Financial benchmarking analysis: Northern Cape farmers

Abstract

English: The primary objective of the study was to develop a financial measurement-based benchmarking system for GWK on the financial status of their producers. Financial benchmarking systems provide the producers with opportunities to evaluate their past and current financial performance, not only to their own financial status but also to other producers that are included in the benchmarking data. To have a better understanding of the performance of the farm’s financial status and to have a possible explanation of why certain changes had occurred, the first secondary objective was to compare trends of the whole agriculture sector of South Africa with those that occurred to the GWK producers in the study. It was found that the GWK producers had followed more or less the same trends than those experienced by the South African agricultural sector. After the trends were compared between GWK producers and the South African agricultural sector, the limited financial statements obtained from GWK, were analyzed by calculating the financial measurements for each farm over the five years. This was done in order to determine the border values that can be used to divide each measurement into three performance groups. These groups will be used to determine the position for each measurement of a farm relevant to the other farms in the benchmarking system. When the producer has seen the indication that a certain measurement is in the midpoint of bottom performance groups, he knows there are other options available to improve that position, as is already being done by other producers. This leads to another secondary objective that was identified and analyzed. When a producer wants to improve one or even more than one financial measurement, certain changes have to be made that will influence the income statement and balance sheet. As these statements are interactive and a change in one area of the statement will have an influence on the overall results, it is necessary to have an idea or indication of what these influences can be. To provide some background on what the possible outcomes can be the correlation between the measurements and their determinants were determined. These correlations will provide important information on what the possible results of a certain change by a producer on a farm can be. As the financial market is ever-changing, the changes cannot always be hundred percent predictable, but one can at least provide an idea of what can be expected. The last secondary objective is to rank the farms according to their operating efficiency for each enterprise, using DEA. As results indicated, this method of benchmarking can be used in coordination with the border measurement benchmarking system. The difference that exists is that the DEA benchmarking system only divides the farms into two groups as being efficient and inefficient. These two groups can be compared to the results obtained from the border measurement benchmarking system; the farms identified as being the efficient ones are mostly the farms that had most of their financial measurements in the top performance and the top half of the midpoint performance groups. The opposite is also true for the farms identified as being inefficient. Conclusions and recommendations from the study include that a benchmarking system can provide very important information to producers on the performance of their farms, not only to past performance, but also with regard to their rivals. When certain adjustments have to be made to improve the performance of the farm, it is important to remember the possible correlation that exists between the financial measurements and what the possible outcomes can be. The correlation between the measurements is also a point that is available for future research. Lastly, it is recommended that when a farm’s financial position is benchmarked to other competitors, more than one benchmarking system is to be used. This will provide more accurate information to the actual performance of the farm, as a wider spectrum is covered by using for example the border measurement and DEA benchmarking systems.

Afrikaans: Die primêre doel van die studie was om ‘n finansiële “benchmarking” stelsel vir die GWK handels area te ontwikkel. Finansiële “benchmarking” bied aan produsente die geleentheid om hul historiese asook huidige finansiële prestasies te evalueer, nie net teenoor hul eie prestasies nie, maar ook teenoor die prestasies van ander produsente in die distrik. Om die finansiële status van die GWK distrik produsente beter te verstaan en redes vir hoekom sekere veranderings plaas gevind het, is die eerste sekondêre doelwit om die tendese van die Suid Afrikaanse lanbou te vergelyk met die tendese van die GWK distrik produsente. Die gevolgtrekking is dat die produsente van die GWK distrik min of meer dieselfde tendense gevolg het as wat deur die Suid Afrikaanse landbou sektor ervaar was. Nadat die tendense vergelyk was, is die finansiële state, verkry vanaf GWK Beperk, ge analiseer deur die finansiële maatstawwe te bereken vir elke plaas oor vyf agtereenvolgende jare. Die analise is gedoen om die grens waardes te bereken wat elke maatstaf in drie prestasie groepe verdeel. Hierdie groepe word gebruik om die posisie van ‘n plaas relatief tot ander plase in die “benchmarking” sisteem te bepaaal. Wanneer die produsent ‘n indikasie kry dat ‘n sekere maatstaf in die middelste of onderste prestasie groep verdeel is weet die produsent dat daar wel opsies beskikbaar is om die maatstaf posisie te verbeter, wat alreeds deur ander produsente bereik is. Wanneer ‘n produsent een of selfs meer as een finansiële maatstaf wil verbeter moet sekere veranderings plaasvind wat die inkomste- en balans- staat affekteer. Die finansiële state is interaktief en ‘n verandering en een area sal ‘n effek op die ander finansiële staat veroorsaak. Daarom is dit nodig om ‘n idée te ontwikkel van wat die moonltike veranderinge en gevolge kan wees. Om moontlike idees te skep is die korrelasies tussen die maatstawwe en hul determinante bereken. Korrelasies wat nodige inligting kan verskaf oor die moontlike gevolge van ‘n verandering wat deur ‘n produsent gemaak word. Omdat daar voortdurende veranderng plaasvind in die finansiële mark, kan die verandering nie altyd honderd persent voorspel word nie. Hierdie is slegs moontlikhede wat verwag kan word. Die laaste doelwit is om die plase in ‘n rangorde, volgens hul bedryfsdoeltreffendheid, vir elke bedryfstak te bepaal. Die rangorde word bepaal volgens die “Data Envelopment Analysis” (DEA) metode. Resultate het getoon dat die DEA as ‘n “benchmarking” sisteem in samewerking met die grensmaatstaf metode gebruik kan word. Die verskil tussen die metodes is dat DEA die produsente in twee groepe verdeel as doeltreffend en ondoeltreffend. Hierdie twee groepe kan vergelyk word met die grens maatstaf metode. Plase wat as doeltreffend geïdentifiseer is, is die plase in die boonste prestasie groep, of in die boonste helfte van die middel prestasie groep. Die teenoortgestelde is dan van toepassing om die ondoeltreffende plase in die onderste prestasie groep. Gevolgtrekkings en voorstelle na afloop van die studie sluit in dat ‘n “finansiële “benchmarking” belangrike inligting aan produsente kan deurgee oor hul prestasie. Die inligting is nie net van toepassing oor hul historiese prestasies nie, maar ook oor huidige en teenoor mededingers se prestasies. Wanneer sekere veranderings gemaak word om die prestasies te verbeter is dit belangrik om te onthou dat daar korrelasies bestaan tussen die finansiële maatstawwe en wat as gevolg daarvan die gevolge kan wees. Korrelasies tussen die maatstawwe is ook ‘n onderwerp vir verdure studies. Ten slotte word voorgestel dat wanneer ‘n plaas se finansiële posisie “gebenchmark” word tenor ander mededingers, moet daar van meer as een sisteem gebruik gemaak word. Dit verseker dan dat akkurate inligting teenoor die prestasie van die plaas deurgegee word as gevolg van die wyer veld van inligting en resultate wat verwerk word. ‘n voorbeeld van twee sisteme is dan die grens maatstaf en DEA wat gesamentlik gebruik was in die studie.