Data Quality & Integrity. Process & Automation. Governance Framework.

Many organizations find that inconsistent and fragmented master data leads to operational inefficiencies, inaccurate reporting, and increased risks during system migrations.

VentureTech provides a comprehensive Master Data Review designed to identify critical data gaps, streamline processes through automation, and establish a robust governance framework for sustained excellence.

Typical Situations

  • Duplicated Records Multiple instances of the same customer, vendor, or product causing confusion, reporting errors and increasing costs.

  • Missing Key Information e.g. incomplete addresses, tax IDs, etc. hindering operations.

  • S/4HANA Migration Preparation Concerns about migrating poor-quality or "garbage" data into a new SAP environment.

  • Inconsistent Data Use Lack of standardized data entry practices and unauthorized custom tables creating silos.

  • Decision-Making Uncertainty Leadership lacks confidence in business reports due to inaccurate or outdated data.

What We Review

Data Quality & Integrity

  • Deduplication & Consolidation Identifying duplicate master data entities to establish a single source of truth.

  • Completeness & Enrichment Assessing mandatory attributes to ensure critical business data is not missing.

  • Migration Readiness Evaluating the accuracy of current records so you leave the "garbage" behind before moving to a new SAP environment.

Process & Automation

  • Workflow Optimization Pinpointing current data entry bottlenecks and manual workarounds.

  • Automated Cleansing Uncovering opportunities to deploy automated data validation and cleansing rules.

  • Integration Health Reviewing how master data flows across your current systems to spot synchronization issues and discrepancies.

Governance Framework

  • Ownership & Stewardship Defining clear data ownership roles to ensure long-term accountability.

  • Standardization & Simplification Assessing the necessity of custom tables and standardizing field usage across the business.

  • Target Architecture Evaluating your current setup against a best-practice Master Data Model and Hub architecture.

Deliverables

  • Executive Summary High-level findings and strategic impact for leadership.

  • Master Data Maturity Map Current vs. target state assessment.

  • Risk & Issue Log Prioritized list of data quality and process gaps.

  • Proposed MDM/MDG Solution Framework for a Master Data Hub and Integration Layer.

  • Implementation Roadmap 90-day phased plan including immediate quick wins.

Delivery Approach

  • Project Kick-off & Discovery Stakeholder identification and vision alignment

  • Current State Analysis Document reviews and process mapping .

  • Gap & Maturity Assessment Comparison against industry best practices.

  • Strategic Roadmap Finalizing recommendations and MDM/MDG solution design.

Duration: 4 weeks

Delivery Model: Remote-first, with optional on-site workshops.

Basic package

  • Master Data Quality & Governance Review

  • Process & Automation Assessment

  • Executive Summary & Strategic Roadmap

  • Prioritized Risk & Issue Log

  • Fully remote delivery

Contact us for inquiry about costs

Includes

  • 4 weeks timeline

  • up to 10 stakeholder interviews

  • Data Structure & Deduplication analysis

  • Data Entry Workflow & Process review

Optional Add-ons

  • On-site Executive Vision Workshop

  • On-site Data Workshop

  • Data Migration Readiness Assessment

  • "Quick Wins" Cleansing Pilot

  • Data Governance Framework Design

  • Data Quality Dashboard Setup