Scenario

Our customer was an international language testing provider based in Victoria who had a very time-consuming and manually-driven financial month-end process. Due to the size of the business, financial data was spread over multiple disparate systems and needed to be collated and reconciled as part of month-end activities.

The solution had to produce the required reconciliation outputs, and had to demonstrate cost-effectiveness against other potential solutions. With this in mind, it made sense to automate this process, as it not only ensured that the process was going to be preserved, but would also deliver value in terms of cost-effectiveness and efficiency.

Solution

Working closely with the business, we designed an automated process whereby a bot would individually retrieve financial data from various different systems and upload that data into a storage location where it could be ingested into a data warehouse. This data warehouse would then produce the required reconciliation outputs and feed into reporting tools. This scheduled process was performed via an unattended bot, meaning that there was no longer any human cost associated with the process – a significant efficiency benefit for the business.

Outcome

After carefully reviewing the process requirements, we quickly developed a process automation that could reliably navigate the existing systems, generate the required data, handle various exceptions, and report on it’s progress to the business.

By automating this process, the business was able to automate their critical process without disrupting existing business systems. Financial data was retrieved and reconciled every night, as opposed to the hectic month-end period. This resulted in more efficient and accurate reporting throughout the month, and also freed up staff to focus on more valuable tasks.

Technology
Automation Initiation

Automation Initiation

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.

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