Applied AI Series: Using ‘Real’ AI in the Complaints Management Process
Recently, we published a Whitepaper on ‘Applied AI: Going Beyond the Buzz and Delivering Real Value to Quality Leaders’. We put together this paper for the following reasons:
- Today, while there’s a lot of buzz on AI and advanced analytics, there is not much explanation of how these technologies will be practically applied to improve your quality and safety processes.
- ComplianceQuest offers real AI-powered features to automate, streamline and “speed up” day-to-day tasks and processes. It’s not about using AI for the sake of it. Instead, it’s about using a design thinking led approach to solve customer and user problems using the power of AI, ML, NLP and advanced analytics.
- We have a series of AI capabilities embedded into various modules including complaints handling, audit management, NC and CAPA management, safety incident management, etc.
For the product team at ComplianceQuest, it was critical to design AI capabilities that could drive business value. We truly wanted to build a solution that would empower quality and safety managers – and, in fact, all users across your organization – to improve efficiency, decrease errors, and free up resources. Sign up for a demo of our powerful AI capabilities today!
In this blog, we focus on how we have built capabilities for intelligent recommendations, advanced decision-making features, and predictive analytics into the complaints management process.
AI-powered Complaints Management: More Efficient from Intake to Closure
Complaints management can be a complicated process, especially for large, regulated businesses. Typically, there are many agents involved in complaints intake, operating from either internal or external call centers. Additionally, complaints must be handled differently for each country, and for each product. Add to the mix a large volume of complaints — and the result is a combination of overburdened, busy agents, confusing and inconsistent processes, an enormous amount of data, and a high risk for manual errors.
ComplianceQuest’s AI capabilities are specifically designed to tackle these difficulties. Below are some examples to show exactly how the ComplianceQuest platform makes the process much more efficient from start to finish.
Reduce Data Entry, Classify & Categorize Automatically, and Get an AI Recommendation for the Complaint’s Risk Level
Let’s take the example of a complaint coming in from a call center to see how CQ’s AI capabilities effectively improve the process of complaints management.
An agent from the Services department receives a call from a customer, opens a case file, and now needs to decide if a complaint must be opened. Thanks to a core integration with Salesforce Services Cloud, the ComplianceQuest platform helps the agent make the decision of opening a complaint with intelligent triage, decreasing the risk of human decision error. The complaint record is auto-populated through the Services connector, removing the need for manual data entry for a more efficient process.
Once the complaint is with the Complaints Department, a different agent must classify the complaint and determine a priority, which depends on the description, the product involved, and the area. This decision bias is again minimized thanks to automatic complaint categorization and automatic priority classification features that are built into the system. The agent also gets an AI recommendation for the complaint’s risk level, further reducing decision bias.
In the case of regulated industries such as medical device manufacturers, agents also get an automated determination of the complaint record’s reportability based on preset parameters. This helps reduce the time needed to go from complaint intake to submitting an eMDR to the FDA, decreasing the risk of non-conformance.
Overall, ComplianceQuest’s AI features make the complaints management process –
- Much more efficient by minimizing errors, simplifying and speeding up decision-making
- It helps accelerate regulatory reporting
- The rules for the categorization and classification of complaints are flexible and can be changed based on different departments, locations, or your business needs
- Automated Categorization and/or Classification of Complaints
- Automated determination of Complaints reportability
- Automated recommendation of Complaint Risk Level (once automatically triaged, all applicable data through services connector auto-populates the complaints record as applicable. The Agent does not need to do manual data entry. With CQ’s compliant management solution, you can reduce time and minimize redundancy and errors.)
- Core integration automation of Salesforce Services Case to Complaints through intelligent triage
Similarity Identification: Making Complaint Investigation Easier
Once a complaint is entered into the system, a Complaint Specialist typically needs to identify if there is a need to open an investigation. This usually means searching through a great deal of data to see if there are previous similar complaints, which can be frustrating and time-consuming. Occasionally they might identify duplicate records which they would then have to manually merge and close, leading to additional manual data entry.
With ComplianceQuest, the Specialist can directly tell if the new complaint record is possibly a duplicate thanks to the automatic detection of Complaints duplicates. They can directly see the duplicate record and automatically merge and close it with one click, without any manual data entry.
Based on the description of the complaint record, the platform automatically brings up similar records and assigns each one a score to indicate how similar the records are. The Specialist can then easily start an investigation with one click, while automatically linking all related complaints records to the new investigation record. This feature saves significant time that would have been otherwise spent manually sifting through previous records. If an investigation is already ongoing, then the agent would be able to see it and simply link the new complaint record to the existing investigation, reducing needlessly redundant work.
Detection of Complaints duplicates, automatically merging and closing them Retrieval of Complaint records with similar descriptions to start an investigation Auto-population of Complaint records with previous complaint insights and data elements
The Big Picture: Direct Impact on Cost Savings
As we wrote in the Applied AI Whitepaper, the ROI for AI initiatives is calculated based on the impact on cost savings or revenue growth.
According to a McKinsey survey, the impact of AI on cost savings and improved operational efficiency is directly apparent. Leaders are able to clearly see the value and ROI of their spending on AI, ML, and intelligent automation. 87% of the leaders who responded to the McKinsey survey said they were able to get at least 10% in cost savings in service operations and manufacturing operations because of AI adoption. 51% believed they were able to get >20% in cost savings in service operations.
Complaints Management is one of those key processes that can be made way more efficient with AI and intelligent automation.
Try ComplianceQuest’s Complaints Management solution, which is a part of our EQMS product suite, to experience the power of real AI. Watch the demo here: https://www.compliancequest.com/demo-video/complaints-management-solution/
To know more about our Applied AI capabilities, please click on this link: https://www.compliancequest.com/lp/applied-ai/
