Context

Enterprises with diversified operations across regions and business units often face fragmented visibility across Finance, Supply Chain, and Workforce domains. Data is strewn across multitude of applications – ERP, 3rd party systems, Cx, HCM systems, etc.

This Use Case addresses a unified AI-powered Enterprise Performance Management (EPM) framework that connects transactional data across business functions into a single integrated financial dashboard with simulation parameters for CFOs and business controllers. Once monthly closing of books happens, be it WD3 or WD5, etc. there is a need to get an integrated view of all this data in standardized format for a forward-looking view for the ensuing month/quarter and year for planning, forecasting and business decision making across functions.

2. Data Landscape

The solution integrates raw data from multiple functional domains such as:

· Accounts Receivable (Customer Invoices, Collections)

· Accounts Payable (Vendor Invoices, Payments)

· Inventory Balances and SKU-wise Movement

· Sales Promotions, Shipment & 3rd Party Logistics Activity, and Workforce Data

Data is in csv format; however, the solution is extendable for data to be integrated directly from multiple source systems or other fragmented parts like pdf files

3. Data Curation and ETL

Raw CSV files are dropped in a folder from where a single-step Windows batch file executes a Python ETL (Extract. Transform & Load) process that reads, validates, and transforms data into optimized Parquet and curated CSV formats. Log files are generated for review including one with summary and drill down comparison between raw file and final curated file for each line item.

The ETL layer ensures data consistency, converts delimited files to efficient formats, and provides a ready-to-consume base for financial modeling and dashboard visualization. It also de-duplicates, removes junk data and normalizes formats from different source systems.

4. Analytical Model and Dashboard

A script powers a Streamlit-based analytical dashboard comprising four modules:

1. KPIs – That presents FY sales, COGS, EBIT, DSO, DPO, DIO, and CCC.

2. Finance – Compares actual vs. policy-based gross margin and EBIT benchmarks.

3. Operations – Displays turnover metrics, inventory turnover and working capital efficiency

4. Simulation – Models what-if scenarios for cash realization and EBIT impact in case of certain decisions taken

5. Simulation Framework

The Simulation tab empowers users to adjust working-capital levers and immediately observe impact on liquidity and profitability. Sliders control parameters for AR, AP, and Inventory.

Lever Drivers Cash Impact EBIT Impact

Accounts Receivable Δ DSO, % Early Pay, Customer Discount % Inflow from faster collections Discount expense

Accounts Payable Δ DPO, % Early Pay Discount, Supplier Discount % Outflow from early payments offset by supplier discount Discount benefit

Promotions / Inventory Δ DIO, Promo Uplift %, Margin Give-up % Reduced holding cost; cash inflow Margin give-up expense

Visualization and Insights

Two compact charts are generated dynamically within Streamlit:

• Total Operating Benefit – Cash vs. EBIT summary bar chart

• Lever-wise Impact – AR, AP, and Promotion impact side-by-side.

This allows decision-makers to instantly assess trade-offs between liquidity and profitability.

7. Strategic Value

The AI-powered EPM framework enhances CFO visibility across domains through automated data integration, real-time simulation, and scenario planning. The resulting benefits include:

• Improved cash forecasting, working capital management

• Unified view of operational and financial levers

• Seamless simulation-to-action insights for business controllers

And all of this can be enabled fast, accurately and in an inexpensive manner.