2.6. Feedback Structure and Dynamics of a Technology-based Growth Business

The first project I undertook after completing my PhD was to model a technology-based growth company operating in Salt Lake City, Utah. With a colleague from MIT, I made the 2000 mile plane journey from Boston to Utah on several occasions to interview the management team and capture their understanding of the business. The company made automated materials handling systems. These systems are expensive and technically complex, but the principle is simple enough. You have probably seen forklift trucks used in factories to move goods from place to place. They are an example of materials handling, with human operators as drivers. Nowadays, the process is largely automated. Visit a manufacturing firm and you will find specialised robot-like machines moving materials. They pick stock items from huge multi-storey racks and deposit them on conveyor belts for production and assembly. At the end of the production line they receive finished goods, count them and store them in a warehouse ready for shipping. The technology is a sophisticated blend of mechanical engineering, electrical engineering and computer science. Product designers are often recruited from the aerospace industry. The equipment is very expensive and is built to order with a long lead time. An automated storage and retrieval system for use say in Harley-Davidson's motorcycle factory in Pennsylvania or BMW's MINI factory in Oxford might cost several million pounds sterling and take more than a year to build and install. Each system is a self-contained engineering project that includes design, proposal writing, competitive bidding, construction and installation.

At the time of the modelling project, automated materials handling systems were new. There was a belief among the management team, and others in the industry, that the market for these complex products was potentially very large. But the fledgling industry had teething problems. Growth was not as fast as expected. Automated handling was still perceived by customers (factory owners and operators) to be inflexible. It was difficult to trade-off promised labour savings against the large capital cost. Customers needed persuasion and reassurance to invest. Nevertheless, there had been a few years of promising growth, but now the product was meeting resistance in the market and there were signs of a downturn in sales. Was growth sustainable? What factors might halt growth? These were the questions the management team wanted to investigate. A series of meetings took place to map out the operation of the business. Deliberately the scope of the analysis was broad extending across functional areas, into the market and including competitors.

The causal loop diagram in Figure 2.12 emerged from the meetings (Morecroft, 1986). It shows four interacting loops. At the top is a 'real growth loop', a structure capable of powering business expansion. Of central importance is the salesforce. The Utah company viewed itself as a leader in automated materials handling and its salesforce was responsible for wooing customers and persuading them of the merits of automation. The bigger the salesforce the larger the pool of customers interested in the technology. However, customers do not immediately buy. They first request a feasibility study with a formal costed proposal for a competitive bid. The more customers, the more study requests, the more study completions and, ceteris paribus, the greater the number of contracts won. More contracts boost the budget for the salesforce enabling a bigger salesforce. The result is a reinforcing loop in which an increase in the salesforce eventually leads to enough extra business to justify a further increase in salesforce, and so on. This single loop in isolation is how the business might look to an established monopoly producer, or to a myopic and optimistic producer unaware of competitors. Admittedly, it is just a brief sketch concentrating on technology diffusion, but it shows a growth engine. Providing the basic economic proposition to customers is good (i.e. automation is reliable and cost effective) then the business will grow steadily, limited only by the time it takes to educate customers about the technology, design systems and agree contracts.

Figure 2.12. Feedback loops in the growth of the automated materials handling business

Source: Adapted from The Dynamics of a Fledgling High-Technology Growth Market, System Dynamics Review, 2(1), 36–61, Morecroft, J.D.W, 1986, © John Wiley & Sons Limited. Reproduced with permission.

If such a growth engine is really at work, why might it falter? Meetings revealed commercial pressure from new entrants which, it turned out, was able to explain the temporary stagnation already observed. This pressure is captured in three feedback loops that extend the boundary of the model to rivals, their combined capacity and, crucially, their collective impact on industry reputation. The hypothesis here is that rapid entry of new firms, attracted by the growth potential of the industry, eventually undermines industry reputation thereby making it much more difficult for any producer (new or established) to woo customers. The industry reputation loop is a good place to start. Here we imagine that study completions (proposals from the established producer in Salt Lake City) are open to competitive bids by new rivals. As no single producer has a monopoly, an increase in study completions leads to more contracts awarded to new competition. The loss of contracts is not, however, the only problem here. It is the knock-on consequences that matter most. An increase in contracts to new competition leads to higher utilisation of new competition capacity. So existing new firms are busy and this success signal leads to an increased start-up of new competition and an expansion of new competition capacity. With more capacity the collective bidding power of new competition rises, but this can hurt the industry. The product is complex and some new entrants are still learning the technology. So as their bidding power rises industry reputation is depressed leading eventually to a reduction in customers interested, fewer study requests and fewer study completions. The result is a balancing loop, the reputation loop, which undermines real growth by attracting naïve and opportunist producers to an industry whose growth depends on the confidence of customers in the merits of a complex product.

The reputation problem is exacerbated by speculative growth of new entrants, shown by the loop at the bottom of Figure 2.12. Here an increase of contracts awarded to new competition leads, as before, to an increase in the bidding power of new competition. New firms compete more vigorously for the available contracts and they win more, thereby attracting even more new firms. The growth process is speculative because new entrants do little to woo customers. Instead, they hijack customers already nurtured by established producers. New firms bid aggressively, win contracts and reinforce the impression that the market is growing.

The final loop is labelled 'capacity control', but in the context of speculative entry it is weak and myopic. If new competition capacity rises then, all else remaining equal, the utilisation of capacity falls thereby deterring entry and stabilising capacity. But all else does not remain equal and speculative growth creates the illusion of capacity shortage. The illusion quickly fades if real growth (in the top loop) becomes negative due to low industry reputation. Then contracts to new competition diminish, utilisation falls and the reality of stagnant or falling demand becomes apparent to new producers and potential new entrants alike.