Out-of-Office Management System for Project Reassignment

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Solution Overview

Problem

Businesses and financial institutions face customer loss and revenue decline due to employee vacations and out-of-office periods, as seamless communication breaks can lead to customer frustration and competition from other companies.

Innovation Solution

An out-of-office management system that monitors employee data to determine the likelihood of an employee being out of office, analyzes affected projects for departure scores, ranks them for criticality, and reassigns them to minimize customer loss, using natural language processing and machine learning for future improvements.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If employee vacations and out of office periods are allowed, then employee well-being and work-life balance are improved, but customer communication continuity deteriorates leading to customer loss

Engineering Contradiction:

Improveemployee well-beingVSAvoidcustomer communication continuity

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The system performs preliminary actions by monitoring employee data to predict out-of-office events before they occur, proactively identifying affected projects and reassigning them in advance. This ensures customer communication continuity is maintained while allowing employees to take necessary time off.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system acts as an intermediary between employees and customers during out-of-office periods. It automatically reassigns projects to other employees and manages customer communications, serving as a bridge that maintains service continuity without requiring direct employee-customer interaction during absence.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If manual project reassignment is performed during employee absences, then customer retention can be maintained, but time and resources are lost due to manual intervention

Engineering Contradiction:

Improvecustomer retentionVSAvoidmanual intervention time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system enables self-service by automatically monitoring employee status, identifying affected projects, determining departure scores, and reassigning projects without human intervention. This automated self-service approach maintains customer retention while eliminating the time and resources required for manual reassignment processes.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system implements feedback loops by continuously monitoring customer sentiments after reassignment and using this information to refine future out-of-office management decisions. This automated feedback mechanism improves customer retention through data-driven adjustments without requiring additional manual time investment.

Inventive Principle:

Principle #23Feedback

3Reliability

If all projects are reassigned during employee out of office, then customer communication is maintained, but system complexity and operational overhead increase

Engineering Contradiction:

Improvecustomer communicationVSAvoidreassignment system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system applies local quality by selectively reassigning only the most critical projects based on calculated departure scores, rather than uniformly reassigning all projects. This targeted approach maintains essential customer communications while reducing the complexity and overhead associated with comprehensive project reassignment.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system uses parameter changes by calculating departure scores based on multiple factors (project criticality, customer relationship strength, timeline urgency) to dynamically determine which projects require reassignment. This parameter-based differentiation simplifies the decision-making process compared to blanket reassignment rules.

Inventive Principle:

Principle #35Parameter changes

4Reliability

If customer sentiments are monitored continuously for machine learning, then future out of office reassignments are improved, but data processing requirements and computational resources increase

Engineering Contradiction:

Improvefuture reassignment accuracyVSAvoidcomputational resources

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system applies partial action by monitoring customer sentiments selectively for projects with high departure scores rather than continuously monitoring all projects. This targeted monitoring approach improves future reassignment accuracy for critical cases while reducing unnecessary computational resource consumption.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11526819B1Out of office management

Publication Date: 2022.12.13 WELLS FARGO BANK NA

AI summary

Out of office management is provided to an institution and customers of the institution. Employee data can be monitored of one or more employees of the institution. A likelihood an employee is out of office is determined. A set of projects of the employee that are affected by the out of office is determined. The projects are analyzed to determine departure scores for each project of the set of projects. The projects are ranked according to the departure scores to determine criticality of each project. The projects are reassigned based on the employee data and the ranking. Customer sentiments are monitored after reassignment for machine learning to affect future out of office reassignments.