Implementing A Customer Loyalty Program With Decision Support System (DSS)

Overview of the Proposed Plan

Question:

Discuss About The Extending Understanding Of Critical Success?

Al Nahdee Pharmacies is a business organization that deals with the sale of pharmaceutical products like medicines, disinfectants and others. In order to maintain and further increase the customer base, the company wants to implement a new business intelligence system that will be able to manage the entire customer loyalty scheme system as well as take the right decisions at various points of the operations.

In this report, the proposed plan for the company has been analyzed and suitable recommendations have been provided regarding the use of DSS in the proposed customer loyalty program.

This project is based on the implementation of a customer loyalty program and its integration with the existing transaction system of the company. As a part of their new business strategy, the company wants to roll out some customer loyalty programs that will enable them to gain more customers as well as maintain the existing customer base by increasing their loyalty towards the organization (Kimball et al, 2015). The features of the proposed system include the following.

Customer Database – The first feature of the system will be to have customer database where all the information of a customer including his dealings with the company will be stored (Wixom et al., 2014). This will help the company to determine whether the customer is loyal to the organization or not.

Loyalty Program – Next, the system should have a list of loyalty programs for the customers that will be based on the subscription of the customers (Laursen & Thorlund, 2016). There will be a number of subscription schemes for the customers depending on which, the specific loyalty pack will be unlocked and the customer will be enrolled in it.

Link with Transaction – Finally, there should be link between the customer loyalty program and the transaction process so that whenever the customer purchases anything, his program will be automatically activated and the billing will be done for the discounted prices only.

As per the proposed plan, the entire system will be automated i.e. none of the loyalty enrolment operations or discount in transactions are to be done manually. Hence, the system needs sufficient intelligence to perform the necessary actions.

The decision making system for the proposed set up needs to perform the following actions.

Enrolment – Whenever a customer deals with the company for the purchase of certain products, the system will automatically search for existing database for the same customer. If database exists, it will redirect the process to the customer loyalty program database. If the database does not exist, it will request the customer to enter his details and enroll for the loyalty program if he is interested (Fan, Lau & Zhao, 2015). The system will also show the customers the various loyalty schemes and the subscriptions that the customer has to buy. The customer can enroll himself by buying a subscription pack on spot.

Transaction – Another action to be performed by the system is to sort the bill of the customers as per their loyalty status, as the customer information is entered during the billing, the system will automatically search for his loyalty status in the system (Larso & Chang, 2016). Based on his subscription and loyalty program, the system will automatically apply the discounts on the bill and print the discounted amount only.

Features of the Proposed System

Decision Support System (DSS) will provide significant business opportunities for the company as the right decisions will be taken during the business transactions regarding the enrollment of the customer for loyalty program and providing suitable discounts and rewards during the billing. Not only it will increase the loyalty of customers but will further enhance the business of the company as the customers will bring in referrals thus increasing the entire customer base. Furthermore, with increasing loyalty level, the customers will be upgraded to higher loyalty rewards thus increasing the business and profit of the company.

All the ossible alternatives that will affect the decision making system will be as follows.

1. During Enrolment – The first decision making stage is during enrolment of a customer in the loyalty program. Whenever the customer starts a deal with the company, the system will take his initial information and search for his profile in the database (Chang, 2014). Here, the system needs to make decision on whether the customer requires a profile or he already has a profile in the database.
2. During Payment – During the payment, the customer information is entered into the system and the system will search for his loyalty status in the database (Yeoh & Popovi?, 2016). The system will have to decide whether the customer has sufficient loyalty status / subscription to earn discounts or he is a new customer without any subscription and hence no discounts.

Again, there are three possible choices for the company to take regarding the type of loyalty program. These programs are listed in the following table along with their advantages and disadvantages.

The business need for the company is to maintain and enhance the existing customer base by keeping hold of the current customers and on the other hand, bring in more customers. The company wants to attract more customers by the new customer loyalty programs. As per the design phase, there are three possible choices for the company.

The most suitable one for this particular organization will be refer friends program where the customers will be requested to refer their families and friends to deal with the company and they will get special rewards and loyalty points in return. This program will definitely help the company to keep hold of their existing customers and they will bring even more customers to the company thus creating a referral chain. This referral chain will accelerate the generation of profit for the company significantly.

There are several tools available for developing such decision making systems. Some of the tools include database management system, statistical data analysis package, data analytics, SAP business intelligence and others. However, judging by the requirements of the particular problem and the new proposed system, the best possible choice for the system will be SAP business intelligence. SAP software is able to develop an internal database where all the information of the customers, subscription policies, customer loyalty programs and others will be stored, processed and management (Moro, Cortez & Rita, 2015). Furthermore, SAP business intelligence will support the decision making process of the system so that the system will be able to take the right decisions while handling and managing the customer data. SAP business intelligence also provides attractive and useful user interface that the enables the users to find any business solutions on the dashboard easily without any hassle.

The proposed project schedule along with the task allocation to the project stakeholders are shown in the following table.

The work breakdown structure for the project is shown in the following diagram.

Figure 1: Work Breakdown Structure for the Project

(Source: Created by Author)

References

Chang, V. (2014). The business intelligence as a service in the cloud. Future Generation Computer Systems, 37, 512-534.

Fan, S., Lau, R. Y., & Zhao, J. L. (2015). Demystifying big data analytics for business intelligence through the lens of marketing mix. Big Data Research, 2(1), 28-32.

George, J., Kumar, V., & Kumar, S. (2015). Data Warehouse Design Considerations for a Healthcare Business Intelligence System. In World Congress on Engineering.

Kimball, R., Ross, M., Mundy, J., & Thornthwaite, W. (2015). The kimball group reader: Relentlessly practical tools for data warehousing and business intelligence remastered collection. John Wiley & Sons.

Larson, D., & Chang, V. (2016). A review and future direction of agile, business intelligence, analytics and data science. International Journal of Information Management, 36(5), 700-710.

Laudon, K. C., & Laudon, J. P. (2015). Management Information Systems: Managing the Digital Firm Plus MyMISLab with Pearson eText–Access Card Package. Prentice Hall Press.

Laursen, G. H., & Thorlund, J. (2016). Business analytics for managers: Taking business intelligence beyond reporting. John Wiley & Sons.

Moro, S., Cortez, P., & Rita, P. (2015). Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation. Expert Systems with Applications, 42(3), 1314-1324.

Richards, G., Yeoh, W., Chong, A. Y. L., & Popovi?, A. (2017). Business intelligence effectiveness and corporate performance management: An empirical analysis. Journal of Computer Information Systems, 1-9.

Wixom, B., Ariyachandra, T., Douglas, D. E., Goul, M., Gupta, B., Iyer, L. S., … & Turetken, O. (2014). The current state of business intelligence in academia: The arrival of big data. CAIS, 34, 1.

Wu, D. D., Chen, S. H., & Olson, D. L. (2014). Business intelligence in risk management: Some recent progresses. Information Sciences, 256, 1-7.

Yeoh, W., & Popovi?, A. (2016). Extending the understanding of critical success factors for implementing business intelligence systems. Journal of the Association for Information Science and Technology, 67(1), 134-147.

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