The Goal
Development of a holistic concept for the Predictive Services for Spare Parts – a predictive spare parts management full-service solution – to complement the end-user-centered technical development.
The Solution
Through a series of interviews with pilot customers and potential end-customers, a value proposition was defined and quantified through a savings analysis model to develop a pricing strategy, business plan, product backlog, and a market entry strategy.
The Impact
The pricing and market entry strategy supported Siemens to launch the product on the market. The value proposition and product backlog enhance future development activities.
Solving the Complex Task of Inventory Management
A sometimes contradictory goal of maintenance management is to reduce the downtimes of production machines while at the same time keeping costs as low as possible. Machine downtime costs can quickly skyrocket while on the other hand spare parts inventory can bound (potentially never needed) capital and needs a lot of space. Therefore, optimizing the spare parts inventory for optimal availability can have a significant impact on maintenance costs for industrial customers.
This is where the idea for Predictive Services for Spare Parts was born. Predictive Services for Spare Parts is designed to provide Siemens customers an intelligent digital service to support an efficient spare part inventory management and ensure their customers’ machine or plant productivity.
Predictive Services for Spare Parts and How We Made It Work
In this project, we designed a holistic concept for Predictive Services for Spare Parts – a digital service that we have been developing with Siemens for over a year.
With the desired success in the market in mind, a product needs to be defined from three perspectives: technological feasibility, customer desirability, and business viability. At Motius we call this a “Holistic Product”. As Predictive Services for Spare Parts was in technical development, technological feasibility was constantly upheld. However, customer desirability (are the developed features needed by customers?) and business viability (will the money be earned with the product later?) needed sharpening and deeper elaboration, which is why we included these aspects in the development process.
Bringing in the Customer Perspective
To achieve a holistic view, we had to bring in the perspective of Siemens’ end-customers to comprehend their individual situation. This also helped to define a unique value proposition as well as a profound product backlog for development.
In the first phase, an Internal Pilot User Assessment was carried out by holding interviews with pilot users. With the help of these results and an analysis of potential savings (time/money), the savings model could be developed. Furthermore, a unique value proposition could be drafted, as well as feature requirements (in the form of user stories) captured.
In the second phase, the insights from phase one were completed and verified through a round of interviews with potential customers.
Understanding the individual situation of Siemens’ industry customers enabled us to quantify the savings (time/money) gained through Predictive Services for Spare Parts. Then, in a series of workshops, the product vision, business model, and pricing strategy could be defined. By basing the pricing of the spare parts on the savings analysis, we create an ROI (return on investment) for the customers of the Predictive Services for Spare Parts and thereby ensuring business viability. We did this by means of a financial plan, which was developed and filled with the acquired data, thus defining the business case. Furthermore, a market entry strategy was developed to finalize the holistic picture.
Developing a Pricing Model for a New Service
Quantifying the value proposition of a product can be done in several ways. We chose a combination of value-based and market-based pricing, as no single strategy provided enough insights. By (1) interviewing pilot users and (2) potential customers in the industry we could identify the value provided through Predictive Services for Spare Parts as well as receive insights into how competitor solutions are priced.
The value could then be quantified into the reduced number of machine downtime and time savings of the maintenance and spare parts managers.
Entering the Market
Through the results of this project, we provided Siemens with a validated foundation to launch a successful product on the market. By bringing in the perspective from the outside (Motius and industry customers), we were able to provide Siemens with new insights. Siemens launched Predictive Services for Spare Parts to their customers as an additional service of a series of „predictive“ services. Besides, Siemens and Motius continue the development of this service continuously based on the defined vision and end-user requirements.
Do you want us to develop your next software, making your business processes more efficient?
Want to build products of the future?
The Goal
Development of a holistic concept for the Predictive Services for Spare Parts – a predictive spare parts management full-service solution – to complement the end-user-centered technical development.
The Solution
Through a series of interviews with pilot customers and potential end-customers, a value proposition was defined and quantified through a savings analysis model to develop a pricing strategy, business plan, product backlog, and a market entry strategy.
The Impact
The pricing and market entry strategy supported Siemens to launch the product on the market. The value proposition and product backlog enhance future development activities.
Solving the Complex Task of Inventory Management
A sometimes contradictory goal of maintenance management is to reduce the downtimes of production machines while at the same time keeping costs as low as possible. Machine downtime costs can quickly skyrocket while on the other hand spare parts inventory can bound (potentially never needed) capital and needs a lot of space. Therefore, optimizing the spare parts inventory for optimal availability can have a significant impact on maintenance costs for industrial customers.
This is where the idea for Predictive Services for Spare Parts was born. Predictive Services for Spare Parts is designed to provide Siemens customers an intelligent digital service to support an efficient spare part inventory management and ensure their customers’ machine or plant productivity.
Predictive Services for Spare Parts and How We Made It Work
In this project, we designed a holistic concept for Predictive Services for Spare Parts – a digital service that we have been developing with Siemens for over a year.
With the desired success in the market in mind, a product needs to be defined from three perspectives: technological feasibility, customer desirability, and business viability. At Motius we call this a “Holistic Product”. As Predictive Services for Spare Parts was in technical development, technological feasibility was constantly upheld. However, customer desirability (are the developed features needed by customers?) and business viability (will the money be earned with the product later?) needed sharpening and deeper elaboration, which is why we included these aspects in the development process.
Bringing in the Customer Perspective
To achieve a holistic view, we had to bring in the perspective of Siemens’ end-customers to comprehend their individual situation. This also helped to define a unique value proposition as well as a profound product backlog for development.
In the first phase, an Internal Pilot User Assessment was carried out by holding interviews with pilot users. With the help of these results and an analysis of potential savings (time/money), the savings model could be developed. Furthermore, a unique value proposition could be drafted, as well as feature requirements (in the form of user stories) captured.
In the second phase, the insights from phase one were completed and verified through a round of interviews with potential customers.
Understanding the individual situation of Siemens’ industry customers enabled us to quantify the savings (time/money) gained through Predictive Services for Spare Parts. Then, in a series of workshops, the product vision, business model, and pricing strategy could be defined. By basing the pricing of the spare parts on the savings analysis, we create an ROI (return on investment) for the customers of the Predictive Services for Spare Parts and thereby ensuring business viability. We did this by means of a financial plan, which was developed and filled with the acquired data, thus defining the business case. Furthermore, a market entry strategy was developed to finalize the holistic picture.
Developing a Pricing Model for a New Service
Quantifying the value proposition of a product can be done in several ways. We chose a combination of value-based and market-based pricing, as no single strategy provided enough insights. By (1) interviewing pilot users and (2) potential customers in the industry we could identify the value provided through Predictive Services for Spare Parts as well as receive insights into how competitor solutions are priced.
The value could then be quantified into the reduced number of machine downtime and time savings of the maintenance and spare parts managers.
Entering the Market
Through the results of this project, we provided Siemens with a validated foundation to launch a successful product on the market. By bringing in the perspective from the outside (Motius and industry customers), we were able to provide Siemens with new insights. Siemens launched Predictive Services for Spare Parts to their customers as an additional service of a series of „predictive“ services. Besides, Siemens and Motius continue the development of this service continuously based on the defined vision and end-user requirements.
Do you want us to develop your next software, making your business processes more efficient?
Want to build products of the future?
The Goal
Development of a holistic concept for the Predictive Services for Spare Parts – a predictive spare parts management full-service solution – to complement the end-user-centered technical development.
The Solution
Through a series of interviews with pilot customers and potential end-customers, a value proposition was defined and quantified through a savings analysis model to develop a pricing strategy, business plan, product backlog, and a market entry strategy.
The Impact
The pricing and market entry strategy supported Siemens to launch the product on the market. The value proposition and product backlog enhance future development activities.
Solving the Complex Task of Inventory Management
A sometimes contradictory goal of maintenance management is to reduce the downtimes of production machines while at the same time keeping costs as low as possible. Machine downtime costs can quickly skyrocket while on the other hand spare parts inventory can bound (potentially never needed) capital and needs a lot of space. Therefore, optimizing the spare parts inventory for optimal availability can have a significant impact on maintenance costs for industrial customers.
This is where the idea for Predictive Services for Spare Parts was born. Predictive Services for Spare Parts is designed to provide Siemens customers an intelligent digital service to support an efficient spare part inventory management and ensure their customers’ machine or plant productivity.
Predictive Services for Spare Parts and How We Made It Work
In this project, we designed a holistic concept for Predictive Services for Spare Parts – a digital service that we have been developing with Siemens for over a year.
With the desired success in the market in mind, a product needs to be defined from three perspectives: technological feasibility, customer desirability, and business viability. At Motius we call this a “Holistic Product”. As Predictive Services for Spare Parts was in technical development, technological feasibility was constantly upheld. However, customer desirability (are the developed features needed by customers?) and business viability (will the money be earned with the product later?) needed sharpening and deeper elaboration, which is why we included these aspects in the development process.
Bringing in the Customer Perspective
To achieve a holistic view, we had to bring in the perspective of Siemens’ end-customers to comprehend their individual situation. This also helped to define a unique value proposition as well as a profound product backlog for development.
In the first phase, an Internal Pilot User Assessment was carried out by holding interviews with pilot users. With the help of these results and an analysis of potential savings (time/money), the savings model could be developed. Furthermore, a unique value proposition could be drafted, as well as feature requirements (in the form of user stories) captured.
In the second phase, the insights from phase one were completed and verified through a round of interviews with potential customers.
Understanding the individual situation of Siemens’ industry customers enabled us to quantify the savings (time/money) gained through Predictive Services for Spare Parts. Then, in a series of workshops, the product vision, business model, and pricing strategy could be defined. By basing the pricing of the spare parts on the savings analysis, we create an ROI (return on investment) for the customers of the Predictive Services for Spare Parts and thereby ensuring business viability. We did this by means of a financial plan, which was developed and filled with the acquired data, thus defining the business case. Furthermore, a market entry strategy was developed to finalize the holistic picture.
Developing a Pricing Model for a New Service
Quantifying the value proposition of a product can be done in several ways. We chose a combination of value-based and market-based pricing, as no single strategy provided enough insights. By (1) interviewing pilot users and (2) potential customers in the industry we could identify the value provided through Predictive Services for Spare Parts as well as receive insights into how competitor solutions are priced.
The value could then be quantified into the reduced number of machine downtime and time savings of the maintenance and spare parts managers.
Entering the Market
Through the results of this project, we provided Siemens with a validated foundation to launch a successful product on the market. By bringing in the perspective from the outside (Motius and industry customers), we were able to provide Siemens with new insights. Siemens launched Predictive Services for Spare Parts to their customers as an additional service of a series of „predictive“ services. Besides, Siemens and Motius continue the development of this service continuously based on the defined vision and end-user requirements.
Do you want us to develop your next software, making your business processes more efficient?
Want to build products of the future?
The Goal
Development of a holistic concept for the Predictive Services for Spare Parts – a predictive spare parts management full-service solution – to complement the end-user-centered technical development.
The Solution
Through a series of interviews with pilot customers and potential end-customers, a value proposition was defined and quantified through a savings analysis model to develop a pricing strategy, business plan, product backlog, and a market entry strategy.
The Impact
The pricing and market entry strategy supported Siemens to launch the product on the market. The value proposition and product backlog enhance future development activities.
Solving the Complex Task of Inventory Management
A sometimes contradictory goal of maintenance management is to reduce the downtimes of production machines while at the same time keeping costs as low as possible. Machine downtime costs can quickly skyrocket while on the other hand spare parts inventory can bound (potentially never needed) capital and needs a lot of space. Therefore, optimizing the spare parts inventory for optimal availability can have a significant impact on maintenance costs for industrial customers.
This is where the idea for Predictive Services for Spare Parts was born. Predictive Services for Spare Parts is designed to provide Siemens customers an intelligent digital service to support an efficient spare part inventory management and ensure their customers’ machine or plant productivity.
Predictive Services for Spare Parts and How We Made It Work
In this project, we designed a holistic concept for Predictive Services for Spare Parts – a digital service that we have been developing with Siemens for over a year.
With the desired success in the market in mind, a product needs to be defined from three perspectives: technological feasibility, customer desirability, and business viability. At Motius we call this a “Holistic Product”. As Predictive Services for Spare Parts was in technical development, technological feasibility was constantly upheld. However, customer desirability (are the developed features needed by customers?) and business viability (will the money be earned with the product later?) needed sharpening and deeper elaboration, which is why we included these aspects in the development process.
Bringing in the Customer Perspective
To achieve a holistic view, we had to bring in the perspective of Siemens’ end-customers to comprehend their individual situation. This also helped to define a unique value proposition as well as a profound product backlog for development.
In the first phase, an Internal Pilot User Assessment was carried out by holding interviews with pilot users. With the help of these results and an analysis of potential savings (time/money), the savings model could be developed. Furthermore, a unique value proposition could be drafted, as well as feature requirements (in the form of user stories) captured.
In the second phase, the insights from phase one were completed and verified through a round of interviews with potential customers.
Understanding the individual situation of Siemens’ industry customers enabled us to quantify the savings (time/money) gained through Predictive Services for Spare Parts. Then, in a series of workshops, the product vision, business model, and pricing strategy could be defined. By basing the pricing of the spare parts on the savings analysis, we create an ROI (return on investment) for the customers of the Predictive Services for Spare Parts and thereby ensuring business viability. We did this by means of a financial plan, which was developed and filled with the acquired data, thus defining the business case. Furthermore, a market entry strategy was developed to finalize the holistic picture.
Developing a Pricing Model for a New Service
Quantifying the value proposition of a product can be done in several ways. We chose a combination of value-based and market-based pricing, as no single strategy provided enough insights. By (1) interviewing pilot users and (2) potential customers in the industry we could identify the value provided through Predictive Services for Spare Parts as well as receive insights into how competitor solutions are priced.
The value could then be quantified into the reduced number of machine downtime and time savings of the maintenance and spare parts managers.
Entering the Market
Through the results of this project, we provided Siemens with a validated foundation to launch a successful product on the market. By bringing in the perspective from the outside (Motius and industry customers), we were able to provide Siemens with new insights. Siemens launched Predictive Services for Spare Parts to their customers as an additional service of a series of „predictive“ services. Besides, Siemens and Motius continue the development of this service continuously based on the defined vision and end-user requirements.
Do you want us to develop your next software, making your business processes more efficient?