Outcome-based models are a type of servitization model that has existed in many forms for a long time. In this blog post, we will dive deeper into outcome-based models, exploring what they are, successful use cases, benefits for customers and OEMs, and how they can enable sustainability.
This post is part of our series on equipment-based servitization models for Original Equipment Manufacturers (OEMs) and Value-Adding Resellers (VARs).
What are Outcome-Based Models?
Outcome-based models are a type of servitization model that focus on delivering a specific outcome or result for the customer, rather than just providing access to a product or service. In this model, the OEM is responsible for achieving a specific performance outcome for the customer, such as reducing energy consumption or increasing productivity. The customer pays for the outcome, rather than for the product or service itself.
Outcome-based models are typically enabled through the use of IoT sensors and other monitoring technologies that track the performance of the product or service. This data is then used to calculate the customer's achieved outcome and bill them accordingly.
According to the TSIA 2019 MaaS offer & pricing survey, only 30% of suppliers have value propositions aligned to outcomes and only 35% of suppliers are able to measure the outcomes. Compared to the customer's desire for achieving value and outcomes, there is quite an opportunity space for the OEM to get this right.
Successful Use Cases
There are several examples of companies that have successfully implemented outcome-based models, including:
Rolls-Royce: The company offers an outcome-based model for its jet engines, where it guarantees the amount of thrust generated by the engines, rather than selling the engines outright.
Siemens Energy: The company offers an outcome-based model for its gas turbines, where it guarantees the amount of electricity generated by the turbines, rather than selling the turbines themselves.
ThyssenKrupp: The company offers an outcome-based model for its elevators. The customer pays a fee based on the number of elevator trips taken. This model has helped ThyssenKrupp to improve customer satisfaction and generate more predictable revenue streams.
In addition to the benefits discussed in the previous posts in this series, outcome-based models offer unique advantages that are not achieved through the former. In this post, we will focus on the specific benefits of outcome-based models that differentiate them from previously covered model.
Outcome-based models transfer the risk of achieving the desired outcome from the customer to the OEM. This ensures that the customer only pays for the outcome achieved and not for the effort made to achieve it.
Increased focus on core business
Outcome-based models allow customers to focus on their core business rather than on maintaining and operating equipment or services.
Customers can be assured that they will achieve the desired outcome, as the OEM is responsible for delivering it.
Increased Value & Revenue
Outcome-based models provide an opportunity for OEMs to create more value for customers by delivering a specific outcome or result, rather than just providing access to a product or service. Customers of outcome-based models bare typically willing to pay more because they are paying for the value they receive from the product or service, rather than just the product itself.
Improved Asset Utilisation
Outcome-based models can help OEMs to improve asset utilisation by ensuring that equipment is being used efficiently and effectively.
Improved Customer Relationships
Outcome-based models help OEMs to build long-term relationships with customers, as they become responsible for achieving specific outcomes.
As the OEM develops new products and services, there is potential to upsell customers to higher-value outcome-based models.
In outcome-based models, sustainability outcomes can be what is being "sold" to customers. By focusing on the outcomes that customers are looking to achieve, such as reduced energy consumption or decreased waste, OEMs can offer a solution that not only meets their customers' needs but also promotes sustainability. This approach can lead to a more significant impact on sustainability than just offering products or services that are more energy-efficient or produce less waste. Additionally, by incorporating sustainability outcomes into their business models, OEMs can differentiate themselves from competitors and potentially attract customers who prioritise sustainability. This can lead to increased revenue and profitability while also promoting a more sustainable future for all.
In some cases, outcome-based models can be structured such that the cost savings achieved through the use of the equipment or service are greater than the cost of the equipment itself. This is particularly true in cases where the equipment is designed to provide energy or consumables savings, such as energy-efficient lighting or water-efficient equipment.
Outcome-based models promote sustainability by incentivizing OEMs to design and manufacture equipment that delivers better outcomes with fewer resources. This is achieved through the use of data analysis to identify areas where improvements can be made in equipment design, maintenance practices, and service delivery.
Additionally, outcome-based models encourage OEMs to take a more proactive role in equipment maintenance, ensuring that equipment is properly serviced and upgraded to deliver the best possible outcomes. By taking a more proactive role in equipment maintenance, OEMs can extend the lifespan of their equipment and reduce the need for new equipment to be produced.
Data utilisation plays a critical role in optimising the performance of assets and ensuring that the desired outcomes are achieved in outcome-based models. Here is a breakdown of the benefits of data utilisation:
Optimising delivery and performance - 5/5
Data is essential for ensuring equipment is operating efficiently and reducing downtime and maintenance costs. Since the OEM is responsible for delivering a specific outcome, it's critical to have data to ensure accurate billing and monitor performance to prevent underperformance.
Developing new products and services - 4/5
Data can provide insights into customer behaviour and usage patterns, which can inform the development of new products and services that better meet their needs. While data is valuable for product development, other sources of insight such as customer feedback can also be useful.
Improving commercial terms - 4/5
Data can help identify areas where customers may not be achieving the desired outcomes and adjust pricing or offerings accordingly. In the say way, data can help adjust pricing up when it suggests overdelivering on outcomes. However, market demand and competitive pricing may also need to be considered in pricing decisions.
Reducing depreciation risks - 3/5
Data is essential for accurately predicting equipment lifespan and value, reducing depreciation risk. However, since the OEM is responsible for delivering a specific outcome, depreciation risks are less relevant in outcome-based models compared to other servitization models. The OEM is better able to manage the equipment and its usage, reducing the risk of depreciation due to misuse or neglect by the customer.
Reducing cost of service delivery - 5/5
Data is crucial for optimising maintenance schedules and identifying potential issues before they become costly problems, reducing the overall cost of service. Since the OEM is responsible for delivering a specific outcome, data can help monitor performance and identify issues to reduce downtime and service costs.
In conclusion, data utilisation is crucial for the success of outcome-based models as it enables accurate billing, optimises equipment performance, reduces downtime, and enhances customer satisfaction. Data plays a critical role in optimising delivery and equipment performance, reducing the cost of service delivery, and ensuring accurate billing based on outcomes. It also helps OEMs develop new products and services that better meet customer needs.
OEMs must prioritise data collection and analysis capabilities to leverage the insights that data provides and make outcome-based models profitable and sustainable in the long term.
Outcome-based models also require financing for similar reasons to previously covered models, but with some differences in emphasis.
Off-balance sheet financing
Off-balance sheet financing can be relevant for OEMs in outcome-based models, as it allows them to remove the equipment from their balance sheet, reducing their financial risk. Since the OEM is responsible for delivering a specific outcome, rather than just providing access to equipment or services, ownership of the equipment may be retained by the OEM to ensure proper maintenance and upgrades. However, this can increase the financial risk for the OEM, as they may need to invest capital to produce the equipment upfront.
Cash flow financing
Financing can also help OEMs manage cash flow in outcome-based models. Since revenue is generated based on the outcome achieved, there may be a delay between the upfront costs of producing and installing the equipment and the revenue generated over time. Financing can help bridge this gap and ensure that the OEM has the necessary cash flow to sustain the model.
Outcome-based models involve a higher level of risk for the OEM than other previously covered models. In those, the OEM is paid regardless of whether the customer achieves the desired outcome. In contrast, in outcome-based models, the OEM is responsible for delivering the outcome, and if it is not achieved, the OEM may be liable for additional costs or penalties. Insurance can help the OEM manage this risk by providing a buffer in case of unexpected expenses or delays.
Overall, securing financing is an important consideration for OEMs in outcome-based models, as it can help them manage cash flow and produce necessary assets. Additionally, insurance can help mitigate risks of unexpected expenses and delays.
The type of financing needed will depend on the specific circumstances of the OEM, such as the amount of capital required, the expected revenue generated over time, and the length of the outcome period.
Financing options may include bank loans, leasing arrangements, captive finance companies, or other sources of funding. OEMs must carefully consider the costs and benefits of each financing option to ensure that the model is profitable and sustainable in the long term.
Additionally, OEMs must ensure that financing arrangements comply with applicable regulations and accounting standards.
Succeeding with Valueport.io
Valueport.io's EaaS capabilities can help OEMs successfully implement outcome-based models in servitization, securing above mentioned benefits such as increased value, improved asset utilisation, and improved customer relationships, as well as promoting sustainability.
Accurately measuring performance is a critical challenge for outcome-based models, as the customer pays for the outcome achieved, rather than for the product or service itself. Therefore, accurate measurement of performance is essential to ensure that the OEM is compensated fairly for the outcome delivered and that the customer receives the desired result.
Valueport.io's EaaS capabilities can help OEMs address the challenge of accurately measuring performance data for outcome-based models by providing real-time data monitoring and analysis. Additionally, Valueport.io's platform can provide customers with a transparent view of their equipment performance data, which can help build trust and long-term relationships.
In conclusion, outcome-based models offer a unique approach to servitization that focuses on delivering specific outcomes or results for customers, rather than just providing access to a product or service. Through the use of IoT sensors and other monitoring technologies, OEMs can track the performance of the equipment or service and bill the customer accordingly. Successful examples of outcome-based models include Rolls-Royce, Siemens Energy, and Schneider Electric.
Outcome-based models provide a range of benefits for both customers and OEMs, such as increased value, improved asset utilisation, and improved customer relationships. Data utilisation plays a critical role in optimising equipment performance, reducing downtime, and ensuring accurate billing based on outcomes. Financing is also necessary for managing cash flow effectively and removing equipment from the OEM's balance sheet.
Overall, outcome-based models have the potential to promote sustainability by reducing waste and improving the lifespan of equipment. OEMs can successfully implement this model by prioritising data collection and analysis capabilities and carefully considering financing options. By doing so, they can meet the evolving needs of their customers in a sustainable and profitable way.