System integration and software development company, Navicon has migrated its analytics solution for FMCG companies to Microsoft Azure cloud. Now Navicon’s clients decrease cost of local infrastructure and use analytical capacity of Azure Data Platform preparing their reports, including AI and big data tools.
Navicon FMCG BI is aimed at simplifying companies’ assessment of its efficiency, including product promotion. The system provides tools to analyze the whole sales chain, activities and efficiency of field staff, to control partners in following contract terms and position of the products among rivals’ products, as well as to calculate prime cost up to SKU. Navicon’s clients also use FMCG BI for bonus calculation for sales representatives, control of accounts receivable, arrangement of P&L structure and other tasks. The solution can work with data from CRM, ERP, CLM and other systems, which were previously implemented in a company as well as databases.
Thanks to migration of Navicon FMCG BI to Microsoft Azure cloud Navicon’s clients:
- can use advanced analytics, including the one for work with big data;
- can decrease cost of local infrastructure;
- can get reports and insights in any part of the world and on any device;
- can quickly scale cloud storage resources, when needed, and, correspondingly, computing capacity of Azure Data Platform.
Now companies can choose the most relevant version of the solution among those offered by the system integration company:
1. Deployment of Navicon FMCG BI on local servers of FMCG companies. This way can be chosen by those, who have enough computing capacity and whose security policy does not allow putting data into cloud.
2. Hybrid scenario. It will be relevant for those, who would want to store data on local infrastructure and use innovative tools for its analysis, which are available in Microsoft Azure cloud.
3. Cloud scenario. It will be suitable for a wide range of companies, which need additional Azure Data Platform tools – big data analytics and AI. Besides, companies, which have just started developing their BI competencies, can lower cost of experiment starting with low capacity and without capital costs.