CaseStudy - 1
RPA helps leading eye care chain save over 3 Million INR annually in their payables Function.
Finance | Healthcare | RPA | UiPath
Overview
The client is a leading Eye care provider in India with over 65 clinics in India. Besides they have clinics in over 10 countries. They have been rapidly growing at the rate of 1 clinic every 2 months. They are known for World class eye treatment with a reputation of being in eye care for over 60 years. Treatments offered in any their clinics across the world are standardized to global benchmarks.
Payables team reduced from 5 to 1
Invoice Processing time reduced from 20 minutes to 2 minutes
Statistics
- 95+ clinics across 11 countries
- Procurement function centralized while goods receipt happens across these clinics
- World class ERP centrally and home-grown Hospital Information Systems in Clinics
- Over 70 vendors in India that supply crucial materials for them.
- Over 20 vendors cater to nearly 90% of their monthly payouts
- Processes nearly 6000 invoices every month from all these vendors
- Average time taken for manually processing each invoice after three-way matching of Purchase Order, Invoice and Good Receipt Note was 20 minutes per invoice prior to automation. This is despite world class ERP and an advanced Hospital Information System
- 5 member payables team before automation
Problem Statement
- Piling up of unpaid invoices - Average time taken to process payments from the date invoices were received to the payment was made was over 30 days
- They had a 5 member team to handle this manual reconciliation process
- Annual spend was in excess of INR 3 Million towards manpower cost associated with this process
- This spend was increasing as new team members were added to manage growing number of invoices.
CaseStudy - 2
Document Digitization
Overview
The Client is a leading digital native insurance organization with a large auto insurance portfolio. They were looking to digitize the claim invoices that come to them from various automobile service centers. They get over 500 invoices a month. Prior to automation they had a team to enter invoice related information from each repairer bill to their core insurance application. Even basic information such as vehicle make, model, plate number and bill details constituted nearly 25-30 pieces of information that were manually entered into their core insurance application. They were still not entering part level information from each of the repairer bill that would mean additional 180 to 200 pieces of information to be entered manually. They were looking to automate the process by which they not only eliminate the manual labor associated with entering core invoice related information but also capture detailed parts level data which can be further used for part level repair analysis.
Over 500 bills a month
200+ pieces of data to be captured from each bill
Solution Overview
- InnoHat provided an end-to-end automation solution using the Microsoft Power Platforms and Azure AI builder Following activities in the entire process chain were automated
- DOCUMENT RETRIEVAL – Retrieving documents or files stored in shared folders retrieved for further processing.
- DATA CLASSIFICATION -Classification of retrieved documents as Repairer and Non-Repairer Bills (Medical bills, Legal charges etc.)
- DATA EXTRACTION – Extraction of parts and core invoice details from the classified documents from these documents
- DATA VALIDATION – Validation of extracted data against reference data.
- DATA UPDATION – Updation of parts level details and invoice details in two separate databases.
- Products Implemented with Microsoft based RPA solution with following modules
- Microsoft Power Apps
- Microsoft Power Automate
- Azure Blob Storage
- Microsoft AI Builder Form Processing
- Microsoft Dataverse
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