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AQPTech · BUSINESS PROCESS INTELLIGENCE

Data-driven business process transformation.

Connect processes, data and applications to understand bottlenecks, choose improvements and validate operational value.

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OVERVIEW

Your transformation starts with understanding the process.

Effective processes connect data, applications and people. Work with AQPTech to clarify today’s workflows, identify bottlenecks and select improvements that can be validated.

For existing ERP/SAP environments or enterprise applications, start by reviewing data sources, supported connections and operational ownership. The result is a pilot scope tied to a specific objective.

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SERVICES

End-to-end transformation, focused on operational value.

From discovery to integration and handover, agree the objective, inputs and evaluation method for each workstream.

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ARTICLES & TEMPLATES

Frequently asked questions about business process transformation

What is Business Process Intelligence (BPI)?

Here, BPI means combining process knowledge and data to analyse current workflows, select improvements and track outcomes. Process mining is one technique that can be used when suitable event data is available.

How can we start without event logs?

Start with user interviews, process maps and a review of systems recording transactions. Then identify missing data; a manual assessment should not be presented as process-mining results.

Can this connect with an existing SAP or ERP system?

Review the product/version, supported APIs or data exchange methods, permissions and a test environment. Confirm integration scope with the system owner after discovery; tooling and licences are considered separately.

Does transformation require replacing every system?

A complete replacement is not assumed. Select a workflow with a clear bottleneck, retain suitable components and add the necessary interface or integration, with checks and a migration plan.

How are the business case and priorities developed?

Agree metrics, baseline evidence, expected impact and costs/dependencies to investigate. Record assumptions and test them in the pilot; do not use unmeasured savings or ROI claims.

What scope should an initial pilot have?

Choose one workflow, one user group and a dataset that can be reconciled. Define outputs, failure handling and completion criteria before committing to timing, resources or expansion.

How are change adoption and user guidance addressed?

Ask users to test the new workflow, record unclear steps and update task-oriented guidance. Agree handover ownership, support and feedback collection for operational use.

Where can AI assist the workflow?

Consider document classification, retrieval assistance or handling suggestions within authorised data. Establish evaluation, tool limits and accountable human confirmation for consequential actions.

How are data access and permissions prepared?

Identify source owners, necessary fields, access permissions and retention. An initial phase may use test data or appropriately prepared data agreed with the responsible organisation.

What can a discovery discussion produce?

Proposed outputs include a process map, source/integration inventory, prioritised opportunities, pilot scope and validation criteria. Actual work is agreed around the company’s systems and needs.

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