Our spend intelligence solution is designed to efficiently integrate with procurement data from any ERP-system such as SAP, Oracle, etc. and is enriched with external data. The processed data is rendered through series of AI based algorithms for further analysis and visualized in an interactive manner to provide actionable insights for decision makers.
Data in an organization is like blood flowing through veins. Power BI is the heart which pumps the data from different sources and provides key actionable insights to business users.
OpenBI’s spend core integrates all data sources, information from isolated procurement systems into a central data warehouse. External data sources are used to enrich internal data using algorithms and AI. The entire architecture of data core aggregation is fully automated to provide near real time refreshes and updates.
Duplicate and inconsistent supplier names across multiple source systems is one of the biggest challenges in effectively measuring the spend across suppliers. OpenBI’s proprietary grouping algorithm can identify suppliers within a common cluster and provide high level of grouping accuracy. The fully automated process recommends and groups potential matches of children and parent suppliers. We also have expertise in mapping the supplier groupings with external databases such as dun & bradstreet and Bloomberg which opens the gateway of external market intelligence such as supplier risk, news, management updates, financial analysis and many more.
Spend data is often found in multiple languages across multiple ERP’s which makes it challenging to provide a global snapshot in a single language. OpenBI leverages Google Translate API to detect the source language and convert it to 100+ languages. The setup is designed in a cost effective manner and is calculated by the number of characters processed on a monthly basis.
OpenBI has in-depth understanding of SAP Ariba spend cube data and has standardized templates to provide quick analysis. OpenBI’s proprietary AI tool classifies SAP data based on custom/ standard taxonomy such as UNSPSC, eCL@ss., rule based, or AI based classification. Subsequently the model learns to accurately predict the classification of new data with high level of accuracy thereby providing intelligent insights through interactive visualizations. This builds foundation for category strategy document leading to higher savings and tracking meaningful procurement KPI’s.