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Academy module

Chemical & Process Industries

Batch genealogy and quality trace flow for chemical and process industries: from raw material batch through process order, output batch, quality inspection and shipment, materialised nightly in Datasphere for a sub-10-second recall trace. — architecture diagram for Chemical & Process Industries, Analytics Legends Academy module M103

As of 2026-08-16

Edited by , sole editor and publication director — 27 years in the SAP ecosystem. How these pages are produced, and where automation is used.

Chemical and process industry analytics on SAP turns on one decision: build a materialised batch-genealogy layer in Datasphere or BW/4HANA, because live joins across MCHA, MSEG, QALS and LIKP take 20-40 minutes -- unusable when a product-recall decision is time-critical -- while a pre-computed table answers the same trace in under 10 seconds. The consultant who can span all five source modules (PP-PI, QM, EHS, LO-BM, and the semantic layer) and ship a compliant genealogy-to-yield-to-REACH reporting chain is rare enough to set the rate ceiling in industrial analytics, because most practitioners know only one or two of the five domains. The stake for a GMP or REACH client is regulatory, not cosmetic: a batch-release report that cannot trace to a signed inspection result under 21 CFR Part 11 fails the audit, and a substance-volume report that ignores the EHS specification link gets rejected by the regulator. Leave this module with the genealogy data model, the yield decision framework, and the language to defend both in front of a quality director.

What you will learn

  • Understand the core concepts behind chemical & process industries
  • Apply Chemical in a typical SAP analytics engagement
  • Recognize the 3-5 common mistakes and how to avoid them
  • Position this skill in your personal brand and rate conversation

Module overview

Chemical and process industry analytics on SAP is defined by one distinctive constraint: the product is a substance, not a discrete part, and its properties — purity, yield, viscosity, batch genealogy — are the primary analytics objects. A chemical plant does not produce 10,000 widgets; it produces 10,000 tonnes of a compound where each batch has a measured quality profile that must be traceable from raw material receipt to customer shipment, for both quality-management and regulatory reasons (REACH, GMP, FDA 21 CFR Part 11 in pharmaceutical chemical manufacturing).

Prerequisites

  • Intermediate hands-on experience on SAP analytics projects
  • Review core concepts first: C087, C083, C046

Outcomes

  • Understand the core concepts behind chemical & process industries
  • Apply Chemical in a typical SAP analytics engagement
  • Explain the core architecture and decision points for Chemical & Process Industries
  • Apply a repeatable implementation pattern in a 15-minute lab format

Full module available to members. The full module adds: the decision framework · the end-to-end scenario walkthrough · the KPI scorecard · the anti-patterns · the code blocks · the knowledge check · the diagrams.

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