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Defining analytics maturity indicators: a survey approach

Defining analytics maturity indicators: a survey approach
Defining analytics maturity indicators: a survey approach
The ability to derive new insights from data using advanced machine learning or analytics techniques can enhance the decision-making process in companies. Nevertheless, researchers have found that the actual application of analytics in companies is still in its initial stages. Therefore, this paper studies by means of a descriptive survey the application of analytics with regards to five different aspects as defined by the DELTA model: data, enterprise or organization, leadership, targets or techniques and applications, and the analysts who apply the techniques themselves. We found that the analytics organization in companies matures with regards to these aspects. As such, if companies started earlier with analytics, they apply nowadays more complex techniques such as neural networks, and more advanced applications such as HR analytics and predictive analytics. Moreover, analytics is differently propagated throughout companies as they mature with a larger focus on department-wide or organization-wide analytics and a more advanced data governance policy. Next, we research by means of clustering how these characteristics can indicate the analytics maturity stage of companies. As such, we discover four clusters with a clear growth path: no analytics, analytics bootstrappers, sustainable analytics adopters and disruptive analytics innovators.
0268-4012
114-124
Lismont, Jasmien
ae828817-8188-4686-89b3-2438fa3ee3aa
Vanthienen, Jan
6f3d818f-0fce-46fa-966b-160e645caf6d
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0
Lemahieu, Wilfried
be4bae3f-12b9-417a-91a1-c3c264ffe068
Lismont, Jasmien
ae828817-8188-4686-89b3-2438fa3ee3aa
Vanthienen, Jan
6f3d818f-0fce-46fa-966b-160e645caf6d
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0
Lemahieu, Wilfried
be4bae3f-12b9-417a-91a1-c3c264ffe068

Lismont, Jasmien, Vanthienen, Jan, Baesens, Bart and Lemahieu, Wilfried (2017) Defining analytics maturity indicators: a survey approach. International Journal of Information Management, 37 (3), 114-124. (doi:10.1016/j.ijinfomgt.2016.12.003).

Record type: Article

Abstract

The ability to derive new insights from data using advanced machine learning or analytics techniques can enhance the decision-making process in companies. Nevertheless, researchers have found that the actual application of analytics in companies is still in its initial stages. Therefore, this paper studies by means of a descriptive survey the application of analytics with regards to five different aspects as defined by the DELTA model: data, enterprise or organization, leadership, targets or techniques and applications, and the analysts who apply the techniques themselves. We found that the analytics organization in companies matures with regards to these aspects. As such, if companies started earlier with analytics, they apply nowadays more complex techniques such as neural networks, and more advanced applications such as HR analytics and predictive analytics. Moreover, analytics is differently propagated throughout companies as they mature with a larger focus on department-wide or organization-wide analytics and a more advanced data governance policy. Next, we research by means of clustering how these characteristics can indicate the analytics maturity stage of companies. As such, we discover four clusters with a clear growth path: no analytics, analytics bootstrappers, sustainable analytics adopters and disruptive analytics innovators.

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Defining Analytics Maturity Indicators a survey approach - Accepted Manuscript
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Accepted/In Press date: 27 December 2016
e-pub ahead of print date: 21 January 2017
Published date: 1 June 2017

Identifiers

Local EPrints ID: 425622
URI: http://eprints.soton.ac.uk/id/eprint/425622
ISSN: 0268-4012
PURE UUID: 3a08c55e-3139-4bd4-a6a9-96c5e666078b
ORCID for Bart Baesens: ORCID iD orcid.org/0000-0002-5831-5668

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Date deposited: 26 Oct 2018 16:30
Last modified: 27 Apr 2022 01:47

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Contributors

Author: Jasmien Lismont
Author: Jan Vanthienen
Author: Bart Baesens ORCID iD
Author: Wilfried Lemahieu

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