مدل فعالیت فرآیند کسب و کار و اندازه گیری عملکرد با استفاده از تجزیه و تحلیل مداخله ای سری های زمانی ARIMA

The degree of performance excellence that an enterprise can achieve greatly depends on the business process flow that the enterprise adopts, where the more efficient and effective the business process flow, the greater the degree of performance excellence the enterprise can achieve. Most conventional business process analyses focus on qualitative methodologies, but these lack solid measurement for supporting the business process improvement. Therefore, a quantitative methodology using an activity model that is described in this paper is proposed. This model involves the use of an adjacent matrix to empirically identify inefficient and ineffective activity looping, after which the business process flow can then be improved. With the proposed quantitative methodology, a time series intervention ARIMA model is used to measure the intervention effects and the asymptotic change in the simulation results of the business process reengineering that is based on the activity model analysis. The approach is illustrated by a case study of a purchasing process of a household appliance manufacturing enterprise that involves 20 purchasing activities. The results indicate that the changes can be explicitly quantified and the effects of BPR can be measured.

The business process is a framework for activities to participate and interact so as to produce a product or a service and achieve the well-defined objectives of an enterprise (Hammer & Champy, 1994; Keung & Kawalek, 1997), and the structure of it greatly affects the overall performance of the enterprise. Moreover, in this ever changing global marketplace, the better the performance of the enterprise, the greater the competitiveness the enterprise can achieve. An enterprise not only faces challenges in external global competition but also faces root challenges of internal business process improvement to drive the performance towards excellence (Schorr, 1998). It is then important to evaluate and analyze the internal business process of the enterprise for the necessary partial or complete redesign of the process to improve the business performance (Morrow & Hazell, 1992). Very often, an enterprise may need to perform a dynamic analysis of their business process so as to simulate and evaluate different sets of processes that could ensure the efficiency and effectiveness of the business process flow as well as improve the overall performance of the enterprise (Alera, Borrajoa, Camachoa, & Sierra-Alonsob, 2002). Business process analysis is based on the business process flow or business process model that the enterprise has adopted. Business process modeling is one of the business tools that help an enterprise to achieve competitive advantages and improve business performance. The business process flow can be systemically represented and mapped by the model, and business process analysis can then be carried out. With the analyzed results, the business process can be revolutionized, redesigned or reengineered, so the enterprise can then achieve the great benefits of enhanced competitiveness (Evans, Towill, & Naim, 1995). Business process modeling and business process analysis are two inter-related research areas. In the research area of business process modeling, research interests ranges from process enactment, such as ECA Rules (Bae, Bae, Kang, & Kim, 2004) and collaboration with business process choreography (Jung, Hur, Kang, & Kim, 2004) to process monitoring, such as enterprise information portal (Hur, Bae, & Kang, 2003) and run-time environment (Kim, Kang, Kim, Bae, & Ju, 2000). Some leading approaches to business process modeling representation have been discussed in the literature, such as the family of Integrated Computer Aided Manufacturing Definition (IDEF) (Defining IDEF, 1992, Kusiak et al., 1994 and US Air Force, 1981), petri-nets approach (Van der Aalst & Van Hee, 1996), hyper-graph approach (Huang, 1997), entity relationship modeling (Maker et al., 1992), the role activity diagrams approach (Ould, 1995), and state-driven approach (Lee, Kim, Kang, Kim, & Lee, 2007). On the other hand, research into business process analysis ranges from process analysis to process improvement, entailing aspects such as workflow mining (Van der Aalst & Aj, 2004), process measurement (Cardoso, 2005), and process optimization (Ha, Bae, Park, & Kang, 2006). Moreover, there are a number of analysis techniques that have been discussed in the literature, such as reachability graph (Yang & Liu, 1998), the structural analysis approach (Sadiq & Orlowska, 1999), Queueing theory (Kleinrock, 1975), self-organizing map (SOP) or dimensional output space (Díaz, Domínguez, Cuadrado, & Fuertes, 2008). The research discussed in the literature and the approaches for business process modeling and analysis all have different advantages and disadvantages. However, research into business process modeling and analysis still has room to improve, since most of the work focuses on the qualitative approach that concerns the logical correctness of the defined process instead of the performance of the defined process. Therefore, in this paper, we propose a quantitative approach using an activity model for business modeling and analysis, in which, adjacent matrixes can be applied to provide explicit performance indicators for the enterprise to identify the inefficient and ineffective activity looping, and the business process flow can then be improved. Moreover, the proposed quantitative methodologies use a time series intervention ARIMA model to measure and compare the simulation results of the business process reengineering. This is based on the process activity analysis, so that the intervention effects and the asymptotic changes can be determined. After this introduction, the rest of this paper is organized as follows: Section 2 contains the description of the basic six types of business activity interactions. The description of the activity model and analysis for business process are proposed in Section 3. Then a time series intervention ARIMA model for measuring process activity changes is discussed in Section 4. The simulation analysis and the results of time series intervention ARIMA analysis of the business process reengineering based on the proposed activity model analysis are presented in Section 5. Finally, conclusions are given in Section 6.

As the business marketplace becomes more globalized, enterprises are more eager to increase their competitiveness. Research on business process modeling and analysis then become more important for driving the business process towards excellence and for gaining a competitive advantage. In this paper, a quantitative approach of activity model analysis is proposed, which involves business modeling and analysis based on the Boolean adjacent matrix A, reachable matrix R and activity cycle matrix C. The inefficient and ineffective activity looping in the business process can then be explicitly identified and tackled, and the business performance can be improved accordingly. With the proposed activity model for business analysis, a time series intervention ARIMA model is then used to provide a precise estimation of the form and magnitude of the intervention effects of the business process reengineering, based on the proposed activity model analysis. Moreover, a case study of a purchasing business process is used to illustrate the effect of the proposed activity model analysis. A time series ARIMA model is then used to measure and compare its simulation results. Both of the analyzed results reflect that the proposed activity model analysis can really provide a useful and quantitative way for business process improvement, and can enhance the efficiency and effectiveness of the enterprise performance.