---
id: "prereq-data-standardization"
type: "prerequisite"
source_timestamps: ["§ 1. Create and maintain high-quality data."]
tags: ["data-engineering", "erp-systems"]
related: ["concept-single-instance-data"]
reason: "Creating a 'single instance data' bridge requires deep expertise in data engineering, ETL pipelines, and cross-departmental change management."
sources: ["tail1"]
sourceVaultSlug: "hbr-seg-tail1"
originDay: 1
articleStem: "hbr-tail-107-lenovo-ai-supply-chain"
sourceUrl: "https://hbr.org/2026/05/how-lenovo-built-an-ai-powered-supply-chain"
sourceTitle: "How Lenovo Built an AI-Powered Supply Chain"
---
# Enterprise Data Standardization

**Prerequisite:** Enterprise Data Standardization.

The text assumes the reader understands the immense technical and organizational complexity involved in taking siloed data from discrete ERP, CRM, and SCM systems and transforming it into 'common data standards and architecture' — i.e., building [[concept-single-instance-data]].

**Why it's required:** Creating a 'single instance data' bridge requires deep expertise in data engineering, ETL pipelines, and cross-departmental change management. Without this competence, [[action-fix-data-infrastructure]] and the whole of [[concept-digital-transformation-1-0]] are not achievable.