 2 is sometimes harder than going from zero to one – to paraphrase the usually cited cliché expression. 

It is true that a venture could succeed with an early exit. Perhaps they are absorbed by a much larger organization that can capitalise on their intellectual property (IP) or the venture’s talent (a.k.a. acqui-hire). But for ventures that seek to build a sustainable business, success comes through scaling. Through efficient repetition, learning how to make the n-th widget, or serve the n-th customer, in better and cheaper ways than the previous n-1. However, this realisation implies that the decisions, the actions and the knowledge that took a venture from “0 to 1” might be different than the know-how required for the next stage. This means acknowledging the importance of the “boring stuff:” their venture’s operations. This acknowledgment could be one of the most useful realisations for founders. 

Scaling and growth can be hindered by an unclear and half-baked strategy. In many cases, though, a new venture’s strategic position tends to be sound. The venture has emerged, after all, through the scrutiny of the search for product-market fit, and the restless pitch attempts to secure funding and the adaptive pivots to spell out the distinctiveness of their value proposition. But if strategy is not to blame, then what is? Why do things not seem to move forward through the expected growth (or even the iconic hypergrowth) trajectory? One can guess: it is the operations, the messy “how” of the business.

Understanding this basic principle early on can enable founders to focus attention on the operational elements of their business models. For example, we have witnessed first-hand new ventures that deploy a business model – often resulting in revenue generation through custom engagements, e.g. technical consulting based on proprietary IP – only to find out later, that scaling such a business model was simply prohibitive due to the inability to source enough experts who could pursue the required number of engagements. 

Given this, the essential question becomes what should founders do to ensure effective scalability and growth. Two key issues come to mind: first, the choice of how much demand variation they are willing to serve. With this comes the identification of how the chosen variation affects their capability to deliver. Second, the introduction of “ruthless” standardization and professionalisation into the parts of their operation associated with significant costs and/or hinder consistent repetition from happening to deliver higher volumes.  

The first one might appear as an issue of strategic positioning for a new venture, but most often it is not. It stems from the lack of knowledge or realisation of the operational limits of a venture’s processes. The typical blueprint tends to run as follows: once product-market fit is established, in the form of an initial contractual arrangement, or some meaningful signals that certain customers are interested in the venture’s offering (e.g. expression of interest etc.), the effort to grow the business translates into adding more and more customers. This often means giving in to their somewhat different product or service preferences vis-à-vis the already existing initial customer demands. The onboarding of those new customers happens based on rational analysis: money and revenues are needed to ensure additional funding or to cover the running costs. But these calculations miss a significant hidden cost component: the cost of the increasing complexity due to the servicing of demand variability. At some level, it should be expected that different customers will always seek some level of differentiation in the service or product they receive. Still, though, onboarding them without assessing the operational implications of the demanded variation leads to significant and undesirable cost implications.

The immediate impact of these choices is that a venture ends up in what we could all an operational “swamp”: they promise variations of their core offering (product or service), only to suffer delays in their delivery, unexpected costs pile up as does coordination complexity. Why is this? Because the assumed demand variation breeds operational problems in terms of the resource prioritization (“what should we work on first?”), uncertainty (“oh we did not expect this problem when altering the product/service specs…”), and eventually productivity (“we managed to deliver to fewer customers than planned”). 

As such, venture founders find themselves in a constant (almost daily) uphill battle to deliver value amidst an operational mess. They lose sight of their growth strategy and objectives, which often results in founders giving away equity to make up for the inefficiencies to keep the engine running. In retrospect, the message eventually lands: it is always useful to first assess (as best as possible) the implications of demand growth through the operational eyes of the organization. Serving more demand should definitely be the objective; but only if the demand can credibly be offered, and if it will not hinder the real prospects of developing a sustainable business. 

Venture founders should also embrace an operational strategy aimed at supporting the hopeful growth in demand and the inevitable variation in demand. To develop such a strategy, a closer look at the operations of their ventures is in order. This allows the team to understand the source of inefficiencies. Then, an effective programme of standardization and professionalisation needs to be put in place to ensure the ability to absorb variation in a way that avoids ending up in an operational swamp. Such a programme, as expected, depends on the specificities of a venture’s operations but some general principles are as follows:

  • Establishing key performance metrics from an operational standpoint; is this about click-rates, number of served customers per day, cost per customer served etc.? Whatever the right metric, it has to be explicit, visible and guiding the processes and the people to achieve this output. 
  • Prioritising which key metrics link to value generation; is the venture seeking to drive speed of service, or highest possible quality or even perhaps lowest cost per job completed? Those dimensions are significantly different and depending on the overall strategy, they will have to be traded-off against each other, e.g., willingness to accommodate some more cost to achieve higher speed of service delivery. 
  • Identifying steps of the operational processes that are essential in hindering the output rate, the infamous bottlenecks (discussed in any 101 Operations management course in a business school). These steps will set the pace of growth for the venture. And admittedly, their output performance will get worse once the output from a venture’s operations will be promised to be custom, bespoke, personalised. 
  • Crafting operational guidelines that reflect the high-level business priorities for the rest of the venture team. There may exist different types of customer demands we have promised to satisfy, but when these demands require access to the same resources (people, equipment, management attention) in order to be delivered, which type of demand comes higher? Operational priority cannot be ad-hoc; the prospect of our people making the choice without guiding could imply serious productivity challenges.
  • Introducing as much commonality as possible across processes that deliver output to different customers. The lesson drawn early on by Luciano Benetton about the value of delayed differentiation springs to mind. Commonality drives operational scaling whereas allowing differentiation to be feasible.    
  • Standardize and professionalise individual tasks to minimize non-value adding time.  It is only natural for any operational task to have activities that deliver the valuable output, but also activities that do not directly add to the delivery; e.g. changing over from serving one customer to the next implies a gap time for the service provider to prepare. Formally identifying these unproductive activities and eliminating them or automating them can be a good starting point. The old adage of SMED1 comes applicable here, but it is also beneficial to borrow from the heavy lean tradition in operations management as well.

Such principles provide a venture founding team with the necessary armoury to revamp their operations so they are ready to scale. At the same time, these principles enable the team to reduce the need for daily firefighting, freeing up time to pay attention to longer term strategy and objectives. 

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1Single-minute-exchange-of-dies stands for an operational practice that seeks to standardize task times and reduce non-value adding time in operations, in particular in cases where a changeover between jobs is required to satisfy variable demands.  

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