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Client Stories

Siemens Building Technologies Transforms its Pricing Data Management with State-of-the-art BI Solution

The Building Technologies Division of Siemens is a leading service provider, system integrator and product vendor in the market for safe, energy-efficient and environment-friendly buildings and infrastructure.Given the competitive landscape it operates in, accurate product pricing management is critical to the profitability of Siemens Building Technologies. The company employs a complex pricing strategy based on parameters such as channel management, sales volume, market and competitive conditions. Price structure is based on these parameters. As a result, a lack of efficient pricing management may impact the pricing strategy effectiveness of the company.

Since pricing data was stored in disparate local SAP systems, centralized visibility and management proved to be a challenge. Though Siemens Building Technologies had previously implemented SAP’s Process Integration (PI) tool, extracting country-specific data and not having a centralized view of this data was a major pain point. As part of a pricing process optimization plan, Siemens Building Technologies required a business intelligence (BI) tool that could organize data from SAP systems and present it in a graphical, intuitive manner.Capgemini, with its global expertise in business analytics and data integration, was commissioned to identify and deploy the right solution. Its Business Information management (BIM) experts collaborated with Siemens Building Technologies and implemented QlikView for pricing data analysis.

The Solution

Capgemini provided a proof of concept for an optimized architecture combining SAP Business Warehouse (BW) and QlikView. This architecture served as the analytical layer and replaced traditional BW cubes, aggregates and accelerators. As a next step, Capgemini and Siemens Building Technologies collaboratively devised guidelines for the design of BI applications that would operate with the architecture. Disparate SAP data was integrated with SAP PI in the SAP BW, and then using QlikView’s SAP SQL Connector, into the QV file system and In-Memory, for better management and visibility.

The Result

With in-built functionality for future developments and data integration, Capgemini’s BI solution enabled Siemens Building Technologies to improve its pricing data transparency. The pricing data is now presented across 13 interactive dashboards which were conceptually designed in-house, allowing local users to view country-specific information and KPIs, and the central management to view global pricing overview.The pricing analysis application is now an essential part of Siemens Building Technologies’ efforts to re-align its pricing processes. This re-alignment is expected to help boost revenue and profitability in countries within the scope of the application.

Siemens Building Technologies had already realized cost efficiencies of the SAP BW system, by reducing aggregation layers and redundancies. The new architecture is slimmer and needed less development effort compared to parallel BW applications.

The entire IT environment now resides and functions from a centralized station. Poor performance can be readily identified and managed.

How Siemens Building Technologies and Capgemini Work Together

At Capgemini, Business Analytics is a core unit within the BIM global service line, servicing over 100 clients in 30 locations around the world. Using its agile development methodology, Capgemini designed a BI solution that consolidated country-specific data across intuitive dashboards.Siemens Building Technologies leveraged Capgemini’s expertise in overcoming technical issues with SAP extractor connectors for QlikView. Capgemini, a leading QlikView and SAP integrator, helped Siemens Building Technologies build up knowledge on QlikView internally. This enabled the building technologies company undertake maintenance and need based development of its pricing application. Capgemini’s agile methodology empowered key users to validate their specific requirements at an early stage, saving process time and increasing efficiency.