Objetivo general del proyecto. Tomar en cuenta todas las asignaturas involucradas

Schrage (1990), emphasizes that the issue in collaboration “isn’t communication or teamwork, it is the creation of value”. Following this, it is possible to conclude that he was looking at collaboration from a perspective of the desired result. Nonetheless, it is in the processes behind that final goal (i.e. the product manufactured, sold, etc.) that interoperability becomes an issue.

In today’s networked economy, strategic business partnerships and outsourcing have become dominant business paradigms evidencing a tremendous increase in trade and investments between nations. According to Friedman (2005), the world is becoming a “tiny flat place” with information exchanged and applied innovatively across continents, independently of races, cultures, languages or systems; where mass-customization has become a major business hub replacing mass-productions; and with trends changing businesses from technology and product-driven to market and customer-product-driven thus increasing trade and information exchange, as well as the need for interoperability (Gunasekaran & Ngai, 2005; Pine & Gilmore, 1999).

This evolution has provided consumers a fundamental role on supply chains and on product design. Reliability and rapid delivery of defect-free products to customers is no longer seen as a competitive advantage, but as a requirement (Mentzer et al., 2001; Panetto et al., 2006). A single company cannot satisfy all customers’ requirements, and today the war is waged between networks of interconnected organisations (Peppard & Rylander, 2006). Therefore, to succeed in this collaborative but at the same time competitive environment, enterprise systems and

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applications need to be interoperable, sharing technical and business information seamlessly within and across organisations, and must be adaptable to different business network environments at all product life cycle (PLC) phases (Jardim-Goncalves et al. 2007; Ray & Jones 2006).

In this sense, being defined as the ability that two or more systems have to exchange information and use it accurately (IEEE, 1990; Software Engineering Institute, 2002), interoperability, more precisely the lack of it, could disturb the creation of new markets, networks, and can diminish innovation and competitiveness of business groups. If multiple systems are being used to manage different portions of a business network (i.e. nodes), several types of costs will be incurred unless those systems have been designed to interoperate. Moreover, if systems are only partially interoperable (IEEE, 1990), translation or data re-entry is required to assure the efficiency of information flows, e.g. in supply chains if the lower tiers do not have the financial resources or technical capability to support interoperability, their internal processes and communications are likely to be significantly less efficient, thus disturbing the performance of the entire business network (W. J. White et al., 2004).

Nevertheless, apart from being a technical issue, interoperability challenges also appear in the enterprises at organisational and semantic level, underlying the need for patterns and solutions that support the seamless cooperation among ICT systems, information and knowledge, organisational structures and people (Jardim-Goncalves, Grilo, et al., 2006).

Nowadays, an enterprise’s competitiveness is largely determined by its ability to seamlessly interoperate with others (Enterprise Interoperability Cluster, 2008). Indeed, the lack of interoperability has been identified in several industrial sectors has a major cost, blocking the achievement of the time-to-market demanded by today’s competitive environment (Ray 2002):

 In the year 1999, NIST¹ published a report on the analysis of interoperability costs in the U.S. automotive supply chain, where the estimated annual costs were calculated at about

$1.05 billion per year (Brunnermeier & Martin, 1999). These values have been reinforced on a later study (in 2004 also by NIST), which estimates that the total cost of managing supplier-customer inventory and schedule information on a supply chain exceeds $5 billion per year in the automotive industry, and almost $4 billion in the electronics sector (W. J.

White et al., 2004).

 Equally dramatic costs are evidenced in the aeronautics industry as well. In 2006, Airbus®

assumed that interoperability problems with the design software used in the multiple factories involved in the A380 plane manufacturing, were the cause for a 2 year delay and a $6 billion slippage (Matlack, 2006). Since then, investment on interoperability and more efficient production and design have been a major driver, e.g., only with the CRESCENDO European research project, the industry is expecting to create an impact of several billions of Euros (CRESCENDO IP, 2009).

1 NIST - National Institute of Standards & Technology (www.nist.gov/index.html)

P a g e | 5 Still, interoperability is not only a concern for large companies. As them, also small and medium sized enterprises (SMEs) do data exchange by implementing business interfaces manually or buying expensive interoperable software solutions, which must suffer complex adaptations in order to meet their own business needs. At the same time, SMEs are, today, confronted with the same level of complexity regarding interoperability as their bigger partners, since they are forced to support similar business interaction patterns. The difference is that they have less human and financial capital to invest in (INTEROP Partners, 2006b).

Within this scope, the funStep initiative (FunStep, 1998) as estimated that the furniture sector (which is SME lead) could benefit largely if interoperability was achieved through a massive adoption of the ISO 10303-236 standard for product data exchange (ISO TC184/SC4, 2006). At the time of the study (2008), it was measured that if the standard implementation followed the expected parameters, the sector could increase the annual benefits in 5% to €6 million by 2010, with a possibility of raising that number to 54% (€70 million) by 2018 and €131 million, 10 years later (INNOVAFUN Partners, 2008). Other references evidencing the value proposition of interoperability are available also for the building and construction sectors, space, and public services (Gallaher et al., 2004; Grilo & Jardim-Goncalves, 2010; Kempler et al., 2009; The United States conference of mayors, 2004).

In the above studies, the costs of poor interoperability show themselves in many ways, some direct and some indirectly, which could be reduced using adequate solutions. Typical areas for incurring cost include (Brunnermeier & Martin, 1999; INNOVAFUN Partners, 2008) :

 Avoidance costs: associated with preventing interoperability issues before they occur (e.g.

the cost of developing translation software, maintaining legacy systems, or buying redundant software to enable business transactions with more partners).

 Mitigation costs: are normally the highest interoperability cost type (almost 90% in some of the above studies), and include the resources required to address interoperability problems after they have occurred, such as manually processing or re-entering data.

 Delay costs: arise from interoperability problems that cause delay in the introduction of a new product, or prolong the sale of bespoke products. These costs include: specification costs such as the cost to re-design a product according to miss-interpreted customer requirements; loss of market share, where customers turn to alternative suppliers for a faster response; post-manufacturing interoperability costs as the marketing and sale of a product; etc.

 Future proofing costs: are generally unknown costs that will be faced at some time in the future in order to integrate with new (currently unknown) system requirements.

Mitigation and delay costs could be eliminated if organisations implement “true” interoperability, where each piece of information needed by a network participant is entered only once. Subsequent use and exchange of that information would be managed automatically through software programs, without the need of manual intervention or translation (Enterprise Interoperability Cluster, 2008; W.

J. White et al., 2004). This way, it is in avoidance that research and investment should be

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encouraged so that the other costs could be reduced and communication across frontiers, among facilities within and between organisations is accomplished seamlessly. Reinforcing this view, the Enterprise Interoperability (EI) Research Roadmap (EIRR) introduces the Interoperability Service Utility (ISU) concept as a grand challenge to obtain a “utility-like capability that enterprises can invoke on the fly in support of their business activities”, with specific IT functions being delivered as services that are cheap, fast, reliable, and without major integration efforts (see Figure 1.1). In summary, effective interoperability would support the Single Market² and its associated “four freedoms of movement of people, capital, goods and services” (Comptia, 2004).

Figure 1.1: EI Grand Challenges (Enterprise Interoperability Cluster, 2008)

Considering the future proofing costs, they are an incognita as they are part of the future. However, to avoid them from becoming measurable in the other cost categories, implementors of the ISU should consider its sustainability over time, including the capacity to deal with market dynamicity and technology evolution. In fact, the 2010 version of the EIRR reinforces the Enterprise Interoperability Science Base (EISB) grand challenge as a research challenge (RC8) with similar concerns. It encourages researchers to formulate the scientific foundations to the Future Internet Enterprise Systems (FInES) activities, which would avoid the development of too many technology-driven solutions that tend to be static and not support changes. Past experiences show that solutions tightly connected to a specific technology are difficult to be updated when the latter is outperformed by a new one. Thus it is expected that applications within the scope of ISU are founded on solid scientific basis and have clearly defined properties and foreseeable behaviour, supported by proper metrics and measurement techniques (FInES Research Roadmap Task Force, 2010).