Original Research

Using historical data to explore transactional data quality of an African power generation company

Patient Rambe, Johan Bester
SA Journal of Information Management | Vol 22, No 1 | a1130 | DOI: https://doi.org/10.4102/sajim.v22i1.1130 | © 2020 Patient Rambe, Johan Bester | This work is licensed under CC Attribution 4.0
Submitted: 16 July 2019 | Published: 19 May 2020

About the author(s)

Patient Rambe, Department of Business Support Studies, Faculty of Management Sciences, Central University of Technology, Bloemfontein, South Africa
Johan Bester, Department of Business Support Studies, Faculty of Management Sciences, Central University of Technology, Bloemfontein, South Africa


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Abstract

Background: In developing countries, despite large public companies’ reliance on master data for decision-making, there is scant evidence to demonstrate their effective use of transactional data in decision-making because of its volatility and complexity. For the state-owned enterprise (SOE) studied, the complexity of generating high-quality transactional data manifests in relationships between customer call transactional data related to an electricity supply problem (captured by call centre agents, i.e. data creators) and technician-generated feedback (i.e. data consumers).

Objectives: To establish the quality of customer calls transactional data captured using source system measurements. To compare this data set with field technicians’ downstream system transactions that indicated incorrect transactional data.

Method: The study compared historical customer calls transactional data (i.e. source system data) with field technician-generated feedback captured on work orders (i.e. receiving system) in a power generation SOE, to ascertain transactional data quality generated and whether field technicians responded to authentic customer calls exclusively to mitigate operational expenses.

Results: Mean values of customer call transactional data quality from the source system and technician-generated feedback on work orders varied by 1.26%, indicating that data quality measurements at the source system closely resembled data quality experiences of data consumers. The SOE’s transactional data quality from the source system was 80.05% and that of historical data set from evaluating feedback was 81.31% – percentages that exceeded average data quality measurements in literature.

Conclusion: Using a feedback control system (FCS) to integrate feedback generated by data consumers to data creators presents an opportunity to increase data quality to higher levels than its current norm.


Keywords

feedback control system; power generation; master data; transactional data quality; electricity supply problem; data management capabilities.

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