A Value-added Business Performance Management System with ...

Value-added Business Performance Management System with Adaptive Ubiquitous Technologies Xiuzhen Feng, Yang Peng, Haoran Xie, Ang Sha

A Value-added Business Performance Management System with Adaptive Ubiquitous Technologies 1

Xiuzhen Feng, 2Yang Peng, 3Haoran Xie, 4Ang Sha Beijing University of Technology, [email protected] 2 The Hong Kong Polytechnic University, [email protected] *3, Corresponding Author City University of Hong Kong, [email protected] 4 The University of Hong Kong, [email protected] 1, First Author

Abstract With the emergence of ubiquitous technology (UT), many enterprises are obsessed with it because it can improve the agility of their business processes. However, the benefit of ubiquitous technologies is limited if they cannot be embedded into the organization’s business information systems, which plays a significant role in the business performance management. Although some enterprises have tried to embed UTs to their core information systems like ERP to grasp the ubiquitous benefits such as higher customer satisfaction, higher productivity, and etc., it’s impossible for an enterprise to equip all the UTs since we have to consider the necessity as well as the cost. Therefore, it comes to a problem that how to establish a suitable business management information system with adaptive UTs to fit a certain enterprise? Besides, what kinds of values can such a system bring to the business of enterprises is unidentified. Accordingly, a multi-dimensional model is presented that shows how the UTs’ solutions are selected through the fit between organizational functionalities of UTs and business characteristics of the enterprise. Based on the proposed model, we have designed a general architecture of ubiquitous business performance management system, which could bring extra business values to enterprises. The identified business values can thus provide the fundamental evidence for the potential benefits that UTs could bring to organizations.

Keywords: Ubiquitous Technology (UT), Business Performance Management (BPM), Business Information System (BIS), Enterprise Resource Planning (ERP), Business Intelligence (BI)

1. Introduction According to AMR Research (Simon et al., 2007), the estimated ERP application revenue would be 43.4 billion US dollars in 2010. ERP system is becoming one of the most representative business information systems in organizations. However, many companies failed to achieve the full benefits of ERP system. On the one hand, companies are not organized in such a way to benefit from the new information tools provided by, and the new disciplines required of, the enterprise systems (Injazz, 2001), and on the other hand, the traditional ERP system has its own deficiencies, which are listed as follows: 

Lack of flexibility: Operations of some programs which are related to finance are fixed;

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Limitations in accessibility: To guarantee the information confidentiality, most companies enable the access to ERP system only on the intranet of the company;

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Disorderliness of delivery: Information is spread out on many fragmented system and there are few people who have an enterprise-wide view of the organization (Injazz, 2001). As for today’s rapid developing e-Commerce and e-Business, the shortcomings of the existing ERP system have become an urgent issue to be solved. However, it is impossible to get the full benefits of an ERP system without having integrated processes (Hammer and Stanton, 1999). Business performance management is a set of management and analytic processes that enable the management of an organization's performance to achieve one or more pre-selected goals (Frolick and Thilini, 2006). Therefore, a possible way of adding business values to the current ERP system is extending it with business intelligence so that the business performance management could be performed by the leverage of data in the ERP system.

International Journal of Advancements in Computing Technology(IJACT) Volume4, Number14, August 2012 doi: 10.4156/ijact.vol4.issue 14.4

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Besides, it can gain mobility from the integration of ubiquitous technologies. The top pressures driving companies turn to the mobile business intelligence are to improve business process efficiency, to improve employee productivity, to speed decision-making, to improve customer relations, and to deliver real-time bi-directional data access where and when decisions are made (David, 2008). In other words, the purpose of adopting the ubiquitous technologies in the performance management system is to bring the ubiquitous benefits for organizations in terms of improving the efficiency and effectiveness not only in the business process management inside, but also the customer relationship management outside. Currently, there are many UTs (e.g., Mobile phones and wireless networks, Radio-frequency identification (RFID), GPS, etc.) for enterprises to embed into their business information systems, so it is important for enterprises to select suitable UTs that can be embedded. Compared with the traditional ERP system, the business performance management system with ubiquitous technologies can get some distinct advantages as below: 

Ubiquity: by adopting the ubiquitous technologies, not only the users can access to the system in anywhere and anytime, but also the data could be entered and modified in the system ubiquitously, which meets the rapid development of e-Business and e-Commerce.

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Instantaneousness: since the business circumstances are changing faster than ever before, it requires organizations to react faster and wiser. By instant data accessing and processing, even analyzing, the real-time or in a short time decision-making support can be achieved.

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Intensiveness: business performance management is related to business intelligence. Since the BI can process data from the ERP system to generate KPIs and metrics analysis that feed reports or dashboards for decision-making support, the ERP system could be intensified by the BI integration. Since the data in ERP system could be accessed, processed and delivered in real-time by the incorporation of business intelligence and ubiquitous technologies, it is not only an enhancement but also a make-up for the current ERP system. Therefore, the current ERP system will be strengthened and new values can be created as well. Thus, the reminder this paper is organized as follows: Section 2 sets up the theoretical foundations of ubiquitous business performance management. In Section 3, the multi-dimensional model of the functionality-characteristic fit is designed to illustrate how to choose the suitable UTs for a certain enterprise to embed into its BIS. The general architecture of the UBPM (ubiquitous business performance management) system is presented in Section 4, and the business values of UBPM are assessed in Section 5. Finally, the findings are summarized, conclusions are drawn and possible future directions are given in Section 6.

2. Threotical fundations 2.1 Related works The applications and benefits of ubiquitous technologies are assessed in particular business processes (Lampe et al., 2004; Massoth & Paulus, 2008; Su, 2009). Consequently, the findings and results of these researches can only be utilized for organizations that have specific requirements on the particular business processes. Some researchers have done researches on the mobile/ubiquitous applications of the core business information system like ERP system (Dabkowski & Jankowska, 2003; Zheng et al., 2008). However, the benefits of the mobile/ubiquitous ERP system on the level of organizations have not been assessed professionally in these researches. For example, Dabkowski and Jankowska (2003) indicated that mobilized ERP system could bring ubiquitous benefits to organizations and illustrated with specific scenarios, however, the detailed benefits are unidentified. Accordingly, some researchers are focus on assessing the benefits of ubiquitous technologies, but these benefits are assessed separately with the business information system (Hillman & Brown, 2002; Rodina et al., 2003; Oertel et al., 2009). The relationship between business performance management and business intelligence is that BPM is focused, however, on a subset of the information delivered by a BI system. (Chuck et al., 2005). Consequently, some researchers have focused on the tools of BI system, which can generate and analyze the information for the BPM. e.g., Data Warehouse Bus Architecture (Kimbal et al, 1998), Corporate Information Factory (Inmon et al., 2001), Data warehouses (Inmon, 1992), Data Warehouse 2.0 (Inmon et al., 2008), online analytical processing (OLAP) (Codd, 1993),

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data mining (Fayyad et al., 1996), user community (Haoran et al., 2012b), semantic link (Xiuzhen et al., 2011b), etc. To improve the efficiency of these BI tools, further researches are also done respectively on data warehousing (Nguyen & Tjoa, 2003; Rick, 2010; Rajdeep & Bikramjit, 2010) and on OLAP (Jens & Wolfgang, 1998; Michael et al, 2003). Beyond data warehousing, Golfarelli et al. (2004) introduced business process management, which is to “decentralize” decision making. Thus Brocke and Rosemann (2010) suggested that BPM is contained within approaches to business process management.

2.2 Research framework The following research framework is proposed for designing a ubiquitous business performance management system with adaptive UTs, which presented in Figure 1. In order to identify the suitable UTs for enterprises to embed, we make a fit between the organizational functionality of UTs and the characteristics of enterprises. Through the characteristic-functionality fit, the adaptive functionalities that a ubiquitous BPM system should be equipped for a certain enterprise are identified. Since they are functionalizes of a ubiquitous BPM system, so it requires not only the UTs but also the BI tools to realize them. Based on the identified functionalities, we design the ubiquitous BPM system with adaptive UTs, and assess the business values of it for the evaluation.

Figure 1. Research framwork

2.3 The organizational functionality of UTs The functionalities of “smart item” for UTs are classified as data storage, data capturing, data processing, communication and performing actions (Oertel et al. 2009). Meanwhile, the organizational functionality of UTs is defined as the functionality of UTs embedded into the ubiquitous BPM system that could be utilized for achieving organizational objectives. Consequently, the different organizational functionality of UTs that can meet different needs of management are UDA (ubiquitous data accessing), UBAF (ubiquitous business activity facilitation), and U-BPM (ubiquitous business process management). The relationship of UDA, UBAF and U-BPM is presented as Figure 2.

Figure 2. The relationship of UDA, UBAF and U-BPM

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Ubiquitous data accessing: It ‘s on the operational level and aims at enabling users to access to the data inside the system in anytime and anywhere. Thus the UTs’ functionalities related to it could be the data capturing and data storage. For the data capturing, the RFID technology can be utilized to grasp the information of products or assets (Su, 2009), and the mobile phone (e.g., Smartphone) can make the information indicated to users ubiquitously (Xiuzhen et al., 2011a). Moreover, the item’s relative or absolute position information could be captured by GPS (Hightower & Boriello, 2001). Ubiquitous business activity facilitation: It’s on the tactical level and defined as the technical support for users to conduct business activities in the real world anywhere and anytime. The data processing capabilities of “smart items” can be used to mitigate the problem of handling large amount of real-time data (Oertel et al., 2009). Based on input about context and environmental conditions, “smart items” can adapt their state or behavior (Haoran et al., 2012a; Oertel et al., 2009; Xiuzhen et al., 2010), for instance, the expiry date of a product can be adjusted automatically to the observed storage conditions (Strassner & Schoch, 2003). For BI tools, the ETL tools could be utilized for data extraction, and ODS (Inmon, 1999) could be utilized for data integration, which involves cleaning, resolving redundancy, categorizing, and checking integrity. Ubiquitous business process management: It’s on the strategic level, which is an ubiquitous application of “business process management” (Golfarelli et al., 2004). It requires nearly all the UTs’ functionalities and BI tools. For the communication and performing actions of UTs, the wireless networks (e.g., Internet, 3G networks, etc.) and wireless transforming technology (e.g., bluetooth) could be utilized for the communication, and “smart items” can actively communicate with humans for performing actions (Oertel et al., 2009). Apart from the BI tools used in UBAF, the BI tools involved in the U-BPM are data mining, OLAP, data warehousing, etc.

3. Model design In order to find the relationship between the functionality of UT and the characteristic of enterprise, firstly, we have to identify the appropriate charactersitics of enterpise that can fit into this campaign. In the perspective of phsical, the UTs can shorten the space moving, and in the perspective of managirial, the UTs can simplize the busienss complexity. Therefore, a matrix model of functionality-characteristic fit is proposed as Table 1. Table 1. The matrix model of functionality-characteristic fit

4. System architecture 4.1 System components Data source: it is consisted of two kinds of databases; one is the DBMS of ERP system, and the other is other databases. 

DBMS of ERP system: the data in UBPM system is mainly from the DBMS of the ERP system. Generally, the DBMS in ERP system is an integrated database, which may consists the data of customers, sales & purchase orders, finance, inventory, employees, etc.

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Other databases: since the BI analysis may need data from other areas, so other databases act as alternative data sources.

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Figure 3. Architecture of UBPM system Business performance management: it aims to perform the business performance management more efficiently and it is consisted of four components, which are BI analytics platform, business monitoring center, invoking server, and BI output database. 

BI analytics platform: it mainly consists of three BI analytics tools (data source viewer, OLAP cubes and data mining engine) and two information communication servers. The data source viewer aims at diagnosing and receiving the data stored in the data warehouses. The OLAP cubes can use a multidimensional data model by taking the complex analytical and ad-hoc queries into account with a rapid execution time. The data mining engine aims at translating the original query from users’ requests for data mining and retrieving the related results worked by OLAP cubes. The difference between a mapping server and a web service server is that mapping server is focus on distributing different analytical tasks to different working group of BI analytics tools, but the web service server is for communication between the BI analytics platform and outside servers.

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Business monitoring center: its function is constantly monitoring the performance in some sensitive business processes (e.g., inventory, cash flows, etc.) based on the analysis result from BI analytics platform.

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Invoking server: it enables the real-time link between a mobile device and the ERP system so that related functional modules in ERP system can be invoked for specific business activities.

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BI output database: the results worked by BI analytics platform will be stored in the BI output database for quick views.

Data preparation: it aims at extracting useful data from the ERP system, distributing the data for different requests, processing data, and storing the processed data. 

Data extraction engine: due to the large redundancy of data in ERP system and other databases, the data extraction is designed for retrieving useful data.

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Data warehousing: it is used for storing the processed data, and providing the right data according to the requests of the BI analytical platform in the business management layer.

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4.2 Operation procedures Step 1. The monitoring server sends commands to the web service server to conduct the BI analysis. Step 2. After web service server received the commands from monitoring server, it will assign the BI analysis task to the suitable BI analytic group in the Parallel BI analytics platform according to the different business performance metrics and KPIs. Step 3. At the same time, the data extraction engine in database part starts to extract the updated data from the DBMS of ERP system as well as other databases. Step 4. The extracted data is distributed and stored in the distributed DBMS of data warehousing for the requests of BI analytics platform. Step 5. The server in the distributed DBMS of data warehousing are interrelated by the communication subsystem. Step 6. Extracted new data is stored to the specific data marts by the programs in the server that the data marts linked to. So each extraction of data will lead to an updating in the related data marts. Step 7. The map server captures the data from specified data marts after comparing, and transforms the data to the data source viewer for confirmation. Step 8. If the data source viewer confirmed that the data is exactly what the OLAP needs, the OLAP and data mining engine would start the analyzing work according to pre-set business performance metrics and KPIs. Step 9. The BI analysis results is sent to the web service server, and transformed back to the monitoring server for matching mechanism. Besides, the newest BI analysis results will be stored in the BI output database for quick views. Step 10. The monitoring server runs the matching mechanism, in which the warning value related to business sensitive areas would be set. Step 11. Users login the system via access control server. The identity of the user would be identified and different authorities would be given to different levels of users. Step 12. If the user with authority wants to access to specific data in the ERP system, he can send his requests to the extraction engine for acquiring the original data in the DBMS of ERP system he wants. The data extraction engine receives the data acquisition request, and then conducts the step 3 to extract data. Step 13. If the user with authority wants to conduct the BI analysis himself, he can also send his requests to the web service server, and almost the same process from the Step 2 to Sep 9 above will be conducted respectively in accordance with the user’s request. Step 14. After the user sending the request to the web service server for BI analysis, he can also choose to access to the BI output database, which stores the latest BI analysis results, to get a quick view about the whole business performance. Step 15. If the user has the authority of conducting business activities in the ERP system, he can send the request (e.g., click on the “Instant ordering” button) to the invoking server. Step 16. After receiving the requests from users, the invoking server will activate the ERP functional modules related to such a business activity (e.g., inventory, sales orders, etc.). Step 17. Users use the RFID scanner & reader to record the product and asset information and transform it to the ERP system.

5. Business value assessment 5.1 Approach To make the business value of the UBPM system explicit, the means-ends objective approach is utilized. Firstly, we listed the functions or services enabled; Secondly, we identified the business objectives and listed after the functions or services; Thirdly, if the business objective is the end, it's the fundamental business objective, whereas if the business objective is not the end, it's the means business objective and the objective identification process will be repeated again and again until the fundamental business objective is identified; At last, we linked the business objectives and functions or services with each other by cause-effect relationship in terms of arrow. The results are summarized as Figure 4.

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Figure 4. Means-ends Objectives Network

5.2 Discussion Efficiency: With the ubiquitous accessibility offered by the 3G network application and the powerful data processing capacity provided by the backstage supporting system, the UBPM system can save a lot of time in communicating, retrieving, updating and utilizing the data/information. Meanwhile, minimizing the redundant and duplicated tasks can save the resources consumed on them. For the realtime decision-making support, it can shorten the lifecycle of the data to information, even information to knowledge in a company, which can save the time in decision-making. Effectiveness: Effectiveness can be enhanced by the maximizing accuracy of data/ information, minimizing errors & mistakes and optimizing the data & process. With the ubiquitous accessibility in the UBPM system, the data is entering and updating in real-time in the UBPM system, so the accuracy of data/ information can be guaranteed to improve the effectiveness in an enterprise. Customer satisfaction: With the ubiquitous accessibility and instant business activity availability in the UBPM system, the communication between external and internal could be enhanced and the quality of service could be improved as well. Besides, the real-time decision-making support can also improve the quality of service by meeting the customer's needs quicker. Cost: The UBPM system can help reduce the operating cost by decreasing the paperwork, minimizing errors and mistakes and eliminating the redundant and duplicated tasks. While the real-time decisionmaking support can offer a clearer and more comprehensive image of business operation image to people in management board so they could understand the whole business processes better and an optimization of resources allocation can be achieved. Risk: Risks can be minimized by the function of 24/7 business monitoring in the UBPM system. In a recent research (Paul, 2010), it is suggested that intelligent use of ERP system in terms of building alerts on certain fields can help mitigate internal fraud for companies.

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6. Conclusion The organizational functionality of ubiquitous technologies is proposed to make the functionalitycharacteristic fit, through which the adaptive ubiquitous technology functionalities can be determined. Thus the identified enterprise characteristics could be utilized as indicators for illustrating that what kinds of enterprises have the need of ubiquitous technologies embedded business information system. Based on the functionality-characteristic fit model, a general architecture of ubiquitous business performance management system is proposed, which provides an innovative way of incorporating adaptive ubiquitous technologies and business intelligence to the ERP system that not only to enhance the functionality of current ERP system, but also bring extra business values to enterprises. More importantly, the extra business values that can be brought by the UBPM system with adaptive UTs are assessed, which are managerial value, economic value, customer value and employee value. Through case studies and surveys, the more characteristics of enterprise could be assessed and identified so that better personalization of the adaptive ubiquitous technologies embedded business information system could be achieved.

7. Acknowledgement The research work presented in this paper was supported by Beijing Planning Office of Philosophical and Social Science “Eleventh Five-Project” Fund (10AbJG389).

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