Dr Maryam Farsi, lecturer in through-life engineering optimisation at Cranfield University explains how a servitisation business model in a service contract can be a win-win for manufacturers and the service provider.
Servitisation is a business model where a manufacturer purchases productive time available on an asset, rather than investing in the capital machinery. It is a key way that companies can increase productivity, raise technology levels and improve the sustainability of manufacturing through the UK’s supply chain. SMEs can get access to cutting-edge production technologies whilst the task of maintaining asset quality, performance and availability lies with the service providers.
There are three ways in which this Product-Service System (PSS) can be categorised:
1. Product oriented focuses on selling the product and providing some baseline services and corrective maintenance on request
2. Use oriented rents the asset to the manufacturer and the provider is also responsible for preventive maintenance to ensure availability
3. Result oriented is where the provider must assure a certain level of asset performance in terms of availability of the asset and quality of the output. This could be achieved by outsourcing the service or providing the final output for the manufacturer
In a service contract like this, profitability for both sides and customer satisfaction bring out a win-win scenario.
Who carries the risk?
Servitisation has been used very successfully in production lines and tooling supply – companies like Rolls-Royce supply engines almost exclusively to their clients based on this model. But there is a huge challenge with this servitisation in manufacturing – after all, the service supplier carries considerable risk, since the machinery is being operated by its customer.
But for high value assets with a long-life span and high maintenance requirements, service contracts under the servitisation model could bring higher asset performance in terms of both availability and capability, and therefore more profit for both the manufacturer and the bespoke provider.
What’s key to this drive towards servitisation models is information management and digitalisation maturity. For the manufacturer, the challenges lie in mitigating the risk of sharing operational information when the values and profitability of a collaboration are not clear. Service providers must mitigate the risk of reaching the agreed performance, since the asset is being operated by their customer. Maintaining the machine quality, performance and availability rests with the supplier too.
And here’s where advanced technology and analytics comes into play.
Monitoring and data analysis are key to success
Cranfield University is developing advanced monitoring technology and analytics for both the machine and manufacturing process, with metrology (the science of measurement) and digital manufacturing at the heart of the solution. We have developed a servitisation model for the machine tool industry using advanced simulation and data analytic techniques.
We are mapping out the business model, necessary hardware and software, data infrastructure and contractual requirements to allow this approach to succeed. The key performance indicators of machine availability and capability are identified and analysed within the simulation model. An integrated cost-benefit analysis tool has been created to assess the profitability of the servitisation contract from the service provider perspective. The data analytic techniques are implemented to specify the key contractual elements – with a view to maximising profitability with the presence of uncertainty in repair and maintenance activities, human and equipment resources and the servitisation cost elements over the length of the service contract.
In the Cranfield model, several real-world scenarios for different service contracts are tested. The outcomes identify the most profitable servitisation contract with respects to the manufacturer requirements, contract length and the age of the asset.
Moreover, it confirmed the fact that eliminating the uncertainty in cost-benefit analysis for servitisation leads to under-pricing contract.
It is clear that servitisation really can re-model our manufacturing sector, and bring benefits for both sides. But manufacturers and their service providers must go into this with their eyes open, and with monitoring and data analytics close at hand.
How digital manufacturing for servitisation could bring more profit…but first, you need data
Dr Maryam Farsi, lecturer in through-life engineering optimisation at Cranfield University explains how a servitisation business model in a service contract can be a win-win for manufacturers and the service provider.
Servitisation is a business model where a manufacturer purchases productive time available on an asset, rather than investing in the capital machinery. It is a key way that companies can increase productivity, raise technology levels and improve the sustainability of manufacturing through the UK’s supply chain. SMEs can get access to cutting-edge production technologies whilst the task of maintaining asset quality, performance and availability lies with the service providers.
There are three ways in which this Product-Service System (PSS) can be categorised:
1. Product oriented focuses on selling the product and providing some baseline services and corrective maintenance on request
2. Use oriented rents the asset to the manufacturer and the provider is also responsible for preventive maintenance to ensure availability
3. Result oriented is where the provider must assure a certain level of asset performance in terms of availability of the asset and quality of the output. This could be achieved by outsourcing the service or providing the final output for the manufacturer
In a service contract like this, profitability for both sides and customer satisfaction bring out a win-win scenario.
Who carries the risk?
Servitisation has been used very successfully in production lines and tooling supply – companies like Rolls-Royce supply engines almost exclusively to their clients based on this model. But there is a huge challenge with this servitisation in manufacturing – after all, the service supplier carries considerable risk, since the machinery is being operated by its customer.
But for high value assets with a long-life span and high maintenance requirements, service contracts under the servitisation model could bring higher asset performance in terms of both availability and capability, and therefore more profit for both the manufacturer and the bespoke provider.
What’s key to this drive towards servitisation models is information management and digitalisation maturity. For the manufacturer, the challenges lie in mitigating the risk of sharing operational information when the values and profitability of a collaboration are not clear. Service providers must mitigate the risk of reaching the agreed performance, since the asset is being operated by their customer. Maintaining the machine quality, performance and availability rests with the supplier too.
And here’s where advanced technology and analytics comes into play.
Monitoring and data analysis are key to success
Cranfield University is developing advanced monitoring technology and analytics for both the machine and manufacturing process, with metrology (the science of measurement) and digital manufacturing at the heart of the solution. We have developed a servitisation model for the machine tool industry using advanced simulation and data analytic techniques.
We are mapping out the business model, necessary hardware and software, data infrastructure and contractual requirements to allow this approach to succeed. The key performance indicators of machine availability and capability are identified and analysed within the simulation model. An integrated cost-benefit analysis tool has been created to assess the profitability of the servitisation contract from the service provider perspective. The data analytic techniques are implemented to specify the key contractual elements – with a view to maximising profitability with the presence of uncertainty in repair and maintenance activities, human and equipment resources and the servitisation cost elements over the length of the service contract.
In the Cranfield model, several real-world scenarios for different service contracts are tested. The outcomes identify the most profitable servitisation contract with respects to the manufacturer requirements, contract length and the age of the asset.
Moreover, it confirmed the fact that eliminating the uncertainty in cost-benefit analysis for servitisation leads to under-pricing contract.
It is clear that servitisation really can re-model our manufacturing sector, and bring benefits for both sides. But manufacturers and their service providers must go into this with their eyes open, and with monitoring and data analytics close at hand.
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