Paper Info
Title
More Observations, More Variables or More Quality? - Data Acquisition Strategies to Enhance Uncertainty Analytics for Industrial Service Contracting.
Abstract
Service business models expose industrial service providers to an increasing amount of uncertainties. In order to design profitable offerings, providers need to understand how uncertainties affect contract profitability. Both, access to data and algorithms are key requirements for accurate analyses. While current research focuses on developing algorithms to derive insights from data that already exist, the need for strategically acquiring relevant data sets has been neglected so far. In this article, we develop a method for defining data acquisition strategies to improve uncertainty analyses for industrial service contracting. We explain how lacking observations, variables and quality of data affect uncertainty analyses, propose data acquisition strategies as a systematic plan to acquire relevant data and develop an approach for ranking acquisition strategies by measuring their acquisition effort and business benefit. The method is applied in an industrial use case to demonstrate its benefit for assessing cost uncertainties in full-service repair contracts.
Year
DOI
Venue
2017
10.1007/978-3-319-56925-3_13
Lecture Notes in Business Information Processing
Keywords
Field
DocType
Strategic data acquisition,Uncertainty analysis,Service contracting,Industrial services
Data science,Computer science,Data acquisition,Service provider,Uncertainty analysis,Profitability index,Business model,Analytics,Data access,Process management
Conference
Volume
ISSN
Citations 
279
1865-1348
0
PageRank 
References 
Authors
0.34
4
3
Name
Order
Citations
PageRank
Björn Schmitz1164.55
Gerhard Satzger29923.89
Ralf Gitzel300.34