Eurotranciatura Case Study

Business Intelligence in the cloud

“Not only that the system we developed jointly with SolidQ is particularly rapid, the data are reliable and the calculation algorithms are documented. All of this ensures transparency and the possibility for access and analysis by all qualified users.”

Bruno Corrada

ICT Distinctive Projects, Eurotranciatura Group

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The self-service BI solution adopted today by Eurotranciatura features a targeted and limited investment in the initial stage, thus avoiding the traditional costs associated with hardware and software infrastructure.

Eurotranciatura, incorporated in 1967, is the largest manufacturing unit of blanked magnetic laminations in Europe. (It specializes in producing loose blanked or interlocked laminations for rotating electrical machinery designed for a wide range of industrial sectors: automotive, white goods, domotics, power tools, generators, wind generators, geared motors, electric motors, hermetic motors, domestic appliances, pumps and ventilation.)

It is part of the Euro Group, an industrial holding company that coordinates and controls the Group’s companies, which supply manufacturers of electric motors and generators. Thanks to the wide range of technology at its disposal, it offers to its customers molds, equipment, blanked components, die-cast rotors and finished piece assembly for prototypes and series production. Euro Group assists its clients in developing their products by suggesting the technologies that are most appropriate for their needs.

In 2012, Eurotranciatura chose to gradually invest in a Business Intelligence (BI) project capable of supporting management’s decisions, creating the foundation for greater company efficiency and competitiveness. The project was entrusted to the Italian team of SolidQ, a multinational company consisting of more than 100 mentors, a Microsoft Gold partner and a well-respected company in the Business Intelligence sector.

Reports, effectiveness and efficiency indices and improving the Quality Management System

Eurotranciatura’s management uses a set of indicators (KPI Key Performance Indicator) to monitor company processes and performance in the context of ISO TS 16949 certification.

The use of SolidQ’s self-service BI solution, initially implemented for some of the processes subject to quality inspection review by international bodies, permitted simplification of activities and a significant reduction in resources and time used.

“We were seeking a solution with a simple interface that would allow us to optimize maintenance, operation and system upgrade costs” – recalls Bruno Corrada, ICT Distinctive Projects of Euro Group. “In addition, we wanted to obtain a wider level of integration with administrative/accounting and plant management application systems to digitize the process, avoid data redundancy and reduce sources of error.”

Bruno Corrada recalls that “management also required a higher degree of autonomy in generating flexible reports and graphics, together with total integration with the data already present in the company.”

The Adaptive BI philosophy: a new Self Service Business Intelligence process

The solution SolidQ proposed to improve the quality of the organization is a new BI self-service process planned in accordance with the Adaptive BI philosophy: It is a discipline that combines the prediction and optimization techniques necessary to support management in the most complex decisions within environments and markets subject to rapid changes, such as the scenario in which Eurotranciatura operates Franco Pigoli, SolidQ Project Manager, explained. Adaptive Business Intelligence deals with fundamental questions for decision makers: what could happen in the future? What is the safest line of action? It is an approach that includes elements of data mining, predictive models, forecasting, optimization and adaptability”.

BI self-service allows reduction in fixed overhead costs. In this case, Eurotranciatura opted for a cloud server (MS Windows 2008R2 with SQL Server 2012 – rather than an on-premises solution) on Azure, the Microsoft cloud platform dedicated to BI which hosts the staging database, the data warehouse and the Analysis Services cubes. This solution minimizes the investments in system hardware and software and allows specific monthly costs to be predicted by implementing only the functionalities needed to reach predetermined goals. The best results are obtained by attempting to saturate the cloud configuration to take maximum advantage of the service agreement.

Thanks to the staging process (The staging process was implemented via SISS on the on-premises virtual instance), adding the data to the platform was automated. The goal of the self-service BI system implemented by SolidQ is “to allow the individual area managers and Management to continuously monitor their work process.”

“The loading processes in the data warehouse and the creation of the cubes – Franco Pigoli explained – happen in the cloud”, thus the managers of all of Eurotranciatura’s departments have more time to dedicate to data analysis and resulting improvement actions.

“We obtain the data rapidly and easily – Bruno Corrada confirms. In addition, the Excel tables allow us to obtain a multidimensional view with a flexible and user-friendly tool, together with a better view of the calculation algorithms that precede the processing of the information.”

The first system of indicators to be transferred to the cloud was the system for the purchasing process: “The Purchasing Manager – Bruno Corrada relates – need only enter monthly 3 numbers that are not present on the system (they are exogenous variables); at this point the Manager will find the KPI already processed by opening the Excel spreadsheet dynamically linked to the BI system on the cloud.”

The reports, delivered to the managers of the various company processes, have acquired greater flexibility: “The solution we planned allows users to independently query the data present on the administrative/accounting and plant systems; using Excel spreadsheets, they can observe the company’s summary indicators, in real time, with tables and graphics” Franco Pigoli added.

“Not only that – Bruno Corrada added – the system we developed jointly with SolidQ is particularly rapid, the data are reliable and the calculation algorithms are documented. All of this ensures transparency and the possibility for access and analysis by all qualified users.

During the trial phase, the project immediately demonstrated significant results: “With SolidQ’s support, we started off working in parallel; we compared the results obtained with the previous Cognos tool to those obtained with the self-service BI system: the results were in perfect agreement with simpler and automated processing stages.”

Self-service BI: the results

The data architecture allows Eurotranciatura’s management to extend Excel’s potential, in accessing data coming from many different sources, both internal and external, structured and unstructured, within a logic that belongs to the Big Data model.

The first report created was structured to monitor the investments (BI-Capex – From CAPital Expenditure). “BI-Capex monitors the investments, allowing viewing of open projects, orders, revenues and planned budget during the investment analysis phase.”

“We planned an xls spreadsheet that queries the database directly on the cloud – Franco Pigoli explains in regard to self-service BI; you need only enter the order code and you immediately see what was ordered and invoiced. Its automated nature allows data to be seen in real time (The pivot table is linked to the database in the cloud and the information is updated in real time with the data passing from the database on AS400). The report can be constructed to manage project work in progress and process reliable work in progress and forecasts.”

The project results are in the final words of Bruno Corrada, who coordinated the project from the trial phase: “The goal we gave ourselves and that we achieved was to make the data summarizing the company’s performance even more immediate, reliable and accessible, by attempting to maximize the time analyzing the data and, at the same time, reducing processing times. Thanks to that, now we can dedicate more time to studying actions to further improve performance.”