Strengths and Weaknesses of the Excess Earnings Method for Valuing Backlog

Enrico Gonnella, Lucia Talarico

Abstract


For make-to-order manufacturing firms, a valuable intangibles asset is represented by the backlog, namely a company's sales orders waiting to be filled. Not infrequently, the value of this asset can constitute a significant part of the value of the company.

Valuation experts may be called on to value the order backlog in case of the sale of both one or more contracts and of firms or business units.

A strongly accredited method both in doctrine and in practice for valuing customer-related assets, such as backlog, is the Excess Earnings Method (EEM). However, theoretical contributions on the use of the EEM in the specific estimate of backlog are quite rare.

This paper examines the topic of backlog valuation performed using EEM. After describing the valuation process, a critical analysis of the EEM when applied to such valuation object is carried out, with the aim of grasping its strengths and weaknesses.

We conclude that backlog valuation performed using EEM while on the one hand is characterized by strong economic rationality and enjoys general acceptance in the context of professional business valuation services, on the other it highlights significant elements of uncertainty due to the multiple estimates needed. Moreover, it is an extremely complex and time-consuming process, whose application requires a high level of specialist knowledge and skills on the part of the valuation expert.

Keywords: backlog, valuation of backlog, excess earnings method, customer-related assets.

DOI: 10.7176/RJFA/11-22-12

Publication date: December 31st 2020


Full Text: PDF
Download the IISTE publication guideline!

To list your conference here. Please contact the administrator of this platform.

Paper submission email: RJFA@iiste.org

ISSN (Paper)2222-1697 ISSN (Online)2222-2847

Please add our address "contact@iiste.org" into your email contact list.

This journal follows ISO 9001 management standard and licensed under a Creative Commons Attribution 3.0 License.

Copyright © www.iiste.org