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Client:
In2 Project Management
The client is an urban water corporation responsible for water and sewerage in Victoria, Australia with $1 billion infrastructure network which includes more than 2,000 km of water mains, 15 water treatment plants, over 1,700 km of wastewater mains and 14 wastewater treatment plants.
In2 Project Management is a leading Business Management Consultant based in Victoria, Australia. Their journey began in 2007 when the two co-founders, Neil Betts and Chris Allford, first met to work together to transform businesses with agile thinking and lean practices across Energy, Transport, Financial Services, Healthcare, Government and Technology in all states in Australia. They are about to rebrand to a new company called “Go True North” with the vision to enable their clients to create more value and learn to solve their own problems.
The value of the tool that Nanonets has developed has been very fundamental in saving cost. Without that, we wouldn't have done such a great job of connecting it all together. We are now working on other user cases to look at internal operating costs, again using Nanonets extract data from handwritten timesheets! Nanonets has got the technology and we understand maintenance. We understand what data they need to look at and we have just brought the two pieces together. Nanonets is our partner in our AI journey with our clients.
The Challenge
In Australia, the Water Industry is subject to economic regulations. The economic regulator is an independent body which determines whether the tariffs charged by the water corporation are prudent and efficient. Pricing and performance regulatory framework for water corporation are shared below.
The client was spending circa $10 million AUD / year to deliver external maintenance support on their infrastructure. The In2 Project management Team were engaged to review the options for delivering the future maintenance services to identify areas of potential cost savings, if any, and suggest a more cost-effective way to deliver maintenance.The team began the drill - getting invoices, building spreadsheets, verifying the data against the supporting data. But they faced a challenge - there were over 72 formats of invoices to look at and over 3500 lines of cost. Neil needed a technology that was smarter and faster than manual power to look at the invoices and identify if there were any discrepancies.
Neil evaluated several data extraction players in the market - Nanonets, Amazon, Microsoft and Rossum. But what he was really looking for was a partner in his AI journey.
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The user had concerns that their maintenance delivery model and the associated costs were not optimised. The invoice information being supplied was not verified because it was time-consuming and difficult to reconcile. 3500 line items every month across 72 different types of service provision was not something one person had the time to analyse.
The Solution
Nanonets setup a data validation workflow that receives invoices from SAP Ariba System, 3rd Party supplier invoices and Sharepoint: Nanonets Pre-trained Invoice Extractor captured information in real-time and routed this information to In2 Project Management’s SQL Database. The extracted information was validated against client's spend management system. The updated database was plugged into Power BI, which brought insightful visualisations alive.
This helped Neil's team draw surprising insights into the client's works management process and the validity of invoices against the client’s spend management systems:
1. Discrepancy of $30k was identified when the expenses raised by client’s SAP Ariba portal were validated against data extracted from invoices by Nanonets Pre-trained Invoice Extractor.
2. Cost Per Service when the expenses raised by client’s SAP Ariba portal where visualised, inconsistencies were identified in the range of cost for the same equipment being supplied by multiple suppliers.
3. Company Validation: In order to validate the authenticity of the company raising the invoice, the supplier ABN number of the company extracted by Nanonets Pre-trained Invoice Extractor was compared live using the tax office ABN lookup web services.The workflow is as below:
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