河北科技师范学院本科毕业论文（设计）外文翻译商业智能在打造无缝冷链物流中的应用院（系、部）名称：商务管理系专业名称：物流管理学生姓名：宋国栋学生学号：9116100407指导教师：李丽杰2013年12月15日河北科技师范学院教务处制Applications of business intelligence in making cold chains seamlessAzimuddin KhanAbstractDue to intense competition, it has become inevitable for business organisations world over to become efficient and cost effective. Seamless cold chain infrastructure is critical for the success of cold chain business. Concurrent growth in demand for products such as fresh agricultural produce, frozen food, photographic films, chemicals and pharmaceutical drugs has lead to the necessity of managing cold chains intelligently. The managers of cold chains at strategic and functional level need actionable information for making their organisations agile. In the recent times, the concept of business intelligence has gained momentum and found application in diverse areas. In this paper, authors have made an effort to develop a framework of BI system for cold chains and highlighted the application areas of business intelligence for cold chains including a case study of cold chain business.Keywords: cold chains; business intelligence; BI; analytics; supply chain;1.IntroductionIndia falls short of 10 million tons cold storage facilities for storing agriculture-based produce, it has nearly 21.7 million tons of such storage facilities against required 31 million tons, and as a result 40% of produce is lost in fields after post-harvesting(KPMG-ASSOCHAM, 2009). India is a populous country and resource utilisation is always a major concern, to meet the demand. The demand for perishable food stuff, i.e., farm produce like fruits, vegetables and milk products, meat, fish, frozen food, photographic films, chemicals, and pharmaceutical drugs is increasing world over. This has also increased concerns regarding food hygiene and safety during storage and transportation to end point.The cold chains are providing integration of farm, processing, warehousing, distribution and retail business. Discrepancies in cold chain management can render products unfit for use so much so that consumption of these can even pose a threat to life. According to Bourlakis and Weightman (2004),the cold chains are vital. Effective management of cold chains is crucial for maintaining the safety, sanctity of food, and profitability of business.Technology finds significant application in facilitating processes related to warehouse, inventory, transportation, and distribution. These processes generate huge volumes of data. Such large volumes of data need to be analysed, streamlined and channelised in an intelligent manner to make organisation agile (Khan and Saxena, 2010). The sensible extract of information aids in prudent decision-making and contributes to value proposition for business by making them more competitive with proper utilisation of business intelligence (BI).In this backdrop, an attempt has been made to understand the concept of BI with reference to cold chains, development of framework for implementation of BI solution, identifying the application areas of BI for cold chains. To date, there have been few academic studies on the use of BI solutionsin cold chains, yet, ractitioners and researchers are interested in understanding the concept for improving performance and profits using BI. An attempt has also been made to understand the cold chain business through a case study of cold chain company.2. Concept of BITechnology has empowered cold chain business to access huge volume of data, which plays a critical role in planning and controlling of cold chain activities like warehousing management, transportation, distribution operation, freight management and of course the compliance management.In the year 1989, Howard Dresner, a research scholar at Garter Group (an IT research and advisory firm in Connecticut) popularised the term BI with a set of methods and concepts to improve business decision-making by using data resources. Simon and Shaffer (2001) stated that the period from 1990 to 1999 was a remarkable decade in which many core computing and communication technologies and developments from the prior decade came together and transformed the method of business. In 1990s, technology led to the birth and widespread acceptance of applications such as enterprise resource planning (ERP) and customer relationship management (CRM). Due to failure of distributed database management system, organisations pursued data warehousing, where data would be consolidated from many distributed and heterogeneous stores of data. Organisations that built and deployed data warehouses typically focused their usage on the informational/analytical side to generate reports, analyse trends, and so on.McDonald et al. (2002) stated that “once the data warehouse has been constructed, the stage is set for effective business intelligence”. A data warehouse provid es the supportinfrastructure for BI. BI is built on the foundation of data warehouse. Kalakota and Robinson (2001) define BI “as a group of applications that enable both the active and passive delivery of information or rather turn raw data into actionable intelligence. Data and information are collected from large databases to answer to mission-critical questions asked by its managers”. Gangadharan and Swami (2004) stated that BI is the result of in-depth analysis of detailed business data, including database and application technologies, as well as analysis practice. According to Moss and Hoberman (2004), the processes, technologies, and tools needed to turn data into information, information into knowledge and knowledge into plans, drive profitable business action. BI encompasses data warehousing, business analytics tools and content/knowledge management.Turban et al. (2007) infersthat “organizations are being compelled to capture, understand and harness their data to support decision making in order to improve business operations. Business cycle times are now extremely compressed; faster, more informed, and better decision-making is therefore a competitive imperative”. BI starts with day to day information that organisations need to run the business and assist to take correct decision based on facts at right time and at right place through out the life of business by doing analytics. This is a modern mantra for modern approaches to BI.As per Cody et al. (2002), BI and knowledge management technologies have been used in improving the quantitative and qualitative value of the knowledge available todecision-makers. BI has applied the functionality, scalability, and reliability of modern database management systems to build ever-larger data warehouses, and to utilise BI tools to extract business analytics from the vast amount of available enterprise data. BI systems facilitate the decision-makers to correct their intuition by taking advantage of analytical tools, which can test and verify intuition before applying it to the decision-making process. Decision-maker can also use predictive models to improve their decision-making. The current state of decision-making is forcing companies, to reap the real benefits of BI. BI solution can turn dynamic, detail data into information, and make it available in real-time to thedecision-makers. Actionable information must be accessible on-demand when it is required. It provides trends and patterns that might otherwise go undetected and unseen bydecision-makers.3. Framework for implementation of BI in cold chainsThe BI can be built with the use of technology through BI system, refining the processes and BI tools for analytics. BI can be applied at all three levels in the cold chains, i.e., strategic, tactical and operational. A framework has been proposed in Figure 1. The framework includes four basic components which are existing IT setup, Transformation tools, data warehousing and various BI tools for analytics.3.1 Existing IT setup for data collectionIn an organisation, online transaction processing system and other enterprise application generate huge volume of data. These data are stored in databases. These databases along with application software, present the business information to the business user through IT infrastructure including PC, Notebook, Tablet, Smart Phone and networks. All the applications for running cold chain business including warehouse management, logistic management, network planning, RFID tracking and monitoring, CRM, inventory management, quality assurance, HR application, order management and data management generate huge volume of data with different database at different location. There are certain external information, and data about the financial and market information which are taken from research organisations, government, regulatory bodies and company’s websites, audio, video, spatial and supplier data. Data can also come from e-mail, voice application, images, spatial data taken from satellite and regulatory compliance (Hazard Analysis and Critical Control Points (HACCP)/ISO 22000 norms) (Keener, 2007). Cold chain business has to heavily rely on radio frequency identification (RFID) tags attached to items, cases or pallets, monitor and log the environment temperature at predefined intervals duringtransportation or product lifecycle. The recorded data can be read and analysedin real time for better analytics.3.2 Data transformation toolsThe objective of this stage is to define and design data management strategy to ensure that organisation has right information and uses it properly. The greatest challenge is to collect the clean data, that too from various sources so that BI solution delivers the correct actionable information to management at different levels. The organisation should concentrate on quality of data, and investment must be made to ensure high levels of data quality. The duplicate data should be unified as it comes from various sources. The data coming from transaction system is atomic level data and should be recorded in detailed form. It is necessary to first clean and validate it using business rules through data cleansing tools. Transformation procedure defines business logic which maps data from its source to destination. Extract, transfer and load (ETL)tools are very helpful to reduce the development time, manage the flow of data from source to destination and upload data to tables of data warehouse.3.3 Data warehousing and data martInmon (1995) defined a “data warehouse as a centralized repository (collection of resources that can be accessed to retrieve information) of an organization’s electronically stored data, designed to facilitate reporting and analysis”. Kimball and Ross (2002) have given another approach where data marts are first created to provide reporting and analytical capabilities for specific business processes. Data marts contain, primarily, dimensions and facts. Facts cancontain either atomic data and, if necessary, summarised data. The single data mart can be build for specific business area such as sales or production. These data marts can eventually beintegrated to create a comprehensive data warehouse. The data warehouse is a play ground for analytics and it provides retrieval of data without slowing down operational systems.3.4 BI tools for analyticsThere are many categories of tools available in the BI market. BI vendors are now also consolidating tools in every category to provide complete BI solution to companies. However, some organisations still prefer to have best of breed strategy in which they select BI tools in each category from different vendors. The various categories are query and reporting, online analytical processing, dashboards and scorecards, performance management, predictive analytics and data mining and advanced visualisation.BI can derive better return on investment (ROI) from complex integrated cold chain management software and other operational systems implemented by unlocking the wealth of information stored in these systems.4.Application areas of BI for cold chainsThe cold chain business is constantly searching for cost effective methods to remain competitive in fast changing world where margins are thin, customer expectation is very high, regulatory compliances are mandatory, and product life is very short. Companies in cold chain are working hard to adopt the information technology to get the rich insight into the hidden trends through cold chain analytics. The BI system provides reports, analyses, and monitors the vast corporate data. It also helps companies to reduce supply chain production cost,improve efficiencies, accuracy, increase revenue and performance. The cold chain analytics also provides the details to reduce waste, produce fresher, higher quality products, and enhance the economic value generated from perishable food industry by giving 360-degree overview of financial and operational results. As per suggested framework, various BI tools can be utilised to generate various analytics in following areas of cold chain business.4.1 Supply chain intelligenceSupply chain intelligence allows cold chains to evaluate supplier performance to negotiate prices, ensure timely deliveries and maintain high standard of quality by analysing the demand patterns, supply networks, operations and customer service requirements.Wal-Mart has set the standard of supply chain analytics. With the analytics driven intelligence, supply chain disruption can be reduced to better manage suppliers. Commodity classification provides information regarding procurement data from various sources within or outside company and classify the spend information into meaningful categories to understand true volumes per commodity. This can be used to develop the sourcing strategies. Spend analysis provides a dynamic ranking system for identifying and prioritising the most valuable suppliers. Demand driven forecasting allows planning of future requirements and management of supply chain by using statistical models. Scenario planning and what if analysis reduces the finished goods inventory and stockouts. The complete process of optimisation of plans and procedures creates an everlasting and sustainable competitive advantage for the organisation throughout a supply chain despite the risks associatedso commonly with unbounded challenges.4.2 Transportation analyticsIncreasing fuel costs, international expansion, and global competition has forced to useBI to streamline operations, distribution, and fleet management. BI optimises service and ensures consistent on-time performance for cold chains. Customers are demanding more services at lower prices, making operational efficiency improvements a requirement for maintaining acceptable profitability. The process of getting products delivered from one place to another on time, efficiently, and at the lowest costwithout losing life are main objectives of cold chains. The temperature conditions at origin and destination, seasonal temperature, load configurations, transport routes and modes, total duration of transit, duration and location of handling and stopover points are very important factors for temperature sensitive transportation. In thisextremely competitive business, one late delivery or losing quality of products can miss revenue opportunities and a lost customerforever. BI tools can help gain insight into the complex process of transportation by providing carrier performance evaluation, mode-cost analysis, supplier compliance analysis, carrier relationship management, capacity planning, cycle time analysis, routing and scheduling, truck and driver performance analysis, and root cause and claims analysis.4.3 Warehouse analyticsWarehouse management provides the ability to know the location of stock, time of requirement, and transporting it correctly in the shortest time. BI provides inventory analysis, warehouse performance analysis based on picking accuracy, shipping accuracy, lines per hour, overtime hours and on time shipments, picking analysis to improve warehouse efficiency and layout design, and warehouse space utilisation analysis for getting cost per unit of space over a period of time.4.4 Inventory analysisInventory optimisation analysis enables to reduce the over capacity and ensure sufficient supplies, monitor carrying cost for obsolete and slow moving items and usage across location and time. These analyses provides inventory carrying costs, inventory turns, order fulfilment lead time, percentage of backorders, average item inventory, finished goods on hands, etc. The intelligent analytics provides improved quality, reduces spoilage, and lowers rejections to make the customer or retailer more satisfied.4.5 Quality life cycle analysis4.6 Asset maintenance analytics4.7 Customer intelligence4.8 Financial analytics4.9 Customer profitability analysis6 Conclusions5.ConclusionsLike every other business, cold chain business has also become fiercely competitive. In order to stay ahead, and remain competitive, the cold chains should implement BI solution. Huge volume of data generation from existing applications like warehouse management, logistics management, inventory management, RFID tracking and monitoring, order management, quality assurance, CRM, and supply chain management has given an opportunity to manager to take smart decision based on analytics rather than intuition. The suggested framework will guide cold chains to streamline their operation. BI solution implementation requires basic operational system in place. With rapid development of information technology, communication system and reduction of cost of smart phones has opened the new doors for cold chains to provide the mobile BI to their executives. There are some new trends like BI search, BI gadgets, and query as web service will make a lot of difference in future BI and those who implement BI solutions intelligently will definite have an edge over others.摘要随着全球竞争的加剧，企业如何控制成本，使企业运营变得更加高效越来越成为世界上所有企业不得不面对的课题。
