SAP Analytics Cloud is a cloud-based analytics solution that allows organizations to analyze and visualize their data in real-time. It provides capabilities for data exploration, data modeling, predictive analytics, and business intelligence reporting.
For its part SAP Fieldglass already contains powerful analytics tools that can analyze data on worker performance, project costs, and vendor performance to make informed decisions and optimize their external workforce management strategies. An integration with SAP Analytics Cloud brings the ability to combine data from SAP Fieldglass with data from other SAP systems, such as SAP S/4HANA or SAP SuccessFactors. This allows users to perform cross-functional analysis and gain a holistic view of their workforce and procurement data.
For example, let's say WorkingNet, a leading manufacturer of data networking equipment, wants to analyze the distribution of its permanent workforce across its offices and compare it with the distribution of its external workforce. By integrating SAP Fieldglass and SAP SuccessFactors with SAP Analytics Cloud, WorkingNet can easily track its entire workforce. By creating an interactive total workforce management dashboard in SAP Analytics Cloud, WorkingNet can visualize the distribution of its workforce on a heat map showing its global offices.
WorkingNet could also analyze its contingent workforce spend across different departments and regions. In that case, SAP Analytics Cloud would combine data on the usage and cost of contingent workers from SAP Fieldglass with financial and operational data from SAP S/4HANA to create an interactive dashboard showing the spend by department, region, and other dimensions. This gives WorkingNet the opportunity to identify areas for cost optimization or process improvement.
WorkingNet can leverage the advanced analytics capabilities that SAP Analytics Cloud offers, such as predictive analytics and machine learning, that can be applied to SAP Fieldglass data. This enables the company to uncover patterns, trends, and anomalies in their workforce and procurement data, and make data-driven decisions to optimize their operations.