Sunitha Anand

The goal of the Improve phase is to make minor, incremental adjustments that will improve the overall quality of the product or service. Following the implementation of solutions, the procedure is continuously monitored to ensure that the expected improvements are achieved. Making minor adjustments at this stage reduces the possibility of disruptions to the entire procedure and change management easier. In this phase, there are multiple tools that can help to locate problem spots, create potential fixes, and test them well. POC or small- scale trials can also be effective before going full scale. Use data driven analysis and collaborative evaluation criteria to decide. If delays stem from poor test coverage, one can prioritize better testing tools. If delays are due to backlog volume, more coders could be the solution. Tools that can be used – Brainstorming of solutions – use cross functional and multi skill or tenure teams Solution Priority Matrix (Create a weighted decision matrix using impact on bug fix speed, cost, ease of implementation, team capacity or skills, scalability) RACI charts (Responsible, Accountable, Consulted, Informed) Performance Metric validation and tracking Risk Management Change Management & Communication plans for the new process Use Agile principles to implement small sprints Stakeholder engagement, weekly check-ins with the implementation team and stakeholders, collect feedback Share quick wins for better buy-in 5 S / Poka Yoke Visual Management and Control Techniques

We should make sure the metrics being measured align with the hospital goals and objective of the project. Get stakeholder buy-in. Define key indicators like eg -patient satisfaction and relate that to the metrics being measured. Ensure that data input is standard and consistent, train and correct where needed Audit the data in the initial phases to see if it aligns to the output Automate where possible for reducing human error

Patient Screening in a Hospital can be one scenario where multiple AI agents may be deployed Patient Interaction AI agent: Answers basic questions and gives generic info on how they may be screened. Interacts with patients and collects symptoms, medical history, and personal details. Message - "Welcome to ABC hospital! Please provide your personal details and describe your symptoms." Symptom Analysis Agent: Agent to analyse patient symptoms and suggests further tests based on referencing medical KB. Message - "Thank you for providing your information. Based on your symptoms, we suggest further tests for possible conditions XXX." Medical Record Verification Agent: Verification step for existing patient records for accuracy and updates. Message - “Thank you for sharing your details. Allow me a few moments to verify the same.” Appointment Scheduling Agent: Post initial analysis and verification of records, this agent schedules appointments based on doctor availability. Record Update Agent: This AI agent updates the hospital's health record system with all details on a regular basis so that doctors will have the most up to date info Challenges in Coordination Data mismatch between the 5 agents deployed with accurate linkage Delays in communication that could lead to low accuracy of screening process Any errors in symptom analysis or record verification need to be recorded and communicated real time Status updates to patients may be delayed due to gaps in agent coordination Design corrections to create a smooth workflow · There should be a centralized data repository where all agents can access and update information real-time. · Agent interactions to be defined through standardized APIs & data formats · System alerts and monitoring to track the progress of the screening process. · If an error occurs, the system should immediately notify the relevant agent and provide a detailed explanation of the issue. · Empathetic agent and user-friendly interface for patients to track their screening status. This interface should provide real-time updates and explanations for any delays or issues to the patient with justification.

Taking an example of the travel industry where AI agent needs to minimize response time and maximize customer satisfaction. Additionally, the agent would need to adhere to strict process rules while also delighting VIP clients. Scenario: A VIP (High value) client contacts the AI agent with an urgent request to change their travel itinerary due to an unforeseen event. The client would expect a swift response because their travel plans are time-sensitive. The change involves multiple flights and hotel bookings, requiring careful coordination to ensure a seamless experience. AI agent should be guided on below points - 1) Recognize the VIP status of the client and prioritize their query. Use client tags, account history, and previous interactions as reference points 2) An initial acknowledgment should be sent within a very short time frame (e.g. within 5 mins) to reassure the client that their issue is being addressed. Use personalized messages by addressing client by name and specifying their issue in the response. Eg - Hello Joe, thank you for reaching out to us. We understand the urgency of your request to change your travel itinerary. We are currently reviewing the details of your travel plans and will provide a comprehensive update shortly. Your satisfaction is our top priority. 3) Transparent and regular communication with expected TAT & steps taken would be key to satisfying the client, Eg - Hi Joe , we wanted to keep you informed about the progress of your itinerary change. We are currently finalizing the rebooking process and expect to have everything confirmed by XX hrs. Thank you for your understanding. 4) Process rules and protocols to be adhered for maintaining compliance to company policies 5) Document and record steps taken for traceability and for future reference 6) Check if human intervention is preferred, look for emotions and respond accordingly 7) Monitor client responses and feedback to gauge satisfaction and adjust the approach accordingly 😎Final response to summarize steps taken to resolve client query, with reference number and a link or number to reach out to for any further issues

In shipping documentation, for eg approximately 90% of booking amendments can be managed by AI. Container size, cargo weights, descriptions, port changes, etc can be easily actioned by AI based on the predefined rules. Areas where human escalation may be needed could be for dangerous / reefer cargo specifications check or if the change impacts customer contract requirements or if there are changes to customs' requirements that are not input in the system. Similarly in a Customer Relations process, most changes can be managed well by AI for loyalty programs, updating/ changing member details, updating bookings or requests. Areas of escalation to humans would be when customer is irate or keeps choosing 'Not satisfied' with the response, legal compliance issues, or high value transactions which need further validations.

The interaction, EI and dialogue needed for managing conflicts or coaching a person seems like 'too human' for AI to manage. However elements of fact gathering could be AI enabled for any of the above. Eg - in a murder investigation, we can depend on AI to visualize, gather data, use many models for analysis. But the questioning of the suspect would be better managed by humans