Automated Data Capture Frees up 70% of Business Managers’ Time at Cushman & Wakefield
How can you automate a heavily paper-based real estate sector? Rossum, OpenBox, and Cushman & Wakefield went on a mission to create a next-generation data capture tool to reduce physical filing, simplify data retrieval, and save business managers’ time. Read on for a detailed overview of this award-winning data extraction solution and the results we were able to achieve together in just one month.
The Need
Cushman & Wakefield is a leading global real estate services firm that delivers exceptional value for real estate occupiers and owners. In the United Kingdom, their Business Rates Management (BRM) Area provides a service to clients with large national real estate portfolios that includes the management and payment of business rates to local councils.
The annual rates demand documents are predominantly paper-based, requiring Cushman & Wakefield’s Ratings Team to process over 10,000 demands from 400 different Government Departments and Councils over a two-month period. The demands are opened, sorted, manually reviewed, compared to estimates in the Riverlake Rates Management system, and either rejected or approved and paid. Once processed, the paper demands are filed away, making them difficult to retrieve quickly whenever queries arise later in the year.
The Opportunity
Open Box delivers software and services to the real estate industry, specializing in the field of Robotic Process Automation (RPA). The company is a partner of Cushman & Wakefield in their RPA program in the EMEA region.
Both companies identified rates demand management as a high-priority candidate for automation. The KPIs for the Ratings Team were efficiency and productivity gains, and the creation of the team’s capacity to focus on more value-added activities for clients. Cushman & Wakefield also wanted a solution capable of reducing physical filing and simplifying data retrieval.
The Challenge
The format of a rates demand document is similar to that of a vendor invoice, which suggests the use of invoice-scanning artificial intelligence (AI) software would allow for the digitization of rates demand processing. However, while the captured fields are similar in nature to those of a vendor invoice (e.g. property description and address, billing authority, rateable value, and total due), there are significant differences in a practical context.
One crucial disparity is the itemization of payment installments, which is sometimes written as a table (similar to line items), a multi-column list, or in other unprecedented formats.
The Solution
Implementation
- The OpenBox solution team mapped the entire data capture process.
- Rossum’s solution engineers provided consulting sessions to iron out the data capture workflow.
- Rossum developed a seamless plugin to handle exceptional installment-related data.
- Roughly 2,000 samples of UK rates demand documents were uploaded to the platform and processed manually using Rossum’s built-in validation interface.