Embedding Fuzzy Criteria in Request-for-Quote Automated Procurement Processes Miguel-Ángel Sicilia, David Palomar, Ignacio Aedo, Paloma Díaz DEI Laboratory, Computer Science Department, Carlos III University. Av. Universidad, 30 28911 Leganés (Madrid), Spain {msicilia, dpalomar, pdp}@inf.uc3m.es,
[email protected]
Elena García Computer Science Department, University of Alcalá. Ctra. Madrid-Barcelona, Km. 33,600 28871 Alcalá de Henares (Madrid), Spain
[email protected]
Abstract. The information-level integration of suppliers in manufacturing processes becomes a critical requirement in mass customization cycles, where the increasing wealth of product variants may force the production of units of size one. As a consequence, transactional procurement activities should be carried out with the help of flexible automated support tools, in order to adjust production costs, qualities and delivery rates. Request-for-quote (RFQ) scenarios in transactional procurement activities can be automated with current standards-enabled asynchronous business integration software frameworks, by using general-purpose message-passing mechanisms. Nonetheless, this automation leads to winning-quote selection criteria that could be considered too rigid in some cases, especially when using compensatory decision-making models. In this paper, we describe how simple fuzzy criteria – described through linguistic labels – can be integrated in the RFQ process to enable more flexible requisition specification and selection rules, and how existing business integration XML specifications can be extended to include that fuzzy information.
1. Introduction The practical implementation of mass customization relies – among other factors – on the potential offered by new technologies in information management, as described in (Piller et al, 2000). The coordination with the external suppliers involved in the individual prefabrication is considered one of the information costs that can be reduced through the use of these technologies. Specifically, Internet technology-based business integration can be considered an important enabler in order to achieve cost-effective hard customization methods (Piller, 2002). Moreover, mass customization leads to small lot sizes and may enlarge the complexity of logistics management (Knolmayer, 2001), and it also may increase the volume of their
associated procurement interactions. In consequence, flexible fully automated or semi-automated procurement processes are a key technological infrastructure in efficient mass customization information cycles. Procurement tasks can be categorized as long-termoriented (strategic) or short term-oriented (transactional). Strategic procurement activities include sourcing processes, identifying vendors and establishing and managing supplier relationships (Gebauer et al 1998). After a stable infrastructure has been established at the strategic level, a large number of individual buying operations occur at the transactional level. In this work, we focus on transactional request-for-quote (RFQ) procurement activities and their automation with software integration tools. Although these activities are sometimes considered as direct strategic ones (Gebauer & Segev 2001), they can also take place at the transactional level. At this level, in many cases the RFQ process could – and ideally should – be almost completely automated by establishing a number of quote selection criteria, which can optionally be carried on the business document itself. Quote selection criteria in natural language are seldom strict, since in many cases it’s difficult to express them through crisp sentences regarding price or other quote attributes. For example, sometimes only a vague price criterion is in the mind of the RFQ issuer, like “around a thousand dollars” or “not very expensive”. To allow for expressing those vague criteria in a direct way, a flexible criteria specification language is needed beyond the numeric and character types available in common business document schemas like XML SCHEMAS (W3C 2001). In this paper, we describe an approach to how this vagueness in quote criteria can be integrated with the business document itself, enabling their automatic communication through existing business-to-business (B2B) software integration engines. Our approach uses linguistic expressions based on fuzzy logic concepts to specify those criteria. Fuzzy logic has been successfully
used in other business and management contexts, for example, to express vague trust levels (Manchala 2000) or to select contractors in a specific industry (Kashiwagi 1995). The rest of this paper is structured as follows. Section 2 describes how fuzziness can be integrated in RFQ specifications. Section 3 details an XML encoding of these specifications, based on one of the existing proposed B2B standards, and describes a simple approach to quote selection. Finally, some conclusions and future research directions are provided in Section 4.
2. Expressing Quotations with Fuzzy Criteria 2.1. A Model for a RFQ-Quote Scenario A RFQ scenario describes the information flow between a buyer and one or more suppliers. The exchange of RFQs and quotes may follow several different workflows (depending on the type of product involved and the entities in the scenario), but it can be summarized by two major business events: the request using the RFQ document and the response in the form of a quote, that usually matches the lines specified within the RFQ. We have selected the OAGIS proposed interoperability standard, but any other specification would have served our purposes as well. The OAGIS standard1 is supported in many widely used B2B frameworks, and it’s prepared for several kinds of extension (OAGIS 2001b). Buyer Organization or Intermediary (Procurement/ Purchasing)
Add RFQ Add Quote
Supplier Organization or Intermediary (Sales Order Management)
Figure 1. A simplified OAGIS RFQ-Quote scenario
asynchronous communication setting. From this scenario, we focus on the Preparation and Quotes phases, assuming that the short list of suppliers is known, and ignoring possible subsequent negotiation workflows and changes in quotations that are of no relevance for our discussion. The simplified scenario is depicted in Figure 1. Let’s introduce a basic formalism about the previously described RFQ process, to be able to precisely state the extensions later. The ADD RFQ Business Object Document (BOD) is made up of a header RFQHEADER and a number of individual requisitions expressed as RFQLINE elements. A RFQ can be considered as an unordered set of requisitions, each of them for a product (or service), specifying a number of requirements. Therefore, a set of attributes is (somewhat implicitly) attached to a specific RFQ, some of them applicable to the entire document (overall) and others applicable only to a specific line. The set of attributes specified in the document for an specific RFQi whose lines are denoted as a set LINERFQi can be represented as follows: overall ATTRFQi = ATTRFQi ∪
l RFQi
U ATT
l∈LINE RFQi
Where the set of attributes of the line l is denoted as: l ATTRFQi = {att | att ∈ Dk }
and attributes applicable to the entire RFQ are denoted through a special name ‘overall’. Every attribute has an associated domain (or data type) on which it’s defined, denoted as D(att). The set of domains includes those defined in XML SCHEMAS (W3C 2001) specification, and those defined in the OAGIS standard. Some of the elements in the ADD RFQ BOD allow the specification of restrictions on those attributes, including the following:
Although the kind of extensions we describe in this paper – extending some aspects of the data model – is not addressed explicitly by OAGIS, we can accommodate changes by adding information items to the document type definitions (DTD) or schemas of the standard in separate namespaces.
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The QUALIFICATN element can be used to specify optional qualifiers (requirements like standards compliance, quality indicators, performance ratings, etc.) that apply to the whole RFQ (if specified in the header) or to a concrete requisition (if specified in a specific RFQLINE).
We’ll take as a model the asynchronous business workflow “Buyer and Supplier RFQ-Quote Scenario” described in the OAGIS specification (OAGIS 2001, section 2, 55th scenario). As is usual in this kind of processes, the scenario assumes a loosely coupled,
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In the RFQSCHEDULE element, dates and quantities required can be specified for a specific RFQ line.
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The segment QUANTITY should be included in all the lines.
1
http://www.openapplications.org/
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FEATVALDAT allows the general-purpose definition of required product’s features as name/value pairs.
fuzziness attributes, but all the previously listed ones may be subject to similar extensions.
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Prices are specified with the OPERAMT element.
Prices can be stated linguistically in a natural way by using linguistic label sets, like for example:
The above attributes are subject to specifying vague criteria, and also to be assigned to extended data types as we’ll describe later for some of them selected as illustrative examples. Constraints (or restrictions) can be specified on the attributes. We’ll specify them as formulas in a set R like “price per unit of the third in RFQ1 must not exceed ten dollars”, that can be formulated as:
rm = { price
3 RFQ1
≤ 10}
Or price = sj if i >= j,
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it exists a negation operator: Neg (si) = sj , such that j = Tg – i,
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it exists a maximization and a minimization operator: Max (si, sj ) = si if si >= sj, and Min (si, sj) = si if si
