Customer Contact Ranked Scheduling Assistance System
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Solution Overview
Problem
Business professionals face challenges in efficiently scheduling customer meetings due to diverse geographic locations and varying meeting frequency needs, leading to inefficient time usage and potential neglect of important relationships.
Innovation Solution
A customer contact ranked scheduling assistance system that prioritizes meetings based on revenue-based criticality ranking, using CRM platforms to determine meeting frequencies and deadlines, and groups meetings by geographic location to minimize travel and maximize revenue generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If meetings are scheduled based on diverse geographic locations and varying frequencies, then customer coverage is improved, but time usage efficiency deteriorates
Solution Approach 1:
The system assigns different meeting frequencies to different customers based on their specific characteristics such as revenue contribution, geographic location, and relationship importance. High-value customers receive more frequent meetings while lower-priority customers are visited less often, optimizing the professional's time allocation across diverse customer bases.
Solution Approach 2:
The system dynamically adjusts meeting frequency parameters for each customer based on multiple factors including revenue percentage, geographic zone, and time since last meeting. This parameter-based scheduling automatically optimizes the schedule to maximize revenue generation while minimizing unnecessary travel and time loss.
2Reliability
If meeting frequency is increased for all customers, then relationship maintenance is improved, but productivity deteriorates
Solution Approach 1:
Instead of applying uniform meeting frequencies to all customers, the system applies partial action by concentrating meeting efforts on high-priority customers who contribute most to revenue. This ensures critical relationships are maintained with sufficient frequency while reducing or eliminating unnecessary meetings with lower-priority customers, thereby preserving overall productivity.
Solution Approach 2:
The customer base is segmented into different priority levels based on revenue contribution and relationship importance. The system then applies different meeting frequency strategies to each segment, ensuring that high-value customers receive adequate attention for relationship maintenance while low-priority customers are served more efficiently with less frequent contact.
3Loss of time
If travel is minimized by grouping meetings, then time efficiency is improved, but scheduling flexibility deteriorates
Solution Approach 1:
The system merges multiple customer meetings into single travel routes by grouping customers in the same or nearby geographic zones. This consolidation minimizes travel time and resources while the underlying ranking system maintains scheduling flexibility by allowing professionals to select from multiple high-priority customers within each zone based on availability and urgency.
Data Source
AI summary
A method of ranking criticality of upcoming customer meetings may comprise receiving, via a network interface device, for a plurality of customers, a meeting deadline date, a meeting frequency value, and a previous sales factor rate indicating revenue or a percentage of previous meetings that resulted in revenue to a user, determining, via a processor, for the plurality of customers, a past due percentage value by dividing the number of days elapsed since the meeting deadline date by a number of days within the meeting frequency value, and determining, for each of the plurality of customers, a criticality ranking by weighting the past due percentage value with the previous sales factor rate. Displaying, via a graphical user interface (GUI), the plurality of customers, listed in order of the criticality ranking, from highest to lowest, for scheduling of upcoming meetings in order of criticality.