Ser­vers in the as­cen­dant

Brief ab­stract for read­ers in a hur­ry

Despite previously advocating ACL’s desktop solution, we now prefer the server version for almost all application scenarios. Technical reasons include its improved performance and central, fail-safe and redundancy-free data storage, not forgetting data protection and data security aspects. From an organisational perspective, you can avoid isolated solutions and situations where losing your only analytics expert brings all data analytics activities to a sudden halt (knowledge retention/knowledge management). Finally, a server version offers improved usability where results can be supplied to every user in their preferred format – because not everyone who uses the results is a data analytics expert skilled in IT. Visualisations and suitable graphics are often required to present results in an understandable way and so bring about the necessary acceptance.

Don't get us wrong – we are big fans of the desktop version. However, for almost two years now, the vast majority of our product presentations have focussed solely on the server version. Not because we are trying to say that “expensive means good”, but because we believe the server version offers a more sustainable solution.

A brief his­to­ry

Our company's growth was founded on ACL™’s desktop software. An initial factor was the successful STAAN project, which we implemented in cooperation with Bayer AG’s Group Auditing department and which led to various articles being published (e.g. in ZIR Zeitschrift Interne Revision). Further details are available here. In summary, numerous ACL software licences were in use. But only in theory. Because the data analytics software was not being widely used. We overcame this with the concept of data extraction from SAP® + predefined analytics steps for ACL ™ + ACL™ Desktop. We achieved all this without relying on a server solution and also advocated this approach to others. But things have now changed. Let me explain how.

 

Data vol­umes and in­for­ma­tion se­cu­ri­ty

A few years ago, it was still possible to provide auditors with a local copy of data. However, this is not so easy today due to the higher expectations placed on analyses and the increased need for information. Distributing several hundred gigabytes via external hard drives is no longer appropriate – even before aspects of information security and data protection are considered. Losing several years of business data on board a train or a plane would hugely damage a company’s reputation. Technical problems such as data losses due to defective hard drives are also an issue where large volumes of data are copied. Such problems were a regular occurrence. Many companies’ own IT departments also recommend a centralised software version as this enables all installation, maintenance and especially back-up processes to be incorporated into the existing software concept.

Ac­cep­tance - Not ev­ery­one likes broc­co­li

In the age of apps, easy-to-use mobile devices and a focus on user experience and usability, it’s no longer relevant to merely present and distribute data analytics results as an endless roll of “data paper”. If you are considering establishing a structured system of data analytics within your company, it is essential to consider the recipients of the results in a differentiated light. While it may be sufficient to provide senior management with a brief and concise report (one-pager) including visualisations, middle management relies on a mix of visualised KPIs or KRIs (Key Performance or Key Risk Indicators) and also needs to be able to access individual transactions where necessary. At operational level, a detailed list of all relevant transactions is still needed (e.g. potential duplicate payments). A server solution can achieve this level of differentiation, helping to establish acceptance among colleagues and make data analytics a success within your company.

Free­ing up lap­tops

Technically, data analytics involves two time-consuming activities: data extraction and analysing huge data volumes in order to generate the results. Using local software tools which are installed only on a user’s laptop or desktop computer may in some cases restrict the use of these devices for several days. The computer cannot be switched off while the data are being accessed or analysed as this would interrupt the processes. While this may be acceptable for a 60-minute analytics run during the lunch break, processes which take 60 hours (such as the huge changes tables in SAP® or sales or condition technique analyses) can block a computer for several days.

Per­for­mance – fas­ter is bet­ter

This aspect is relatively easy to explain. Even a separate analytics server will clearly not be able to work miracles. However, corresponding hardware equipment will enable significant performance enhancements for analytics processes compared to pure desktop solutions.

Per­haps the most im­por­tant be­ne­fit lies else­where

If you use ACL™’s server version, you will need to set up pre-defined analyses on the server. It should be pointed out that this has nothing to do with C* aspects (Continuous Controls Monitoring / Continuous Auditing). If you want your server to perform purchase analyses in preparation for an audit, you will need a set of these analyses (a form of macros or apps) which then generate the results. On closer inspection, what may at first seem a disadvantage is in fact the most important benefit. In most cases, the alternative is for a few individuals within a company (in many cases just one or two people, even in large audit departments) to perform complex analyses using the locally installed desktop version. Frequently, these analyses offer little standardisation and are rarely documented because the data analyst himself has the requisite knowledge. The problem really comes to the fore if the analyst moves department or even joins another company. In such cases, data analytics will often come to a standstill because it is inextricably linked with that person. By using a server, you establish a solution where the contents are independent of any specific individual. Consequently, the costs of training, analytics software and analytics apps are not lost if personnel changes occur. In our opinion, only a client/server solution is able to offer sustainability in terms of knowledge management, transparency and know-how management while avoiding an isolated solution.

Con­clu­sion

Alongside increasing technical requirements for data analytics software, users’ expectations as regards the content and presentation of results have also risen. This, combined with the key benefit of sustainability/knowledge retention leads us to conclude that in most cases and irrespective of team size, establishing a powerful and robust client/server solution is the only viable path.