Business performance measurements in asset management with the support of big data approach

Jaime Campos, Pankaj Sharma, Erkki Jantunen, David Baglee, Luca Fumagalli

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    Abstract

    The paper reviews the performance measurement in the domain of interest. Important data in asset management are further, discussed. The importance and the characteristics of today's ICTs capabilities are also mentioned in the paper. The role of new concepts such as big data and data mining analytical technologies in managing the performance measurements in asset management are discussed in detail. The authors consequently suggest the use of the modified Balanced Scorecard methodology highlighting both quantitative and qualitative aspects, which is crucial for optimal use of the big data approach and technologies.
    Original languageEnglish
    Title of host publicationProceedings of MPMM
    Subtitle of host publication6th International Conference on Maintenance Performance Measurement and Management
    PublisherLuleå University of Technology
    Pages89-95
    ISBN (Print)978-91-7583-841-0
    Publication statusPublished - 2016
    MoE publication typeA4 Article in a conference publication
    EventMaintenance Performance Measurement and Management Conference - Luleå Tekniska Universitet, Luleå, Sweden
    Duration: 28 Nov 201628 Nov 2016

    Conference

    ConferenceMaintenance Performance Measurement and Management Conference
    Abbreviated titleMPMM
    CountrySweden
    CityLuleå
    Period28/11/1628/11/16

    Fingerprint

    Business performance
    Asset management
    Performance measurement
    Data mining
    Methodology
    Balanced score card

    Keywords

    • business performance measurements
    • asset management
    • big data technologies

    Cite this

    Campos, J., Sharma, P., Jantunen, E., Baglee, D., & Fumagalli, L. (2016). Business performance measurements in asset management with the support of big data approach. In Proceedings of MPMM: 6th International Conference on Maintenance Performance Measurement and Management (pp. 89-95). Luleå University of Technology.
    Campos, Jaime ; Sharma, Pankaj ; Jantunen, Erkki ; Baglee, David ; Fumagalli, Luca. / Business performance measurements in asset management with the support of big data approach. Proceedings of MPMM: 6th International Conference on Maintenance Performance Measurement and Management. Luleå University of Technology, 2016. pp. 89-95
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    title = "Business performance measurements in asset management with the support of big data approach",
    abstract = "The paper reviews the performance measurement in the domain of interest. Important data in asset management are further, discussed. The importance and the characteristics of today's ICTs capabilities are also mentioned in the paper. The role of new concepts such as big data and data mining analytical technologies in managing the performance measurements in asset management are discussed in detail. The authors consequently suggest the use of the modified Balanced Scorecard methodology highlighting both quantitative and qualitative aspects, which is crucial for optimal use of the big data approach and technologies.",
    keywords = "business performance measurements, asset management, big data technologies",
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    Campos, J, Sharma, P, Jantunen, E, Baglee, D & Fumagalli, L 2016, Business performance measurements in asset management with the support of big data approach. in Proceedings of MPMM: 6th International Conference on Maintenance Performance Measurement and Management. Luleå University of Technology, pp. 89-95, Maintenance Performance Measurement and Management Conference, Luleå, Sweden, 28/11/16.

    Business performance measurements in asset management with the support of big data approach. / Campos, Jaime; Sharma, Pankaj; Jantunen, Erkki; Baglee, David; Fumagalli, Luca.

    Proceedings of MPMM: 6th International Conference on Maintenance Performance Measurement and Management. Luleå University of Technology, 2016. p. 89-95.

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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    T1 - Business performance measurements in asset management with the support of big data approach

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    AU - Sharma, Pankaj

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    AU - Baglee, David

    AU - Fumagalli, Luca

    N1 - Project code: 104824

    PY - 2016

    Y1 - 2016

    N2 - The paper reviews the performance measurement in the domain of interest. Important data in asset management are further, discussed. The importance and the characteristics of today's ICTs capabilities are also mentioned in the paper. The role of new concepts such as big data and data mining analytical technologies in managing the performance measurements in asset management are discussed in detail. The authors consequently suggest the use of the modified Balanced Scorecard methodology highlighting both quantitative and qualitative aspects, which is crucial for optimal use of the big data approach and technologies.

    AB - The paper reviews the performance measurement in the domain of interest. Important data in asset management are further, discussed. The importance and the characteristics of today's ICTs capabilities are also mentioned in the paper. The role of new concepts such as big data and data mining analytical technologies in managing the performance measurements in asset management are discussed in detail. The authors consequently suggest the use of the modified Balanced Scorecard methodology highlighting both quantitative and qualitative aspects, which is crucial for optimal use of the big data approach and technologies.

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    KW - asset management

    KW - big data technologies

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    EP - 95

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    Campos J, Sharma P, Jantunen E, Baglee D, Fumagalli L. Business performance measurements in asset management with the support of big data approach. In Proceedings of MPMM: 6th International Conference on Maintenance Performance Measurement and Management. Luleå University of Technology. 2016. p. 89-95