What Are the Needs to Agricultural Software? An Analysis of Experiences and Requirements of Agricultural Consultants

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1 What Are the Needs to Agricultural Software? An Analysis of Experiences and Requirements of Agricultural Consultants Rainer M. Sodtke a, Manuel Gottschick b a University of Hamburg, Research Center of Biotechnology, Society and Environment, Hamburg/Germany, rainer.sodtke@uni-hamburg.de b University of Hamburg, Research Center of Biotechnology, Society and Environment, Hamburg/Germany, gottschick@agchange.de Abstract Agricultural software can improve the quality of agricultural consultancy and may augment the farmers income while causing a lower impact on the environment. However, agricultural practice reveals that sophisticated software solutions are not widely accepted. This study evaluates the requirements of 38 consultants on agricultural software. In a series of qualitative interviews, we asked about the type of software that consultants usually apply and which specific problems, experiences and obstacles they were confronted while using them. The questioning was focused on the pros and cons of Excel applications which are widely used among consultants, commercial agricultural software and scientific computerbased decision support systems (DSS) in crop production. The results showed that Excel applications are very common because of their great flexibility, transparency and modifiability. Whereas complex software and DSS are viewed more sceptically because they do not fulfil these functions. By a detailed analysis we draw conclusions for the further commercial and scientific development of agricultural software. Key words: Agricultural software, decision support systems, Excel, agricultural consultancy, qualitative interviews. 1 Introduction Agricultural software is conceived to support various processes related to agriculture and farming. It may possibly improve the quality of agricultural consultancy, help to increase farmers income or help to diminish unintended impacts on the environment (Werner et al., 2000). Accordingly, in the past numerous ICT tools for agricultural decision support have been developed just in the EFITA proceedings from 1997 to 2005 about 50 papers deal with decision support systems (DSS). However, agricultural practice and scientific research reveal that sophisticated software solutions are not widely accepted. Farmers as well as consultants still very infrequently make use of DSS provided by scientific organisations (e.g. Gelb and Offer, 2005; Parker, 2005). Since several studies investigate reasons for adoption constraints and software requirements by farmers (e.g. Rosskopf and Wagner, 2003; Stricker et al., 2003) only few information is available about what kind of software agricultural consultants use, neither what are their experiences nor their requirements to it (e.g. Morrow et al., 2004). Agricultural consultancy in Germany is a rather inhomogeneous sector characterized by various types of institutions and modes of funding: State-run, semi-public and private non-profit services as well as commercial consultancy which are more or less funded by public money and/or by farmers membership fees or charges co-exist to varying degrees in the Federal states (Hoffmann et al., 2000). Additionally,

2 farmers may receive product-related consultancy, e.g. by suppliers of agricultural machinery, seeds, fertilisers and pesticides, by companies of the agricultural food chain, banks, insurance companies etc. The main task of consultancy is to provide farmers with knowledge and expertise which is both, actual and relevant for management decisions, i.e. problem-specific, comprehensible and applicable for practical use by different clients. The consultants advisory work comprises all aspects of farming, like scheduling of crop production, animal husbandry, financial budgeting, subsidy acquisition, quality management as well as socio-economic consultancy. This work involves to talk to farmers, face-to-face or via telephone, and to discuss farm records and operational goals with them. Moreover, consultants frequently arrange the exchange of experiences between farmers, e.g. through farmers working groups. The study presented in this paper analyses utilisation of and requirements to agricultural software by 38 consultants in northern Germany. In a series of qualitative interviews, we asked about the type of software that consultants usually apply and which specific problems, experiences and obstacles they were confronted while using them. 2 Methods Within the scope of an interdisciplinary research project 1 we interviewed 38 agricultural consultants by telephone and by means of a qualitative manual. The interviews were half-standardised i. e. with open and given possible answers and took approximately 20 to 40 minutes. In general, the manual was sent to the interviewees in advance. The questioning dealt with agricultural software for crop production. It was focused on the pros and cons of Excel applications which are widely used among consultants, commercial agricultural software and scientific computer-based decision support systems (DSS). A first set of interviews with eight consultants was conducted by Milena Schuldt in August 2004 (Schuldt, 2005). The results were considered for the design of a second series of interviews in winter 2005/06. This article summarises the results of the second interview series. The group of the interviewed consultants can be characterised as follows: The consultants mainly work as employees for lobby organisations in Northern Germany (mainly in Lower Saxony and Mecklenburg- Western Pomerania). Only a few of them are privately organised. The sample did not contain state-run consultancy. The consultants usually are organized in offices with two to five employees. Their professional experience varies between less than five years and more than 15 years. Most of the interviewees were male only two were female. Each consultant gives advice to 20 to 160 farmers with an average of 80 farmers. Farm sizes vary mostly between 75 and 200 ha (rarely between 200 and 500 ha or more than 500 ha). Most consulted farms cultivate cash crops or produce forage in conventional farming. Ten consultants also advise organic farms. 3 Results 3.1 Utilisation of spreadsheet analysis software Modern agricultural consultancy is not possible without using software in almost all fields of advisory. According to the first series of interviews our results suggest that consultants very commonly use spreadsheet analysis software (our interviewees solely refer to MS Excel applications). This holds especially for farm scheduling, production planning and financial budgeting. For advisory in crop production, animal husbandry, cross compliance and quality management most consultants prefer available commercial software but here many of the interviewees apply Excel applications, too. Excel applications from most of the consultants point of view offer the advantage of being very adaptable and user-friendly. This is also expressed in the other mentioned positive attributes: Excel applications are described as well arranged and understandable, fast, orientated to practical work, up-todate and less expensive than commercial agricultural software. For being used in consultancy it is very important that integrated formulas can be checked or manipulated. Calculations have to be transparent so that the consultant can present the accomplished results to the farmer. One consultant put it like that: 1 The research was conducted under the project AgChange. Conflicts of the New Agricultural Policy, funded by the German Federal Ministry of Education and Research under the Programme Social-Ecological Research (SÖF), cf.

3 Comprehensible results are very important. So far, I have not come across a commercial software with this ability. In this context it is also of some importance that the consulted farmers are used to work with Excel, too. Thus, it is possible that Excel applications can be handed over from the consultant to the farmer and can be used and changed by him in future. In accordance with these findings many of the interviewees are also of the opinion that Excel applications do not have any disadvantages. When asked more insistently, however, some consultants find fault with an insufficient functionality, a lower comfort, and a faulty layout in comparison with commercial software. The consultants criticise a relatively high risk for errors when changing formulas or when a farmer inputs data. Some respondents also mentioned restrictions when importing data or comparing results as well as software instabilities when processing high data volumes. Finally, most of the consultants emphasized their interest in further improving their Excel applications. Frequently the revision by experts was suggested: "Improving our own Excel application can not be done by an ICT specialist. Only an experienced consultant may further develop our applications." Professional training and support were mentioned, too. However, respective training should be based upon the consultants' experiences and requirements. 3.2 Utilisation of software for decision support In order to analyse the fields of application of agricultural software the consultants were asked to name the activities at which they employ software. Therefore, we divided the advisory process into the following phases: problem analysis, information retrieval, decision making, accompanying the farmer's implementation of actions, controlling, and iterative improvement of farmers actions. Most consultants particularize that besides problem analysis they apply software especially in the field of decision making. One consultant confirms: "I wish to use software in accompanying the farmer's actions, but unfortunately it is not possible." Another states: "For controlling I have to check a crop stand on my own." The results may indicate a software utilisation or need, respectively, in case of decision making that are decision support systems (DSS). However, the following results show that the consultants' understanding of "software for decision support" is obviously different from a scientific point of view (cf. Bonczek et al., 1981). In order to analyse more distinctly if the consultants actually use DSS for cropping advisory we proposed a scheme of software functionalities with an increasing degree of complexity. The consultants were asked if they knew and/or use, would like to use, like to get to know agricultural software with such functionalities, or if they judge it as not useful for their job. The proposed functionalities comprised: (1) documentation, (2) information and data processing, (3) visualisation, (4) accounting, (5) access to external information (e.g. weather data), (6) scheduling/predictions (e.g. yield estimation), (7) scenario planning (comparison of options, implications, risk analysis), (8) procedures for objective-oriented evaluation and ranking, (9) combined systems for option/scenario generation, objective-oriented evaluation/ranking and recommendations. The last category is equivalent to our understanding of DSS. But we avoided to use the term "DSS" in order to get unbiased information. The main result was that the more complex the software functionality is in the proposed scheme, the less the interviewees know or use such a software and the more sceptic and prejudiced against such a software they are (Fig. 1). Almost all interviewees stated to know or use software for documentation, information processing and accounting purposes. To a smaller degree this holds also for visualisation software. Software which enables to access external information is known or used by half of the interviewees. About 3/5 of the interviewees stated to know or use software for scheduling/prediction or scenario planning. Software for evaluation purposes is used by 1/6 of the interviewees, known by every third. Only three interviewees said that they also knew and use combined systems. About one third to one sixth of the interviewees pretends that they like to use software that allows to access external information, scheduling, scenario planning/evaluation or combined DSS on principle. However, with an increasing degree of complexity the number of interviewees who judge a respective software as not useful for their work increases, too. In case of combined systems (DSS) this number is almost one third of the consultants. One interviewee formulates: That s the work I am doing as a consultant! I don t think that computer programs would help us here. It is a cross-linking within the brain evolved in the long run and referring to the region. Another states: Systems for scenario planning and evaluation are unreasonable, too complex. My own assessments on errors and ranges are sufficient.

4 Documentation Information Visualisation Accounting External information Scheduling Scenario planning Evaluation Combined functionalities known used like to use not useful like to get to know 0 10 Number of answers Fig.1 Knowledge, utilisation and needs of agricultural software with different functionalities Everyone wishes something else from his software. Such complex applications (like DSS) cannot exactly fulfil what is needed. They are too specific. Other interviewees are open to use software offering extensive functionalities: If-then-analyses and scenario planning would be tempting. Summing up, it may be stated that there is a (small) number of consultants which does not use DSS but which is still interested in using it in the future. 3.3 The good fairy of informatics: three wishes free Finally, we wanted the consultants to point out in which direction agricultural software should evolve and to specify further software properties they are missing up to now. The aim was to receive creative hints on software requirements which differ from the known functionalities and which may be satisfied by medium-term developments. Therefore, the question was put in such a manner that the consultants had to imagine a good fairy would fulfil three of their wishes. The interviewees were asked to specify three software improvements or solutions they desired most for consultancy. The various answers we received to that question we related to the categories: (1) Desired common software properties, (2) desired specific functionalities of agricultural software, (3) desired complete agricultural software products (cf. Tab. 1). Amongst the common software properties a simple and comprehensible operation modus is quoted most frequently. Furthermore, the software should preferably not contain any errors and should be easy to modify. The software should offer preferably quick queries and should also be comprehensible to the farmer. Periodical updates should guarantee the software s actuality. However, it should not be updated too often so that we are not continuously forced to purchase new software. Another expresses: The fairy should not be too quickly (in fulfilling our desires), so we may keep pace with the development. Amongst the specific software functionalities half of the interviewees desires interfaces to commercial software in order to facilitate easy data exchange. Especially in case of farm scheduling software many interviewees require manifold analysis options and a respective wide range of software functionalities. Further wishes refer to automated data acquisition and data input, possibly free access to centrally stored data and techniques of speech recognition. Regarding complete agricultural software products the interviewees most frequently specified the availability of simple farm scheduling systems as well as scheduling systems with integrated modules for scenario analysis and forecasting. At this, particularly the option to conduct perennial schedules (e.g. in case of crop rotations) was named. Furthermore, a low-cost solution for a controlling software e.g. usable for developing farm-specific bench-marks is desired. To summarise, agricultural software on the one hand, should be simple to operate and to input data on the other hand, it should be utilisable in various fields of consultancy and situations. One consultant subsumes: An ideal agricultural software is like an easy-to-handle all-in-one device suitable for every purpose.

5 Tab. 1 Desired improvements and solutions of agricultural software from the consultants perspective Category Desired software improvements or solutions Number of answers (a) Common software properties Simple to operate, comprehensible 11 Error-free, confidential data 6 Modifiable 5 Actual (updates) 4 Updates not too often 2 Quick queries 2 Comprehensible to the farmer 2 Portable to other operating systems 1 Telephone service 1 (b) Specific software functionalities interfaces/data exchange with commercial software, compatible 15 Comprehensive functionality/diversified analysis options 9 Automated data acquisition/data input 3 Free access to centrally stored data 2 Speech recognition 1 (c) Complete agricultural software products Simple farm scheduling system 8 Integration of scenario analysis and forecasting options 8 Low-cost controlling software (bench working) 3 Perennial scheduling system 2 Simple rating system (farm comparisons) 1 4 Conclusions In order to get information about software use and requirements we applied and analysed a set of qualitative interviews. This explorative method may indicate how software is used by agricultural consultants. However, interpreting qualitative interviews may lead to wrong conclusions if the results are supposed to be representative for all consultants. The qualitative approach illustrates that the results could be found within our sample. But no evidence can be given if and how many other opinions exist in the entirety of agricultural consultants, nor any information about the frequency of the findings. Furthermore, as it is generally true for interrogations, individuals which are willing to give an interview usually are open-minded to the thematic. Therefore, it must be taken into consideration that the interviewees may answer questions e.g. to the interest in DSS more positively than they would in the everyday practical routine. The main result of the analysis is to recognize that consultants do not seem to ask for scientific expertise in the form of complex agricultural software products as they are developed by agricultural scientists and/or offered by commercial suppliers. In the contrary, agricultural consultants prefer comparatively simple Excel applications because of their great flexibility, transparency and modifiability. Whereas complex software and DSS are viewed more sceptically because they do not fulfil these functions. This raises the question if and how software developers are interested in improving Excel applications as a short-term strategy to support consultancy. For this aim, it seems promising to improve interfaces for data exchange, to develop respective macros for data conversion, or to generate add-ons to be integrated into the spread-sheet in order to extend the applications functionalities. Add-ons could e.g. manage the data transfer to external software as well as access information stored in data bases such as data from actual agricultural statistics, weather data or other information for plant protection. If software developers would rather support agricultural consultancy in the long-term knowledge-based systems and other classical commercial software should be further developed. The technical requirements to such a software may be summarized to the following four aspects: (1) The software must contain interfaces for data exchange with other agricultural software, (2) it must be simple to operate, (3) internal calculation procedures have to be kept transparent and (4) the software must be kept modifiable in order to be adaptable to a specific advisory situation.

6 However, these technical aspects are not sufficient for increasing software adoption. This holds particularly for complex software solutions like DSS which are per se conceived to relieve the user of integrating knowledge and evaluating management options. Our results suggest that DSS do not facilitate the advisory work nor improve the quality of consultancy because consultants do not use DSS they do not understand. Accordingly, the more complex a software s functionalities are i.e. the more functions of a DSS (in a narrow sense) they integrate the less they are used, the less they are known and the less their usefulness is known by consultants, either. One reason for this might be the personal confidence placed in consultants by farmers which is primarily based upon personal sympathy and technical competence (Weiland et al., 2007). Obviously, in order to approve and increase this confidence consultants want to have the feel of their agricultural software on their own. Therefore, it is important for the consultant that he/she does not rely on a prefabricated software which a farmer could also use without a specific technical competence but offers his own specific software solution. Furthermore, a farmer expects a consultant to explain and substantiate every given advice in detail. If the consultant could only refer to a hardly comprehensible DSS he would not be able to explicate the facts in depth and so he would possibly risk the farmer s confidence. Nevertheless, our results indicate that there is a small number of consultants who admittedly do not use any DSS but who are anyhow interested in using it. In order to motivate these consultants in using agricultural software its development has to be integrated more deeply into the consultants workflow, i.e. the social process of advising farmers. And it has to be integrated into the staff training process. For this, a DSS from the first beginning has to be developed in close cooperation with the users in terms of a transdisciplinary approach. Such a DSS would not necessarily lead to other or better decisions in the first instance but it could relieve the consultant in his/her job. In a following step such a system could be enhanced by knowledge bases and evaluation algorithms in a target-oriented manner. To summarize, we assume that there is a gap between consultants software needs and software use which cannot be closed by an improved communication or training. In fact, agricultural software has to better address consultants practical needs. From the consultants perspective, existing scientific and commercial software needs to be improved. Agricultural software has precisely to fulfil the technical and non-technical demands of consultants because as one interviewee said : Toys in the shape of computer programs do really exist enough. 5 References Bonczek, R. H., Holsapple, C. W., Whinston, A. B., Foundations of Decision Support Systems. New York. Gelb, E., Offer, A., ICT in Agriculture: Perspectives of Technological Innovation. E-Book available at European Federation for Information Technology in Agriculture, Food and the Environment (EFITA) and The Hebrew University of Jerusalem, Center for Agricultural Economic Research, Jerusalem, Israel. Hoffmann, V., Lamers, J., Kidd, A. D., Reforming the organisation of agricultural extension in Germany Lessons for other countries. AgREN Network Paper, 98. odi Agricultural Research & Extension Network. Morrow, L., Kelly, T., Kirley, T., ICT - Its Potential as a Channel for Enhanced Extension Services. AIAEE 2004, Proceedings of the 20th Annual Conference. Dublin, Ireland. Parker, C. G Technology Acceptance and the Uptake of Agricultural DSS. In: Boaventura Cunha, J., Morais, R. (Eds.), Proceedings of the EFITA/WCCA 2005 Joint Conference, July Vila Real, Portugal, Rosskopf, K., Wagner, P Requirements for agricultural software and reasons for adoption constraints results of empirical studies. In: Harnos, Z., Steffe, J., Herdon, M. (Eds.), EFITA2003 Conference Papers. 5-9 July Debrecen-Budapest, Schuldt, M., Erfahrungen mit Agrarsoftware, Schwerpunkt Entscheidungsunterstützung. Ergebnisse einer Befragung von landwirtschaftlichen Beratern. BIOGUM-Research Paper, 14. University of Hamburg, Hamburg. Stricker, S., Emmel, M., Pape, J Situation of agricultural information and communication technology (ICT) in Germany. In: Harnos, Z., Steffe, J., Herdon, M. (Eds.), EFITA2003 Conference Papers. 5-9 July Debrecen-Budapest, Hungary, Weiland, S., Gottschick, M., Sodtke, R., Governance for Sustainable Agriculture. The Role of Agricultural Consultants as Change Agents. J. of Env. Policy and Planning. Special Issue on Governance for Sustainable Development. 9 (1), (in press). Werner, A., Bachinger, J., Sodtke, R., Roth, R., Jarfe, A., Zander, P., Schuler, J Decision support systems in crop production on the farm and field level. In: Kukula, S., Fotyma, M., et al. (Eds.), Development of sustainable agriculture on the verge of the 21st century. Pamietnik pulawski - Materialy konferencji Zeszyt, 120/II