The Sales Business Model

The simplest business model is one where the firm focuses on producing, marketing and selling its product. In this instance, the firm decides on the design parameters of its product, the quantity to produce, the amount of marketing and the price. All this, in turn, will determine the demand for the firm's product.

While many firms originally adopted a sales business model, the quickly realized that they were leaving a lot of value on the table: Third parties were able to capture the entire after-sales market for repairs and spare parts. A market worth over $1 Trillion in the US alone.

The Sales with After Sales Sevices Business Model

With the sales with after sales sevices business model, the firm continues to make design, production, and marketing decisions but builds in after-sales into its offering through long term warranty contracts. This makes it more attractive for the buyer to come back to the firm for repairs and spare parts.

At the same time, the firm enjoys not just the revenue from the sale of its product but also the (on average 2.5 times) higher margins of the after-sales market. Indeed, Komatsu, one of the major players in the construction equipment sector, generates nearly 60% of its revenue in the after-sales market. This business model clearly dominates the traditional sales model and has become the benchmark to beat for newer business models--such as platforms and sevicization--that have been enabled by emerging technologies.

Internet-of-Things (IoT)

Companies are increasingly integrating IoT technologies into their, which allows manufacturers, for example, to monitor usage and link payments to usage or base preventive and predictive maintenance operations on real-time operational data.

Cloud Storage

The data collected from IoT devices is stored in the cloud. Pooling data from many users of its equipment gives the manufacturer unprecedented access to data about how its products operate under different environemental conditions and usage levels.

Data Anlaytics

Data analytics enables firms to analyze the data from the cloud to make decisions on iterations of its products for subsequent selling seasons. It also enables the firm to perform real time analysis to understand which equipment is more likely to break down soon and take preventive action.

Servicization refers to linking the payment from the customer to the firm to the actual usage or utility that the customer receives from the product. With servicization, the manufacturer retains ownership of the asset and charges the customer for usage, which can be tracked with IoT devices. Typically, mintenance and repairs are included in this usage-based fee.

In the heavy equipment example, usage may come in the form of amount of material extracted or amount of material moved multiplied by the distance moved. That is the exact function the user of the equipment gets. What this does is to shift the risk of demand to the manufacturer of the equipment. When the customer faces higher demand, it has more usage and is happy pay the fee for higher usage. When the customer faces lower demand it is able to reduce the payments to the manufacturer commensurately, limiting its exposure to risk. The heavy equipment manufacturer is in a better position to absorb this risk as it spreads the risk across many customers, some of whom will have higher than expected usage and some lower. This business model also aligns incentives. The manufacturer has every incentive to ensure the equipment is well mainted: It only receives revenues if the machine is in working order. These insights apply to many other indusries, which have also adopted servicization as a business model.

Which business model a firm adopts will depend on its own individual circumstances. This includes the type of environments its equipment is used, the customer segements that it targets, and the level and type of competion that it faces. For instance, servicization allows the manufacturer to extract a higher surplus from customers with low usage requirements, whom it would have to exclude under the sales and after sales business model. This makes servicization more attractive. The presence of third-party service providers also changes the dynamic. With less competition from third party service providers, the sales with after sales services business model is more attractive.

Which business model a firm adopts will also have an impact on environmental and social outcomes. The design parameters for products will be different for different business models. This will influence the longevity of the product. The amount of usage that each unit produced will also be different for different business models. The combination of these impacts on the environment, manufacturing emissions and usage based emission will result in different environmental impacts.

The above findings are robust across sectors but the specific circumstances of a given firm or sector will warrant specific analysis. For insights curated to your unique circumstances, to make use of predictive models, for collaboration opportunities, and speaking arrangements, please reach out through the contact form.