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Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
Specifying information systems for business process integration
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Specifying information systems for business process integration

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  • 1. Specifying Information Systems for Business Process Integration – A Management Perspective1 Joerg Becker, Alexander Dreiling, Roland Holten, Michael Ribbert University of Muenster Dept. of Information Systems Leonardo-Campus 3 48149 Muenster, Germany {isjobe|isaldr|isroho|ismiri}@wi.uni-muenster.deAbstractSupply chain management and customer relationship management are concepts foroptimizing the provision of goods to customers. Information sharing and informationestimation are key tools used to implement these two concepts. The reduction of deliverytimes and stock levels can be seen as the main managerial objectives of an integrative supplychain and customer relationship management. To achieve this objective, business processesneed to be integrated along the entire supply chain including the end consumer. Informationsystems form the backbone of any business process integration. The relevant informationsystem architectures are generally well-understood, but the conceptual specification ofinformation systems for business process integration from a management perspective,remains an open methodological problem. To address this problem, we will show howcustomer relationship management and supply chain management information can beintegrated at the conceptual level in order to provide supply chain managers with relevantinformation. We will further outline how the conceptual management perspective of businessprocess integration can be supported by deriving specifications for enabling informationsystem from business objectives.KeywordsBusiness Process Integration, Supply Chain Integration, Supply Chain Process Management,Customer Relationship Management, Managerial Views, Business Objectives, DataWarehousing1 IntroductionIn order to ensure customer satisfaction, knowledge about customers is vital for supplychains. In an ideal supply chain environment, supply chain partners are able to performplanning tasks collaboratively, because they share information. However, customers are notalways able or willing to share information with their suppliers. End consumers, on the onehand, do not usually provide a retail company with demand information. On the other hand,industrial customers may hide information deliberately. Wherever a supply chain is notprovided with demand forecast information, it needs to derive these demand forecasts byother means. Customer relationship management (CRM) thus provides a set of tools toovercome informational uncertainty.Efficient supply chain management requires the integration of business processes betweensupply chain partners. As a result, supply chain process management becomes necessary,1 This work has been funded by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung), record no. 01HW0196. Page 1
  • 2. focusing on global supply chain processes. One of the main resulting managerial activities isthe optimization of supply chain processes beyond the borders of participating companies(Hammer 2001).Efficient optimization activities require information systems (IS), especially if they havereached the degree of complexity inherent in supply chain process management or customerrelationship management. IS are vital for business process integration from an operativeperspective, by enabling data exchange and integrated process flows between supply chainpartners. On the other hand, IS support the managerial activities of monitoring andcontrolling supply chain processes. Decision support systems in particular are designed toassist managers in making better decisions (Todd, Benbasat 1999). In this context, IS are theenablers for creating competitive advantage (Johnston, Vitale 1988; Porter, Millar 1985).Because IS play such a central role, the perception, that IS form the vital backbone of anorganization, instead of being simple business support tools (Henderson, Venkatraman 1999;Li, Chen 2001; Venkatraman 1994) has increased significantly since the so-calledinformation revolution (Porter, Millar 1985).Today, the development of information systems is faced with increased pressure from thebusiness perspective. Ongoing discussions on the business value of IS (Hitt, Brynjolfsson1996; Im, Dow, Grover 2001; Mukhopadhyay, Kekre, Kalathur 1995; Subramani, Walden2001; Tam 1998) clearly point out that the risk awareness of IS development projects haschanged. High costs and high overall failure rates of IS projects (Standish GroupInternational 2001) have emphasized these discussions even more. Finally, a focus on ISproject planning methods is needed, because inadequate IS project planning may lead toproject failure. Keil states that a significant number of IT projects (30-40%) exceedingpredefined time restrictions and allocated resources, but never reaching their objective, willultimately escalate and fail (Keil 1995; Keil, Mann, Rai 2000).From an IT perspective, a broad variety of methods, architectures, and solutions aim atsupporting the IS development process (Hirschheim, Klein, Lyytinen 1995). As an example,data warehouse architectures are well understood and data warehouse projects have beenconducted over a long period. Nonetheless, many data warehouse projects fail for severalreasons (Vassiliadis 2000). Some reasons for failure of data warehouse can hardly beinfluenced, such as bad source data quality. Other reasons can be influenced during theproject, such as the involvement of management as targeted users of the system ormanagement support both of which contribute to system quality and system success (Wixom,Watson 2001). The high failure rate, especially of complex IS projects, indicates that someso-called best practices for IS development are inadequate. There is a continually increasingneed for methodological approaches that are theoretically sufficiently well-founded to handlecomplex IS projects (Jiang, Klein, Discenza 2001).The conceptual specification of information systems for business process integration from amanagement perspective, is an open methodological problem. Data warehouses support themanagement perspective technically, but their implementation is extremely costly. It is thusall the more important for the development of data warehouses to be effective and efficient.Effectiveness is achieved if the data warehouses support the desired managerial analysis.Efficiency targets the amount of necessary resources for development. The critical factor fora data warehouse project’s effectiveness is its value for future business. It is determined bythe ability of a data warehouse environment to support essential managerial analysis. Thispaper aims at achieving effectiveness of data warehouses for business process integration.We introduce a specification approach for managerial views on business processes. Theseviews are derived from business objectives, which are an essential output of managerial Page 2
  • 3. work. Approaches, focusing on managerial objectives as input for information systemsspecifications have been found useful within the domain of requirements engineering(Rolland, Prakash 2000). Our approach supports the conceptual management perspective ofbusiness process integration.As an introduction to the topic, in Section 2, we first provide an overview of supply chainmanagement and customer relationship management and outline how these concepts can beintegrated. Conceptually, we focus on the impact of information sharing on supply chains anddescribe how estimated information can replace shared information, if it is not shared bysingle supply chain partners. Technically, we provide an overview of enterprise applicationintegration (EAI) for integrating business processes along supply chains. For the technicalintegration of business processes from a management perspective, we introduce the conceptof data warehousing and describe a framework for supply chain process management.In Section 3, we introduce the MetaMIS approach for the specification of managerial viewson business processes as a support tool of the conceptual management perspective. Theproblem of deriving MetaMIS specifications is targeted by the definition, decomposition, andtransformation of business objectives into MetaMIS model constructs. We discuss thetheoretical background of business objectives, integrate them into MetaMIS, and introduce anelaborate example of an objective system. Section 4 deals with transforming the objectivesystem into MetaMIS specifications, which can be used to derive data warehouse structures.Finally, the findings are summarized and future prospects discussed.2 Integration of Business Processes2.1 Supply Chain ManagementThe objectives of supply chain management are the design, operation and maintenance ofintegrated value chains, so as to satisfy consumer needs most efficiently by simultaneouslymaximizing customer service quality (Bechtel, Jayaram 1997; Christopher 1998; Hewitt1994). SCM is currently accepted as a concept integrating inter-organizational businessprocesses. In order to fulfill its objective, it must include other concepts such as efficientconsumer response (ECR), quick response, continuous replenishment and customerrelationship management (Bechtel, Jayaram 1997; Stadtler 2000). The design of supplychains requires the specification of business processes and supply-chain-wide planningroutines. These specifications are imperative for the development of information systemswhich form the backbone of any supply chain integration (Miller 2001; Rohde, Wagner2000). Information systems are widely perceived as the enabler for supply chain integration(Bechtel, Jayaram 1997; Hewitt 1994; Meyr, Rohde, Wagner 2000). Partners in a supplychain have to perform their activities in the most efficient way, by concentrating on their corecompetencies (Christopher 1998).The Supply Chain Operations Reference (SCOR) model provided by the Supply ChainCouncil, is a reference model for structure, processes, and information flows within an inter-organizational supply chain (SCC 2001). The SCOR model contains measures for operationalcontrol and best practices for supply chain design. Five main processes characterize theSCOR model: Plan, Source, Make, Deliver and Return. The SCOR model is structured infour hierarchical levels. The main processes are defined at the top level (level one). At thesecond level, these main processes are clustered into process categories which depend on theunderlying process model. There are three relevant business categories for the SCOR modelat this level. These are "Make-to-Stock", "Make-to-Order", and "Engineer-to-Order".Additionally, at level two, some enabling processes are identified. The highest level of detail Page 3
  • 4. within the SCOR model is the third level, where each process category from level two isrefined by inter-related process elements. The processes and their relationships are defined bymeans of tables. Level four is not covered by the SCOR model, since it would contain adetailed description of the internal business processes of the cooperating enterprises. As aresult, the SCOR model needs to be extended by a framework adjusting internal and externalbusiness processes. This enables the alignment of an existing process infrastructure withinter-organizational processes that result from the SCOR approach.Parallel to the SCOR model, several standardization initiatives have published documentsthat focus on the design of supply chain processes. The RosettaNet consortium, for example,is a non-profit group of more than 400 companies in the information technology andelectronics domain. It aims at standardizing the trading networks between these companies,by providing standards for business documents such as purchase orders. Furthermore, so-called partner interface processes (PIPs), e.g. acknowledgement of receipt, serve the purposeof defining process interaction between trading partners (RosettaNet 2003).2.2 Impact of Information Sharing on Supply Chain ManagementInformation sharing is one of the basic supply chain management concepts. Evidence of thepositive effects of information sharing can be found through various approaches, wheresavings are estimated in an information sharing supply chain environment using simulationmodels (Aviv 2001; Cachon, Fisher 2000; Gavirneni, Fisher 1999; Lee, So, Tang 2000). Thefocus of this section is not to quantify the effect of information sharing along supply chainsand thus proving the effect, but to assume a positive effect and justify it with simple model-based explanations.The integration level of material and inventory management and the structure of order costsare the main parameters of supply chain management (Christopher 1998). We illustrate thisby using a simple model of inventory development and the effects of an integrated materialand inventory management on order costs (see Figure 1). Two variables are relevant forcalculating the economic ordering quantity. These variables are warehousing costs and fixedcosts per order (in the interest of simplicity, costs per unit are assumed to be constant and willtherefore not be considered; the results would be the same if discounts on certain order sizeswere deducted). Warehousing costs increase linearly with increasing order quantities, sincethey are linked directly to the inventory level. Fixed costs per order decrease with anincreasing order size, because fixed costs are spread over more units. The total cost functionis the sum of these two functions as shown in the top left model of Figure 1. Page 4
  • 5. Base Model inventory cost level order total cost warehousing size costs average level ordering level fixed cost per order safety stock per unit X order size X time min total cost delivery time Effects of integrated Material and Inventory Management inventory level average level 2 ordering level 2 safety stock 2 time delivery time 2 Effects of Reduced Ordering Costs inventory cost level total costs 1 warehousing costs average total costs 2 level 3 ordering level 3 cost per order cost per order min total cost 2 min total cost 1 order size X time delivery time 1 Source: (Holten et al. 2002).Figure 1: Effects of information on material and inventory management and ordering costsThe development of inventory over time is shown in the top right model of Figure 1. Acertain safety stock is required to guarantee production in cases of supply shortages. For astart, we assume stock above this level. Furthermore, we assume a linear consumptionfunction over time. Based on a given delivery time, we can determine the reorder point forthe economic ordering quantity.It is important to understand that information itself has no direct business value. The effectsof information on business are always indirect. Two relevant effects of improved informationavailability for the management of supply chain processes can be explained using the simplemodel in Figure 1. Firstly, information availability enables an enterprise to reduce theaverage stock level by reducing safety stocks and delivery times. Using informationcorrectly, ensures that required materials can be delivered on time. This effect is basedsimply on the exchange of information between partners during the course of the businessprocess (see the center model in Figure 1). If production planning systems of manufacturersand scheduling systems of suppliers are provided automatically with point-of-saleinformation from the retail partner, planning tasks can be performed with improved quality. Page 5
  • 6. This results in a reduction of safety stocks and delivery times, since delivery time entails notonly shipment time, but also the time taken to organize the entire business transaction.Furthermore, delivery time can be influenced in make-to-order scenarios by the lag untilproduction for an order commences and the time it takes to produce, pack, and deliver theproducts to the place the logistics partner can collect them. The structure of production,logistic and organization times can be optimized and decreased dramatically. The effectsdiscussed so far, clearly provide a case for an integrated material management such as vendormanaged inventory (VMI).Secondly, information availability enables an enterprise to reduce the average stock level byincreasing order frequencies. This effect is based on the duration of contracts between supplychain partners. Based on long-term agreements, the costs per order can be reduced, becausesome uncertainty for suppliers and manufacturers is eliminated.In the simple model introduced in Figure 1, this results in reduced costs and a reducedoptimal ordering quantity (see bottom left model in Figure 1). This implies increasing orderfrequencies, which is economically logical (see bottom right model in Figure 1). To benefitfrom this effect, which leads to a reduced average inventory level because of reduced ordersizes, an integration of material and finance management is necessary.Throughout the paper, we will use a consistent example to explain our concepts. Our examplecompany is part of a supply chain which decided to decrease delivery times, in order toincrease customer satisfaction. Products are directly shipped from company warehousesaccording to customer orders. The company stocks a small number of products and attemptsmainly to produce just-in-time. An example of a managerial objective focusing on profitingfrom the positive effects of information sharing along supply chains is the following (thediscussion on management objectives and their role in specifying MIS will be continued inmore detail in Section 3): • Objective Delivery Time Reduction of Business Unit Automotive Supplies: Decrease the average delivery time of all products of business unit Automotive Supplies to a maximum of 24 hours within the next year.Most supply chains can potentially achieve higher customer satisfaction by reducing thedelivery times of ordered products. The additional effort required to decrease the deliverytimes, can be justified with the savings from decreased stocks along the supply chain. Thesavings can be passed on to the customer, invested in improving customer service or instrengthening the supply chain. To decrease delivery times of ordered products, the efficiencyof operative business processes along the entire supply chain needs to be increased. A majormanagerial responsibility is to define business objectives and undertake the necessary steps todeploy improved business processes. Furthermore, control mechanisms need to beimplemented to monitor the degree to which business objectives have been reached.2.3 Customer Relationship ManagementEvery supply chain ultimately provides an end consumer with a product or service. The endconsumer’s decision to buy or not to buy a product influences a supply chain’s economicsuccess, and is thus the critical element. In the interest of the entire supply chain andespecially the final partner interfacing with the end consumer, this decision needs to beinfluenced positively. Customer satisfaction can be addressed in several ways. In the 1990’s,a new strategic approach called relationship marketing evolved. Originating in the service orindustrial marketing literature, relationship marketing focuses on the development and Page 6
  • 7. cultivation of long-term profitable relationships (Berry 1983; Grönroos 1994; Peck et al.1999).Following Payne, et al. (Payne et al. 1998), relationship marketing considers relationships “inevery direction”. The customer relationship management approach, focuses only on profit-enhancing relationships with customers (Ahlert, Hesse 2002; Greenleaf, Winer 2002). Basedon the notion of a customer life cycle (Ives, Learmonth 1984), a relationship can be seen asan investment, where, for example, customer relationship campaigns are conducted toachieve positive customer values at the end of the life cycle. Depending on the differentphases of the customer life cycle, recruitment, retention, and recovery (Bruhn 2001), differentneeds of the customers occur and must be satisfied. A consideration of the special needs ofcustomers, combined with individualized marketing campaigns, leads to higher sales(Gillenson, Sherrell, Chen 1999; Stone, Woodcock, Wilson 1996) and increased retention ofexisting customers (Buchanan, Gilles 1990). Keeping existing customers is about five timesmore profitable than finding new ones (Buchanan, Gilles 1990; Reichheld 1996). Modern IS,using large amounts of customer data, enable CRM and one-to-one marketing on a massscale (Gillenson, Sherrell, Chen 1999).Deriving knowledge about customers is one of the main challenges confronting analyticalCRM. Usually, customer buying behavior is analyzed to forecast potential products, points oftime, or quantities of future orders. This knowledge is used mainly by companies in order toprovide customers with what they require at a given time and place. Furthermore, thisknowledge is useful for manufacturing industries, because they can adjust their productdevelopment to market requirements. In turn, this may lead to decreased delivery times,which as pointed out above, contributes potentially to customer satisfaction.2.4 Impact of CRM Information on SCMAs indicated above, the design of supply chains requires the specification of supply-chain-wide planning routines as a special component of the development of information systems.The concept of advanced planning incorporates integrated supply chain planning as a coreconcept. Advanced planning systems (APS) support this integrated planning task (Rohde2000). Demand planning data and demand fulfillment data at the sales stage, is fed back intodistribution planning and transport planning at the distribution stage. Ideally, industrialcustomers are able to provide their suppliers with precise demand information, obtained fromcollaborative forecasting with their industrial customers. Unfortunately, end consumersgenerally do not provide retail companies with demand information, and some industrialcustomers are unable or unwilling to provide demand information.Missing demand information within supply chains, prohibits the notion of integrated supplychains. To compensate for potential losses which arise from non-integrated supply chains,CRM information can substitute missing demand information to a certain degree. Forexample, if the component supplier is neither able nor willing to share demand data, businessprocesses between the component and part supplier need to be optimized using CRMmethods initiated by the part supplier.At the retail stage, CRM provides a set of tools for increasing the forecasting quality ofretailers. Using CRM information within the supply chain, potentially maximizes the endconsumer’s satisfaction in several respects. Firstly, efficiently derived high-qualityforecasting information shared with suppliers enables stock and cost reductions within SCM.Secondly, the out-of-stock problem can be reduced through higher demand data quality,given that demand will be satisfied. Thirdly, the bullwhip effect resulting from non-stationarydemands can be reduced if the entire supply chain is provided with high-quality demand data Page 7
  • 8. for the final supply chain partner. If the quality of forecasted customer demand is sufficientlyhigh as to almost correspond with actual demand, the effects of sharing this information willbe as they have been proven for information sharing supply chains (Aviv 2001; Cachon,Fisher 2000; Gavirneni, Fisher 1999; Lee, So, Tang 2000).Apart from customer-related information gained by CRM, market-related information isrequired within the strategic planning of a supply chain. Market research is a tool fordecreasing the risk of marketing and resulting product development decisions (Proctor 1997).Whereas CRM focuses on forecasting the demands of known customers, market researchprovides information on markets. Both CRM information and market research informationneed to be provided to the preliminary supply chain, in order to increase the quality ofoperative demand-planning processes. For this purpose, CRM should be applied to industrialcustomers within the supply chain. Additionally, market research is required at every stage ofthe supply chain. Figure 2 contains the information flows necessary to implement thisconcept. Raw Material Basic Material Parts Component End Consumer Market Market Market Market Market Raw Material Basic Material Component Product Part Supplier End Consumer Supplier Supplier Supplier Assembler Legend Supply Chain Information CRM Demand Information Market ResearchFigure 2: Supply Chains and MarketsIn Section 2.2, an example of a managerial objective has been introduced, that aims atprofiting from the positive effects of information sharing along supply chains. The definitionof the objective remains constant in a non-information sharing environment. If the customersof business unit Automotive Supplies are end consumers, they will not share demandinformation with our example company. Demand information may also be not available, ifindustrial customers are unable or unwilling to share demand information. In any event, thecompany needs this demand information and therefore needs to implement forecastinganalysis tools. The set objective of decreasing delivery times, which are affected partially bythe time required to proceed with the customer order, its production, packing, shipment, isstill that of decreasing delivery times. The difference lies in the application of methods ofanalytical CRM, instead of information sharing as a basic concept of SCM at the operativelevel.2.5 Technical Integration of CRM and SCM DataThe integration of supply chain management and customer relationship management can beassisted by efficient information systems and information technology. In order to support the Page 8
  • 9. integration of SCM and CRM, the implementation of IS needs to target the operative as wellas the management perspective of the integrated concepts.From an operative perspective, enterprise application integration aims at combining IS ofbusiness partners by transmitting data between them (Buhl, Christ, Ulrich 2001). Even ifthese IS are highly heterogeneous, the data in exchanged documents must not be changed,misinterpreted, or lost. Data exchange is facilitated by schema matching mechanisms. Severalprotocols and document standards are used for EAI purposes, such as XML or EDIFACT.Software products such as Microsoft’s BizTalk Server, provide a software platform forexchanging business documents. Technically, data can be exchanged using the Internet.From a management perspective, data warehouses provide an accepted architecture for thedevelopment of decision support systems. A data warehouse stores materialized views onrelational representations of business processes, in order to provide relevant information formanagerial decisions (Inmon 1996; Inmon, Hackathorn 1994; Inmon, Welch, Glassey 1997).The warehouse is the central layer of a theoretically ideal three-layer architecture connectingonline transaction processing (OLTP) systems and components enabling online analyticalprocessing (OLAP) (Becker, Holten 1998; Chaudhuri, Dayal 1997). Contributions within thefield of data warehousing range from technical discussions of databases and algorithmsenabling OLAP functionality (Agarwal et al. 1996; Cabibbo, Torlone 2001; Codd, Codd,Salley 1993; Colliat 1996; Gyssens, Lakshmanan 1997; Vassiliadis, Sellis 1999) to studies onthe information search behavior of managers (Borgman 1998) and to papers concentrating onmethodologies for information systems development (Golfarelli, Maio, Rizzi 1998).Recently, methodological contributions (Jarke et al. 1999; Jarke et al. 2000) propose aquality-oriented framework for data warehouse development. OLAP supports adequatenavigation for the purpose of managerial analysis, through so-called multi-dimensionalinformation spaces. Business process data from OLTP systems are the source of OLAPanalyses. Typically, the integration of OLTP systems and a data warehouse is based on toolsperforming extraction, transformation, and loading tasks (ETL) on the source data (Inmon1996; Widom 1995).At an intra-organizational level, business-supporting information systems produce data aboutbusiness transactions. For the purpose of CRM and logistical optimization (as the intra-organizational fundament of inter-organizational SCM), this data can be analyzed, enablinganalytical CRM and logistic optimization. Due to the fact that this data is encoded in variousoperational data sources, there needs to be an integrating layer to derive relevant managerialinformation from these data sources. This can be achieved by local data warehouses. Fromthese data warehouses, several management reports can be generated, which supportcorresponding managerial activities.To support supply-chain-wide information sharing, data from operational data sources ofsingle supply chain partners, need to be integrated in a supply-chain-wide data warehouse.This data warehouse then serves as a basis for generating managerial reports at the inter-organizational as well as intra-organizational levels. Figure 3 shows an architecture enablingthe integration of inter-organizational and intra-organizational data for the purpose of supplychain process management analysis. Page 9
  • 10. Figure 3: Technical Integration of CRM and SCM DataThe architecture serves analytical CRM as well as analytical SCM, implying operationalCRM and SCM components within the local information systems environments. Thus, themanagement reports at the inter-organizational and intra-organizational levels, contain CRMand SCM information, enabling the optimization of business processes from bothperspectives.Even if the data warehousing architecture is well understood, data warehouse success islinked directly to its additional use for the business. Additional use can be achieved bysupporting the process of providing essential managerial analysis more efficiently than in thepast. For this reason, the development of data warehouses needs to be supported from aconceptual perspective, an unresolved methodological problem, which is considered in thenext section.3 Business Objectives and Managerial Views on Business ProcessesAs depicted in Section 2, supply chain management and customer relationship managementenable the integration of business processes at a conceptual level. SCOR and RosettaNet areapproaches for implementing supply chains from an operative perspective, supportingprocesses of trading networks. From a technical perspective, business process integration istargeted by several communication protocols, architectures, concepts, and software products. Page 10
  • 11. As one of the concepts, EAI aims at integrating information systems of business partners.From a management perspective, data warehousing provides an accepted architecture formanagerial views on business processes. Data warehouses can be used for managerial intra-organizational as well as inter-organizational analysis.Even if the introduced concepts are well-understood by researchers and practitioners, thereremain resolved methodological problems. Besides the operative and technical perspective,business processes have to be integrated from a conceptual management perspective. For thispurpose, in this section we discuss the specification of managerial views on businessprocesses with MetaMIS. Furthermore, we provide a detailed introduction to the definition ofbusiness objectives, which will be integrated into MetaMIS to create MetaMIS models.Finally, a detailed example is introduced, consisting of an objective system. The objectiveswill be decomposed to their defining components, which will be transformed into MetaMISmodels in a comprehensive discussion in the next section.3.1 Specification of Managerial Views with MetaMISFrom a conceptual management perspective, the MetaMIS approach aims at specifyingmanagerial views on business processes (Holten 2003). The MetaMIS approach is anchoredby a meta model featuring several concepts necessary to define a specification language formanagerial views on business processes and activities (Becker, Holten 1998; Holten 1999;Holten 2003). MetaMIS models feature a degree of formality, which allows for deriving datawarehouse structures from these models (Holten 2003). The MetaMIS approach has beenvalidated at the Swiss reinsurance company Swiss Re, where the managerial activity GroupPerformance Measurement has been modeled (Holten, Dreiling, Schmid 2002).MetaMIS commences with the definition of dimensions (concept Dimension). Dimensionsare defined by hierarchically-ordered dimension objects (concept Dimension Object), e.g.,products, customers, points in time, or customer sales representatives. Based on the enterprisetheory of Riebel (Riebel 1979), dimension objects can be understood as entities subject tomanagerial analysis. In order to prevent information overflow, subsets of existing dimensions(dimension object hierarchies) need to be defined. For this purpose, dimension scopes anddimension scope combinations are introduced (Holten 1999; Holten 2003; Holten, Dreiling,Schmid 2002) (concepts Dimension Scope and Dimension Scope Combination). Dimensionscopes are sub-trees of dimensions. Dimension scope combinations comprise dimensionscopes, creating navigation spaces for managerial analysis. Dimension scope combinationsdefine a space of multi-dimensional objects. Referring to Riebel’s enterprise theory, theconcept Reference Object denotes vector types within this space. Reference objects are“measures, processes and states of affairs which can be subject to arrangements orexaminations on their own” (Riebel 1979, p. 869).The next concept required is Aspect. Aspects can be either qualitative (concept QualitativeAspect) or quantitative (concept Quantitative Aspect, Synonym to Ratio). Management ratiosare vital for specifying information in management processes. They belong to the class ofinterval or ratio measures (Adam 1996; Hillbrand, Karagiannis 2002; Holten 1999). Ratiosare core instruments for measuring the value of companies (Copeland, Koller, Murrin 1990),the business performance (Eccles 1991; Johnson, Kaplan 1987; Kaplan, Norton 1992;Kaplan, Norton 1996; Kaplan, Norton 1997; Lapsley, Mitchel 1996) and for analyzing thefinancial situations of enterprises (Brealey, Myers 1996). Synonyms found in themanagement accounting literature are, e.g., operating ratio, operating figure, performancemeasure. Ratios like “gross margin” define dynamic aspects of business objects and haveclearly specified meanings. Their calculation is defined by algebraic expressions (e.g. “profit Page 11
  • 12. = contribution margin – fixed costs”). Qualitative aspects can be used, if business facts aremeasured by categorical values, such as efficiency or quality (Becker, Dreiling, Ribbert2003). They belong to the class of nominal or ordinal measures.Aspects are organized into aspect systems (concept Aspect Systems). Aspect systems arestructured hierarchically according to an aspect’s importance for a managerial analysis. Adrill-down logic is implied for aspect systems, which is to be separated especially from analgebraic definition of ratios. Aspect systems are assigned to dimension scope combinations(navigation spaces), in order to create business facts (concept Fact), such as the number ofproducts sold in a certain region by a specific customer sales representative or the turnoverachieved with one customer. Business analyses usually require a comparison of businessfacts. In order to conduct such dynamic analyses, fact calculations can be defined, involvinga variable number of business facts which are processed according to calculation expressions(Holten, Dreiling 2002) (concept Calculation Expression). Examples of fact calculations arethe profit-growth rate of a business group or the variance between planned and actualturnover of a product group. Dimension scope combinations, aspect systems, and factcalculations are combined into an Information Object. Thus, it is a relation between a set ofreference objects and a set of aspects with the element types being business facts. Figure 4shows a segment of the meta model underlying the MetaMIS approach. Page 12
  • 13. Reference Object Structure (0,m) (0,m) Combined Reference CRO-Coordinates Object (0,m) Dimension Object Hierarchy (0,m) (0,m) (0,m) Operator CE-Ot-As (0,1) Dimension Object (0,m) (1,1) (1,m) (1,m) Calculation Expression DO-DS-AS (1,m) (1,m) (0,m) Operand CE-On-As Dimension Scope (0,m) u,t Fact DS-DSC-AS (0,m) (0,m) Aspect (1,m) A-AS-As u,t Quantitative Aspect (Ratio) Dimension Scope Combination (0,m) (0,m) Aspect System (0,m) Qualitative Aspect Information Object (1,m) Dimension Grouping D-DG-AS (1,1) (1,m) Dimension DO-D-AS (1,m) (1,m) D-HL-AS DO-D-HL-AS (1,1) Hierarchy Level Legend Specialization (Types: Reinterpreted - u unequivocally, e equivocally <Identifier> Entity Type <Identifier> Relationship Type - t total, p partial) Connector ( (min,max) <Identifier> Relationship Type - min minimum cardinality, - max maximum cardinality) Source: (Holten 2003).Figure 4: Segment of the MetaMIS meta modelAn unresolved methodological problem is how the crucial modeling constructs such asdimensions, dimension scopes, dimension scope combinations, aspects, and informationobjects are derived. In the next section, we will show how business objectives can be used toderive MetaMIS structures together with personnel from various business domains. Thiscloses the loop from defining business objectives to monitoring if they have beenaccomplished. Page 13
  • 14. 3.2 Objectives from a Business PerspectiveThe designer of an information system for managerial analysis needs to know whichmanagerial analysis the systems must to support, information that only managers ormanagement supporters can provide. To assist the complex process of obtaining informationrequirement models, e.g., MetaMIS models (Holten 1999), we will show, how managers’information requirements can be derived from corporate objectives. With respect to theintegration of objectives into the MetaMIS approach, we discuss several objective typesfound in the literature. Parallel to this, we introduce meta model concepts for the differentobjective types in order to construct a meta model of objectives. The base concept introducedis Objective.According to Porter (Porter 1979), the most abstract and general business objectives aredefined in a business strategy. A business strategy deals with defending and strengthening acompetitive business position. It must focus on five contending forces (Porter 1979), whichare threats of entry, powerful suppliers, powerful buyers, substitute products, and jockeyingfor position. Based on the identification of these forces, the company is able to define itsstrengths and weaknesses. Knowing the strengths and weaknesses, a strategy can beformulated consisting of the three major aspects of positioning the company within theindustry, influencing balance and forces, and exploiting industrial changes. Following Porter(Kotler 1999; Porter 1996), strategic positioning targets performing different activities thancompetitors or performing similar activities of competitors in different ways. Operationaleffectiveness is achieved, if activities are performed better than the ones of competitors.Clearly defined strategic objectives and operational effectiveness are essential to superiorperformance and long term profitability (Porter 1996). In order to take strategic objectivesinto account for constructing our objective meta model, we divide Objective into twospecializations of which one is the entity type Strategy, General Conditions, and Guidelines.Hierarchically structured objectives can be represented as a pyramid, where the degree ofmeasurability increases towards the bottom (Steiner 1969). Three different hierarchical levelsform the top of the pyramid (strategy or general conditions). These are business mission(Meffert 2000), corporate identity (Birkigt, Stadler, Funck 1993), and policies and practices(Ansoff et al. 1990). Following this categorization, we introduce the meta model constructBusiness Mission, Corporate Mission, and Policy and Practice.A major difficulty of business strategies is their non-operational character. Operationalobjectives are defined by a certain measure, level, time frame, and reference (Adam 1996).Objectives need to be defined operationally in order to be manageable (Latham, Kinne 1974).Usually, business strategies are not measurable. Nonetheless, operational effectivenessrequires the definition of operational objectives. In order to align business strategy andoperational effectiveness, the business strategy needs to be broken down into operationalobjectives in several steps. In the words of Porter “the essence of strategy is in the activities”(Porter 1996), which means that operational objectives enable management to do the rightthings (defined by the business strategy) right (by derived operational objectives).Types of operational objectives that can be derived from business strategies are generalgoals, organizational unit goals, business unit goals, and marketing-mix-based goals.General goals specify aggregated operational objectives. They can be seen as benchmarks,which help managers from different organizational units to specify their objectives, such asrevenue or cost on a corporate level (Kupsch 1979). Organizational unit goals specify generalgoals at an organizational unit level. Examples are planned production department costs orplanned sales department revenues (Meffert 2000). Business unit goals break downorganizational unit goals to the business unit level. Marketing-mix-based goals further split Page 14
  • 15. up business unit goals into, e.g., planned prices, promotions, places, and products.Operational Objective is introduced to the objective meta model as the second specializationof Objective. Both existing specializations are unequivocal and total, meaning that everyobjective either has an operational or a strategic character. Operational Objective is devidedunequivocally and totally into the specializations General Goal, Organizational Unit Goal,Business Unit Goal, and Marketing-Mix-Based Goal.The Balanced Scorecard is another approach that breaks down general business objectivesinto operational ones (Kaplan, Norton 1992). The BSC is a top-down approach that providesmanagers with a comprehensive framework, translating a company’s strategic objectives intoa coherent set of performance measures (Kaplan, Norton 1993). Four different perspectivesare provided. Information about traditional financial measures are enhanced by measures ofcustomer performance, internal processes, and innovation and improvement activities(Kaplan, Norton 2000). Thus, the BSC enables balancing between external measures such asincome or revenues and internal measures like product development and learning (Kaplan,Norton 1993). Furthermore, the BSC shows cause-and-effects links, which avoid trade-offsamong different success factors.For constructing the objective meta model we need to structure objectives. Objectives can beorganized hierarchically. Each objective can be part of more than one hierarchy, which leadstechnically to an Objective Structure as a relationship type connecting Objective with itself.We can furthermore add specializations, e.g., the categorization of Objective into the morecommonly used terms Strategic Objective, Tactical Objective, and Operative Objective. Theintroduced specializations, however cannot be regarded as an exhaustive list of possibilities.Other specializations may exist beyond theses introduced. Depending on the modelingpurpose they can be specified. Figure 5 contains the meta model constructs that have beenintroduced above. Page 15
  • 16. Objective Structure (0,m) (0,m) Objective Strategy, Strategic u,t General Condition, u,t Business Mission u,t Objective and Guideline Tactical Corporate Identity Objective Policy and Operative Practice Objective Operational Objective u,t General Goal Organizational Unit Goal Business Unit Goal Marketing-Mix- Based Goal Legend Specialization (Types: Reinterpreted - u unequivocally, e equivocally <Identifier> Entity Type <Identifier> Relationship Type - t total, p partial) Connector ( (min,max) <Identifier> Relationship Type - min minimum cardinality, - max maximum cardinality)Figure 5: Specializations of Objective including Objective StructureObjective systems, especially large ones, face a major problem: they are usually inconsistent,which means that achieving one objective, inevitably leads to the failure of another. Theinherent problem, as to how strategies are formed in organizations, is targeted by majorresearch projects in the management research community (Allison 1971; Ansoff 1965;Barbuto Jr. 2002; Barnard 1938; Granger 1964; Mintzberg 1973). However, we do not aim tosupport the definition of consistent objective systems. In fact, we assume that inconsistenciescan be overcome by the approaches presented in the literature. We do support the monitoringof given objectives by comparing them to actual business developments.3.3 Integration of Objectives into MetaMISThus far, the MetaMIS approach for the specification of managerial views on businessprocesses has been introduced, followed by a discussion on business objectives. To integratebusiness objectives into MetaMIS, the set of meta model constructs introduced in the lastsection, needs to be extended and connected to already existing MetaMIS modelingconstructs.In contrast to non-operational objectives, operational objectives can be integrated intoMetaMIS, because their defining components measure, time frame, reference, and level can Page 16
  • 17. be transformed into MetaMIS constructs. In order to measure an objective, we introduce theconstruct Objective Measure. Different objectives may have different objective measures.Financial ratios like earnings or costs are represented by the construct Quantitative Measure.Qualitative aspects such as efficiency or quality are subsumed by the construct QualitativeMeasure. Quantiativ and qualitative measures are generalized into the construct Aspect.Operational objectives need to be achieved within a certain time frame, e.g., one year.Furthermore, operational objectives consist of another mandatory component, a reference.Every objective must refer, for instance, to a product, product group, service, customer, ormanagement unit. The construct Reference Object represents both time frame and objectivereference as required components for defining operational objectives.Finally, the construct Objective Level is necessary to define a quantitative or qualitative levelto which the objective has to be accomplished. The objective level combines an objectivemeasure with a reference object. Having defined the objective measure, e.g., average deliverytime and a reference object such as ‘business unit Automotive Supplies, any product’, wehave to set the average delivery time of any product of the business unit Automotive Suppliesto a value of, e.g., 24 hours. The meta model consisting of the introduced constructs and theirrelationships is shown in Figure 6. Objective Structure (0,m) (0,m) Objective Strategy, u,t General Condition, and Guideline Operational (0,m) OO-OL-AS Objective Quantitative Aspect (0,m) Objective (0,m) (Ratio) u,t Objective Measure Level Qualitative Aspect (0,m) Reference Object Legend Reinterpreted <Identifier> Entity Type <Identifier> Relationship Type Connector ( (min,max) <Identifier> Relationship Type - min minimum cardinality, - max maximum cardinality) Specialization (Types: - u unequivocally, e equivocally - t total, p partial)Figure 6: Objective Meta ModelMetaMIS already contains the constructs Reference Object, Quantitative Measure, andQualitative Measure (see Section 3.1). The decomposed objective references will betransformed into dimension objects (see Figure 4) which will constitute dimensions. Thus, we Page 17
  • 18. derive an initial set of information on the construction of navigation spaces for managementanalysis, which will be discussed in more detail in Section 4.3.4 Defining and Decomposing Business Objectives – A Sample CaseAfter we discussed the definition of operational objectives consistent with a businessstrategy, described a way to decompose them into their defining components, and structuredthese components within a model, we now introduce a comprehensive case. The mainobjective has been introduced in Section 2.2 and is consistent with the general goal of long-term profitability according to the management approach CRM: • Objective Delivery Time Reduction of Business Unit Automotive Supplies: Decrease the average delivery time of all products of business unit Automotive Supplies to a maximum of 24 hours within the next year.The time frame for the objective is next year. Furthermore, it refers to all products ofbusiness unit Automotive Supplies. The time frame combined with the reference constitutesthe reference object. Average delivery time is a quantitative measure. If a time value (not atime frame) is assigned to the reference object, this value becomes a business fact. Sincedelivery time is composed of production time and shipment time, the objective is brokendown into two sub-objectives. The first sub-objective has been set as follows: • Objective Increase Production Efficiency: Increase production efficiency at assembly line V8 engine in factory alpha from level 8 to level 9 within the next year.As in the case of the main objective, the time frame is next year. The reference of theobjective is assembly line V8 engine in factory alpha. Efficiency is a qualitative measure,which can be expressed by the values (categories) zero to ten. The efficiency categories canbe calculated by algorithms, which consider various influencing variables or are derived byan auditing process, where trained personnel set the efficiency based on their observations.The second sub-objective to decrease delivery times refers to the shipping efficiency: • Objective Increase Shipping Efficiency: Increase shipping efficiency of products shipped out of factory alpha by any logistic partner from level 8 to level 9 within the next year.The time frame again is next year. It refers to factory alpha, any logistic partner, and anyproduct and is measured by the qualitative measure efficiency. Both sub-objectives aremeasured qualitatively. In order to derive the efficiency measures for both sub-objectivesdeterministically, each is split up again into three sub-objectives. Production efficiency isdescribed by the following objectives: • Objective Rejection Rate Reduction: Decrease the average rejection rate of product group Original Equipment – Engines products at assembly line V8 engine in factory alpha from 0.4 to 0.2 percent within the next year, without increasing the rejection rate of other product groups products assembled at this line, • Objective Machine Defect Rate: Decrease average machine defect rate of machines at assembly line V8 engine in factory alpha from 0.7 class A defects per week to 0.3 within the next year, • Objective Lead Time Reduction: Achieve an average lead time reduction during production of any single product of product group Original Equipment – Engines at assembly line V8 engine in factory alpha from 256 minutes to 240 minutes within the next year. Page 18
  • 19. On the other hand, shipment efficiency is broken down into these three objectives: • Objective Decrease Just-In-Time Deviation of Logistic Partners: Decrease the average just-in-time deviation of any logistic partner for any product shipped from factory alpha with an appropriate transportation to five minutes within the next year (Just-In-Time deviation is the time difference between planned and actual collection of a customer order by a logistics partner), • Objective Decrease Packing Time: Decrease the average packing time of factory alpha warehouse workers for any customer order to one hour within the next year, • Objective Reduce Warehousing Costs: Reduce the total costs of factory alpha warehouse to € 500,000 within the next year.These six objectives can each be decomposed into their defining components. Table 1 givesan overview of the entire objective system by decomposing each objective to time frame,reference, measure, and level. Sub-Objective Sub-Objective Time Main Objective Reference Measure Level Level 1 Level 2 Frame Delivery Time Reduction of Business Unit Automotive business unit automotive supplies, average delivery next year 24 hours Supplies any product time assembly line V8 engine, factory Increase Production Efficiency next year efficiency 9 alpha products of product group Original Rejection Rate average rejection Equipment - Engines, assembly next year 0.2 percent Reduction rate line V8 engine, factory alpha Machine Defect machines, assembly line V8 average machine 0.3 class A next year Rate engine, factory alpha defect rate defects per week single products of product group Lead Time Original equipment, assembly line next year average lead time 240 minutes Reduction V8 engine, factory alpha Increase Shipping Efficiency factory alpha, any logistics partner next year efficiency 9 Decrease Just-In- factory alpha, any logistics partner, average just-in- Time Deviation of next year five minutes product time deviation Logistics Partners Decrease Packing factory alpha warehouse workers, average packing next year one hour Time customer, order time Reduce Warehousing factory alpha warehouse next year total costs 500,000 € CostsTable 1: Operational Objective ComponentsThe defining components of decomposed operational objectives are structured according tothe model constructs introduced in Figure 6. In order to monitor the degree to which anobjective has been accomplished, operational objectives need to be transformed into planscenarios. After the end of the planning period has been reached, deviation analyses help tocompare these plan scenarios to the actual business development. The next section showshow objectives can be transformed into plan scenarios.4 Deriving MetaMIS models from Business Objectives4.1 Constructing DimensionsHaving defined operational objectives and structured them hierarchically, we are now able tocreate a conceptual model of the information system supporting managerial analysis. We first Page 19
  • 20. need to define dimensions which consist of hierarchically-structured dimension objects. As afirst step, the initial set of objective references taken from the definitions of operationalobjectives can be decomposed. The objects of the Reference column in Table 1 representsuch decomposed objective references, which will be redefined as dimension objects andstructured hierarchically. They thus form the basic structure of what will be a dimension.This process is complex creative work. Even so, without a methodological approach such asthe one presented here, no assistance with this process would be available.Questioning managers on basis of the specified operational objectives is imperative forderiving further insights into the structures of the information systems supporting managerialanalysis. Our example objective Rejection Rate Reduction states that rejection rates of otherproduct group’s products must not increase. This inevitably leads to the question as to whichother product groups should be considered for managerial analysis. The plan scenario thatneeds to be set up, will include the objective level of the product group Original Equipment –Engines, which needs to be decreased according to the objective. Furthermore, it includes theobjective levels of all other product groups which must not exceed the respective levels fromthe previous year.The identification of dimensions can be assisted by answering the question of whether theelements of operational objective references are structured in an n:m relationship or in a 1:mrelationship. The first case implies the modeling of two dimensions (because dimensions arehierarchical constructs of dimensions objects) whereas in the latter case, only one dimensionis modeled. This decision needs to be made carefully. It needs to be identified whether this1:m relationship occurs only temporarily, just as objective references of operationalobjectives, or generally. If it occurs generally, it is imperative to know, if the relationshipmight be changed by an ongoing business strategy. As mentioned above, identifyingdimensions is a complex process which directly influences data warehouse structures. It canbe seen as a strategic decision during the MIS specification process.In our example objectives from Table 1, there are eleven types of fundamentally differententities, business units, assembly lines, warehouses, factories, product groups, workers,products, logistic partners, time entities, orders, and customers. Now, does an assembly linealways belong to one factory or can it be spread over more than one factory? Is it possiblethat a factory runs more than one assembly line? Do workers work in one factory (at oneassembly line) or are they allocated to more factories (assembly lines)? Is a product alwaysassigned to exactly one product group? Questions like these have been made possible by thedefinition of operational objectives with the proposed method. They need to be answered byresponsible personnel from business domains to specify the management-supportinginformation system.Implying 1:m relationships between business units, product groups, and between productgroups and products, these three different entity types can be aggregated within onedimension Product. If, furthermore, all other entity types are bound by n:m relationships,each will be structured in one dedicated dimension. Only warehouses and assembly lineshave been aggregated within one dimension, because allowing analysis between these entitytypes would serve no purpose.To distinguish plan scenarios from actual business developments, we need the dimensionVersion. Version is a dimension consisting of the dimension objects Actual, and several planssuch as Plan, Plan optimistic, Plan pessimistic, or Forecast. Due to the fact that we transformobjectives into plan scenarios to compare them to future business development, we need toadd a dimension object of Version to each business fact. If it is a planned fact, a reference toa plan-version is necessary. In case of actual business facts, the Version dimension object Page 20
  • 21. Actual is referenced. Deviation analysis later compares business facts that differ only in thereference component of the dimension Version. Figure 7 contains all dimensions necessary tobuild the MIS environment, which allows for the managerial activity monitor delivery time. Product Production and Storing Facilities Automotive Supplies Assembly Line V8 Engine Original Equipment Machine V8 - JH7765K OE Engines Machine V8 - HJG5RF4 OE Chassis Components Assembly Line Chassis Components OE Electronic Components Factory Alpha Warehouse Replacement Electronic Components Personnel Engine Parts Assembly Line V8 Engine Foreman Electronic Parts Machine V8 - JH7765K Foreman Workplace 1 Industrial Supplies Workplace 2 Services Machine V8 - HJG5RF4 Foreman Time by Month January 2004 Assembly Line Chassis Components Foreman February 2004 Factory Alpha Warehouse Foreman Logistics Partner Factory Partners for Engines Factory Alpha Partners for Chassis Components Factory Beta Customers by CRM Class Order Class A Customers Order 0000001 Class B Customers Order 0000002 Version Plan Actual Legend <dimension identifier> <non-opened non-leaf dimension object identifier> <opened non-leaf dimension object identifier> <leaf dimension object identifier>Figure 7: Set of dimensions for managerial activity monitor delivery timeAfter the identification of dimensions, their basic structure of dimension objects which havebeen derived from operational objectives needs to be completed. Other dimension objectsthat will further be necessary to answer the managers’ questions, need to be added. Basically,this means that all relevant products of all product groups (product group Original Equipment– Engines and all others obtained from the answer to the question derived from theoperational objective Rejection Rate Reduction) are added to the product dimension. In thiscase, the product dimension would be extended by the products, product groups, and businessunits shown in Figure 7. This procedure needs to be repeated for every identified dimension.4.2 Constructing Navigation Spaces for Managerial ActivitiesThe definition of business objectives first needs to be followed by the managerial activity ofundertaking the necessary steps to implement improved business processes. Secondly, Page 21
  • 22. management must monitor the degree to which the defined business objectives have beenachieved. To address the problems of information overflow and information misuse, we needto define dimension scopes for specific managerial monitoring activities.To monitor the objective Increase Production Efficiency introduced in Section 3.4, we needto define six dimension scopes. As time can be limited to all time dimension objects of thesub-hierarchy 2004, the first dimension scope Time by Month Year 2004 consists of alldays and months in 2004 and the year 2004 itself. All other time entities are blanked out.Five more dimension scopes are built similarly. The dimension scope Factory FactoryAlpha reduces all factories of the dimension Factory to Factory Alpha, Product ProductGroup Automotive Supplies – Original Equipment – OE Engines focuses on engines, andProduction and Storing Facilities Assembly Line V8 Engine reduces the total set ofwarehouses and assembly lines to assembly line V8 Engine.Version is reduced to Plan in one dimension scope (Version Plan) and Actual in another(Version Actual), which allows for comparing the business facts based on these twovaluations. The dimension scope combination Production Efficiency joins all six dimensionscopes. It creates a navigation space for the required information of the managerialmonitoring activity corresponding to the objective Increase Production Efficiency. Thisnavigation space consists of all combined reference objects which are necessary to monitorthe objective Increase Production Efficiency itself, and all of its sub-objectives once therespective qualitative and quantitative measures have been assigned to them. The dimensionscope combination features two hierarchy levels. To create a combined reference object, onedimension object of each dimension scope of the first hierarchy level needs to be selected.Version is split up into two dimension scopes, which means that one of its dimension scopesneeds to be picked for the valuation of business facts. This is necessary, because noinformation would be aggregated from the versions, Actual and Plan (Holten, Dreiling 2002;Holten, Dreiling, Schmid 2002). Figure 8 contains the dimension scopes and the dimensionscope combination for the managerial activity monitor production efficiency. Page 22
  • 23. Product Product Group Automotive Time by Month Year 2004 Supplies - Original Equipment - OE Engines January 2004 Automotive Supplies 2004-01-01 Original Equipment 2004-01-02 OE Engines Production and Storing Facilities February 2004 Assembly Line V8 Engine Assembly Line V8 Engine December 2004 Machine V8 - JH7765K Factory Factory Alpha Machine V8 - HJG5RF4 Factory Alpha Version Plan Version Actual Plan Actual Production Efficiency Time by Month Year 2004 Product Product Group Automotive Supplies - Original Equipment - Engines Production and Storing Facilities Assembly Line V8 Engine Factory Factory Alpha Version Version Plan Version Actual Legend <dimension scope identifier> <dimension scope combination identifier>Figure 8: Set of dimensions scopes and dimension scope combination for managerial activity monitor production efficiencyThe second sub-objective Increase Shipping Efficiency of the main objective Delivery TimeReduction of Business Unit Automotive Supplies requires the construction of a different set ofdimension scopes and a different dimension scope combination. Four existing dimensionscopes can be used for the managerial activity monitor shipment efficiency, which are Timeby Month Year 2004, Factory Factory Alpha, Version Plan, and Version Actual.Additionally, five new dimension scopes are necessary for customers, logistic partners,orders, personnel, and production and storing facilities. Each reduces the total set of itscorresponding dimension’s dimension objects to the relevant one for the managerial activity.As for the managerial activity monitor production efficiency, a dimension scope combinationjoins all of these dimension scopes (Shipping Efficiency). In order to create combinedreference objects, again one dimension object from the first hierarchy level of the dimensionscope combination, needs to be selected as well as one element of either one the versiondimension scopes. Figure 9 contains the dimension scopes and the dimension scopecombination for the managerial activity monitor shipment efficiency. Page 23
  • 24. Time by Month Year 2004 Factory Factory Alpha January 2004 Factory Alpha 2004-01-01 Customers by CRM Class Any Customer 2004-01-02 Class A Customers Class B Customers February 2004 December 2004 Order Any Order Logistics Partner any Logistics Partner Order 0000001 Partners for Engines Order 0000002 Partners for Chassis Components Personnel Factory Alpha Warehouse Workers Production and Storing Facilities Factory Alpha Warehouse Foreman Factory Alpha Warehouse Version Actual Factory Alpha Warehouse Actual Version Plan Plan Shipping Efficiency Time by Month Year 2004 Logistics Partner any Logistics Partner Factory Factory Alpha Personnel Factory Alpha Warehouse Workers Customers by CRM Class Any Customer Order Any Order Production and Storing Facilities Factory Alpha Warehouse Version Version Plan Version Actual Legend <dimension scope identifier> <dimension scope combination identifier>Figure 9: Set of dimensions scopes and dimension scope combination for managerial activity monitor shipment efficiencyThe introduced dimension scopes and dimension scope combinations from Figure 8 andFigure 9, correspond to two managerial activities of the managers responsible for productionand logistics. Both managerial activities serve the purpose of reducing the delivery time ofbusiness unit Automotive Supplies as introduced with the main objective in Section 2.2. Theactivities of the higher management may just require the information, whether the deliverytimes have been reduced or not. The determining factors for this reduction are clear to theproduction and logistics managers, but in order to minimize information overflow, they arenot part of upper management’s view on business processes. Also, the hierarchical depth ofthe dimensions Product and Time by Month have been reduced. In contrast to the horizontalreduction of dimensions, this reduction is made vertically. It is no longer possible to drilldown from months and product groups to more detailed dimension objects such as productsor days. Figure 10 contains the dimension scopes and the dimension scope combination forthe managerial activity monitor delivery time of business unit automotive supplies. Page 24
  • 25. Product Business Unit Automotive Supplies Time by Month Year 2004 Automotive Supplies January 2004 Original Equipment February 2004 OE Engines December 2004 OE Chassis Components Version Actual OE Electronic Components Actual Replacement Version Plan Electronic Components Plan Engine Parts Electronic Parts Delivery Time of Business Unit Automotive Supplies Product Business Unit Automotive Supplies Time by Month Year 2004 Version Version Plan Version Actual Legend <dimension scope identifier> <dimension scope combination identifier>Figure 10: Set of dimensions scopes and dimension scope combination for managerial activity monitor delivery time of business unit automotive supplies4.3 Constructing Aspect SystemsAll defined business objectives from Section 3.4 have now been decomposed and used toconstruct dimensions. Furthermore, navigation spaces have been created to monitor if thebusiness objectives have been accomplished. In the next step, aspect systems will be definedwhich will be assigned to navigation spaces, allowing for the construction of business facts.The decomposition of facts in Section 3.4, led to measures which have been used to quantifyor qualify the references. As shown in Figure 6, these measures will be transformed eitherinto quantitative or qualitative aspects, depending on the nature of their values.To monitor the objective Increase Production Efficiency introduced in Section 3.4 severalaspects are necessary. First, production efficiency is a qualitative aspect. Levels from zero toten can be used to value production efficiency. The objective Increase Production Efficiencyhas been broken down into three sub-objectives, which have been transformed intoquantitative aspects. The measures of the three sub-objectives are average rejection rate,average defect rate, and average lead time. All three aspects will be organized into an aspectsystem Production Efficiency Measurement as sub-aspects of the aspect productionefficiency. For analytical purposes, the production efficiency is significant and used as astarting point. In case something is wrong, it is possible to drill-down to the influencingaspects average rejection rate, average defect rate, and average lead time.The construction of the second aspect system for the objective Increase Shipping Efficiencyis similar to the construction of the aspect system for the objective Increase ProductionEfficiency. Shipping efficiency is the most significant aspect. Three sub-aspects are derivedfrom the sub-objectives of the objective Increase Production Efficiency, which are averagejust-in-time deviation, average packing time, and costs.The construction of the main objective’s aspect system Delivery Performance Measurementdiffers from the first two aspect systems. It is constructed from three aspects, which areaverage delivery time, shipment efficiency, and production efficiency. Shipment efficiency andproduction efficiency are taken from the first two aspect systems, but in contrast to the Page 25
  • 26. production and logistics management, there are no drill-down possibilities for the aspectsShipment Efficiency and Production Efficiency. This again is due to avoid informationoverflow. All aspect systems for the three managerial activities monitor productionefficiency, monitor shipment efficiency, and monitor delivery time of business unit automotivesupplies are shown in Figure 11. 1 67 34 29 57 5 9 Production Efficiency Measurement Production Efficiency Average Rejection Rate Average Defect Rate Average Lead Time 1 67 34 29 57 5 9 Shipment Efficiency Measurement Shipment Efficiency Average Just-In-Time Deviation Average Packing Time Costs 1 67 34 29 57 5 9 Delivery Performance Measurement Average Delivery Time Shipment Efficiency Production Efficiency Legend 1 67 34 29 57 5 <aspect system identifier> 9 <super-aspect (hierarchically)> <sub-aspect (hierarchically)Figure 11: Aspect Systems for the managerial activities monitor production efficiency, monitor shipment efficiency, and monitor delivery time of business unit automotive supplies4.4 Constructing Information ObjectsAs pointed out above, a managerial activity which monitors if a business objective has beenaccomplished, needs to compare plan scenarios with actual business developments. Thenature of such analyses is that the reference objects of compared business facts differ only ina value of dimension Version (Holten, Dreiling 2002; Holten, Dreiling, Schmid 2002). Tocompare planned facts with actual business facts, fact calculations need to be defined. Anybusiness fact of a dimension scope combination which features the included dimension of thefact calculation, can be calculated according to the calculation expression. Figure 12 showsthe fact calculation Plan Variance. It calculates a percentage, which represents the deviationby which planned aspects differ from actual aspects. The fact calculation abstracts fromaspects. It can be assigned to each dimension scope combination, where part of it equals todefinition of Version in Figure 12. Page 26
  • 27. + % - Plan Variance Version Version Plan Version Actual Plan Variance := (Plan/Actual)*100 Legend + % - <fact calculation identifier> <dimension identifier> <dimension scope identifier> <calculation expression>Figure 12: Fact Calculation Expression Plan VarianceFinally, we are able to construct information objects for the three main objectives introducedin Section 3.4. Each information object in our example, consists of a dimension scopecombination, an aspect system, and a fact calculation expression. The information objectProduction Efficiency assigns the aspect system Production Efficiency Measurement to thedimension scope combination Production Efficiency. Furthermore, the deviation analysis ofplanned and actual aspects is rendered possible by the fact calculation Plan Variance. Bothother information objects are structured similarly. Figure 13 contains the information objectsProduction Efficiency, Shipment Efficiency, and Delivery Performance Measurement. Production Efficiency Production Efficiency 1 67 34 29 57 5 9 Production Efficiency Measurement + % - Plan Variance Shipment Efficiency Shipment Efficiency 1 67 34 29 57 5 9 Shipment Efficiency Measurement + % - Plan Variance Delivery Performance Measurement Delivery Time of Business Unit Automotive Supplies 1 67 34 29 57 5 9 Delivery Performance Measurement + % - Plan Variance Legend <information object identifier> + % - <fact calculation identifier> <dimension identifier> <dimension scope identifier>Figure 13: Information objects for the managerial activities monitor production efficiency, monitor shipment efficiency, and monitor delivery time of business unit automotive suppliesThe constructed information objects consist of planned and actual business facts. Besides theplanned facts that arise from plan scenarios defined by the introduced business objectives,other facts are included within these information objects. Examples are production efficiencyof factory alpha, shipment efficiency of logistic partners, or the average delivery times forcustomer orders within the year 2003. These other facts are part of a dynamic managerialanalysis which aims at detailing or generalizing the examined aspect of the business. Page 27
  • 28. 5 Summary and OutlookInformation Sharing is the conceptual core of inter-organizational business processintegration. Positive effects of information sharing on stock levels and delivery times alongsupply chains have been shown. Customer relationship management has been introduced toovercome informational uncertainty if information sharing is not possible. Informationsystems form the backbone of any supply chain integration and complex customerrelationship management analysis. Even though the information-technology side of supplychain integration is well understood by researchers and practitioners, the conceptualspecification of information systems for business process integration from a managementperspective remained an unresolved issue.In order to overcome the open methodological problem, we have introduced the MetaMISapproach for the specification of managerial views on business processes. In a sample case,we have shown how a system of operational sub-objectives aiming at achieving the objectiveof delivery time reduction, can be transformed into MetaMIS specifications. Thesespecifications can be used to create data warehouse structures (Holten 2003). With thepresented approach, the conceptual management perspective is assisted by first derivingspecifications of managerial views from defined business objectives, and second, thedevelopment of an information system supporting managerial analysis.Our future research will focus on validating our approach in various case studies fromdifferent business domains. We will further develop a tool for supporting the specification ofmanagerial views on business processes, in order to assist the development of enablinginformation systems from a conceptual management perspective.6 ReferencesAdam D (1996) Planung und Entscheidung, 4th edn. Gabler, Wiesbaden, GermanyAgarwal S, Agrawal R, Deshpande PM, Gupta A, Naughton JF, Ramakrishnan R, Sarawagi S (1996) On the computation of multidimensional aggregates. In: Proceedings of the 22nd International Conference on Very Large Data Bases, Morgan Kaufmann, San Francisco, CA, USA, pp. 506-521Ahlert D, Hesse J (2002) Relationship Management im Beziehungsnetz zwischen Hersteller, Händler und Verbraucher. In: Ahlert D, Becker J, Knackstedt R et al. (eds.) Customer Relationship Management im Handel, Springer, Berlin, Germany et al., pp. 3-30Ansoff HI (1965) Corporate Strategy, McGraw-Hill, New York, NY, USAAnsoff HI, McDonnell E, Lindsey L, Beach S (1990) Implanting strategic management, 2nd edn. Prentice-Hall, London, UKAviv Y (2001) The Effect of Collaborative Forecasting on Supply Chain Performance. Management Science 47(10): 1326-1343Barbuto Jr. JE (2002) How is Strategy Formed in Organizations? A Multi-Disciplinary Taxonomy of Strategy-Making Approaches. Journal of Behavioral and Applied Management 3(1): 64-73Barnard CI (1938) The Functions of the Executive. Harvard University Press, Cambridge, MA, USABechtel C, Jayaram J (1997) Supply Chain Management: A Strategic Perspective. The International Journal of Logistics Management 8(1): 15-34 Page 28
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