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Automation investment appraisals
Intelligent automation software technology is key to remaining competitive in the current growing digital landscape. Appropriate techniques should be used to appraise such investments and make correct automation investment decisions. After a comprehensive literature review, three limitations on auto...
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| Format: | Thesis |
| Language: | English |
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College of Accounting
2023
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| Summary: | Intelligent automation software technology is key to remaining competitive in the current growing digital landscape. Appropriate techniques should be used to appraise such investments and make correct automation investment decisions. After a comprehensive literature review, three limitations on automation investment decisionmaking were found in the extant literature: (1) time value of money not considered, (2) interpretative and definitional issues related to the popular Return on Investment (ROI) technique, and (3) the widely recommended Net Present Value (NPV) technique appeared not to have been used. This study aims to identify which automation investment appraisal and valuation techniques are used in South Africa in practice and the relevant metrics applied, to assess these for potential gaps in their application and to ascertain the quality of automation investment decision-making. An online survey questionnaire was distributed to organisations that have invested in automation technology in South Africa to gather data from automation consumers and automation consultants. Payback period, ROI, and budget availability were the most common appraisal techniques used by respondents, followed by popular Discounted Cash Flow (DCF) capital budgeting techniques, NPV and Internal Rate of Return (IRR). The results further point toward deficiencies in the application of appraisal techniques compared to finance literature, which indicates suboptimal quality automation investment decision-making. Important unquantified qualitative factors influencing the decision-making process were also identified. These qualitative factors were considered by respondents more often in their decision-making process than quantitative factors. Future research in this area should include quantifying qualitative factors to improve the quality of automation investment decision-making. |
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