Standardizing Multi-Plant Manufacturing KPIs on a Single Governed Analytics Layer

Standardizing Multi-Plant Manufacturing KPIs on a Single Governed Analytics Layer

Artha Solutions supported an enterprise client in Manufacturing on an engagement focused on Standardizing Multi-Plant Manufacturing KPIs on a Single Governed Analytics Layer. The work used Qlik Cloud Analytics and Talend and highlights documented outcomes, including 15-20 hrs analyst hours recovered per monthly review cycle, per plant, by eliminating manual reconciliation.

KEY HIGHLIGHTS
  • Industry Manufacturing
  • Focus Area Manufacturing Analytics & KPI Governance
  • Client A Multi-Facility Discrete Manufacturer
  • Region Global
  • Technologies
    Qlik Cloud Analytics Talend Qlik Open Lakehouse SAP S/4HANA Oracle ERP Epicor Infor Plex FactoryTalk Siemens Opcenter

Key Results & Business Impact

15-20 hrs
Analyst hours recovered per monthly review cycle, per plant, by eliminating manual reconciliation.
2-3x
Faster decision cycles on operations investments once KPI definitions are standardized.
0 min
"Whose numbers are right?" debate at the start of every monthly business review, down from 20 minutes.
1
Governed KPI catalog, owned by the analytics team, applied consistently across all plant dashboards.

Executive Summary

A multi-facility discrete manufacturer partnered with Artha Solutions to bring one governed set of manufacturing KPIs to every plant after site-specific MES implementations left OEE, yield and scrap defined differently everywhere. A single KPI catalog in the Qlik Cloud Analytics semantic layer now drives every plant dashboard, so monthly reviews start with analysis, not reconciliation.

Client Profile & Context

A Multi-Facility Discrete Manufacturer operates in Manufacturing, with a Global footprint, and a focus on Manufacturing Analytics & KPI Governance. The case study references Qlik Cloud Analytics, Talend, Qlik Open Lakehouse, SAP S/4HANA.

Problem Statement with Critical Operational Vulnerability

A multi-facility discrete manufacturer had implemented a different MES at every plant, so OEE, yield and scrap were calculated differently at each site, plant performance could not be compared like for like, and executive dashboards were trusted by no one.

Critical Operational Vulnerability

Every monthly business review opened with 20 minutes of debate over whose numbers were right, analysts spent 15-20 hours per cycle per plant stitching MES and ERP extracts together in spreadsheets, and an earlier IT-led attempt to make the data match had failed.

Solution Implemented

Artha Solutions built a centralized semantic layer in Qlik Cloud Analytics with one governed definition of OEE, yield, scrap and related KPIs, applied to every plant dashboard and traceable to the same source. Talend and Qlik Open Lakehouse connected SAP S/4HANA, Oracle ERP, multiple MES platforms, FactoryTalk and Siemens Opcenter, leaving existing plant tools in place.

AI Overview & Impact Summary

A governed semantic layer in Qlik Cloud Analytics gave a multi-plant manufacturer one definition of OEE, yield and scrap across every dashboard, removing the 20-minute reconciliation debate from each monthly review. Analysts recover an estimated 15-20 hours per cycle per plant and decision cycles on operations investments run 2-3x faster.