Development of the Shared-Service-Center Improvement Framework

Table of Contents

This solution was developed for a Shared Service Center to allow the middle managers of each department to track their KPI, identify errors that waste time and money, figure out why they happen, simulate possible actions, and track their impact on improving the KPI.

It’s a flexible reporting layer connecting data from SAP and external databases with Azure Data Factory in an Azure SQL Server for flexible analysis with BI Dashboard tools.

Summary

This documentation consists of three main parts:

  1. The Business Background
  2. Solution Design and Concepts
  3. The Actual Implementation

of the flexible data warehouse project to gain insights into the business processes of a Shared Service Center. The solution enables effective process improvement, inevitably leading to cost savings that the automation KPI can track.

The Business Background

Explains the use case from the business perspective. It is the summary of many discussions with the company’s finance department and lays the foundation for the solution design.

Especially if you’re an IT guy like me, this is a MUST read. Because we are fascinated by technology, we are all too often excited by flashy charts, AI analysis, and Demo videos.

It is crucial to understand that just because something is technically possible does not mean it is valuable.

The chapter shines a light on how business sees things.

You can read it here.

Solution Design and Concepts

This chapter builds on top of the first, discusses the necessity of a different approach for the agile KPI layer, and presents a working solution design for its implementation. The chapter highlights the chosen architecture and outlines the benefits and trade-offs compared of the classic data warehouse and operational reporting.

You can read it here.

The Actual Implementation

This chapter is proof that this document is not just a consulting company slide-(shit)-show.

Through the last year, we implemented the flexible data warehouse described in chapter two.

For now, I only included the highlight of the SQL ETL functions.

You can check out the coding highlights here.

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