Name
Abstract | ||
|---|---|---|
This paper identifies management capabilities for data value chains as a gap in current data value research.It specifies a data value management capability framework and a first data value monitoring capabilitymaturity model (CMM). This framework and CMM will enable organisations to identify and measure thecurrent state of their data value monitoring processes, and show how to take steps to enhance valuemonitoring in order to exploit the full data value potential in their organisation. This new approach to datavalue management is needed since, despite the success of Big Data and the appeal of the data-drivenenterprise, there is little evidence-based guidance for maximising data value creation. To date, most datavalue optimisation has focused on technological gains such as data platforms or analytics, without bridgingthe gap to organisational knowledge or human factors research. The evidence of best practice gathered herefrom the state of the art shows that there is a hierarchy of data value dimensions for data value monitoring,starting with cost and peaking with utility (understanding value creation). The models are validated by a case study of three organisations that are managing data value and using it to support strategic decision-making. |
Year | Venue | Field |
|---|---|---|
2018 | ICEIS | Data hierarchy,Best practice,Computer science,Bridging (networking),Knowledge management,Capability Maturity Model,Business-IT alignment,Exploit,Analytics,Big data |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rob Brennan | 1 | 50 | 7.20 |
| Judie Attard | 2 | 97 | 11.01 |
| Markus Helfert | 3 | 618 | 158.65 |