The development of data analytics maturity assessment framework: DAMAF

Abstract

Today, data analytics plays a vital role in attaining competitive advantage, generating business value, and driving revenue streams for organizations. Thus, the organizations pay significant attention to improve their data analytics maturity. Nevertheless, the existing literature is dramatically limited in proposing a comprehensive roadmap to assist organizations for this scope. Thus, this study focuses on developing data analytics maturity assessment framework (DAMAF) that evaluates the organizational data analytics maturity in a staged manner from maturity level 0: incomplete to maturity level 5: optimizing. The DAMAF comprises the nine different data analytics attributes to address the specific needs of each data analytics maturity level. Accordingly, it aims to support organizations in assessing their current data analytics maturity, determining organizational gaps in data analytics, and preparing an extensive roadmap and suggestions for data analytics maturity improvement. In this research, we employed the DAMAF in an organization as a case study to evaluate its applicability and usefulness. The results showed that DAMAF properly reveals the data analytics gaps and provides a structured roadmap for continuously advancing the data analytics maturity of an organization.

Znanstveno-raziskovalni izzivi na poti digitalne preobrazbe

“…Med digitalnimi tehnologijami je še posebej pomembna uporaba podatkovne analitike, na podlagi katere lahko iz podatkov pridobimo nova spoznanja, razvijamo storitve in izdelke, ki so strankam bolj prilagojeni, in podpremo odločitve, da so te utemeljene na podatkih (Król & Zdonek, 2020;Qin, 2014). V tej smeri se razvijajo tudi modeli podatkovne zrelosti, ki so namenjeni oceni zrelosti podatkovne analitike v podjetju, na primer model DAMAF avtorjev (Gökalp et al, 2021), s katerim lahko ocenimo, ali ima podjetje podatkovno analitiko že v uporabi in zakaj jo uporablja.…”

A reference model for software product line capability assessment

“…[19][20][21] CMMI and SPICE are used as evaluative and comparative basis for process assessment and improvement. The observed benefits of these models and standards, such as cost savings, more involved employees, improved and predictable quality, and increased productivity, generating a consistency of process capture and use, 22 lead to the adaptation of the same approach to domains other than software development such as Medical, 23 Automotive, 24 Government, 25 Open data, 26,27 Data Science, [28][29][30] Big Data, 31 Digital Transformation, 32,33 and Industry 4.0. 34 Although researchers are attempting to develop a prescribed and systematic way of improving SPL processes, 35 there are a limited number of studies related to measuring SPL process capability maturity in the literature, [36][37][38][39][40] and none of the existing studies is developed based on a well-known process capability maturity model or standard.…”