AUTOMOTIVE
Functional skills and SAP solutions for companies in the vehicle and component manufacturing sector
AUTOMOTIVE
Supply chain management with EDI and logistics flows
For over a decade, the transformations and trends in the Automotive sector have been significant and have affected the entire sector, from component manufacturers to vehicle manufacturers.
From electric cars, to connected ones up to those with autonomous driving. Not to mention the disruptive digital transformation that continues to innovate and automate manufacturing and assembly processes and the supply chain.
We know the characteristic processes of the Automotive sector, from those of the supply chain, to those relating to demand forecasts, to the execution of process and external procurement orders, from the active cycle to components management.
Functional skills in Automotive
SALES
- Sales Management
- CRM
PRODUCTION
- Production and assembly process
- Quality control Flows with subcontractors
- Plant budget
- Plant maintenance
- Cost accounting
- Project management
LOGISTICS
- Traceability Incoming and outgoing
- EDI integration with customers and suppliers
- Warehouse management
PROVIDERS
- Procurement management of parts and components
SAP Solutions
Blog Insight
In the current climate, the ability to rapidly transform a company’s information assets into strategic decisions is a key factor in business growth. Many organisations, however, continue to grapple with the inefficiencies of traditional Business Intelligence models: complex infrastructure and fragmented data prolong response times and maintain a high level of dependence on technical systems. The shift to conversational BI introduces a different paradigm: data is queried using natural language, with reduced response times, within an integrated and governed architecture. Overcoming the bottlenecks of traditional BI For over twenty years, Business Intelligence has relied on pre-configured dashboards and reports. Self-service BI has broadened access to data, but a certain familiarity with the tools and the data model remains necessary. When senior management requires an ad hoc analysis, the IT team is often still needed to write complex queries or modify data extracts, resulting in delays in decision-making. Conversational analytics models reduce this barrier. Management can query databases directly using natural language, with greater autonomy and significantly faster access to insights.
L'AI-Powered BI supera i limiti della BI tradizionale: interroga dati cross-sistema in linguaggio naturale, con governance e sicurezza.
Every day, companies produce a huge amount of data: from management systems to customer interactions, from sales to warehouse activities. But collecting data does not automatically mean using the information effectively . That's why today there is increasing talk of Data & Analytics : a strategic approach that allows you to transform data chaos into clear, useful, and immediately accessible insights. What do we mean by Data & Analytics? We are talking about the ability to: organize and centralize data , avoiding dispersion between disconnected systems; analyze information with advanced tools to identify patterns, trends, and anomalies; share these insights across different teams, fostering a more collaborative and informed approach; act faster, more focused, and more effectively thanks to decisions based on concrete evidence. With technologies such as Microsoft Fabric , these activities can be managed in a unified, scalable, and secure manner, facilitating the entire data lifecycle. Why it is more important than ever In an increasingly competitive and unpredictable environment, the ability to quickly interpret what is happening - inside and outside the company - makes the difference between those who drive change and those who suffer it. Here are some key reasons: We have more data than ever before, but we need tools to read and understand it. Decisions can no longer be based solely on intuition: objective, real-time analysis is needed. The adoption of artificial intelligence requires reliable, well-organized data. Sharing information between teams speeds up processes and improves strategic alignment.
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