Table 4 Factors related to relational...

Table 4

Factors related to relational preconditions in the context of DT

		Illustrative quotes on data sharing practices
Factor		[A] Data sharing practices related to process connectivity	[B] Data sharing practices related to asset/equipment connectivity	[C] Data sharing practices related to product connectivity
Need for complementary resources Assets and capabilities to use the data are not at the sharing firm	High need for complementary resources Firms need to look externally for: – Product/process know-how – DT competences (including data management and analytics) – Datasets that complement the ones owned by the firm	Production planning [A3] You can’t solve SC issues at a local level, you need multi-tier data. That’s what our customers have understood – SC platform, Founder and CEO	Quality [B6] The supplier matches our product quality data with their internal process data. Through artificial intelligence, they find patterns – Supplier 2, ICT Director	Quality/New product development [C7] We have the simulation models for our components, not the OEMs. It is up to us to make sense of quality issues – Supplier 2, Head of R&D
		Logistics [A6] They [the logistic service provider] have developed tools for logistics optimization. We realized that the more they can access the data of different manufacturers, the more they can optimize the service – Supplier 1, Supply Chain Manager	Process optimization [B8] We access data as clients realize that they haven’t achieved anything – Metal equipment, General Manager Big data analytics is something a single manufacturer is not able to do leveraging on internal data and expertise – Metal equipment, Head of Project Management We looked for external capabilities on how to collect, analyze, and import data – Commercial OEM, Head of Industry 4.0 We had partners for this project, one for data analytics, one for the 3 D scan and the digital twin. We shared the data with them – Premium OEM 2, Head of Industry 4.0	Service access/provision [C4] All the sensors and cameras that [OEM name] is using are ours. We know them and develop related algorithms – Supplier 2, Production Manager «Sensor-generated data from connected vehicles can be … managed by OEMs. Only smaller OEMs have the data on our servers, lacking resources – Supplier 2, ICT Director
			Maintenance [B9] At the beginning, we partnered up with different companies for proofs of concept. We didn’t have competence in hard data analytics and machine learning back then – Premium OEM 2, Head of Industry 4.0 We wanted to detect compressed air leakages through microphones. We shared data through the cloud with specialized companies – Supplier 2, ICT Director	Service access/provision [C6] Some data need to be analyzed in large volume to detect patterns, beyond what is under the purview of a single OEM. That’s why we leverage data aggregation platforms – Premium OEM 2, Head of Innovation
	Low need for complementary resources Firms have internal: – Product/ process know-how – Dedicated staff and technologies – DT capabilities	Production planning [A3] Manufacturers are concerned of becoming dependent on an external provider for planning activities. They already have staff and technologies – SC platform, Founder and CEO	Quality [B6] We recently adopted brushless electric motors. As there were failures, we analyzed the data. The supplier was a small firm without a structured approach to problem solving – Supplier 2, Head of R&D	Product use [C1] There are cases where business customers, having developed their own infrastructure and capabilities, manage their data internally – Premium OEM 1, Head of Connected Vehicles
			Process optimization [B8] Advanced customers manage themselves machine data» – Plastic equipment, CIO We know the production process. External providers would just look at the wrong variables – Supplier 2, Managing Director The algorithms are continuously learning, it is an ongoing process. So, if you only rely on industrial technology providers … it is something that increases the cost. … No one has 20 years of experience with a proven solution – Supplier 2, Head of Production
			Maintenance [B9] We have maintenance capabilities, so we don’t see the added value of sharing data – Commercial OEM, Head of Industry 4.0 We approach smart maintenance in-house for simpler machines and through external players for more complex ones – Premium OEM 1, Head of Production
Level of dependence Sum of dependence between the actors, higher likelihood of joint action	High level of dependence Firms have: – A high share of common business – Personal relationships – Strongly entwined business processes	Production planning [A2] Whenever we have strong ties and a personal relationship with a supplier it is easier to get the necessary data. … We have visibility on suppliers involved in processes that start and get back at our plants – Supplier 3, Head of Purchasing «It is easier with mid-sized companies, where we have strong partnerships in place. We discuss this directly with the owners – Supplier 2, General Manager	Maintenance [B9] In an industry that does not carry inventory, it is important to ensure continuity in case of breakdowns. We need to get more data and in real time – Plastic equipment, CIO
		Logistics [A4] [A5] As we establish partnerships with few logistic service providers, we can have them adopting our systems for data exchange – Supplier 1, Head of Logistics We have integrated information systems intercompany and with the supplier park – Mass market OEM, Production Manager
		Traceability [A7] We didn’t experience any operational benefit with the blockchain besides strengthening our reputation and the partnership – Supplier 1, ICT Director
Dependence asymmetry Difference in actors’ dependence on each other	High dependence asymmetry Powerful buyers exert pressures	Logistics [A4] [A5] We have the power to impose on our providers to share the data and adopt our technologies – Commercial OEM, Head of Industry 4.0	Traceability [B5] Under a vendor tooling agreement, the supplier couldn’t refuse to connect the machine – Commercial OEM, Head of Industry 4.0
	High dependence asymmetry Powerful buyers exert pressures	Traceability [A7] The blockchain is usually imposed by powerful and large customers, who reap the benefits – Supplier 1, ICT Director
	Low dependence asymmetry Large suppliers oppose resistance	Production planning [A2] We are facing resistance from larger suppliers producing for different OEMs – Premium OEM 1, Head of Industry 4.0 Large suppliers reject everything.… We lack the levers – Supplier 3, Head of Purchasing	Traceability [B5] Whenever suppliers share their technical capacity with multiple customers, they are not willing to share data. If customers are powerful––depending on the business share––they will be successful at getting the data – Supplier 2, Head of Production
		Logistics [A4] [A5] Larger service providers are reluctant. They have their own technology and data formats – Supplier 3, Head of Purchasing	Logistics [A5] Even regarding the traceability of trucks… only smaller freight forwarders accepted – Supplier 2, ICT Director
Protection mechanisms Clauses preventing leakages and opportunistic behavior	Presence of protection mechanisms Data protected by: – Legal clauses – Technology – Organizational setups (digital platforms as intermediaries)	Production planning [A1] [A2] [A3] Technology is a big enabler, especially cloud-based applications. Until a few years ago, it was not possible for external users to directly enter the data in our systems – Supplier 2, Head of Production If you enable people to share the data—not directly, let’s say through a third party platform—then we can optimize the SC – Supplier 3, Head of Purchasing By sharing data through a trusted third party like our platform, individual firms can keep the confidentiality of the data – Supplier 3, Head of Purchasing	Quality [B6] The project was initiated by our supplier, we signed an NDA [Not Disclosure Agreement] as regards to the use made of our data – Supplier 2, General Manager	Service access/provision [C1] [C3] [C4] [C5] [C6] The data contract between the final user and the OEM is very detailed – Importer, Marketing Manager Legal mechanisms in place regulate third-party data sharing – Commercial OEM, Head of Connected Vehicles Initially we made mistakes. We didn’t think that the data would be so important. Now, … we are very careful in the contracts – Commercial OEM, Head of Digital Transformation The only approach is to work as service provider. We would never be able to go to a competitor with their data – Premium OEM 1, Head of Connected Vehicles Data are shared through protected channels. In aggregation platforms, data are anonymized – Premium OEM 1, Head of Connected Vehicles
		New product development [A8] Thanks to solutions such as VDI, it is hard to “steal” data and know-how whenever you outsource engineering activities – Metal equipment, CIO The software allows us not only to have control over errors, but also to make sure that our data and methods can’t be downloaded – Plastic equipment, CIO	Maintenance [B8]/Process optimization [B9] We are allowed to use customer data to provide a service, but we can’t pool them together with those of other clients. This is most certainly a limitation, but we respect that – Metal equipment, General Manager
	Absence of protection mechanisms Protection mechanisms not in line with corporate policies	Production planning [A1] [A2] [A3] Large suppliers are sharing data because of company policy – Supplier 3, Head of Purchasing We have so many restrictions when using third-party software because of data and network security – Supplier 2, General Manager	Maintenance [B8]/Process optimization [B9] We can’t connect our internal system with an external network because of information security reasons, it is simply not allowed. This is also why the algorithms are generated in-house – Supplier 2, Head of Production
Benefit distribution mechanisms Upfront definition of benefit distribution	Presence of benefit distribution mechanisms Benefits captured within joint ventures		Maintenance [B8]/Process optimization [B9] To overcome reluctance, we are setting up joint ventures with manufacturers to ensure transparency on data handling and benefit distribution –Metal equipment, Head of Project Management Should we just ask for customer data, it would never work. We need to offer something different, basically not the product but service and performance – Metal equipment, CIO	Service access/provision [C1] [C5] [C6] Usually, our business customers share connected vehicle data. The important thing is that they get benefits from this, such as maintenance, route optimization, and a lower insurance premium – Commercial OEM, Head of Connected Vehicles Most OEMs have a stake in data aggregation platforms – Premium OEM 1, Head of Innovation
	Absence of benefit distribution mechanisms Benefits captured by the sharing firm/not accessible to competitors	Production planning [A1] Having visibility into our inventory, suppliers decide when and how to build stock. They become more efficient. We indirectly benefit from this – Commercial OEM, Head of Digital Transformation	Quality [B7] Data sharing allows our supplier to reduce scraps and increase the useful life of molds. The benefits for us are a better control of the porosity of our products – Supplier 2, ICT Director	Quality/New product development [C7] Sharing connected vehicle data with first-tier suppliers comes at a cost. But what is the benefit? They won’t develop new products just for us – Luxury sports OEM, Head of Connected Vehicles
		Logistics [A4] Information systems integration enables our supplier park to adapt in real-time to any change in the sequence. There is a double benefit for us, because the supplier is practically “ours”: we carry zero inventory both at our premises and at theirs – Mass market OEM, Production Manager	Maintenance [B8]/Process optimization [B9] We have to consider the benefits we can get. The machinery and equipment we use are rather standard. If the industrial technology provider implements innovations that are improving our efficiency, we have no issue sharing our data. When the technology is customized …, we do not want to share data and improvements with our competitors for free – Supplier 1, Head of R&D The data are shared with the machine provider. … The provider will know the algorithm, but we don’t have many competitors in our country – Supplier 2, ICT Director

		Illustrative quotes on data sharing practices
Factor		[A] Data sharing practices related to process connectivity	[B] Data sharing practices related to asset/equipment connectivity	[C] Data sharing practices related to product connectivity
Need for complementary resourcesAssets and capabilities to use the data are not at the sharing firm	High need for complementary resourcesFirms need to look externally for:– Product/process know-how– DT competences (including data management and analytics)– Datasets that complement the ones owned by the firm	Production planning [A3]You can’t solve SC issues at a local level, you need multi-tier data. That’s what our customers have understood – SC platform, Founder and CEO	Quality [B6]The supplier matches our product quality data with their internal process data. Through artificial intelligence, they find patterns – Supplier 2, ICT Director	Quality/New product development [C7]We have the simulation models for our components, not the OEMs. It is up to us to make sense of quality issues – Supplier 2, Head of R&D
		Logistics [A6]They [the logistic service provider] have developed tools for logistics optimization. We realized that the more they can access the data of different manufacturers, the more they can optimize the service – Supplier 1, Supply Chain Manager	Process optimization [B8]We access data as clients realize that they haven’t achieved anything – Metal equipment, General ManagerBig data analytics is something a single manufacturer is not able to do leveraging on internal data and expertise – Metal equipment, Head of Project ManagementWe looked for external capabilities on how to collect, analyze, and import data – Commercial OEM, Head of Industry 4.0We had partners for this project, one for data analytics, one for the 3 D scan and the digital twin. We shared the data with them – Premium OEM 2, Head of Industry 4.0	Service access/provision [C4]All the sensors and cameras that [OEM name] is using are ours. We know them and develop related algorithms – Supplier 2, Production Manager«Sensor-generated data from connected vehicles can be … managed by OEMs. Only smaller OEMs have the data on our servers, lacking resources – Supplier 2, ICT Director
			Maintenance [B9]At the beginning, we partnered up with different companies for proofs of concept. We didn’t have competence in hard data analytics and machine learning back then – Premium OEM 2, Head of Industry 4.0We wanted to detect compressed air leakages through microphones. We shared data through the cloud with specialized companies – Supplier 2, ICT Director	Service access/provision [C6]Some data need to be analyzed in large volume to detect patterns, beyond what is under the purview of a single OEM. That’s why we leverage data aggregation platforms – Premium OEM 2, Head of Innovation
	Low need for complementary resourcesFirms have internal:– Product/ process know-how– Dedicated staff and technologies– DT capabilities	Production planning [A3]Manufacturers are concerned of becoming dependent on an external provider for planning activities. They already have staff and technologies – SC platform, Founder and CEO	Quality [B6]We recently adopted brushless electric motors. As there were failures, we analyzed the data. The supplier was a small firm without a structured approach to problem solving – Supplier 2, Head of R&D	Product use [C1]There are cases where business customers, having developed their own infrastructure and capabilities, manage their data internally – Premium OEM 1, Head of Connected Vehicles
			Process optimization [B8]Advanced customers manage themselves machine data» – Plastic equipment, CIOWe know the production process. External providers would just look at the wrong variables – Supplier 2, Managing DirectorThe algorithms are continuously learning, it is an ongoing process. So, if you only rely on industrial technology providers … it is something that increases the cost. … No one has 20 years of experience with a proven solution – Supplier 2, Head of Production
			Maintenance [B9]We have maintenance capabilities, so we don’t see the added value of sharing data – Commercial OEM, Head of Industry 4.0We approach smart maintenance in-house for simpler machines and through external players for more complex ones – Premium OEM 1, Head of Production
Level of dependenceSum of dependence between the actors, higher likelihood of joint action	High level of dependenceFirms have:– A high share of common business– Personal relationships– Strongly entwined business processes	Production planning [A2]Whenever we have strong ties and a personal relationship with a supplier it is easier to get the necessary data. … We have visibility on suppliers involved in processes that start and get back at our plants – Supplier 3, Head of Purchasing«It is easier with mid-sized companies, where we have strong partnerships in place. We discuss this directly with the owners – Supplier 2, General Manager	Maintenance [B9]In an industry that does not carry inventory, it is important to ensure continuity in case of breakdowns. We need to get more data and in real time – Plastic equipment, CIO
		Logistics [A4] [A5]As we establish partnerships with few logistic service providers, we can have them adopting our systems for data exchange – Supplier 1, Head of LogisticsWe have integrated information systems intercompany and with the supplier park – Mass market OEM, Production Manager
		Traceability [A7]We didn’t experience any operational benefit with the blockchain besides strengthening our reputation and the partnership – Supplier 1, ICT Director
Dependence asymmetryDifference in actors’ dependence on each other	High dependence asymmetryPowerful buyers exert pressures	Logistics [A4] [A5]We have the power to impose on our providers to share the data and adopt our technologies – Commercial OEM, Head of Industry 4.0	Traceability [B5]Under a vendor tooling agreement, the supplier couldn’t refuse to connect the machine – Commercial OEM, Head of Industry 4.0
	High dependence asymmetryPowerful buyers exert pressures	Traceability [A7]The blockchain is usually imposed by powerful and large customers, who reap the benefits – Supplier 1, ICT Director
	Low dependence asymmetryLarge suppliers oppose resistance	Production planning [A2]We are facing resistance from larger suppliers producing for different OEMs – Premium OEM 1, Head of Industry 4.0Large suppliers reject everything.… We lack the levers – Supplier 3, Head of Purchasing	Traceability [B5]Whenever suppliers share their technical capacity with multiple customers, they are not willing to share data. If customers are powerful––depending on the business share––they will be successful at getting the data – Supplier 2, Head of Production
	Low dependence asymmetryLarge suppliers oppose resistance	Logistics [A4] [A5]Larger service providers are reluctant. They have their own technology and data formats – Supplier 3, Head of Purchasing	Logistics [A5]Even regarding the traceability of trucks… only smaller freight forwarders accepted – Supplier 2, ICT Director
Protection mechanismsClauses preventing leakages and opportunistic behavior	Presence of protection mechanismsData protected by:– Legal clauses– Technology– Organizational setups (digital platforms as intermediaries)	Production planning [A1] [A2] [A3]Technology is a big enabler, especially cloud-based applications. Until a few years ago, it was not possible for external users to directly enter the data in our systems – Supplier 2, Head of ProductionIf you enable people to share the data—not directly, let’s say through a third party platform—then we can optimize the SC – Supplier 3, Head of PurchasingBy sharing data through a trusted third party like our platform, individual firms can keep the confidentiality of the data – Supplier 3, Head of Purchasing	Quality [B6]The project was initiated by our supplier, we signed an NDA [Not Disclosure Agreement] as regards to the use made of our data – Supplier 2, General Manager	Service access/provision [C1] [C3] [C4] [C5] [C6]The data contract between the final user and the OEM is very detailed – Importer, Marketing ManagerLegal mechanisms in place regulate third-party data sharing – Commercial OEM, Head of Connected VehiclesInitially we made mistakes. We didn’t think that the data would be so important. Now, … we are very careful in the contracts – Commercial OEM, Head of Digital TransformationThe only approach is to work as service provider. We would never be able to go to a competitor with their data – Premium OEM 1, Head of Connected VehiclesData are shared through protected channels. In aggregation platforms, data are anonymized – Premium OEM 1, Head of Connected Vehicles
		New product development [A8]Thanks to solutions such as VDI, it is hard to “steal” data and know-how whenever you outsource engineering activities – Metal equipment, CIOThe software allows us not only to have control over errors, but also to make sure that our data and methods can’t be downloaded – Plastic equipment, CIO	Maintenance [B8]/Process optimization [B9]We are allowed to use customer data to provide a service, but we can’t pool them together with those of other clients. This is most certainly a limitation, but we respect that – Metal equipment, General Manager
	Absence of protection mechanismsProtection mechanisms not in line with corporate policies	Production planning [A1] [A2] [A3]Large suppliers are sharing data because of company policy – Supplier 3, Head of PurchasingWe have so many restrictions when using third-party software because of data and network security – Supplier 2, General Manager	Maintenance [B8]/Process optimization [B9]We can’t connect our internal system with an external network because of information security reasons, it is simply not allowed. This is also why the algorithms are generated in-house – Supplier 2, Head of Production
Benefit distribution mechanismsUpfront definition of benefit distribution	Presence of benefit distribution mechanismsBenefits captured within joint ventures		Maintenance [B8]/Process optimization [B9]To overcome reluctance, we are setting up joint ventures with manufacturers to ensure transparency on data handling and benefit distribution –Metal equipment, Head of Project ManagementShould we just ask for customer data, it would never work. We need to offer something different, basically not the product but service and performance – Metal equipment, CIO	Service access/provision [C1] [C5] [C6]Usually, our business customers share connected vehicle data. The important thing is that they get benefits from this, such as maintenance, route optimization, and a lower insurance premium – Commercial OEM, Head of Connected VehiclesMost OEMs have a stake in data aggregation platforms – Premium OEM 1, Head of Innovation
	Absence of benefit distribution mechanismsBenefits captured by the sharing firm/not accessible to competitors	Production planning [A1]Having visibility into our inventory, suppliers decide when and how to build stock. They become more efficient. We indirectly benefit from this – Commercial OEM, Head of Digital Transformation	Quality [B7]Data sharing allows our supplier to reduce scraps and increase the useful life of molds. The benefits for us are a better control of the porosity of our products – Supplier 2, ICT Director	Quality/New product development [C7]Sharing connected vehicle data with first-tier suppliers comes at a cost. But what is the benefit? They won’t develop new products just for us – Luxury sports OEM, Head of Connected Vehicles
		Logistics [A4]Information systems integration enables our supplier park to adapt in real-time to any change in the sequence. There is a double benefit for us, because the supplier is practically “ours”: we carry zero inventory both at our premises and at theirs – Mass market OEM, Production Manager	Maintenance [B8]/Process optimization [B9]We have to consider the benefits we can get. The machinery and equipment we use are rather standard. If the industrial technology provider implements innovations that are improving our efficiency, we have no issue sharing our data. When the technology is customized …, we do not want to share data and improvements with our competitors for free – Supplier 1, Head of R&DThe data are shared with the machine provider. … The provider will know the algorithm, but we don’t have many competitors in our country – Supplier 2, ICT Director

Source: Author’s own creation

[ViewLarge]