We helped design a new end-to-end process where a UiPath robot could automatically read customer data in a SQL database, and then intelligently merge all associated customer records.
Our customer was a local council in Victoria who needed to undertake significant customer data cleaning as they were building a single customer view to help them better serve their ratepaying community. They had customer information spread across multiple cloud and on-premise systems that had accumulated over many years of operation.,p>Customer information had grown unchecked in the business, resulting in out-of-date information, duplicate customers and conflicting information across the CRM, financial and document management systems. The estimated human effort required to cleanse all this customer information was over 6 months. This was a prohibitive cost in terms of of staff time, not to mention the cost in terms of employee satisfaction at executing such a tedious task.
Teaming up with the business we helped design a new end-to-end process where a UiPath robot could automatically read customer data in a SQL database, and then intelligently merge all associated customer records in the Technology One , Dynamics CRM and ObjectiveConnect front-ends.
Leveraging an enterprise framework, a robot was quickly developed that could successfully move through an end-to-end process of cleaning customer information across all systems. The robot navigated each system, applied rule-checking logic and executed the necessary steps to clean customer data, whilst producing a report to the business of its activities. By automating this process, staff were able to focus on more valuable tasks such as customer interaction and planning. The business could also reliably use their systems for information to drive informed decision making about their customers.
Our data platform specialists are equipped with the tools, methodologies, and experience that help to enhance and expand your platform in a structured approach. We work with data platforms from design to implementation across all key technical components such as Data Lakes, Databases, ETL processes, Cubes and Reporting.
We provide clear timelines and expectations for what can be delivered and when, and what interactions are needed between the business and the technical team.