Knowledge base and BOTs – redefining workforce estimation model. (6th June 2022)

• Record Type: Journal Article
• Authors: Deb, Varsha; Vashisht, Vasudha; Arora, Nidhi
• Is Part Of: International journal of services and operations management. Volume 42:Number 2(2022)
• Page Start: 267
• Page End: 280
• Publication Date: 2022-06-06
• Subjects: knowledge base -- KB -- forecasting techniques -- forecasting error -- workforce forecasting -- knowledge reuse -- ITSM -- ITIL -- MS Excel Solver -- time series -- customer relationship management -- service level agreement -- SLA; Production management -- Periodicals; 658.5005
• Languages: English
• ISSNs: 1744-2370

Abstract

Workforce estimation has always been a challenging task for service organisations. The revenue and profits are directly impacted by the number of resources deployed, thus accurate workforce estimation becomes a key objective for any service. With time, many organisations are taking leap in implementing BOTs or implementing knowledge base for reusability; the workforce estimation also needs changes. This paper first presents application of forecasting models to estimate the workforce requirement for an IT service organisation. As many organisations are promoting the culture of knowledge reuse, this paper later presents how the same model can be modified to forecast the workforce when an organisation implements a knowledge base (KB) for resolving customer's requests/incidents. A detailed implementation of this model is presented using MS Excel. The model presented is generic in nature and can be reused by other organisations having similar type of work or requirement.