USING INFORMATION AND COMMUNICATIONS TECHNOLOGY TO IMPROVE THE EFFICIENCY AND ACCURACY OF A UTILITY’S NETWORK DATA COLLECTION BUSINESS PROCESS

“You can see the computer age everywhere except in the productivity statistics”. Thisoffhand remark by Robert Solow, the Nobel prize-winning economist [1] has stimulatedmany other economists to conduct more rigorous analyses on the impact of informationtechnology on productivity.The research presented in this dissertation has been conducted on a largetelecommunications utility. An important business process of the utility, that of collectinginformation on its geographically dispersed network assets, was automated using mobilecomputing and wireless technologies. The research compared this newly developedautomated process with the current, manual, process of sourcing the field network assetdata using paper-based templates, and capturing the data manually from the templates.The results of the pilot for this automated business process were encouraging anddemonstrated an improvement of over 50% in the productivity of the data collectionprocess, and its integrity. An important aspect of the research outlined in this dissertationwas to design and implement the mobile computer-based electronic data collectionprototype to minimise user obstruction to the technology deployed. The prototype wastested for technology acceptance by the targeted field workers. This test also provedsuccessful.The research demonstrated that an improvement in productivity of over 50% wasachievable from a well-considered investment in information technology. The resultsfrom the research also pointed the way for the deployment of this data collection solutionin other utilities, e.g. electricity distribution, water reticulation, and municipalities.Through user prototype tests and a cultural intervention process on the targeted users(field workers), the research also demonstrated how the automated business process canbe geared for use by low-skilled field workers, so important to improve productivity indeveloping economies such as those in Africa.