Implementing Business Intelligence in Textile Industry

Implementing Business Intelligence in Textile Industry Are Managers Satisfied? 1 Kornelije Rabuzin, 2 Darko Škvorc, 3 Božidar Kliček 1,Kornelije Rabuzin University of Zagreb, Faculty of organization and informatics Varazdin, Croatia, kornelije.rabuzin@foi.hr 2 University of Zagreb, Faculty of organization and informatics Varazdin, Croatia, darko.skvorc@foi.hr 3 University of Zagreb, Faculty of organization and informatics Varazdin, Croatia, bozidar.klicek@foi.hr Abstract In this paper we show how a business intelligence solution was implemented within the textile industry. Before the implementation phase took place, we explored whether different levels of management could use information technology and business intelligence in order to build reports on their own. As it turned out, they were all using computers on a daily basis and they said that they would use business intelligence in order to make better decisions. After the system was implemented, we built another questionnaire and we used another application to detect whether the system was useful and used. As it turned out, the system was well designed and useful, but managers didn t use the business intelligence system. In fact, they increased the number of requests and the IT department had to create even more reports than earlier. 1. Introduction Keywords: Data warehouse, Business intelligence (BI), Textile industry In the past decades many applications were built in order to support different business processes. As a consequence, one can find many examples, i.e., companies that have similar problems. Although many applications (information systems) exist (within some company), they are not compatible. When one has many systems to search for a piece of information, the process of finding that piece of information may be expensive and many steps may be required to get some result. Moreover, when one needs another piece of information, one has to do the things (steps) all over again and that is not something that one should encourage. Business intelligence and data warehouses became popular in the past decade (although they are a little bit older) because they tried to solve the problems that many incompatible applications and information systems imposed. When you build a central data structure called a data warehouse, many reports can be built within seconds and one can make decisions based on clean and integrated data coming from different sources. However it is not easy to build a data warehouse and many things can go wrong along the way. People that use data warehouses know what Extract-Transform-Load (ETL) is and they know how much time it takes and what problems it has to solve. Just to get an idea, some members of our team worked on a few such projects including a project that had to integrate sales data for two grocery stores from two different locations. In this particular project, both grocery stores used the same application, although that doesn t have to be the case. Before a data warehouse was built, it was not possible to compare the sales data from two stores at all. Namely, although products sold in those stores were the same, each store used different product id and different product name (for same products). As such, one couldn t just compare products by their name or id. In order to do so, data had to be cleaned and one common table of products had to be built. This new table was then connected to the sales data (sales data had to be moved to another table called a fact table, but we skip the details). So when building one such common table, you have to resolve different problems like missing data, wrong data, incomplete data, etc. More information regarding Data Warehouses (DW), ETL and Business Intelligence (BI) can be found in references [6], [9] and [12]. If one looks back, companies that had more capital and that were more profitable usually invested in BI solutions. Some industries that are not so profitable don t have enough money to invest is such International Journal of Information Processing and Management (IJIPM) Volume 6, Number 1, February 2015 1

projects as such project can be expensive, especially in the beginning. Reasons as to why BI was not used/implement within the textile industry in Croatia have already been explored in a previous paper [15]. In that paper results were presented that we obtained by building a questionnaire for manager and IT professionals within the industry. Some interesting answers are used in this paper as well. As one can find in [15]: In recent years many articles were published on BI and different aspects of implementation of BI systems. Articles that can be found usually describe what we would call the best practice from the areas where business intelligence has been applied successfully, such as the telecommunication sector, financial sector, etc. ([2], [8], [14]). There are only a few studies that present implementations in other business areas like industry, tourism, etc. In most of those papers business intelligence is analyzed only from the perspective of IT professionals (specialists) and deals with technical aspects of implementation (methods of data mining and data warehousing, analytical tools for data processing, etc.). A small number of papers deals with issues related to organizational aspects of business intelligence implementation like project management, critical success factors, etc. [5]. In [7] authors show that theoretical research dominates among published articles. In [11] authors point out the insufficient number of papers that contain a comprehensive, empirically validated and generally applicable methodology and guideline for implementation of BI systems, although a few can be found. In [10] the authors propose a Business Intelligence Roadmap, in [17] a methodology that puts accent on high quality artificial intelligence tools is proposed, and in [18] the authors put accent on critical success factors to implement a BI system. Other interesting references are [1], [3] and [4] as well. When one builds a BI system, many problems are more likely to occur. According to SAS, the problems are [14]: - BI tools are too expensive, - there are no IT professionals in the field, - benefits of BI systems are not obvious and cannot be measured, - top management doesn t support such projects, - the organizational climate is not appropriate, etc. In [15] we tried to identify and explore why BI was not used in Croatian textile industry. As we wrote in [15]: In order to determine the current state of the art regarding the management decision-making process and to examine the reasons why BI is not used in the Croatian textile industry, the survey was conducted among managers and IT professionals employed in the Croatian textile industry. The main goals of this study were (for managers) to determine their opinion on the importance of information in decision-making process, to determine which sources of data and which software packages are used by managers in the decision-making processes, to determine their opinion on business intelligence, to examine their opinion on the reasons why BI is not implemented in their company and to determine the degree to which managers embrace new technologies. Regarding the IT specialists, we wanted to determine their opinion on BI and why BI has not yet been implemented in their company. The results that we got were attention-grabbing for sure. In this paper authors describe how a BI system was implemented and used, i.e., authors also measured the customer satisfaction. The paper is organized as follows; in the first part we present some questions and answers from the questionnaire and then we present the BI system that was developed. Then we describe (briefly) how the system was used (customer satisfaction) and in the end the conclusion is presented. 2. Questionnaire In [15] we used two questionnaires that were prepared according to the IBM guidelines which can be found in [13]. In [13] one can find questions that can be used to determine whether a company is a good candidate to implement the BI system. Since more profitable companies invest capital in BI solutions, some companies do know what BI is and are aware of its importance. However, they do not invest in such solutions. In order to determine why that is so, a survey was conducted within the Croatian textile industry which included managers as well as IT professionals. The results that we received from managers are listed in the table below (Table 1); first column contains the question and second column contains their answers (more information on the sample can be found in [15]): 2

Question Can you notice positive and negative trends in the business as well as opportunities and problems in your company and its environment? Does your company perform detailed market research before placing a new product to the market? Do you have accurate, complete and prompt information needed for decision making? Do you make decisions based on information from business reports or based on your experience and intuition? Regarding the previous question, the managers were also asked which activity was more time-consuming: report or decision-making. Do you know what Key Performance Indicators (KPI) are? Which data sources do you use when making decisions? Do you know what Business Intelligence is? Managers were then offered a brief explanation of the term "Business intelligence", and they were asked whether such a system was needed in their company or not. Do you think that your company is ready to implement the BI system i.e. does it fulfill all technical, human, financial and organizational requirements necessary for successful implementation? Table 1. Answers received from managers Answer (managers) - 68 % responded that they generally could notice trends - 20 % responded that they couldn t notice trends - 12 % responded that they could always notice opportunities and problems - 44 % answered that they did not have this kind of information - 32 % thought that the company did not perform market research - 24 % thought that the company performed market research only partially - 56 % said that they always had accurate and complete information - 36 % said that they mostly didn't have accurate and complete information - 60 % said that their decisions were mainly based on the information from business reports - 32 % said that they made decisions based on their own experience and intuition - 68 % responded that they spent more time on collecting data and preparing reports - 24 % said that they spent more time on decision-making - 8 % didn t know - 88 % responded that they knew what key performance indicators were - 12 % responded that they didn t know what key performance indicators were Furthermore: - 48 % monitored key performance indicators periodically - 32 % monitored key performance indicators regularly - 20 % didn't track key performance indicators at all 40.38 % used internal sources, then data from the Internet (34.62 %) and then external data sources (25 %) - 52 % knew what BI was - 40 % heard about BI but they only partially knew what BI was - 8 % heard about BI, but they had no idea what it was - 84 % thought that such a system was required and should be implemented - 16 % believed that the BI system was needed, but the moment to implement such a system was not appropriate - 36 % thought that the company was not ready and that it would be ready in the near future - an equal number of managers believed that the company was not ready yet, but that it would be ready in the near future - 24 % were not able to answer that question - 4 % thought that the company was ready for implementation 3

Figure 1 shows the main reasons that managers indicated why the BI system was not yet implemented (each manager had to pick three possible reasons): Figure 1. What are the main reasons why BI is still not used in your company? In the end we used TRI index ([16]) to see whether managers would use new technologies, including business intelligence as well. As we already wrote in [15], TRI evaluates whether a person is a "technology type" (person accepts technology) or a "non-technology type" (person rejects technology). The methodology consists of several statements and for each statement respondents must choose whether they agree with it or not. The statements are related to various aspects of ICT, and they reflect a person's beliefs and opinions about ICT. Their answers are shown in the next figure: Figure 2. The opinion of managers about ICT (according to the TRI methodology) 4

We also built another questionnaire to see what IT people working in the company thought about BI solutions and managers in their company. Their answers can be summarized as follows (for more information one should look at [15]): - Most IT specialists (88.89 %), knew what business intelligence was; - Most IT specialists (88.89 %) believed that their company needed a BI system and that such system should be implemented; - Some IT specialists (55.56 %) had no experience with business intelligence development tools, and 44.44 % had only some experience; - Regarding the implementation process, 55.56 % considered that their company was not ready to implement such a system. It is interesting to see what IT specialists thought about main reasons why BI was not yet implemented (Figure 3): Figure 3. The main reasons why BI is not used in the company As one can see, many insights have been revealed. Furthermore, the company turned out to be a very good candidate for BI implementation, although people thought that the time to implement such a system was not right. 3. Data warehouse model Based on the results above, it was decided that a data warehouse should be implemented and several data marts were developed with only one external consultant (Figure 4): Figure 4. The developed data warehouse model 5

Database management system that was used in the company was Oracle. Because of that Oracle Warehouse Builder was used to build the data warehouse, and QlikView and RapidMiner tools were used for reporting and data analysis. Here we skip the technical details (the implementation phase was not too complex). After the system was implemented, different reports were built in a matter of seconds. We do not show them all for obvious reasons; one report just shows sales data (quantity) per regions (Figure 5): Figure 5. Sales data per region After the BI solution was implemented, we decided to test what people thought about it. Another even more important item that our team tested was customer satisfaction. The results are presented below. 4. Customer satisfaction After the implementation phase was over, users started to use the developed solution and we started to measure their satisfaction with the system. In order to do that, two things were done: - another questionnaire was built (for managers); - a small application was used to track requests for reports that were sent to the IT department. The first question in the questionnaire tested manager s satisfaction with the system. 78,26 % of them answered that they were very satisfied with the system and 21,74 % answered that they were satisfied. Then they were asked whether the BI system satisfied their needs. 69,57 % of them responded that the system satisfies their needs entirely, and 30,43 % of them answered that the system satisfies their needs (mostly). The next step was to determine whether the system was easy to use. According to the answers that were received, reporting was simple, OLAP analysis was more complex and data mining was considered to be the most complex for managers (Figure 6). As shall be presented, although reporting was considered to be simple, users didn t use this feature very much. 6

Figure 6. Customer satisfaction The application that was used to track requests for different kinds of reports showed that after the BI system was implemented, the number of requests increased. This means that managers had an opportunity to use the BI system to produce reports on their own, but that didn t happen. Instead, the number of requests increased, i.e., they sent requests to the IT department (somebody in the IT department should create reports for them). According to the IT department, although the solution that was developed was simple, managers just didn t want to tackle with the new tools as it all seemed to be too complicated for them. After the system was implemented, the application that was used to store data on requests showed that the number of requests increased by 20 %. 5. Conclusion This paper presents how to implement a BI system in a company that may seem to be a good candidate to implement such a system. Before the implementation took place, a survey was conducted to see what people thought about such a solution. Some informative observations were revealed in the survey and they are presented in the paper. After the survey was conducted, the BI system was implemented and it began to be used on a daily basis. Another questionnaire was built and a small application was used to test customer satisfaction. Although the system turned out to be simple and intuitive, at least for reporting purposes, the developed solution was not used as we expected it to be. 6. References [1] Anderson, J., Kotsiopulos, A., Enhanced Decision Making using Data Mining: Applications for Retailers, Journal of Textile and Apparel, Technology and Management, vol. 2, 2002. [2] Business Week, Getting Smart About BI: Best Practices Deliver Real Value, New York, The McGraw-Hill Companies Inc., 2006. [3] Danis, D., Proulx, M., Improving ROI and Success Rate of Your Business Intelligence Project, Pyxies Technologies, 2009. [4] Howson, C., Successful Business Intelligence Secrets to Making BI Killer App, McGraw Hill, 2008. [5] Hwang, M., Success Factors for Business Intelligence: Perceptions of Business Professionals, In Proceedings of the 19th Annual Conference of the Association of Chinese Management Educators, Mount Pleasant, Central Michigan University, 2009. [6] Inmon, W. H., Building the Data Warehouse, Indianapolis, Wiley Publishing, USA, 2005. [7] Jourdan, Z., Rainer, R. K., Marshall, T. E. Business intelligence: An analysis of the literature, Information Systems Management, vol. 25, pp. 121-131, 2008. [8] Khan, A. et al., Drivers and Barriers to Business Intelligence Adoption: A Case of Pakistan, In European and Mediterranean Conference on Information Systems 2010, Abu Dhabi, pp. 1-23, 2010. 7

[9] Kimbal, R., Ross, M. The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, Indianapolis, Wiley Publishing, 2004. [10] Moss, T. L., Atre, S., Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications, Addison-Wesley Professional, Boston, 2003. [11] Olzak, C., Ziemba, E. Approach to Building and Implementing Business Intelligence Systems, Interdisciplinary Journal of Information, Knowledge, and Management, vol. 2, 2007. [12] Rabuzin K., Deductive data warehouses, International journal of data warehousing and mining, vol. 10, no. 1, 2014. [13] Reinschmidt, J., Francoise, A., Business Intelligence Certification Guide, San Jose, IBM Corporation, 2000. [14] SAS Institute, Business intelligence Maturity and the quest for better performance: Why most organizations aren t realizing the full potential of BI and what successful organizations do differently, SAS Institute, 2007. http://www.eurim.org.uk/activities/ig/voi/bi_maturity.pdf, downloaded: 13.11.2010. [15] Škvorc, D., Rabuzin, K., Business Intelligence in Croatian Textile Industry, The Global Management & Information Technology Research Conference 2012, The Business Review, Cambridge, vol. 19, no. 2, New York, USA, pp. 187 194, 2012. [16] Techno Ready Marketing, The Technology Readiness Index, http://www.technoreadymarketing.com/tri.php, downloaded: 20.01.2011. [17] Thieruf, R., Effective business intelligence systems, Quorum Books, Westport, 2001. [18] Yeoh, W., Koronios, A., Gao, J., Managing the Implementation of Business Intelligence Systems: A Critical Success Factors Framework, International Journal of Enterprise Information Systems, vol. 4, 2008. 8