Anatomy of a poor quality engineering or construction claim
Find out how to improve the quality of claims, how to drive efficiency gains and control the associated time, cost and quality benefits.
Engineering and construction commentators have long stated that poor quality claims are a leading cause of dispute. But what constitutes ‘poor quality’, and where should you focus limited resource to ensure claim prospects and business outcomes are not compromised?
This paper will resonate with commercial, claim and dispute managers and the executives that have oversight of them.
It describes the hallmarks of poor quality, their impact and the link with the technology skills shortage in the sector. In addition to numerous recommendations, it highlights competing drivers between client and advisor and machine learning’s potential as a mechanism to achieve a return on investment from claim expenditure.
Over the coming months' we will publish a combination of case studies and example scenarios intended to further illustrate the time, cost and quality benefits highlighting in this paper. Register above to recieve notifications of related content.
Looking further ahead we will provide insight into the largely untapped of AI document capture, its benefit to claims or dispute and how it provides a mechanism for achieving a return on investment from claim expenditure. We will examine how they outperform traditional capture technology and why they will become an indispensable part of the digitally enabled advisor’s toolkit.