A Process for Product and Service Definition David Callele Department of Computer Science University of Saskatchewan Saskatoon, Canada callele@cs.usask.ca Krzysztof Wnuk Department of Computer Science Blekinge Institute of Technology Karlskrona, Sweden krzysztof.wnuk@bth.se Abstract— This short paper presents an iterative and incremen- tal process to improve the probability that the product or service definition leading to requirements and implementation is both representative of the market needs and has a reasonable expecta- tion of a financially viable business model. Rather than a relative- ly linear process wherein marketing delivers a product definition to the development team, this process ensures that all assump- tions are validated during the definition stage and that all team members are engaged. The process balances the need to address current challenges against future opportunities, providing short- term customer satisfaction (and justification for purchasing or adoption) and a coherent vision for future development efforts (and maintaining and growing the customer base). The process is applied to a case in the agriculture commodities sector. Index Terms—Product definition, service definition, process. I. INTRODUCTION Product definition is always challenging, especially for Software As A Service (SAAS) applications [2]. Barriers to competitive entry are often low and competition can be fierce – especially if the target market expects the service to be free. Competitors can register as users, study the service and use a fast-follower business model to copy differentiating features thereby rendering the initial innovation investment a high-risk decision. Service providers must quickly become the dominant platform in their sector or become “just one more competitor” in the marketplace. The need to become the dominant platform means, especially in the era of free software where the user data is monetized instead of explicitly monetizing the service, that services must be launched as broadly as possible in the hopes that they can engage sufficient early adopters to domi- nate their market via the network effect. SAAS providers are further challenged by the need to be a service leader rather than a follower and to capitalize on inno- vation investments such as market research, business case analysis, requirements engineering and software engineering [1]. To maximize the potential return on innovation investment they must maintain barriers to competitive market entry, espe- cially when threatened by service clones, while cost-effectively acquiring, and keeping, paying customers [3]. Requirements Engineering (RE) traditionally focusses on precise product or service definitions; ISPMA, the International Software Product Management Association considers RE to be the core of product planning [5]. However, many RE practi- tioners first define a list of requirements or a list of features based on their imperfect and potentially biased view of what the system should do or how the needs/goals are constrained by the requirements. Only after the requirements are generated is a competitive analysis performed, if at all – in many cases the RE practitioners expect that this task has been performed a priori or is someone else’s responsibility [6]. We present here an iterative, incremental process leading to requirements definition that incorporates techniques from busi- ness case analysis (principally competitive analysis and finan- cial viability analysis), requirements engineering and software engineering to deliver financially viable results that meet mar- ket needs. While this process has been successfully applied to the B2B SAAS case presented in this work, the process has also been used for product definition. II. CASE CONTEXT We describe the grains sector of the agriculture market, in the context of a Canadian firm operating within the North American marketplace by characterizing the supply chain and focusing on the interactions between farmers and buyers as they supply and purchase these commodities. There are approximately 200,000 farms in Canada of which approximately 100,000 are situated in the prairie provinces of Alberta, Saskatchewan and Manitoba, the core Canadian grain producing areas. Grain and oilseed production in the prairie provinces generates approximately $25B CDN in annual gross receipts. Approximately 5% of the farms generate approxi- mately half of these gross receipts; farming operations are increasingly consolidating into ever larger operations. There are both great distances and complex supply chains between the supermarket and the origin of the food in the store and software systems can contribute to managing all aspects of this complex environment. A. Technology in the Agriculture Sector Grain farming is now technically sophisticated and utilizes numerous technologies that highly optimize the production process. These technologies are generally referred to as preci- sion agriculture. Precision agriculture employs a wide variety of data sources that feed a decision support system that guides the farmer’s production processes in a wide variety of ways. Typically, location-specific characteristics such as topography, moisture levels, soil nutrients and past crop production results are mapped into a geographic information system – often at resolutions of up to sub-meter accuracy. This data is then ana- lyzed and, for a given commodity, highly targeted site-specific Author's copy