Managing operations in a company require making decisions on a day to day basis. In their bid to achieve organizational goals, managers in a company are faced with various situations that require making decisions. According to Fennis and Stroebe (2014), such decisions may have short- or long-term effects in the company. Decisions in a company revolve around production process, marketing, distribution, and sales process. As mentioned above, decisions have varying effects on the company; both short- and long-term effects. For this reason, decision-makers in the company try to be more accurate as possible to avoid wrong decisions that would cause negative effects in the company. To improve the quality of decisions made, the people who make decisions in a company employ various methods that increase the probability of making the right decision.
One of the methods used to improve decision making in a workplace includes strict observation and following of the decision-making steps. Additionally, decision-makers try to gather a lot of information about the subject they are to decide on. At some advanced levels, computer-aided decision-making techniques are employed to improve the accuracy of the final result. The common techniques used by several bodies in making decision include Advanced Decision Support Systems. Such a technique helps in making predictions with maximum accuracy on the given data sets. This paper illustrates how Advanced Decision Support Techniques are applied in Direct Marketing Campaign to make predictions with maximum accuracy on the given data set.
Direct Marketing Campaign
Direct marketing is a type of marketing that involves direct communication with target customers. Direct marketing is also referred to as direct response marketing. In this type of marketing, the company representatives contact the customers directly through database marketing, promotional letters, and cell phone text messaging (Risselada, Verhoef, & Bijmolt, 2014). In some cases, the company representatives may also employ the use magazine advertisement, catalogue distribution, email, as well as online advertisements. It is worth noting that one of the essential aspects of this type of marketing is the ability to measure consumer response.
Some of the benefits of direct marketing are that the process allows the marketer to promote the product directly to the target customers and measure the results immediately. Additionally, the marketer can reach a specific customer with personalized information and get feedback. After researching a given market, direct marketing enables the marketer to convince the market using specific luring methods of one on one basis.
Direct marketing enables marketers to operate even on tight budgets. If one uses online platforms or phone messages as a method of reaching customers, the segmentation and targeting concept employed help reduce marketing costs. By addressing the specific target audience, the marketer can set realistic goals and expectations. The technique also helps the marketing team address specific customer needs to be given that each client is given time; decisions are not general but specific based on each customer.
Direct marketing helps to increase sales from existing and former clients. Through this marketing, there has been active relationship with customers; informing them of any developments and new products available. By keeping in touch with the former and current customers, the company increases sales by reactivating and selling to dormant customers.
Direct marketing improves customer loyalty. As illustrated above, this form of marketing gives the marketer an opportunity to interact with one client at a time. Through this, the client has the time to explain his or her needs through feedback. Upon addressing specific issues raised by the customer, the customer feels satisfied and well attended to. Customer satisfaction improves customer loyalty hence better brand image in the market.
Direct marketing enables marketing teams to create new business opportunities. The method allows one to get first-hand information in the market trends and emerging customer needs. Such new needs open new markets as the company could end up producing the new needs in the market. Finally, the direct market campaign enables instant response from the customer. Based on the feedback the marketer gets, the company can analyze the response and make necessary adjustments. Immediate feedback also allows the company to get a timely analysis of how their products perform in the market. In the same way, direct marketing campaign helps the company evaluate the performance of the marketing team and methods employed.
Based on the above illustrations, direct marketing campaign involves communicating with the customers directly. This process involves gathering data from the customers based on their response and putting them in different categories. The marketing team then analyzes the gathered data and makes decisions based on the findings. From the fact that such decisions have far-reaching consequences on the future of the company; the decisions need to be as accurate as possible. For this reason, companies such as the banks try to make decisions as accurate as possible. In this regard, the paper analyses the application of Advance Decision Support techniques to solve the marketing task in the bank (Moro, Laureano, & Cortez, 2011). Using data on phone calls made between the bank's marketing team and various customers, missed and received calls, the bank needs to make accurate marketing decisions.
Advance Decision Support
Advance decision support systems are computer systems that process information and help business entities like companies and organizations in decision making activities. As illustrated by Bonczek, Holsapple, and Whinston (2014), some of the systems are computer-based programs that collaborate extensively with users to solve structured and semi-structured problems. These systems are used at operations, management, and planning levels of a given company to make decisions based on rapidly changing data. The systems are also necessary for areas where the data is not well specified in advance. In should be noted that decision support systems can be fully computer-based, human-powered or apply both.
Some of the basic features of advanced decision support systems include their ability to be applied at various management levels, an individual or group. The systems are applicable as long as there is real data, structured or semi-structured, with a basing of human judgment. The systems support all the stages of the decision-making process; identification, designing, selecting, and implementing the decision. Some of the known techniques used in advanced decision support systems include Artificial Neural Networks and Adaptive Boosting of Decision Trees.
Artificial Neural Networks
These are computing systems developed based on biological neural networks. It should be noted that Artificial Neural Networks are not algorithms on their own. They are frameworks of algorithms working together to learn and process complex data. Such networks are not programmed with any task-specific rules.
Adaptive Boosting of Decision Trees
These are meta-algorithms that work hand in hand other algorithms that support learning to improve performance. When used, the output from other algorithms is combined for the final result of the process. This type of system reacts to noisy data and those that fall out of the normal. The system is referred to as adaptive in that the previous misclassified instances are replaced by adjusted subsequent weak learners.
Parameters in Advanced Decision Support (ADS) are always the basic source data that fluctuate in the process. In this case, the parameters that are adjustable in the decision-making process include the number of missed and received calls. The data obtained from the parameters can always be adjusted to analyze how their variation affects the whole decision-making process. Based on how this system works and the parameters used in this situation, it is recommended that the bank marketing use the calls data in making decisions when aiming to improve the accuracy of the process. These parameters can model waste-specific features in the banks marketing process. These features are important for proper assessment and improvement of accuracy in the process of making decision.
Moreover, these variables are available or under development at the time when the decisions are made. The parameters do not allow adjustments on the basic properties or add any more waste components. Finally, the parameters include an advanced decision processor can create. As mentioned above, decisions have varying effects on the company; both short- and long-term effects. For this reason, decision-makers in the company try to be more accurate as possible to avoid wrong decisions that would cause negative effects in the company. To improve the quality of decisions made, the people who make decisions in a company employ various methods that increase the probability of making the right decision.
As illustrated above, the accuracy in making decisions in direct marketing campaign helps in the proper guidance of future operations. This paper indicates that Direct marketing is a type of marketing that involves direct communication with target customers. Data obtained by the bank from direct phone communication with the customers can be used to analyze and improve the accuracy of decisions made in the bank.
Application of techniques like Artificial Neural Networks is of great importance in the process. It should be noted that Artificial Neural Networks are not algorithms on their own. They are frameworks of algorithms working together to learn and process complex data. Additionally, making use of the meta-algorithms that work in together with other algorithms that support learning, helps enhance how performance under Adaptive Boosting of Decision Trees.
According to Elsalamony (2014), the current banking system involves various operations that accumulatively help in the process of making decision in the bank. Adaptive Boosting of Decision Trees technique enables the bank marketing team to bring together all the participating factors together. Given that the advanced decision support systems are applicable as long as there is real data, which is structured or semi-structured, with a basing of human judgment. The presence of data taken from the phone calls helps improve the accuracy of the decisions made in the bank's direct marketing.
For this reason, companies such as the banks try to make decisions as accurate as possible. In this regard, the paper analyses the application of Advance Decision Support techniques to solve the marketing task in the bank. Using data on phone calls made between the bank's marketing team and various customers, missed and received calls, the bank needs to make accurate marketing decisions.
Bonczek, R.H., Holsapple, C.W. and Whinston, A.B., 2014. Foundations of decision support systems. Academic Press.
Elsalamony, H.A., 2014. Bank direct marketing analysis of data mining techniques. International Journal of Computer Applications, 85(7), pp.12-22.
Fennis, B.M. and Stroebe, W., 2014. Softening the blow: Company self-disclosure of negative information lessens damaging effects on consumer judgment and decision making. Journal of business ethics, 120(1), pp.109-120.
Moro, S., Laureano, R. and Cortez, P., 2011. Using data mining for bank direct marketing: An application of the crisp-dm methodology. In Proceedings of European Simulation and Modelling Conference-ESM'2011 (pp. 117-121). EUROSIS-...
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