Cognitive Solutioning of Highly-Valued IT Service Contracts

Shubhi Asthana (), Aly Megahed and Ahmed Nazeem
Additional contact information
Shubhi Asthana: IBM Research - Almaden
Aly Megahed: IBM Research - Almaden
Ahmed Nazeem: IBM Research - Almaden

A chapter in Advances in Service Science, 2019, pp 261-269 from Springer

Abstract: Abstract Different service providers compete to win high valued IT service contracts in a tender kind of process, by providing comprehensive solutions that would fulfil the requirements of their client. Client requirements include services such as account management, storage systems, databases, and migrating the client infrastructure to the cloud. Preparing a solution is a step-wise process where a client shares the Request for Proposals (RFP) which documents the details of services required, and then service providers prepare solutions to fulfil these RFPs. The latter, usually referred to as “solutioning”, can be a lengthy, time-consuming process. Therefore, solutioning automation could result in efficiency increases and cost reductions for the providers. In this paper, we propose an automated, cognitive, end-to-end solutioning methodology that is comprised of 3 steps. The first step involves a textual analytics approach for mining the RFP documents, and extracting the client requirements and constraints. Second, we formulate an optimization model that chooses the optimal set of offerings (that the provider can offer) and their attribute values that cover the client requirements at a minimum cost. Finally, we require market benchmarks to compute pricing of the chosen offerings. Market benchmarks are sometimes unknown for some offerings or for some attributes of these offerings. Thus, in that third step, we show an iterative method to estimate the missing benchmarks along with a confidence score. We validate our methodology by applying it to a real-world application with a comprehensive dataset. We show that it takes minutes to run our method, compared to the days and sometimes weeks for the case of manual solutioning. We also illustrate that our methodology provides more accurate solutions compared to manual solutioning.

Keywords: IT services; Text analytics; Optimization; End-to-end solutioning; Estimating prices; Service benchmarking (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-04726-9_26

Ordering information: This item can be ordered from
http://www.springer.com/9783030047269

DOI: 10.1007/978-3-030-04726-9_26

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().