An Alternative to the High Cost and Bureaucracy of Traditional Operational Gain Solutions

A good portion of companies’ costs are absorbed obtaining information from different data sources, primarily for the elaboration of reports, verification of performance-related results and indicator monitoring. These operational activities force many employees to use hours of their time extracting data, accessing the interfaces of several different systems and end up even leading to machine processing idleness. In these scenarios, automating data collection, including even the scheduling of such extractions, becomes a differential, boosting performance and improving the quality of results.

That is why Routine Automation is one of the pillars of the Business Process Automation (BPA) solutions, designed to help optimize operational actions and automatically manage information databases. It represents a possible alternative for companies faced with the impossibility or high cost of implementing traditional automation solutions – usually related to the need for integration between different systems. This process is generally expensive and requires interaction with the IT team to allow for accesses, permissions and approvals – which can rarely keep up with the speed and urgencies required by today’s companies and their processes, due to the complexities inherent to changing a critical system that is already part of the company’s production process.

As related to the monitoring of company needs, other major differentials of this automation method include: its low cost, which ensures a quick investment payback; fast implementation, ensuring only a minimum impact on the operation; and its easy customization, guaranteeing a fast response time if the automation project needs to be upgraded. This model works well for scenarios in which the activities are completed in a centralized fashion, where there is a high level of interaction with the systems and ERPs – such as Shared Service Centres (SSC) or for user simulations in peak access scenarios, actions in sequence, multiple accesses of the same information, etc.

This solution is also an excellent option when there is the need to automate the data collection routine and there is no availability for direct access with its source, leaving a manual collection process via the system interface as the only viable alternative for this data collection. In this situation, Routine Automation accurately simulates all the actions that a human user would performs, interacting with any front-end. Accordingly, even if there is no direct integration with the system in question, it becomes possible to automatically collect the data. It is important to point out that the implementation of this model does not bring the company only tangible benefits related to the process, such as improved speeds and reduced costs, but also intangible benefits – such as the elimination of operational activities (which can discourage professionals and even hinder their development) and increased potential for process quality (due to the elimination of errors resulting from manual processes).

If we also consider that at many companies, the same activity may be completed by different areas without the knowledge of each, this method becomes even more strategic, granted that the benefit may extend beyond the area in which the Routine Automation was initially developed and generate wide-scale improvements for the organization. Once the data collection process is automated and stable, robust and constant, without generating any additional effort for the data “generating” area, this information can be formally disseminated to the other areas of the company, using the service level and reliability that the model offers as backing.

As an example of the scenario described above, we can cite periodic consultations of the financial databases, extracted by the accounts payable, accounts receivable, invoice registration or treasury areas. Suppose that in each of these areas that perform the same activities, there is a person who spends 15 hours per week doing such extractions, and that this person has an average work hour value of $ 10.00. When adopting the Automated Routine operation, the company would have saved approximately $ 30,000.00 in one year (or four months of the allocated resources’ time).

The following are some cases of the application of the model presented in this article:

Database Extraction Automation for Performance Reports from a SSC

We found an area with an oversized headcount, where a considerable portion of the employees were involved with an intense daily routine of manual database extractions. Factors that worsened this intense manual routine included the fact that the activity was repetitive, discouraging and highly susceptible to error, besides the fact that it allocated a great amount of time of those employees qualified in operational tasks with a low generation of value. This presented a clear opportunity to improve an inefficient and expensive process.

After developing the automation project – which included the login automation, necessary parametrizations, data versioning and export – we identified an approximate 80% reduction in the number of hours that were previously dedicated to these activities, together with the improved reliability of the data collected and the opportunity to allocate qualified employees to activities that were more strategic for the company. The 20% remaining human effort represented the allocation of a part-time resource who monitored the robots (automation tools) as well as any process-related upgrades. Below is a graphic illustrating the gain in hours after the project was implemented



Database Extraction Automation for a Supply Board

We found an area where part of the team was responsible for an intensive daily routine of manual extractions from the database of different systems, where practically all of the employees were over-allocated, with a great deal of effort focused on obtaining information.

After implementing the project to automate these extractions, we identified an approximate 85% reduction in the number of hours dedicated to these activities, together with improved information quality and a significant reduction in the operational cost. It is crucial to point out that, after automating these manual actions, the analytical tasks could be better distributed, helping to improve the quality of the results. Below is a graphic illustrating the gain in hours after the project was implemented





Daniel Marinho is consultant at Visagio and holds a degree in Production Engineering and Management for Oil & Gas Industry at UNESA.