QUALITY MANAGEMENT M an a g e me n t Ac c o un t in g i n t h e W in e g r ow i ng S e c to r : P r op o sa l an d D ev el op m en t of a n “ Ad H oc ” Co n tr o l Syst em Leonardo CASINI*, Enrico MARONE**, Gabriele SCOZZAFAVA*** Abstract
The purpose of this study is to propose a management control model which, for the time being, targets establishing the winegrower’s production cost for a single bottle of wine, and flexibly utilizes the tools of management accounting by cost centres and/or by activity on the data already available to each winegrowing farm. Towards this end, we have built a specific software capable of determining the cost differences for each product typology even departing from little available information. The proposed model was tested on several Tuscan wineries and proved to be a flexible control instrument capable of providing useful information for the management, especially for those farms which need to estimate the distribution of costs between the different generic types of products and between the various phases in which the production processes are divided, but that do not have a system for detecting and recording costs. Keywords: wine business, winegrowing sector, accounting management.
1. Introduction
Wine-growing farm management is becoming increasingly more complex in terms of the technical-production aspects and economic-financial aspects (Casini et al. 2012). The internalisation of markets and the consequent growth of competition make it necessary to find innovative solutions to support a more efficient and more effective farm management. Knowing the costs of production is a fundamental element in farm management (Hill 2000; Kaplan 2002), and is at the basis of a proper strategy to determine the sales price and to verify the efficiency of the various production phases (Agliati, 2002; Mastroberardino, 2002; Salghetti, 2007). The offer of managerial software is currently quite wide, but these are mainly programmes conceived for the manufacturing sector, and not for that of agriculture, and even less for the winegrowing sector. The quite limited diffusion of computer-controlled systems in the Italian winegrowing sector can be explained by both the unaffordability of these instruments for small and medium-sized farms in relation to their dimensions and total sales, and by the lack of specific systems built to efficiently respond to the peculiar characteristics of the winegrowing farm. The near totality of winegrowing farms is represented by multi-product concerns that encounter objective difficulties in attributing indirect or shared costs (Juchau 1996). We are referring to costs generated by production factors employed in more than one production sector and, within the same production sector, by more than one product (i.e. the amortization of a machine, administrative and commercial costs, financial, taxation and insurance burdens etc.) (Watts 1990). Consequently, costs are normally measured by converging indirect or shared costs into cost centres (Brusa1995), but also by following the Activity Based Cost method (Bubbio 2001), which means debiting these costs to the management activities that generated them. In the first case, we must identify the smallest cost centre (production, auxiliary and function) whose costs (indirect with respect to the single product) become direct with respect to the cost centre itself. Accounting by activity, on the contrary, makes it possible to identify the causes that generated each cost, with positive implications in formulating future management programmes by the farm (Ciaponi 2005).
While the main problem is to supply systems of analysis that are certainly necessary even without utilising an analytical industrial accounting system, resorting to mixed systems could allow us to limit surveying to only those elements essential to feed the few cost centres required to offer the data necessary to determine the cost of a specific activity. Once the cost by activity has been determined, if this significantly differs among the vineyards (and therefore among the different wines which we presume to be our final product), the activity cost can be divided up in relation to the parameters that have been identified as the causes for these differences (soil conditions, specificities of grape species, etc.) (Cinquini 2008). The purpose of this study is to propose a management control model which, for the time being, targets establishing the winegrower’s production cost for a single bottle of wine (Juchau 2001), and flexibly utilises the tools of management accounting by cost centres and/or by activity on the data already available to each winegrowing farm. Towards this end, we have built a specific software capable of determining the cost differences for each product typology even departing from little available information. The system can accept information with different levels of precision, and makes it possible to increase the degree of precision of the final result by refining the information gathered from one year to the next.
2. The proposed model
The winegrowing farm is characterised by very diversified production phases which are in turn characterised by the fact that in each phase (Booth 2003), the product of the previous phase, as well as the product originating from outside of the farm, can be acquired as inputs. Likewise, for each phase, it is possible to transfer the product to the following phase or place it on the market. In order to render the system adaptable for the most diverse farms of the sector, the control model has been studied so that it can uncouple the 4 phases of winemaking, which are at times also associated to different farm typologies: Phase 0 – Production (from the vineyard to grapes);
——————— * University of Florence, Italy, Department of Agricultural, Food and Forestry Systems Management, E-mail:
[email protected]. ** University of Florence, Italy, Department of Agricultural, Food and Forestry Systems Management, E-mail:
[email protected]. *** University of Florence, Italy, Department of Agricultural, Food and Forestry Systems Management, Corresponding author, E-mail: gabriele.
[email protected].
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QUALITY MANAGEMENT Phase 1 – Transformation I (from grapes to vintaged wine); Phase 2 – Transformation II (from vintaged wine to aged wine); Phase 3 – Bottling and marketing (from aged wine to labelled bottle).
From planting up to the bottle, and by successive phases, the software processes the costs of grapes, vintaged wine, aged wine and bottle per single “label”, providing a final and provisional profit and loss statement that simulations can be performed on, in order to support the strategic business decisions typical of the sector. Each phase of the winemaking process is characterised by the presence of incoming raw materials and outgoing semi-finished products/finished products. By means of the value chain, the single activities of the winegrowing farm can be analysed, identifying their related costs and profits. Using this model, we can thus understand the farm’s capacity to generate value along the ordered sequence of the activities it performs. This value is the result of the difference between profits generated by products sale, and the costs sustained in performing the activities. The software follows an analogous approach and, by inserting in every phase, the data related to the costs sustained and the profits obtained, it calculates the value generated by each activity. One of the model’s innovative elements is represented by the possibility to calculate the accumulated costs for wines that will be marketed over the span of several years. The software is indeed capable of transferring the production costs recorded in one year to the following years, working on the data related to accounted stock, which is available both in terms of quantities and value. By subtracting the quantities sold each year from the “initial stock”, and marking up the quantities transferred by their related costs, we can identify the additional cost (for example, the cost of the depreciation quotas of the containers occupied for aging the wine for several years) for the product that comes out of the production cycle after various years. The database indeed has a cascade functioning whereby each piece of information inserted in one phase, is transferred to the following phase. The system has a user interface that can run in Excel, and utilises an SQL server as a database and to analyse data. It is divided into two distinct files, one called “Records management”, the other “Economic analysis”. Each of these files analyses the four previously described phases. The “Records management” file makes it possible to manage the information related to the production techniques adopted for each year. It is divided into a “general” part that serves all the production process phases, and a “specific” part for each of the 4 phases analysed. The “general” part collects information pertinent to the data on the machines and equipment, labour, vinification and ageing tanks, and the containers for marketing the products. The information of a “general” nature concerns the typology of the factors utilised, their purchase value, expected economic life, costs of farm and extra-farm maintenance, hours of use per year. These records of a “general” nature embrace the data related to generic expenditure listings, that is to say not attributable to a specific vineyard/wine, such as for example, administrative, distribution, commercial, financial and energy costs, part of labour costs, part of machines and equipment costs, third-party expenses, consumables, extraordinary maintenance, consultancy and insurance costs. In these records, for each listing analysed, the production phase and year it refers to must be indicated. The “specific” records are instead attributed to the processes that are characteristic and exclusive to each of the 4 phases identified; they are divided into two separate sections. The first section contains the descriptions of human resources, machines and raw materials necessary to feed that specific phase of the production process with respect to a specific vineyard/wine. In the second section, the productions, quantities and values of grapes/vintaged wine/ purchased or sold wine are indicated for each grape species and for each vineyard. In phase 0 which refers to grapes production, the factors considered for each vineyard are planting density, surface area,
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slope and annual cost of terrain (i.e. property lease), distance from the cellar, the non time-discounted cost and planting fees, vineyard life as expected by the winegrower, form of cultivation, complexity of management and day/month of harvest. This information enables us to distinguish, for example, between a vineyard planted on level terrain with soil characteristics capable of facilitating its cultivation, situated near the cellar and another vineyard situated on a steep incline, hard to cultivate, and more distant from the cellar. This information is then tied to quantifying the single field activities in terms of hours and/or total cost of labour and of the machines utilised. In the second sector and again for each grape species and for each vineyard, we define the productions, purchases and sales expressed in quintals recorded. The same approach is used for phase 1, that of winemaking. In its first section, each grape species and thus each grape production is associated to the corresponding vintaged wine made and the quantity produced. In the second section, called “Vintaged wine stock”, the initial and final quantities of vintaged wine are indicated, along with the losses recorded during this phase. In particular, the software automatically retrieves the quantity of vintaged wine produced and inserted in the previous phase, labelling it as “initial”. From this amount, it then subtracts the quantity that remains in the vintaged wine stock at the end of the pertinent year (“final quantity”) and the quantity that, having terminated the winemaking process, starts the ageing process (“transferred quantity”), thus calculating the “inventory adjustments”, that is to say the losses. In this case too, the system adapts to the specific farm realities and allows the insertion of the quantity of vintaged wine that has been purchased or sold outside the farm, with its respective price. Furthermore, this screen also visualises the “initial cost”, calculating the production cost of each vintaged wine produced. The phase 2 records, which refer to the ageing of vintaged wine, are made up of the sections “Aged wine” and “Aged wine stock”, similar to the corresponding phase 1 sections. Moreover, in this phase, the “Ageing tanks” described in the general records are associated with the wines they contain, the respective quantities, and the ageing period. When wine ageing lasts for periods of more than one year, as generally occurs, the software retrieves the “final quantity” inserted in the previous year and labels it as “initial quantity” of the current year. In this way, the system facilitates entering data, especially for those wines characterised by a particularly long ageing, and makes it possible to monitor the spills and weight losses that occur in this phase. Before entering the data on the finished product, phase 3, it is necessary to define a priori the mix of wines and the packaging to use for bottling, by means of describing the various mixes made, their composition, the type and quantity of containers utilised. Finally, the phase 3 sections consider the last part of the production process which concerns packaging and marketing, and consists of two sections: the “Finished product” and its related “Stock”. In addition to providing information on the finished product’s commercial name, related quantities, original mix and packaging, the “Finished product” screen also indicates the cost of possible damage and breakage, time in the cellar, percentage of returns and unit prices of the material used in packaging. In the software’s second file, called “Economic analysis”, the costs for all the phases of the winegrowing production process are processed by means of automatically drafting a final and/or provisional profit and loss statement. This second file functions by identifying algorithms for indirect costs allocation for each phase of each product, to which it adds all the direct costs defined in the records file. The system proposes several parameters to make the allocation on, such as surface area and grape species production, distance from the cellar, and management complexity, but it also permits the user to manually enter the drivers and to attribute specific allocation percentages to each criterion defined. In this way, veritable algorithms are defined which, considering several factors, permit us to attribute and distribute the listings of the generic costs on the semi-finished products and on the finished products. In particular, all the expenditure listings that constitute the cost of production can be allocated in function of
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QUALITY MANAGEMENT specific drivers that can be modified in function of the cost listing and of the production process phase. After identifying the drivers, in “Economic analysis”, the software visualises the direct and indirect costs, and calculates the total and unit costs referring to the final product of each phase, until it determines that of the single “label”. In this section, the system identifies the incoming raw materials and the outgoing final products of each stage of the production process. For example, for the phase 0, whose input is vineyards and output is grapes, the software defines the planted vineyard units and related grape species, while for phase 1, the system identifies the vineyards the grapes come from and connects them to their respective vintaged wines. For phase 2, the aged wine products are identified, placing them in relation to the vintaged wines they come from, and in phase 3, the connection between finished product and mix of origin is defined. The system thereby makes it possible to trace the product, given that it can trace the grapes and the vineyards of origin for each “label”. For each phase, the software processes the quantities produced and sold with their respective profits, also considering the quantities of semi-finished product that the winegrower purchases externally or markets directly, and defines the quality and value of the initial and final stock. Stock value is calculated as a unit production cost multiplied by the quantity on hand, while it is expressed as market value in the accounting balance. The production cost processed by the software is therefore the function of the quantities and values of the stock. Furthermore, it is possible to identify the weight of direct and indirect costs on the production cost of the semi-processed product and the single final product, with all of their listings of expenditure, subdivided by macro-categories.
3. Data Analysis
The proposed software allows to obtain useful information both in the context of microeconomic (check the efficiency of business management) both at territorial level (definition of planning strategies). In the preset research we propose some of the results that can be properly used for the macroeconomic approach. The model was tested on 40 representative wineries of DOCG Chianti Classico, based on data referred to the 20092010 vintage wine, with the aim to verify the functionality and effectiveness in the definition of the average production cost. For each winery, data on the most spread type of wine were gathered in order to define its production cost per bottle. This choice allowed us to analyze homogeneous data for several reasons: the limited area in which this research was conducted, the farm type (all of them run throughout the entire production process, from production to bottling the grape) and the fact that for each winery the basic product was considered. The results showed that the average cost of production of a bottle of Chianti Classico DOCG is equal to 4.89 euros, with a minimum value of 3.66 euros and a maximum of 9.62 euros. The first result that came out thanks to the use of the software has been to discriminate the costs in relation to the different stages of production. This aspect is one of the strength of the instrument used as it allows to define both at farm and territorial scale the convenience of unifying the whole production process in a single winery or outsource a part of the process. In the analyzed case the costs that are more relevant to production of a bottle of Chianti Classico are those attributable to packaging and marketing (43%) and secondarily those for the production of grapes (34%); wine (13%) and aging (10%) account in a minor way (Figure 1). These results show how the choice of bottling is costly (56% of the total cost), and thus it is economic sustainable only if entrepreneur uses a distribution channel that is able to assure prices that cover all the costs. From the other side, the option of selling not bottled wine shows even more problems. As a matter of fact, the average production cost for Chianti Classico DOCG bulk wine is of 2.87
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Figure 1. Percentage distribution of average costs for each phase of production per bottle (Chianti Classico DOCG)
euros/litter (with minimum value equal to 1.79 and maximum 5.73 euros/litter), while its average selling price in recent years is around 1.45 euros/litter (Source: Chamber of Commerce of Florence 2009). From the decision maker point of view these results give a very important information for the definition of territorial policies. For example, high incidence of bottling and commercial cost might suggest further policy towards territorial actions that could reduce these costs or that increase consumer willingness to pay in respect of wines bottled on the farm. The second strength of the software is to identify the nature of the production cost by dividing them into explicit costs, implicit, variable and fixed. The survey results showed that the weighted average explicit costs amounted to 3.18 euros/bottle and those implicit to 1.71 euros/bottle. Examining the distribution of cost types we notice that the variable costs (32%) represent the largest proportion, followed by depreciation (20%) and labor not provided by the family (21%). Less weight, however, is represented by the general costs (12%) and family labor (9%), while interest on capital, land rights and replanting absorb only 6% of the cost of production (Figure 2). The variables shown until now are aggregated values, but in reality the software allows a much greater level of detail. As a matter of fact, it is possible to decompose the variable costs (packaging, distribution costs, marketing, third party, DOCG certification, pest management, fertilizer, fuel, sundries store, etc.), the depreciation (plant vineyards, buildings, wood small, large wood, equipment, agricultural machinery, tanks, vehicles, etc.) and the general costs (consulting, maintenance, taxes, rents, energy, administration, insurance, etc.).
Figure 2. Percentage distribution of average costs by type of cost per bottle (Chianti Classico DOCG)
The third point of force of the proposed model is represented by the fact that the analysis of the nature of the costs described above can be carried out also at the level of each single phase of production. The data are not reported here due to space, but they might offer additional interesting information under the view of a more efficient business management.
4. Conclusions
The system transfers the costs of each phase onto the successive phase, and reports both the value of the entire production that emanates from the previous phase and the figure allocated by product typology, and to this figure it adds the direct and indirect costs of the specific phase. In the case of a phase that lasts for several years, the system visualises the production cost recorded up until the previous year, and to this it adds the
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costs determined by the lengthening of the production process. For example, the software calculates the cost generated by lengthening the ageing period, which enables the winegrower to identify the incidence of the costs determined by the wine’s prolonged permanence in the cellar, on the overall production cost. Market prices of the analyzed type of wine highlight a situation in which it is difficult to cover the production costs, moreover if the long-term costs and the costs for the remuneration of all factors of production are considered. The depth analysis of production costs, which became possible thanks to the use of the software, showed that the option of selling bulk wine is not being sustainable as the prices of such products in recent years have remained at about the 1.45 euros/litter while the production cost oscillates between 1.79 and 5.73 euros/litter. The solution of bottling has shown a significant additional cost to the winery (nearly 60%) and a high concentration of production costs per bottle in a range between 3.7 and 4.7 euros, with only some exceptions with higher costs. This outlook enables the winegrower to examine how much the wine product has cost or, in a provisional hypothesis, would cost, and to compare this unit cost to the sales prices, which enables him to make the first decisions in terms of strategic
choices. The software thereby offers the winegrower tools to improve the farm organisation at every stage of the production process and within the same phase, with respect to the various cost listings and individual vineyard units. At the same time, all these information might be used by the decision maker too for the development of useful territorial policies and actions. Utilised on various sample winegrowing farms, the software pointed out many shortcomings of a management nature in the farms studied, which can be solved only by means of a precise survey of the possible costs that only precise and detailed surveying can produce. Even without a rigorous analytical accounting system, the experiment conducted with the software has shown that also reclassifying the accounting data can lead to satisfactory results. In the case-studies examined, the failure to define an analytical accounting system has entailed the necessity to begin experimenting the system by analysing the balance sheet and, in particular, examining the data in the profit and loss statement. As these are divided into macro-categories, the direct contact with the company’s management and administration has made it possible to implement several general criteria to reclassify them and attribute indirect costs to the pertinent company Q-as sector and to the pertinent production process phase.
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