Financial Planning and Analysis (FP&A) is a group within a company's finance organization that provides senior management with a forecast of its profit and loss (income statement) and operating performance for the upcoming period, quarter, and year. These forecasts inform management on the progress and effectiveness of the company's strategic plans and investments. They also enable management to communicate with external stakeholders.
FP&A team is responsible for generating key executive and managerial reports like Budget vs. Actual for the cost centers or departments, short term cash flow, operational review, and company's financial statements. Organizations are also looking to get predictive insights by implementing advanced use cases like spend and revenue analytics to identify opportunities to optimize spend and improve the bottom line. These reports and analysis require iterative discussions with accounting and business teams due to multiple views of the organization's same data. FP&A team needs access to spend (direct and indirect) and revenue (operating and non-operating) data recorded in multiple transactional applications hosted on-premises or in the cloud. Hence, they spend a lot of time collecting, cleansing, classifying, and analyzing expenditure and revenue data from various sources within the organization every month.
The FP&A reporting and analysis require to aggregate vast volumes of data at the P&L level and analyze them by corporate reporting hierarchies (usually maintained in planning and budgeting tools like Hyperion or ePBCS) like entities, cost centers, products, locations, customers, suppliers, etc. We need the ability to drill down to the sub-ledger to the transactional level details. The advanced and predictive analytics use cases like spend, revenue, and ROI demand iterative data preparation, model development, training, and testing on the large volume of enterprise data. If done manually in SILOs, these tasks become time-consuming, error-prone, and inefficient.
Jade Global has designed and developed multiple cloud data warehouse solutions to help resolve Financial analytics and reporting workloads utilizing Oracle Integration Cloud (OIC), Oracle Object Store, Oracle Data Integrator (ODI), Oracle Autonomous Data Warehouse (ADW), Oracle Data Catalog, and Oracle Cloud Analytics (OAC) on Oracle Cloud Infrastructure (OCI).
The above reference architecture illustrates how Oracle Cloud Infrastructure (OCI) can be utilized to build the centralized cloud FP&A data warehouse that collects, processes, and stores all types of data from a broad range of enterprise data resources and deliver single-source-of-truth for FP&A reporting and analytics workloads. Suppose your critical financial data like ERP, planning, budgeting, forecasting data reside in the Oracle SaaS or PaaS. In that case, the above solution is even better to utilize OCI's native integration functionalities and achieve a robust, scalable, and cost-effective unified cloud data warehouse solution.
Ingest: Integration with enterprise data applications at scale is a primary requirement to build enterprise cloud data and analytics solutions. OCI Provides multiple purpose-built methods to ingest data from a variety of applications. E.g., Oracle BICC can be used to ingest financial data from Oracle Fusion ERP. Oracle EPM Automate can be used to ingest the plan, budget, and forecast data from ePBCS. OIC can be used to ingest another third-party spend, sourcing, travel, expenditure, sales, and revenue data FP&A data lake in OCI object store in their row format. Oracle Data Integration provides a wide range of knowledge modules to natively integrate with tons of data applications.
Transform, Curate, and Store: Once data is ingested into Oracle object-store buckets, OCI Data Integrator performs data curation and transformation tasks to prepare the collected row data into a conformed dimensional model used for data analytics and dashboarding use cases.
Oracle Data integrator is also responsible for making the end-to-end data pipelines (ingestion, curation, transformation, post-load processing, etc.) automated via batch, streaming, and event-based processing.
The curated and transformed data is stored in the Oracle Autonomous Data Warehouse (ADW) in conformed forms to enable a unified view of the enterprise's financial, operational, and external data. As the data and complexity grow, we can leverage Oracle Analytics Views features in the ADW to optimize the queries' performance, requiring dynamic aggregations on enterprise hierarchies.
Analyze and Consume: The cloud FP&A data lake enables the centralized storage for the enterprise financial and operational data and metadata (business and technical) to support the following workloads.
- Enterprise Canned dashboards: Role-based dashboards that deliver a unified view to the FP&A, accounting, and business teams and enable seamless collaborations to improve accuracy, efficiency, and productivity.
- Data Discovery Sandboxes: Data Discovery projects promote self-service reporting, visualizations, and analytics by utilizing IT controlled subject areas. The users can further blend personal or external data to analyze and find new spending or revenue patterns.
- Data Science/ Lab: Oracle Analytics' augmented analytics capabilities to design, build, and train machine learning models for complex use cases like spending classifications, supplier scoring, or revenue predictions.
Data Governance: OCI also delivers rich features to govern the in-motion or at-rest data in the cloud data warehouse. OCI data catalog can be used to index, monitor, and govern the technical and business metadata, while Oracle Analytics delivers the security at user, object, and row-level data.
How Jade Global can help: Reach out to Jade Global if you are looking to unify the FP&A data into a cloud data warehouse, eliminate the teams working in SILOs, and improve the team's productivity exponentially.