Kérdéssor – Novacon teszt

Step 1 of 11

Context

These contextual questions are not part of the 30 maturity questions and are not scored. They help us interpret your answers correctly.

Visibility: a single respondent may not have reliable visibility across all nine domains – select only the areas you can assess. On any individual question you can also choose “Insufficient visibility / Not able to assess”.
S/4HANA stage: the same maturity gap can carry very different urgency depending on the transformation stage.

Company / organization

C1What is your role / function?

C2What is your organization's current S/4HANA transformation stage?

Step 2 of 11

Strategic Alignment

Ensures S/4, AI and enterprise transformation are anchored in business strategy, executive ownership, measurable outcomes and clear governance.

What to look for: Look for one coherent roadmap, executive sponsorship, decision rights, outcome KPIs and portfolio-level steering.

Recommended respondents: CEO, CFO, CIO, Transformation Lead

Enterprise Transformation – Coordinated business, process, data, technology and organizational change across multiple functions or business units.

Q1 · Transformation & AI StrategyIs there a single enterprise transformation strategy that aligns S/4, AI and business priorities with measurable outcomes?

Definitions

AI (Artificial Intelligence) – In this assessment, AI means systems that perform tasks requiring inference, generation, prediction, recommendation or autonomous/assisted decision-making. It does not mean generic RPA, OCR or rule-based automation by itself.
Enterprise Transformation – Coordinated business, process, data, technology and organizational change across multiple functions or business units.
S/4 / SAP S/4HANA – SAP’s current ERP platform and the associated business/process transformation program, not only the technical software upgrade.

No coherent S/4, AI or enterprise transformation strategy exists.Separate SAP, AI or business initiatives exist, but they are not aligned and measurable outcomes are unclear.A common roadmap exists for major initiatives, with defined objectives and KPIs for selected domains.S/4, AI and business priorities are aligned in one enterprise roadmap with measurable operational and financial outcomes, and the portfolio is continuously reprioritized using realized value, strategic priorities and outcome evidence.Insufficient visibility / Not able to assess

Q2 · Executive SponsorshipIs there active and visible executive sponsorship for S/4, AI and enterprise transformation initiatives?

Definitions

Enterprise Transformation – Coordinated business, process, data, technology and organizational change across multiple functions or business units.

No active executive sponsor is identified.Individual leaders support selected initiatives, but sponsorship is inconsistent.Executive sponsors are assigned to major transformation programs and remove key barriers when needed.A cross-functional executive group actively steers portfolio priorities, funding, risks and decisions, with regular governance that continuously reinforces accountability and value realization.Insufficient visibility / Not able to assess

Q3 · KPI & Outcome GovernanceAre transformation success KPIs defined and linked to operational, process and financial outcomes?

Definitions

KPI – A Key Performance Indicator with an agreed definition, calculation logic, owner, source and review cadence.
Value Realization – Measurement of whether expected operational, financial, customer or risk benefits from an initiative are actually achieved and sustained.

Success measures are undefined, fragmented or conflicting.Some initiative-level KPIs exist, but they are not consistently linked to business outcomes.Core transformation KPIs are defined for major S/4, AI and process initiatives.Operational, process and financial KPIs are consistently linked to transformation objectives, reviewed in governance forums and continuously refined using realized business value to steer portfolio decisions.Insufficient visibility / Not able to assess

Q4 · Transformation GovernanceIs there a formal governance model for S/4, AI and enterprise transformation, with clear decision rights and escalation paths?

Definitions

Transformation Governance – Formal decision rights, ownership, forums, escalation paths, portfolio prioritization, risk management and performance/value review for transformation initiatives.

No formal transformation governance exists.Governance exists for isolated initiatives, with unclear ownership or escalation.Formal governance, decision rights and escalation paths exist for major programs.Enterprise-wide governance coordinates portfolio priorities, dependencies, risks, funding and ownership, with evidence-based decisions and continuous adjustments reflecting business value, changing priorities and risks.Insufficient visibility / Not able to assess

Q5 · E2E Process OwnershipAre Global Process Owners or equivalent end-to-end process owners formally assigned for critical S/4-related processes?

Definitions

End-to-End (E2E) Process – A business process viewed from its triggering event to the final customer/business outcome across functions and systems.
Global Process Owner (GPO) / E2E Process Owner – A role accountable for an end-to-end process across functions/sites, including standards, KPIs, controls and improvement.

No formal end-to-end process ownership exists.Ownership is local or functional and responsibilities overlap.Formal owners exist for major end-to-end processes, but authority varies.End-to-end process owners have clear decision rights for standards, KPIs, controls and improvement across sites and functions, and use enterprise-wide data and governance to continuously steer performance and standardization.Insufficient visibility / Not able to assess

Q6 · Process StandardizationAre critical S/4-related business processes standardized across sites and functions, with controlled localizations or deviations?

Definitions

Process Standardization – Use of common process designs, roles, controls and system behaviors across the enterprise, with explicitly governed localizations/deviations.

Processes differ significantly by site/function and standards are not defined.Common process concepts exist, but local variations dominate.Core processes are standardized, with documented exceptions for major areas.Enterprise process standards and local deviations are governed through clear approval rules, with continuous control of standards and approved deviations using process performance and compliance evidence.Insufficient visibility / Not able to assess

Q7 · Workflow Governance & AuditabilityAre key approvals and workflows executed in governed workflow tools rather than email/Excel, with end-to-end auditability?

Definitions

Workflow – A digitally managed sequence of tasks, decisions, approvals and handoffs with defined roles, rules, status and traceability.
Auditability – Ability to reconstruct who/what executed a transaction or workflow step, when it happened, what decision/rule was applied and what changed.

Key approvals and handoffs are mainly managed manually through email, spreadsheets or offline communication.Some digital workflows exist, but coverage, controls and traceability are inconsistent.Major workflows are executed in dedicated tools with defined roles, approvals and basic audit trails.Critical workflows are standardized, role-controlled, integrated and auditable end-to-end across systems, with audit evidence continuously used to monitor and improve performance, controls, exception handling and human interventions.Insufficient visibility / Not able to assess

Q8 · Continuous Improvement / OpExIs there a formal Continuous Improvement / Operational Excellence framework for systematically improving end-to-end processes?

Definitions

Continuous Improvement / Operational Excellence – A structured management system for identifying, prioritizing, executing and sustaining process/performance improvements using common methods and benefit tracking.

No formal Continuous Improvement / Operational Excellence framework exists.Local improvement activities occur, mostly reactively and without a common method.A common improvement method and governance exist for major functions or value streams.Enterprise-wide Continuous Improvement / Operational Excellence has clear ownership, prioritization and benefit tracking, embedded in regular management routines with a sustained improvement pipeline driven by process performance and business value.Insufficient visibility / Not able to assess

Step 4 of 11

SAP Modernization

Assesses whether the S/4 transformation is governed toward simplification, Clean Core and sustainable rollout/template adoption.

What to look for: Look for a robust roadmap/business case, Clean Core controls, simplification before customization and evidence-based rollout governance.

Recommended respondents: CIO, SAP Program Lead, Enterprise Architect

S/4 / SAP S/4HANA – SAP’s current ERP platform and the associated business/process transformation program, not only the technical software upgrade.

Q9 · S/4 Roadmap & Business CaseIs there a defined S/4 transformation roadmap and business case with scope, milestones, value drivers and ownership?

Definitions

S/4 / SAP S/4HANA – SAP’s current ERP platform and the associated business/process transformation program, not only the technical software upgrade.
Value Realization – Measurement of whether expected operational, financial, customer or risk benefits from an initiative are actually achieved and sustained.

No agreed S/4 roadmap or business case exists.Initial scope or business-case discussions exist, but ownership and milestones are unclear.A formal S/4 roadmap and business case exist for major scope areas, with defined milestones and owners.The S/4 roadmap is actively governed against scope, milestones, dependencies, risks and value targets, with roadmap and investment decisions continuously adjusted using realized value, delivery evidence and changing business priorities.Insufficient visibility / Not able to assess

Q10 · Clean CoreAre SAP Clean Core principles formally defined, governed and applied to extensions, integrations and custom developments?

Definitions

Clean Core – SAP principle of keeping the ERP core as standard as practical and managing extensions/integrations through governed, upgrade-safe approaches.

Clean Core principles are not understood or applied.Clean Core is discussed, but decisions remain case-by-case and governance is weak.Clean Core rules exist for major initiatives, with basic review of extensions and custom development.Architecture and change governance consistently favor appropriate standard, side-by-side or API-based solutions over customization, while continuous landscape-wide Clean Core monitoring drives active reduction of technical debt and exceptions.Insufficient visibility / Not able to assess

Q11 · Process SimplificationIs business-process simplification prioritized before custom SAP development or technical customization?

Existing complexity is largely replicated in the target solution.Simplification is discussed, but custom development is often chosen before process redesign.Major processes are challenged for simplification before custom development is approved.Formal governance requires process simplification, standard-fit and value assessment before customization, with continuous review of simplification outcomes and customization demand to reduce complexity and technical debt.Insufficient visibility / Not able to assess

Q12 · S/4 Rollout & Template GovernanceIs S/4 rollout progress and template/process adoption monitored against defined scope, milestones and KPIs?

Definitions

Template Adoption – The degree to which deployments/sites adopt the agreed target process/system template, including approved local deviations.

Rollout scope, milestones and template expectations are unclear or not monitored.Project progress is tracked, but process/template adoption and rollout readiness are measured inconsistently.Defined milestones, rollout scope and major template/process adoption indicators are monitored for key deployments.Governance regularly reviews rollout progress, deviations, adoption, risks and readiness across plants, entities and processes, using consistent evidence to proactively correct deviations and improve subsequent deployments.Insufficient visibility / Not able to assess

Q13 · Master Data Ownership & StewardshipAre ownership and stewardship roles clearly assigned for critical master-data domains?

Definitions

Master Data – Relatively stable business entities used across transactions and processes, such as customer, supplier, material/product, asset or employee data.
Data Owner – Business role accountable for policy, quality expectations, access and decisions for a data domain.
Data Steward – Role responsible for day-to-day data standards, quality monitoring, issue coordination and governance execution for a data domain.

Critical master-data domains have no clear business owner or steward.Ownership exists informally or only for selected systems/domains.Formal owners and stewards are assigned for major master-data domains, with basic responsibilities defined.Master-data ownership, stewardship, decision rights, standards and issue resolution are consistently governed enterprise-wide, with owners and stewards using measured performance to continuously improve quality, standards and lifecycle controls.Insufficient visibility / Not able to assess

Q14 · Data Quality & TrustAre critical data domains managed through defined data-quality KPIs, and are the results trusted by business users for operational and reporting decisions?

Definitions

Data Quality KPI – A measurable indicator of data quality, such as completeness, validity, uniqueness, consistency, timeliness or accuracy.

Data-quality expectations and KPIs are not defined, and business trust is low.Some quality checks exist, but metrics are inconsistent and users frequently reconcile or correct data manually.Defined data-quality KPIs are monitored for major domains and trust is adequate for most key use cases.Enterprise-wide quality rules, ownership, monitoring and issue resolution deliver trusted operational and reporting data, with proactive trend and root-cause management sustaining quality and consistent reuse across business use cases.Insufficient visibility / Not able to assess

Q15 · Migration ReadinessHas S/4 migration data been profiled, cleansed, validated and governed with clear readiness criteria?

Definitions

Migration Data Profiling – Systematic analysis of source data before migration to understand quality, completeness, patterns, duplicates, invalid values and transformation needs.

Migration data has not been systematically profiled and major quality risks are unknown.Initial profiling or cleansing has started, but scope, ownership and readiness criteria are incomplete.Critical migration datasets are profiled, cleansing actions are planned and readiness criteria are defined.Profiling, cleansing, validation, ownership and cutover readiness are consistently governed for all critical migration objects, with repeatable rehearsals, measurable quality thresholds and controlled issue closure providing readiness evidence before cutover.Insufficient visibility / Not able to assess

Q16 · Automation Coverage & GovernanceAre repetitive business and SAP activities automated through governed tools, standards and ownership?

Definitions

Automation Governance – Common standards for selecting, designing, securing, deploying, owning, monitoring and retiring automations across platforms.

Automation is minimal, ad hoc or dependent on individual workarounds.Isolated automations exist, but tool choice, ownership and controls are inconsistent.Major repetitive activities have governed automations with defined owners and standards.Automation is governed across platforms through common design, security, lifecycle and value-management standards, with the portfolio continuously optimized and rationalized using performance, risk and business-value evidence.Insufficient visibility / Not able to assess

Q17 · Cross-functional Workflow IntegrationAre cross-functional workflows implemented and integrated across SAP and non-SAP systems?

Definitions

Workflow – A digitally managed sequence of tasks, decisions, approvals and handoffs with defined roles, rules, status and traceability.

Cross-functional workflows are mostly manual, fragmented or system-specific.Some digital workflows exist, but handoffs across functions/systems still rely on manual intervention.Key cross-functional workflows are digitalised across major SAP and non-SAP systems.Enterprise integration standards, governed APIs/events and clear ownership support reliable end-to-end workflows across SAP and non-SAP systems, with reusable integration patterns and continuous improvement guided by performance, exception and integration data.Insufficient visibility / Not able to assess

Q18 · Monitoring, Exceptions & AuditabilityAre workflows and automations monitored for performance and exceptions, with clear escalation and complete audit trails?

Definitions

Exception – A transaction, case or process instance that does not follow the expected path, rule, threshold or outcome and requires attention.
Auditability – Ability to reconstruct who/what executed a transaction or workflow step, when it happened, what decision/rule was applied and what changed.

Failures and exceptions are discovered mainly through user complaints; audit evidence is incomplete.Basic monitoring exists for selected workflows and automations, but exception handling and auditability are inconsistent.Major workflows and automations have defined monitoring, exception routing, escalation and audit trails.Enterprise-wide monitoring makes automation performance, failures, controls and exceptions transparent across platforms, and proactively uses monitoring data to prevent recurring failures, optimize controls and improve performance.Insufficient visibility / Not able to assess

Q19 · KPI Governance & Performance ManagementAre operational and financial KPIs consistently defined, trusted and used in regular performance reviews and decisions?

Definitions

KPI – A Key Performance Indicator with an agreed definition, calculation logic, owner, source and review cadence.

KPIs are fragmented or untrusted; performance reviews are largely subjective.Some common KPIs exist, but definitions and review practices vary.Key operations use defined, trusted KPIs with regular performance reviews.Enterprise KPI governance aligns definitions, targets and ownership, with trends and leading indicators driving proactive action.Insufficient visibility / Not able to assess

Q20 · E2E Process Transparency & Process MiningIs end-to-end process performance visible and analyzed using process data and, where appropriate, process mining to identify bottlenecks and root causes?

Definitions

End-to-End (E2E) Process – A business process viewed from its triggering event to the final customer/business outcome across functions and systems.
Process Mining – Use of system event logs to reconstruct and analyze how processes actually run, including variants, bottlenecks, rework and conformance.
Root Cause Analysis – Structured identification of the underlying causes of performance problems or recurring exceptions, rather than only treating symptoms.

End-to-end process performance is largely invisible and analysis is mainly anecdotal or manual.Some process metrics or manual analyses exist, but visibility is fragmented and root causes are hard to confirm.Key end-to-end processes have consistent performance views and structured root-cause analysis; process mining is used selectively where useful.Enterprise process visibility combines KPIs, event data and process mining for systematic bottleneck and root-cause analysis, with insights routinely used to prioritize and verify improvements and trends monitored to confirm sustained results.Insufficient visibility / Not able to assess

Q21 · Predictive Reporting & Risk ManagementHow systematically is reporting used to forecast outcomes, identify emerging risks and enable proactive action?

Definitions

Leading Indicator – A measure intended to signal a likely future outcome before the final result is visible.
Early-Warning Indicator – A threshold, trend or risk signal designed to identify emerging issues before material impact occurs.

Reporting is mainly retrospective; issues are managed reactively.Basic trends and risks are visible, but forecasting is limited.Key processes use trends and risk indicators to anticipate issues.Enterprise reporting systematically uses forecasts and early-warning indicators to support proactive decisions.Insufficient visibility / Not able to assess

Step 8 of 11

AI Readiness

Assesses whether AI use cases are value-led, governed and operationally adopted with appropriate risk and human oversight.

What to look for: Look for disciplined portfolio prioritization, AI governance/HITL, adoption and model/output monitoring.

Recommended respondents: CIO / CDO, AI Lead, Business Transformation

AI (Artificial Intelligence) – In this assessment, AI means systems that perform tasks requiring inference, generation, prediction, recommendation or autonomous/assisted decision-making. It does not mean generic RPA, OCR or rule-based automation by itself.

Q22 · AI Use-case Prioritization & ValueAre AI use cases prioritized based on measurable business value, process impact and feasibility, with benefits tracked after implementation?

Definitions

AI Use Case – A defined business problem/opportunity where AI is applied to create measurable value, with an owner, users, data, risk profile and expected outcome.
Value Realization – Measurement of whether expected operational, financial, customer or risk benefits from an initiative are actually achieved and sustained.

AI ideas are pursued ad hoc, without clear business value or prioritization criteria.Some use cases have business sponsors, but prioritization and benefit measures are inconsistent.Major AI use cases are prioritized using agreed value, feasibility and process-impact criteria, with expected benefits defined.The enterprise AI portfolio uses consistent governance for prioritization, funding and value realization, with continuous reprioritization based on realized value, adoption, risk and strategic impact.Insufficient visibility / Not able to assess

Q23 · AI Governance, Risk & HITLAre AI solutions governed through formal policies, risk controls, security/access controls and Human-in-the-Loop requirements where appropriate?

Definitions

AI Governance – Policies, decision rights, accountability, risk/compliance controls, security, monitoring and lifecycle management for AI solutions.
Human-in-the-Loop (HITL) – A control design in which a human reviews, approves, overrides or intervenes at defined points in an AI-supported or automated process.

No formal AI governance, risk, security or human-oversight requirements exist.Basic policies or manual reviews exist for selected AI initiatives, but application is inconsistent.Major AI use cases have defined governance, risk assessment, access controls and human-oversight requirements.Enterprise AI governance consistently covers policy, compliance, security, risk, accountability and HITL controls throughout the AI lifecycle, with controls regularly tested and adjusted using incidents, model performance, regulatory changes and business risk.Insufficient visibility / Not able to assess

Q24 · AI Adoption & MonitoringAre AI-supported workflows actively adopted by users, with model/output quality, performance and risk continuously monitored?

Definitions

AI Monitoring – Ongoing monitoring of AI usage, output quality, performance, risk, incidents and relevant technical/model indicators.

AI usage is minimal or resisted, and model/output monitoring is absent.Pilot adoption exists, but user enablement and monitoring are mostly manual or inconsistent.Selected AI-supported workflows have structured user enablement and defined monitoring for quality, performance and risk.AI adoption and monitoring are governed enterprise-wide through clear ownership, usage metrics, quality and risk thresholds and escalation, with adoption and monitoring evidence continuously improving models, workflows, controls and user experience.Insufficient visibility / Not able to assess

Q25 · Change ManagementIs structured change management embedded in S/4, AI and enterprise transformation programs?

Definitions

Change Management – Structured management of stakeholder impacts, communication, leadership alignment, training, resistance, adoption and reinforcement during transformation.

Change impacts, stakeholder needs and resistance are not systematically managed.Communication or training activities occur, but change management is reactive and inconsistent.Major programs use a structured change approach covering stakeholders, impacts, communication, training and adoption.Organizational change capability embedded and governed across the transformation portfolio through adoption measures, leadership actions and resistance managementInsufficient visibility / Not able to assess

Q26 · Leadership & IT-Business AlignmentDo executives, business and IT jointly own transformation priorities, decisions and outcomes?

Transformation priorities are conflicting and business/IT ownership is strongly siloed.Collaboration occurs on selected initiatives, but decision rights and shared accountability are inconsistent.Business, IT and executive sponsors jointly own major transformation decisions and outcomes.Enterprise governance aligns business and technology priorities, funding, architecture and value accountability, with shared ownership embedded in management routines and cross-functional decisions driven by outcomes rather than organizational boundaries.Insufficient visibility / Not able to assess

Q27 · Skills, Training & AdoptionAre employees systematically trained and prepared to use new SAP, data, workflow and AI capabilities in their daily work?

Major capability gaps exist and training/adoption support is largely absent.Training is tool- or project-specific, with limited role-based preparation and adoption support.Structured role-based training and enablement exist for major capabilities and impacted user groups.Enterprise capability development covers role skills, practice, support, adoption measures and manager reinforcement, with continuous learning embedded in daily work and skill and adoption data guiding development to sustain new ways of working.Insufficient visibility / Not able to assess

Q28 · Performance Management & Problem SolvingAre performance gaps systematically translated into root-cause analysis, actions and follow-up?

Definitions

Root Cause Analysis – Structured identification of the underlying causes of performance problems or recurring exceptions, rather than only treating symptoms.

Problems are mainly handled through reactive firefighting.Local problem-solving routines exist, but follow-up is inconsistent.Key operations use structured root-cause analysis and action tracking.Structured management routines systematically connect performance gaps, root causes, actions, escalation and continuous learning.Insufficient visibility / Not able to assess

Q29 · Optimization & Value RealizationAre operational improvement opportunities systematically identified, prioritized and tracked through realized value?

Definitions

Value Realization – Measurement of whether expected operational, financial, customer or risk benefits from an initiative are actually achieved and sustained.

Optimization is mainly reactive to errors, incidents or urgent cost pressure.Improvement opportunities are identified locally, but prioritization and benefit tracking are inconsistent.A structured pipeline exists for major improvement opportunities, with owners, priorities and expected benefits.Enterprise governance prioritizes improvements by performance gaps, strategic value, effort and risk and tracks realized benefits, continuously reprioritizing the portfolio using realized value, capacity, operational performance and emerging opportunities.Insufficient visibility / Not able to assess

Q30 · Operational Discipline & AgilityAre standardized processes consistently followed while allowing governed, rapid adaptation to changing business needs?

Definitions

Operational Discipline – Consistent execution of agreed standards, controls and management routines in daily operations.
Enterprise Agility – Ability to change processes, rules and operating models quickly in response to business needs while preserving governance, control and E2E consistency.

Processes are not standardised or standards are frequently bypassed; changes in the standards are slow or disruptive.Standards exist, but adherence varies and changes rely on local workarounds or lengthy escalation.Core standards are followed and a defined change process can adapt key operations when needed.Operational discipline and controlled change governance ensure consistent execution and timely approved adaptations, with performance evidence enabling rapid changes to standards and processes while maintaining control, compliance and end-to-end consistency.Insufficient visibility / Not able to assess

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Context

Strategic Alignment

Process Maturity

SAP Modernization

Data Maturity

Automation Maturity

Reporting & Transparency

AI Readiness

Organizational Readiness

Operational Excellence

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