The Role of Agentic AI in Automating Multi-Department Reports

Multi-department reports are crucial for the smooth functioning of a company. These reports offer a comprehensive overview of a company’s performance, enabling decision-makers to make informed, data-driven improvements. They are crucial for optimizing operations, enhancing efficiency, and improving customer service. 

While these reports are helpful for company growth, generating them can be a challenge. Here are some challenges that companies typically face while generating the reports:

• To begin with, different departments use different systems. This leads to data silos. 
• The data is not available in a standardized format, which makes data consolidation difficult.
• The data collection and report generation processes are both time-consuming and prone to errors.
• The chances of missing SLAs, human oversights, and delays are higher, leading to rework on reports.
• Companies would have to hire a large team to gather, standardize, analyze, and generate reports. 

However, companies can overcome these challenges by using agentic AI.

Let’s examine how they can do it with an example of one of our clients, a leading player in the Ambulatory Cardiac Monitoring space in India.

The Challenges In Generating Reports

The client, a leading player in Ambulatory Cardiac Monitoring, was operating on a multi-departmental service model. This meant that there had to be seamless collaboration between the Sales, Patient Assistance, Analysis, and Quality teams. One of the core functions that needed the most collaboration was “Report Delivery.”
For example, the patient assistance team would manage SLA-based and on-demand report delivery, patient queries, and act as an interface for the analysis team.
The analysis team had to analyze the data and create reports, while the quality department would do a post-quality analysis of the reports delivered the previous day.
Each department had to adhere strictly to the SLAs and on-demand requests. However, the client faced multiple operational challenges in generating these reports.

• To begin with, the teams used manual interventions to track requests, manage task queues, allocate or re-allocate tasks, and generate reports for review.
• This led to frequent quality issues, such as non-adherence to SLAs, delays in task completion, and report rework.
• The escalations were also not handled in a streamlined manner. For example, the teams utilized various communication channels, including WhatsApp, email, and phone, for escalations. This proved to be inefficient.
• The client had only 90 team members, which made it challenging for them to scale more quickly. The four departments had to work together to generate over 5,000 multi-department reports each month. 

To minimize errors and enable the departments to generate over 15,000 reports each month, the client decided to automate the process.

How Agentic AI Helped The Client Automate Multi-Department Reports

We deployed agentic AI to help the client streamline workflows, automate repetitive tasks, and enhance cross-departmental coordination. We implemented LangGraph – an open-source AI agent framework designed to build, deploy, and manage complex generative AI agent workflows. This framework enables the creation of agents that can allocate and manage tasks and maintain the quality of multi-departmental reports.

Here’s a glimpse of how the process works:

While the implementation is still underway, the client is already observing improvements in efficiency, quality of reports, and resource utilization. The teams are on their way to achieving the goal of publishing 15,000 reports per month.

Conclusion

Generating multi-department reports can be challenging, especially when there are multiple stakeholders involved. To add to the woes, manual intervention delays the report generation process and leads to errors. However, as seen in the case of our client, automating the process with agentic AI can help companies generate multi-department reports effortlessly and without mistakes.

Need help in deploying agentic AI for activities like generating complex reports? Get in touch with us for more information.