Q1. Could you briefly outline how your role has evolved, and what core responsibilities you take on when leading Oracle Cloud and IT transformation engagements across industries?

15 years of Oracle experience:

• Knowing the inside sales organisation and the field sales organisation
• Working with Presales / ACEs on large projects (multiple years)
• Selling On-Prem Licence -> DB + Options commercial sales position
• Working with GLAS – Oracle’s Software Advisory Team / LMS on closing license gaps
• Selling Exadata / Systems
• Selling Oracle Middleware – WebLogic Server
• Selling Oracle Cloud Infrastructure and Platform – OCI
• Selling Exadata Cloud at Customer – Hybrid Cloud Platforms
• Working at Enterprise Projects with Oracle Consulting – OCS & ACS (paid consultation)

Client Industries:

• Finance, Insurance
• Travel Transportation
• Retail
• Automotive, Manufacturing
• Public Sector

Client Size:

• Greenfield, New Logos
• Small and medium-sized clients
• Enterprise Clients
• Strategic Clients

As a sales director, I’ve negotiated the end-to-end client deals through partners or directly. My latest deal is a 180 million USD public sector Oracle Transformation program in the Netherlands, outlined from 2025 to 2030.

Q2. With so many enterprises shifting from on-premise ERP/IT to cloud ERP/SaaS, what do you see as the biggest non-technical challenges (culture, change management, processes) that companies underestimate?

Companies underestimate the change, the adoption of the new tech world and its effect on people’s daily lives. The fear of changing habits often leads to strong resistance. A positive culture with an openness to new technologies is essential for the adoption.

Q3. As cloud ERP systems increasingly embed AI/ML agents for automation, forecasting, and analytics — which business processes do you believe benefit most from AI first, and where should companies still be cautious?

Yes, Oracle is at the forefront of embedding AI functions into its ERP.

• Oracle Fusion Cloud (ERP) creates early wins where processes are transactional and where many repetitions are needed, such as in:
• Finance – invoice ingestion, routing, approval flows, recommendations, predictive cash flow forecasting.
• Sales - as an example, when it relates to Forecasting, ML agents could extract the salesforce information automatically without human generation of Excel files.
• Retail or supply chain planning - demand forecasting or stock optimisation in local stores could be use cases.
• Transportation - route optimization and lead time predictions are use cases
• Any HR department could use retention modelling based on AI, schedule optimisations (shift workers), compensation benchmarking, and skills detection of candidates (from resumes).

Cautious areas:

• Financial accuracy – legal exposure
• Segregation of duties in regulated industries, public sector
• HR – AI is bias-prone, maybe with discrimination risks and GDPR considerations in place
• Tax ruling changes regularly, and AI may be outdated
• Legal liability at negotiations (sales-driven AI)

Q4. For large enterprises with multiple subsidiaries or geographically distributed operations, how do you evaluate whether a ‘two-tier’ cloud-plus-core ERP architecture makes sense — versus a full consolidation under a single cloud or legacy stack?

Two Tier:

• In Germany, a global ERP system creates more friction than value, and subsidiaries often spend a lot of time working around global processes. Therefore, simple, localized, non-standard processes, the two-tier setup makes sense. Two-tier deployments are faster, so acquired sub-co’s can be better integrated.
• The core stays global, whereas in regulated markets, a subsidiary can innovate independently with a two-tier system.
• Full consolidation:
• When companies have a business model where there are the same products, supply chain, service model, financial process, and master data structures.
• In the public sector or highly regulated industries.
• When real-time global P&L is required, global supply view, inventory, and group-wide scenario planning.

Q5. In sectors like retail, manufacturing or public services — where compliance, regulatory audits, data governance and security matter — how do you design cloud/ERP migrations so that security and observability scale with agility and flexibility?

Before migrating, the High-Level Design (HLD) needs a security-by-design and observability-by-default architecture. Centralised audit and logging as well as threat monitoring, anomaly detection.

• Governance layer – roles – segregation of duties, risk control
• Monitor application performance with APM, logging analytics and end-to-end tracing
• Data governance structure – must be consistent
• Zero trust design
• Continuous compliance and security operations
• Retail:
• Sensitive PCI data → strict RBAC, data masking
• High volume API traffic → APM for POS/OMS/ERP integrations
• Fraud prevention → Risk Cloud SoD + continuous monitoring
• Manufacturing:
• Traceability for audits → strong logging, end to end tracking
• Shop floor integrations → APM tracing for IoT/PLC → OIC → Fusion
• Change control → strict configuration audit trails
• Public Services / Government:
• Citizen PII → encryption + RBAC + strong audit policies
• Compliance mandates (GDPR, national data residency) → Logging Analytics + access monitoring
• Procurement integrity → SoD, risk analytics, fraud detection

Q6. Given enterprise demand for agility and rapid ROI, what metrics or KPIs do you use to define and measure success for a cloud-transformation or ERP-migration project during and after implementation?

During migration:

• # of applications, # of databases, # of servers – document dependencies at pre-migration phase, assessments of risk and complexity
• Baseline costs – compare with cost reduction objectives post-migration
• Response times, availability, latencies, and patch duration as benchmarks
• Application migration success rate
• Cutover accuracy
• Velocity of sprints
• User readiness and training completion
• Data quality pass rate

After migration:

• Application response time
• Uptime, system availability
• Scale workloads – yes or no
• Metrics for how resources are utilised
• RTO / RPO as critical DR metrics
• Cost per resource
• Optimisation gains – cloud cost reductions – yes or no
• TCO probably explains the delta
• ROI
• Security incident rate
• SLA’s
• User satisfaction
• Time improvement of certain process flows (order to cash, month-end closure, procurement approval times)
• Time to deploy new features or integrate new apps
• Business continuity tracking

Q7. If you were advising leadership or investors on where to place strategic bets in enterprise IT over the next 5 years, which technologies, business processes, or industry verticals would you prioritise for cloud/ERP transformation to deliver durable value?

• Modular ERP architectures like Oracle Fusion become more strategic
• AI agents provide more automation
• Domain owned – data mesh architectures, fully scalable
• EUCS, Data Act, and Gaia X drive investments in sovereign, compliant cloud and data spaces (in EU)
• Smart manufacturing and smart cities
• Industries: manufacturing, healthcare/public sector, financial services, and retail/CPG