Cornairs Strategies - Assignment Example

Introduction The purpose of this formal report is to analyze Cornair and its current situation in order to introduce an effective information systems approach to help the company improve its current focus. This study will include the application of smart technology as well as business optimization to Cornair’s strategies. Relationships between data, information, knowledge, and intelligence will also be considered in this analysis. How smart business systems can be applied to Cornair will be presented, and the situations present in the company will be resolved. Methods The methods of this formal report include: 1. Researching business information systems strategy to find an answer to Cornair’s needs 2. Analysis of Cornair in order to understand necessary needs 3. Use of Internet and libraries to discover appropriate theories that can be applied to cornair. Analysis of Cornair: Strategic Analysis SWOT: Cornair Pre SWOT Analysis: Cornair Strengths: Cornair has several strengths to consider. As the case study states, “Comair has been an award-winning leader in the regional carrier industry. The FAA and various trade magazines have recognised Comair many times for its profitability, management, time-keeping, cancellation and lost luggage statistics.” Opportunities: Cornair has the opportunity to build a better informational system strategy in order to optimize its current business strategies. Weaknesses: Cornair unfortunately has several weaknesses to consider. These include the strikes present and unhappy workers, repercussions of 9/11 for flight companies, and their own inability to create an effective information system. Threats: The general threat here is the ineffective running and possible closing of the company due to its poor record of information systems. PESTLE analysis Political Factors: Political factors include the repercussions of 9/11 on all airline industries, which has caused many airlines to seek out alternative help from the government. Economic Factors: Due to the strike, 9/11, and its own failings in its information systems, Cornair is currently experiencing an overall loss of money and production. This can be reversed by focusing on new information systems strategies, as well as making sure employees are happy. Social: The employee strike is the most threatening social implication at this time, because the employees do seem to have a history of questioning the company’s approaches. Technological: The technological failures of the information systems in this company will need to be addressed in order to ensure the company’s success. Legal: Legal aspects focus on the employee strike, and the company must consider that if it is unable to keep its employees happy, this may result in lawsuits. Environmental: After 9/11 most airline companies suffered, and this is also true of the current economic crisis. Value Chain Inbound Logistics: The inbound logistics of Cornair focus on the receiving of the goods they intend to deliver to their customers, focusing on their regional carrier strategies. Operationis: Once these items are received, the primary service that the company offers is the carrying of these goods from one destination to another. Outbound Logistics: The completion of the delivery of the goods results in the completion of the outbound logistics. Marketing and Sales: Marketing and sales focus on the transportation of customers’ various goods; thus, the company needs to make sure they meet the customers’ respective deadlines. Service: The service focus on the transfer of goods or items from one area to another via airplane. Results Developing a New System: What Cornair Should Consider Currently, there are differing views of smart technology that needs to be considered by Cornair. As a starting point, it should be noted that smart technology is also known as data or information fusion, which is fanning out to applications as diverse as systems that predict earthquakes or traffic jams and robots that display hand–eye coordination. Some researchers see information fusion one day surpassing artificial intelligence and fuzzy logic in the breadth of real-world problems it can address. But others caution that the technology, which had its origins in military targeting systems, is still new and evolving over time. Essentially, in the military, the focus is on the monitoring of environmental parameters and making decisions based on predetermined scenarios that support an optimum solution. Just as the human brain assimilates input from all five senses, say a tangy strawberry, information fusion unifies multiple data streams in computers. For example, automatic target recognition—the seminal application—melds input from several sources into perceptions of “friend” or “foe.” (Thierauf, 1995) In a typical organization like Cornair, intelligence examines the distilled essence of customers’ and employees’ personal experiences and needs as well as a company’s operations that are interrelated with external sources. In the past, business intelligence was rarely shared, even among peers. Also, typically, such insights to understanding important relationships never reached top executives. However, more companies today are getting involved in the full utilization of business intelligence in terms of their everyday operations. Business intelligence has come a long way—from servicing a limited number of decision makers in a company to supplying hundreds of thousands of customers, employees, and partners throughout an enterprise—from systems that draw on most internal databases and data warehouses to those that access external data sources as well. Cornair, therefore, needs to implement the strategy of being open and honest—by doing this, they can keep their employees informed and avoid future issues, like strikes (Davis, 1994). Although business intelligence has helped a wider range of individuals within and outside the typical organization, there is a shifting paradigm to optimization that assists these same individuals to allocate a company’s resources in a more effective way. Basically, optimization means that after all data, information, and knowledge have been thoroughly understood (i.e., intelligence), the next level of importance to decision makers is the optimization of resources that they have at their command. Today, optimization is the essence of smart business systems. While effective intelligence focuses on a more thorough understanding of a company’s operations by its decision makers, effective smart business systems are concerned with monitoring a company’s operations that results in optimization or as near to optimization as possible. As such, smart business systems can enhance the effectiveness of a company’s operations by providing decision makers with very desirable solutions. Based on optimal answers or near optimal answers to a company’s operations, this approach can assist decision makers in getting a better handle on what is transpiring today and tomorrow for a typical company. Optimum (or near optimum) answers for decision makers in the various functional areas of a typical company means that all parameters of a problem or an opportunity have been identified for consideration. Having a thorough definition of the problem’s or the opportunity’s parameters goes a long way toward its formulation and its final solution using the appropriate computer software. If Cornair can apply this, they should be able to slowly and effectively solve their information systems problems (Gartenberg, 2001). Getting started on smart business systesm for the optimized organization like Cornair means starting small. That is, decision makers need to start with one operating unit and utilize optimization techniques to get this one area under control. Next, they can then move on to a higher level where there are several operating units working together. In all cases, decision makers need to keep the total organization in mind so that the bottom line of the organization improves as incremental improvements are made to the organization. This incremental approach to employing smart business systesm will be evident throughout the text. Today, optimization of the total enterprise can take several directions. For one, the optimization of profits within its financial constraints is a desirable goal. In other cases, the focus of optimization could be on providing a certain level of customer service or maintaining a certain level of stock for customer convenience. With supply-chain partnerships in wide usage today, there could be a combined company, customer, and supplier optimization approach so that there is a “win-win” situation for all parties. The utilization of optimization gives a typical company the necessary means (i.e., “smarts”) to meet most challenges facing it. Or to state it another way, optimization is stepping in to give a typical company the necessary smarts to face increasing competition (Neil, 2001). In the past, information systems told decision makers what had happened, but not why and what should be done. Today, the focus is on finding out why and what can be done so that there is a thorough understanding of what optimization approach would be best in order to have an optimized organization. While “what had happened” only provides the decision maker with an approach to solve today’s superficial problems, the “why” and “what should be done” help the decision maker to get at the root of the problems in order to prevent future occurrences. The same can be said for opportunities facing a company. Tied in with getting at the whys and whats is the search for improved profits that never ends. Many of the obvious areas for increased profit have been exhausted in the past. Both data gathering and management have been automated, even by smaller firms. Optimization, however, can be used to extract detailed information and knowledge from a system to yield new business opportunities. Optimization can fine tune operations to create further improvements in efficiency (Davis, 1994). For many companies the need to optimize centers around the existence of repetitive processes. For many operations, improving the efficiency of a single process, even by small amounts, can lead to substantial gains for the overall operation. Cornair would be no exception to this rule. Many production assembly lines have already been automated for improved efficiency, but further gains may be achieved by considering the order in which products are sent along the line. The gain for each product may be miniscule, but the overall gain for the assembly system increases with each product sent along the line. When the magnitude of the operation is large, the overall gain can be very large. Essentially, optimization allows a myriad of possibilities to be assessed and the most effective solution found in a timely manner (Gartenberg, 2001). There are numerous optimization techniques for use. The techniques used depend on the problem or the opportunity presented to the decision maker (i.e., it is situational). As will be seen in future chapters, there are a number of optimization techniques today that are an integral part of smart business software. These include linear programming, goal programming, integer programming, non-linear programming, transportation, and assignment methods. Also, software in the areas of optimization include predictive analysis, data mining or knowledge discovery, statistical analysis, and simulation, along with heuristic programming, and are a great boost to decision makers seeking to optimize one or more areas of an organization. Typically, optimization techniques and related software are giving decision makers the “smarts” necessary to guide a company in these fast changing times. In Cornair’s case, the use of such software could help with its current information technology problems (Patch, 1998). Currently, many companies are charging their application development teams with refining existing business processes through the use of specialized optimization tools. These tools are based on sophisticated software optimization algorithms, which traditionally required the skills and expertise of highly trained mathematicians and operations research professionals. However, vendors, such as supply chain management, are including these algorithms in their products, thereby adapting them to their customers’ industries. In the process, optimization techniques have become more accessible to developers who may or may not have stellar programming or mathematical skills, but who have keen business acumen and a drive to improve the company’s bottom line (Davis, 1994). Related to which optimization technique to use is the interpretation of the output. More specifically, this means going beyond the numbers generated. There may be a need to employ sensitivity analysis for interpretation of results by posing and answering “what if” questions. As such, business analytics are generally necessary in real time to respond to rapidly evolving markets and changing customer dynamics. Analyzing business conditions requires analytic horsepower beyond conventional query and reporting tools (Patch, 1998). How Cornair Should Develop its New System To assist in integrating effective business solutions for decision makers that optimize a company’s operations within Cornair, a recommended approach is to establish a basic framework for smart business systems. Reference can be made to Figure 1.1. Although the architectural components and tools to integrate data, information, knowledge, and intelligence are still evolving, the basic underlying structure for smart business systems include a shift toward even more E- (Davis, 1994). Figure 1.1 commerce. As shown in Figure 1.1 (a), corporate planning oversees the major functional areas of a typical company, that is, marketing, manufacturing, and accounting, within an effective SBS framework. Optimization software (b) is used to process aged and real-time data within some type of computer networking environment that includes a company’s trading partners. The end result (c) is some type of optimization, discovery, new opportunities, detailed analysis, and new ideas. Related to the underlying structure for a typical company in Figure 1.1 is E-commerce. While companies are becoming more connected by the Internet and the World Wide Web, customers, suppliers, and business partners are directly connected by intranets and extranets. Because E-commerce is a very important part of an effective SBS framework, E-commerce centers on applying computer technology to create newer channels of distribution and communication with business partners and suppliers, to establish new contact points for delivering products and services to customers, and to support and interact with those customers so that operations are optimized for all parties (Thierauf, 1975). Regarding the inputs set forth, there must be a realization that the activity of any one function or part of a company will have some effect on the activity of each of the other functions or parts. In order to make effective decisions or actions in a company, decision makers must identify all important interactions and determine their impact on the company as a whole. Initially, functional relationships are expanded deliberately so that all the significantly interacting parts and their related components are contained in a statement of the problem. A total enterprise approach examines the entire area under the manager’s control rather than just one specialized area. This approach provides a basis for initiating inquiries into problems that seem to be affecting performance at all levels (Barrett, 2000). Many problems look relatively easy to solve on the surface but become more like “an iceberg” when their solution is pursued in greater depth. For example, inventory that may not seem complicated at first inspection can be extraordinarily complex. The manufacturing department is looking for long, uninterrupted production runs that will reduce setup costs and cleanup costs. With this goal in mind, solving the problem may not be complex. However, such long production runs may result in large inventories of raw materials and work in process, but produce finished goods in relatively few product lines—a situation that can create bitter conflicts with the marketing department, not to mention the accounting and human resources departments. Hence, inventory as a manufacturing function cannot be isolated from other functions. Marketing, whose aim is to give immediate delivery for a wide variety of products (product lines), prefers a diverse and large inventory as well as a flexible manufacturing department that can fill special orders on short notice. Accounting prefers to minimize inventory investment so that alternative uses can be made of much needed capital. Finally, human resources prefers to reduce labor turnover by smoothing out manufacturing runs and so keeping temporary layoffs at a minimum. Thus, an effective inventory policy affects the operations of many functional areas (Davis, 1994). In view of the preceding difficulties, an inventory problem should be analyzed with painstaking care, examining all of the elements in each department affected. These elements might include the following: the cost of material procurement; manufacturing, setup, and cleanup costs; and stockout costs. When all of the factors affecting inventory are known, an appropriate mathematical or statistical model can be formulated. The solution to this model, having properly related the functions (i.e., manufacturing, marketing, accounting, and human resources) and their component parts, should result in the minimization of the total-cost curve, an effect referred to as optimization of inventory (Patch, 1998). In contrast, suboptimization generally refers to the individual maximization of specific profit objectives for the company’s various functions. In the inventory example, the long production runs may produce the lowest costs for the manufacturing department. But if the merchandise cannot be sold, of what good is the merchandise? The best solution for this inventory problem is one that leads to optimization for the whole company, but not necessarily to optimization for the various functions (departments) of the company. It is necessary to modify the action for each level so as to affect a balance between the various functions and subfunctions. In addition, suboptimization can be applied to the entire company rather than to just its departments, but when this is the case, the suboptimization solution is usually the result of unclear objectives or objectives that conflict with or contradict each other. Suboptimization can also result when an optimum solution for the short term is adopted without regard for the long term or when certain intangible or nonquantifiable factors are not taken into account. Other cases of suboptimization result from failure to examine all of the available alternatives or to consider all of the relevant information (Johnson, 1999). From another perspective, overoptimization is the opposite of suboptimization. This condition results from optimizing to an extreme degree (i.e., when the costs of applying very exacting models are far greater than the expected savings). In the preceding inventory example, an elaborate mathematical model—accurate to several decimal places—could have been constructed and overseen by decision makers. However, such an enlarged approach to optimizing inventory levels would be unwarranted since the additional costs of such accuracy would far outweigh the potential of the model during its expected life (Barrett, 2000). Underlying effective smart business systems is a creative approach to a company like Conair’s operations. Related to creativity is the whole area of decision making that centers on solving a company’s problems. But more importantly, decision making is related to the use of problem finding and its related techniques (i.e., determining present and future problems, along with identifying future opportunities that come from uncovering problems). In turn, the two approaches to the problem-finding process (i.e., the problem-centered approach and the opportunity-centered approach), are given. These two approaches tie in with the traditional problem-solving process for solving well-structured, semistructured, and unstructured problems (Patch, 1998). Post Swot: Cornair Strengths The implementation of new smart business software will make the analysis of the business much more successful, solving the technological issues. Also, keeping employees informed will result in fewer employment strikes. Weaknesses Weaknesses include the necessity of continuing to update technology. If technology is not updated, the entire purpose of smart business approaches will not function. Opportunities Opportunities include using smart business systems to make themselves a better and more competitive technological company. These increases can help put Cornair on top of their field. Threats Threats would primarily include the continued use of technology and ensuring that the company does not fall behind, and the fact that competitors may come out with new and better systems. Conclusion An important consideration for defining smart business sytems revolves around the term “optimization.” Essentially, optimization is the process of finding the best or near best solution from a set of possible solutions. Optimization can be divided into two classes: global and local. Global optimization finds the best or near best solution from the set of all solutions (the global optimum). In contrast, local optimization finds the best or near best solution from a set of solutions that are close to one another (a local optimum). In local optimization, the solution found depends on the starting point for the optimization. Global optimization will always find the same solution regardless of the starting point, but usually will require more computational power. Because it may be nearly impossible to find the global optimum in some applications or there may be no way to check whether a solution is the global optimum, however, even local optima may prove beneficial. In reality, finding the global optimum may not be necessary. Finding a good solution quickly may be more desirable than finding the best one for Cornair. For example, a customer service representative may want to give a delivery time to customers when the order is entered into the system. A good schedule is generated by local optimization although this may not be the best schedule. Thus, the representative can give a delivery time to the customer quickly and know that the actual delivery time will be the same or earlier, depending whether or not global optimization is used later. As noted previously in the text, the type of optimization required for a problem depends on the structure of the problem. If all the decision variables are defined and the objective and constraints are linear functions, linear programming or its variants are usually the best approach. However, real-world applications often require nonlinear functions, set variables, or logical variables and constraints. The ability of approaches to handle such complications is the primary factor to be considered when deciding among the approaches (Johnson, 1999). Because optimization refers to the ability to assess a myriad of possible solutions in order to find the best one or near best one, smart business systems use optimization as their focus to solve a company’s problems and pursue new opportunities. From this broad perspective, companies are looking at the organization holistically. This generally means extending a company’s functions, processes, and technology via E-commerce to its trading partners (i.e., customers and suppliers). A smart business system centers on managing a company’s internal and external information, knowledge, and intelligence in a proactive manner in order to create a competitive advantage that is linked to a company’s achievable objectives and its measurable goals. An effective SBS operating mode centers on optimizing a company’s operations. A smart business system uses any tools, techniques, and procedures that allow decision makers to gather, organize, analyze, distribute, and act on critical business issues, with the goal of helping companies like Cornair make faster, better, and more informed business decisions (Barrett, 2000). In light of the essentials of smart business systems they can be defined as systems for business that can turn selected information, knowledge, and intelligence into optimized solutions for decision makers to solve problems and explore new opportunities. The type of system and software used is situational for solving a company’s functional area problems and opportunities. Also, this can result in a holistic approach to the entire company, thereby resulting in the optimized organization. Smart business systems employ various mathematical, statistical, and collaborative tools that interact with a company’s database infrastructure. Overall, smart business systems provide decision makers with the ability to guide action toward desired actionable goals that result in optimal or near optimal solutions. They provide decision makers with timely information, knowledge, and intelligence for problem solving and, in particular, problem finding (Patch, 1998). Recommendations The four essential elements in developing and implementing smart business system center on optimizing Conair’s operations that are based on trends, patterns, and relationships of the past and the future. In other words, the focus is on optimization of a company’s operations for decision makers in a manner that was not possible before. To accomplish this desired focus, the essential elements found in these types consist of (1) upgrading current information systems to tie in with smart business systems, (2) employing data warehousing and data mining to their fullest, (3) utilizing smart software and optimization techniques to improve and better understand a company’s total operations today and in the future, and (4) making great use of computer networking with an accent on E-commerce. All of these essential elements are set forth below (Barrett, 2000). In terms of the first element, current information systems that are capable of being upgraded to tie in with smart business systems include business intelligence systems, knowledge management systems, on-line analytical processing systems, decision support systems, and executive information systems. Basically, smart business systems enable decision makers to access data, information, and knowledge in ways they never could before to obtain a better understanding in order to optimize a company’s operations. This simple fact is the main thrust behind the growing popularity of smart technology. A mix of these systems (first element) with the other three elements below provide the typical decision maker with insights and relationships necessary to meet global competition today as well as tomorrow (Gartenberg, 2001). The second element centers on building the appropriate data, information, and knowledge infrastructure that is related to data marts, data warehouses, and operational databases. Typically, before the appropriate smart business system can function effectively using the selected software, it is necessary to have a massive amount of aged and/or real-time data, information, and knowledge to solve the present problem(s) or future problem(s) under study. The same can be said for current and future opportunities (Gartenberg, 2001). Regarding the third element of smart business systems is the utilization of appropriate software to optimize a company’s operations. It is sufficient to say that there is a wide range of software packages that meet most decision makers’ needs within an SBS operating mode. The attendance circumstances will dictate which software package is best suited to meet a decision maker’s needs (Barrett, 2000). The fourth element is the use of computer networking that ties in with a company’s intranets, extranets, the Internet, and the World Wide Web, as well as E-commerce, which has the capability of changing the way companies deal with their customers, suppliers, and employees. If applied properly, sophisticated computer networking can help companies optimize their operations. In effect, computer networking provides a road to the future by allowing company information systems to talk to one another in an optimum manner. E-commerce enables businesses to streamline their everyday operations. At the same time, computer networking is allowing the dissemination of important output from smart technology to the appropriate parties whether they are within or outside the organization (Thierauf, 1995). References Barrett, Alexandra. 2000. “Optimize the Enterprise,” Information Week , pp. 149–156. Davis, Stan. 1994. “The Coming of Knowledge-Based Business,” Harvard Business Review, p. 165–170. Gartenberg, Michael. 2001. “Why Ubiquitous Computing Will Supplant the PC,” Computerworld, p. 23. Johnson, Colin. 1999. “Data Fusion New Darling in Smart Technology,” Electronic Engineering Times, pp. 1, 16. Neil, Stephanie. 2001. “It’s Time to Optimize,” Managing Automation, pp. 24–30. Patch, Kimberly. 1998. “Business Systems Makes Some Noise,” InfoWorld, pp. 69, 74. Thierauf, Robert. 1975 Systems Analysis and Design of Real-Time Management Information Systems. Englewood Cliffs, NJ: Prentice-Hall. Thierauf, Robert. 1995 Virtual Reality System for Business. Westport, CT: Quorum Books. Read More