LA ANTIGUA ACADEMIA 1 1

Survey respondents were asked whether their department were using any particular software packages to assist in analysing accounting data. Only 50% of respondents indicated that their departments did use software packages to assist in the analysis of accounting data, 22% percent responded that their department did not, and 28% did not know. Given the positions of the people surveyed it is surprising that almost 30% of the respondents were not aware of the usage of particular software for accounting data analysis. When surveyed respondents were asked whether their department utilised data mining technologies, 62% did not know about it while only 19% indicated they utilised data mining technologies. This correlated with the limited knowledge many seem to possess regarding the use of analytical software for AIS, and uncertainty about the utilisation of data mining within their department. It does support the view that the usage of data mining is minimal at this time. Table 5.8 summarizes the results.

Table 5.8: Use of analytical/data mining software

Categories Frequency %

Yes, please specify 68 50.0

No 30 22.1

Use of analysis software

Don’t know 38 27.9

Yes 25 18.8

No 25 18.8

Use of specific data mining technologies

Don’t Know 83 62.4

An important issue is identified in terms of utilisation in Table 5.9. A comparison was made between job function and utilisation. For each job category 50% or more of respondents indicated that they did not know whether data mining technologies were in use. In accounting group for example, about seventy-eight percent (38) of them were don’t know about this. In this case alone, of 49 respondents with accounting job function, 38 of them were either not aware or not familiar with data mining techniques. Looking at those respondents who indicated ‘yes’ to this question, 48% were auditors.

Table 5.9: Primary Job Function vs. utilisation

Utilise data mining

Job function Yes No

Don't Know Accounting 5 6 38 Finance 2 3 15 Information Management 3 3 3 Auditing 12 9 19 Others 3 4 8 25 25 83

Interviews were able to offer additional insights into the utilisation of data mining technology. Three of the interviewees indicated that they utilised data mining tools. They were involved in mining, analysing and interrogating the data in their work environment. Since all of them were involved in auditing work, they seem familiar with this kind of analysis. All were using Audit Command Language programs,

called a CAATs25 method in audit. As one interviewee said: ‘We use the ACL program with the CAATs method. In CAATs there are many types of software we can use, even excel. There are 2 softwares commonly used by the auditor, IDEA and ACL, here we have used ACL since 1986.’ Another describing their work. ‘Auditing is based on data provided by the accountant from the general office. We audit, interrogate, for example the voucher sampling or expenditure trend analysis. We use CAATs, through software ACL...’ One interviewee commented using an ACL:’...all data about personal salary is kept at the accountant’s general office, so if we want to analyse it we request the data from them, upon receiving the data we use data mining tools, whether data from e-spkb or from salary we just use ACL...we can search vouchers, trend analysis and various analysis, salary for instance, we can see who have overpay or no salary left..We can do all that with ACL...’

Those respondents who had adopted data mining tools in analysis were very happy with these current tools. One interviewee discussed the Audit Command Language (ACL). ‘As for now, the tool that we use is the best, but I heard there is a new one, I can’t recall what it was. Anyway it’s acceptable because it makes our work easier, the only problem with ACL is that you need training...’ Another explains their function in helping evaluating systems. ‘That’s why we do an audit, for example segregation of duties, if the system doesn’t develop a very tight process, we are not able to detect its weaknesses. That is our function. If there is a loophole with the system, we will inform them. In giving proof of that loophole, we do a test. In some ways it is good for the auditee to be able to know whether is there any improvement needed for their system. We can detect a probability of a loophole or fraud...’

The utilisation of software such as ACL in everyday work has improved the speed of work. ‘.... now we have, what they called ACL you know, audit command language,

25

CAAT refers to computer-assisted audit technique which implies that an auditor’s use of a computer-assisted audit technique via the use of certain data analysis software. This software has the ability to extract data and normally can perform a variety of queries and other analyses on the data. Some of the features are: data queries, data stratification, sample extraction, missing sequence identification, statistical analysis and calculations (Sayana, 2003). It include a range of computerized tools and procedures used by auditors in various phases of the financial statement audit, operational and special audits (Debreceny et al., 2005)

so using ACL we can analyse whether the data available is good or not, reliable or not, but prior to ACL, we used a manual system, we looked at the record, manually checked it and calculated the information and manually looked at the documents, but now we use a lot of software that helps to speed up our work.’

For some departments there is a problem implementing data mining technologies as all or some of the data is kept at other sites ‘At the general audit office, we do have data mining, but here in the ministry we don’t have the data, all the data are with the accounting office’.

Interestingly 81% of respondents (Table 5.8) indicated their department did not, or that they were unaware of specific data mining technologies being used in analysis. This could reflect limited knowledge about software use within the department. For example, one interviewee indicated that the current system in use was Oracle but knew little else about it. ‘..So far, we don’t have any specific software for analysis data for decisions...we just use the normal pc with Microsoft (excel), no specific softwares, we do it manually, manual analysis...We don’t have specific software, we combine all general data, there is no software, I’m not using it, maybe there is not available at my level, I don’t know’. Or perhaps specific software was not seen to be necessary as analysis requirements are simplistic. ‘Perhaps in government there are analyses activity, but not properly managed. And then we don’t have software. We have all files but without software we cant come out with analysis...’.In my opinion, data within government is rather based on historical data, meaning past events, so based on that data we present for decision making, a simple analysis. For that, excel (Microsoft Excel) is enough but I am not sure about the future.’ A common response from those who did not adopt data mining technology was: ‘It’s not we don’t need it, it just we don’t have it. We just produce reports, so I’m not sure, because when I joined here, the systems were ready, so I just use it’. A further interviewee felt lack of knowledge may be related to their level of seniority. ‘In term of the system, I do not have a chance to try, because my ranking wasn’t high enough to do that, maybe at the upper level, I keep and provide the data, and then they will analysis it. I often use the

MIS. In terms of analysis, they will need to meet different requirements and will be undertaken by various peoples...’

Six of the nine interviewees commented that their departments used no specific software for data analysis. It would appear that simplistic forms of analysis are common using spreadsheets such as excel to perform basic data analysis required by their job function or the needs of management. Interviewees indicate that even though specific software may not be used for data analysis this does not mean that data analysis is not undertaken, they may not be aware of it. However, there is recognition that analytic software is important and can be utilised to increase job performance.

In conclusion, more than 50% of the respondents either did not utilise data mining or analytical software or were not aware if any was used in their department. Half of the respondents indicated that they use software packages to assist in the analysis of accounting data. However, in terms of utilising specific data mining tools for their analysis, only nineteen percent utilised such technology. Interviews also reveal that the actual use of data mining is minimal during at this time. Notwithstanding though, it is not uncommon for departments to use a generic software such as Microsoft Excel to undertake basic data analysis suited to their job function. Thus, the utilisation rates of data mining or analytical software in government departments in Malaysia could be described as moderate. The finding also suggests that the level of awareness about data mining itself was low. This may be the result of the term ‘data mining’ itself is technological jargon rather than an everyday terms as the interviews reveal.

5.5.3 Factors influencing organisation’s decision to employ data