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Risk Predictor for accounts in Service Desk Delivery Disclosure Number: IPCOM000216346D
Publication Date: 2012-Mar-31
Document File: 7 page(s) / 38K

Publishing Venue

The Prior Art Database


The WeatherVane Risk Predictor for Service Desk Delivery is a model designed to take input from a defined set of metrics, analyze their performance against historic trends and benchmarks, and provide output risk levels that alert the Delivery manager on the account's health, enabling them to proactively manage the account and ensure operational excellence

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Risk Predictor for accounts in Service Desk Delivery

1. Introduction to the WeatherVane Risk Predictor for Service Desk Delivery

Disclosed is a Risk Predictor model designed to enable Service Desk Management teams proactively manage delivery by trending and observing key metrics critical to the account health and customer satisfaction. The model principle can be extended to other industry domains apart from service desk delivery.

In order to effectively manage service delivery, management teams need to move from a reactive mode of operation to a proactive mode by predicting the account's health and performance, so as to avoid critical situations that lead to a possible executive escalations and potential loss of business to the company.

The WeatherVane Risk Predictor model allows teams to evaluate the risk level of their account by:

Defining key metrics which can impact account health

Taking input from these key metrics

Analyzing trends and providing an alert mechanism based on historic performance and industry thresholds

Providing a risk level prediction of the account, highlighting the focus areas

With the service desk delivery industry becoming increasingly competitive, cost of delivery and/or location are no longer differentiators for a company aspiring to grow in the domain. In order to differentiate services, quality of delivery is key and superlative quality assurance is a mandate, to inspire and sustain customer's confidence. This model is unique in its sphere, by providing a quality assurance model for service providers which emphasizes their commitment to uninterrupted, consistent and continually improving service delivery.

2. Model Design

2.1 Risk Prediction Factors

The risk prediction factors selected for inclusion in WeatherVane are a combination of delivery design and


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operations criteria, dynamic metric progression and customer perception. Key aspects of delivery aregrouped into three areas:

A] Environmental Risk Factors

These factors evaluate the environment in which the account is being delivered and if the account is risk-prone by design. It considers the following indicators: Tenure of


Number of


The number of queues that the helpdesk has to escalate tickets to increases the chances of misroutes, thereby impacting MTTR which is felt keenly by the customer. In addition, a large number of queues also results in several resolver groups to chase, which becomes an additional risk factor for accounts that perform E2E work.

Updated KB If the knowledge base has many documents which are not updated or incorrect, then chances of error by the team increase. This directly impacts the customer experience.


Attrition If the management team is unable to control its unplanned attrition, this leads to a high churn in the system, thereby raising a risk of loss of knowledge and the additional



Performance stabilizes with length of time that the account has bee...