Erosion risks

• Large automation peers expand application engineering coverage
• Channel partners capture more of the service relationship
• Remote commissioning reduces need for on-site support

Leading indicators

• IAB services/solutions revenue mix
• Customer renewal/retention for service offerings
• Gross margin resilience vs automation peers

Counterarguments

• Global peers (e.g., Siemens/ABB/Schneider/Rockwell) offer comparable field service capability

Erosion risks

• Customers standardize on vendor-neutral OT data platforms
• Open standards improve portability of production data
• Cybersecurity incidents reduce willingness to connect systems

Leading indicators

• Number of connected sites/users for i-BELT/i-DMP
• Recurring software/services growth within IAB
• Customer churn or renewal rates for i-BELT

Counterarguments

• Manufacturers can build analytics layers in-house or adopt competing platforms from automation peers or hyperscalers

Erosion risks

• Quality/reliability issues or recalls damage reputation
• Feature parity from rivals plus retail price competition
• Regulatory limits on health-claim marketing

Leading indicators

• Unit volumes and ASP/mix for blood pressure monitors
• Repeat purchase and accessory attach rates
• Share of recommendations/ratings in key retail channels

Counterarguments

• Many home BP monitors are commoditized; promotion and channel placement can shift demand quickly

Erosion risks

• Competitors secure similar authorizations and narrow differentiation
• Higher compliance costs or regulatory changes slow launches
• Data privacy constraints reduce connected-feature value

Leading indicators

• New FDA/CE approvals and launch cadence
• Connected app adoption (active users) and engagement
• Premium product mix for clinically differentiated models

Counterarguments

• Regulatory authorization is necessary but not sufficient; rivals can catch up and compete on price/marketing

Erosion risks

• Competitive tenders prioritize lowest cost over incumbent continuity
• Policy pushes for open standards and vendor switching
• Large SI/electronics peers bundle broader systems and displace incumbents

Leading indicators

• Win rate on station system upgrades/replacements
• Installed base modernization cycle (ticket gates/monitoring)
• Service backlog and renewal rates

Counterarguments

• Operators can still switch vendors on major refresh cycles; incumbency does not guarantee renewal

Erosion risks

• Cyber incidents undermine trust in remote monitoring
• Operators insource monitoring/maintenance or use third parties
• Budget constraints reduce scope of maintenance/service contracts

Leading indicators

• Recurring service revenue share within SSB
• System uptime/SLA performance
• Expansion of remote monitoring deployments

Counterarguments

• Remote monitoring/maintenance can be standardized and competed by general-purpose IT/OT service providers

Erosion risks

• Low-cost competitors compress margins and narrow performance gaps
• Customer multi-sourcing reduces the impact of differentiation
• Potential structural changes (e.g., carve-out/spin) disrupt execution

Leading indicators

• DMB gross margin trend and mix shift to high-value products
• Design-win momentum in EV/renewables-related components
• Defect rates and on-time delivery performance

Counterarguments

• Many component categories are price-driven and increasingly commoditized; process know-how may not translate into sustained pricing power

Erosion risks

• Field failures or recalls damage supplier reputation
• Competitors match reliability while offering lower prices
• OEMs shift to standard parts to simplify procurement

Leading indicators

• Supplier scorecards and qualification outcomes at key OEMs
• Warranty/return (RMA) rates and defect metrics
• Customer concentration and retention

Counterarguments

• Even trusted suppliers face continuous price-down pressure in components; buyers may switch if cost/availability improves elsewhere

Erosion risks

• Privacy regulation limits data linkage/usage or raises compliance cost
• Data breaches reduce ability to collect/link sensitive datasets
• Competition from larger aggregators or public datasets narrows uniqueness

Leading indicators

• Linked-user count and linked dataset volume
• Model performance improvements and product releases
• Regulatory/legal developments on healthcare data usage

Counterarguments

• Network effects may be bounded by regulation and fragmentation; scale does not always translate into defensible advantage

Erosion risks

• Customers standardize on general-purpose BI/AI stacks and reduce vendor dependence
• Interoperability standards make switching easier
• Consultancies replicate process redesign without proprietary platforms

Leading indicators

• Net revenue retention and contract renewals
• Expansion of service touchpoints (e.g., BPO/field service domains)
• Customer adoption of linked-data products

Counterarguments

• Clients may resist lock-in for sensitive data and keep analytics in-house or with large, trusted incumbents