MSP Service Data & Automation Readiness Survey – Einar & Partners Research Unit

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How quickly can you launch and commercially activate a new managed service across your entire customer base?

Ad-hoc (Months): Each launch requires manual engineering, bespoke contracts, and client-by-client setup.
Catalogued (Weeks): Services are defined in a catalog, but deployment and billing are largely manual.
Automated (Days): Services can be provisioned quickly, but commercial activation (pricing, billing) lags.
Productized (Real-time): New services are instantly consumable with automated provisioning and billing.
Not equipped to reply

To what extent is integration with customer tools a competitive advantage in winning and retaining business?

To what extent is integration with customer tools a competitive differentiator in winning and retaining business?

No integrations available: Customers must adapt to our tools, platforms, portals and processes.
Reactive: Integrations are built only when demanded by large or strategic clients.
We provide standard connectors for all customers, which are developed and maintained internally, with little room for tailoring to the customer's needs
Plug and play interoperability for each customer and their needs has always been a core value proposition and a distinct competitive advantage
Not equipped to reply

How tightly are sold contracts, entitlements, and pricing linked to your technical service models?

Disconnected: Contracts are static documents; operations lack visibility into entitlements.
Manually Aligned: Entitlements are checked manually before provisioning services.
Modelled: Contracts and services are modelled, but enforcement is not automatic.
Enforced by Design: Technical services automatically reflect sold entitlements and pricing.
Not equipped to reply

How frictionless is it for an existing customer to adopt a new service or upgrade their current tier?

High Friction: Requires new SOWs, approvals, and manual provisioning by each technical team (network, virtualization etc.)
Moderate Friction: Requests are digital, but fulfilment and billing are manual.
Low Friction: Provisioning is automated; billing updates require manual intervention.
Seamless: Click-to-buy triggers instant provisioning and real-time billing updates.
Not equipped to reply

How clearly defined is the role of your core platform versus surrounding tools (RMM, PSA, ERP, Cloud)?

Undefined: Tool responsibilities overlap; ownership is unclear.
Siloed: Departments operate separate systems and “sources of truth.”
Converging: Consolidation is underway, but integration remains complex.
Blueprinted: A clear, intentional architecture links platforms to value streams.
Not equipped to reply

How confident are you that all delivered services are accurately billed?

Low Confidence: Billing relies on estimates and manual reconciliation.
Partial Visibility: Major assets are tracked, but leakage is likely.
Audited: Regular audits exist, but they are time- and labor-intensive.
Assured: Automated traceability ensures delivered services always match invoices.
Not equipped to reply

What primarily drives your IT operations and service management strategy today?

Stability: Keeping systems running and tickets under control.
Efficiency: Reducing manual effort and operational cost.
Optimization: Improving speed, quality, and consistency of delivery.
Value Creation: Using automation to shift talent toward advisory and growth work.
Not equipped to reply

How do you balance customer-specific requests with scalable standard services?

Deal-Driven Customization: Custom work is common, accepted, and creates long-term complexity.
Flexible Core: A standard base exists, ut exceptions can be made for strategic customers.
Governed Customization: Exceptions are controlled, priced, and deliberately designed.
Platform-Native Scaling: Standard blueprints enable scale without dilution.
Not equipped to reply

How well does your data model support both operational execution and business decision-making?

Fragmented: Finance, sales, and operations use different definitions and datasets.
Technical: A CMDB exists but is used mainly by technicians.
Infrastructure elements are mapped to technical/business services.
Unified: A common service data model (e.g., CSDM) connects consumption, cost, and delivery.
Not equipped to reply

How efficiently can you onboard a customer or acquired entity into your standard operating model?

How efficiently can you onboard a new customer or acquired entity into your standard operating model?

Isolated: Legacy tools and processes persist indefinitely.
Manual Migration: Transition projects are lengthy and resource-heavy.
Data-First: Data migrates quickly, but legacy processes linger.
Blueprint-Driven: Environments are rapidly mapped to a standard model.
Not applicable
Not equipped to reply

How much confidence do leaders have in reports on cost, risk, and profitability?

Low: Reports require spreadsheets and reconciliation across tools.
Operational: Trusted for incidents, not for financial or strategic decisions.
Broad but incomplete: Strong infrastructure insight, limited business linkage.
Strategic: The platform is a trusted system of record for decision-making.
Not equipped to reply

How effectively are commercial services linked to applications, tools, and infrastructure?

Disconnected: No automated relationships across layers.
Point-to-Point: Brittle integrations between individual tools.
Technically Mapped: Infrastructure and apps are linked, but not to sold services.
Unified Service Graph: Business services dynamically relate to all supporting layers.
Not equipped to reply

Who is accountable for the lifecycle of Configuration Item/Asset data?

Who is accountable for the accuracy and lifecycle of service and asset data?

No Clear Ownership: Data quality depends on individual technicians.
Platform Admins: Admins maintain data without full business context.
Process Owners: Partial ownership exists, with gaps between domains.
Service Owners: Clear accountability for data quality within defined service domains.
Not equipped to reply

How prepared is your service data foundation for advanced automation and AI?

Not Ready: Data is inconsistent, incomplete, or duplicated.
Foundation Phase: Active clean-up and standardization underway.
Automation-Ready: Structured enough for rule- and script-based automation.
AI-Native: Standardized, governed data enables AIOps and predictive insights.
Not equipped to reply

Are there any additional challenges or constraints that impact maturity of your data and services?

Thank You for Your Participation

We sincerely thank you for taking the time to complete this survey. Your insights and experiences are invaluable in helping us better understand the current state of MSPs and its future direction. We deeply appreciate your contribution.

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