Strategic Business Intelligence

Ans1. Business problems refer to the challenges that may be long term or short term to be faced by the organization. These problems at times lead to divergence in the strategies that are supposed to be executed by the company. These problems also threaten the survival of the firm.

For Thrill seekers in their strategic one day plan of Kayaking and Triking tours proposal, the main problem is of competition. In the market various companies are already offering the same package. The competitor's company is running this business for a longer duration of time. They have an existing customer base. Also, the popularity of their packages will be higher. Thrill-seekers are at the infant stage. They have to create a market base for themselves. Since, other companies are running this business for long, it will be a tough task to enter and capture the market.

Key opportunities that Thrill seekers have:

  • The company is into the business of travel for long and has a customer base of its own.
  • The company has a hostel for travelers. They can promote their package to them. Since people will be using their services already, there are better chances that their package will be sold.
  • Thrill-seekers have an active Facebook page where people like their packages. They can promote their day package there and see what are the chances that people will opt for that.
  • They can also get in touch with people, who have booked their package with them and do cross-selling accordingly.
  • There might be certain changes that customers are looking for in already prevailing packages. They can do a survey and customize their package accordingly.

Thus, Thrill seekers might face tough competition as various companies already are running this package. But the key opportunity Thrill seekers have is that, they already provide packages that are for a longer duration. They can cross-sell the package to the already existing customers and the people who will be saying in their hostel.

Ans 2. Various types of data are available and there is data that is to be obtained for understanding the gaps and analyze it accordingly. The following data sources can be used by the company:

  • Structured data: Structured data refers to the data that is properly aligned with a database of names and phone numbers included in it (Dai, Dai & Song, 2016). This type of data for the company can be collected through the company's database. It will consist of the customers that are planning to visit. The company will have all the information about them. The company should get in touch and sell their package before they arrive. This gives an edge to the company. Also, the data for the people who have booked the hostel will be in a structured form and it can be used.

The problem with this respect to structured data is that, most of the data will be of the people who have already visited, which will not be of any use. Hostel might have impromptu bookings, this will reduce the amount of data for the company.

  • Unstructured data: Unstructured data set refers to the data that has no specified defined manner (Balducci & Marinova, 2018). The responses of the Facebook that the company will receive after promoting its package will be unstructured. Random people will like it and some will enquire about the package. It might be in the form of emails or direct messages. The company should collect this data too and use it to understand the interest of people in the package they are offering.

The problem with this data set is that, there will be no guarantee and no specified number or person to get in touch with. People might randomly choose to check the package, even when they are not traveling. Thus, this data will not bring any concrete results, till the person liking or asking about the package turns into a real customer.

Semi-structured data: Semi-structured data refers to a model that does not have a fixed model but still possesses some properties of organization (Tsirogiannis et. al, 2017). It is an easier data set to analyze. The company can collect this data and understand through the reports of competitors firm about the customer base and the package that is being sold at the highest. Also, the company can collect data through customer requirement form on its web page. This will help them understand the kind of package customers are looking for.

The main problem concerning this type of data is that interpretation of data becomes hard as well as storing this type of data has a higher cost than others.

Ans 3. The "P" Step of the IMPACT model states that the data should be articulated in a manner that can be interpreted concerning the question of the business about rolling out the strategic plan of Triking and Kayaking and the competition it may face in the market (Appelbaum, 2017). The questions lie whether the proposal will bring in profit or it will fail in the market.

The data analytics techniques that can be used are as follows:

  • Association rule learning: It will help in answering the questions whether the customers who are staying in a hostel or purchasing a tour package would like to purchase Triking and Kayaking. This data analytics method provides correlation and will help in understanding the correlation between the above-mentioned factors.
  • Machine learning: This is another data analytics technique that determines the probability and also helps in learning the user preferences and make recommendations appropriately. This will help in analyzing the chances of a customer purchasing the day tours in the category of customers for longer duration tours. It will also help in knowing whether the customer in the hostel will prefer their package or of others.
  • Regression analysis: It helps in determining the changes in one variable concerning other (Saura, Herraez & Reyes-Menendenz, 2019). This will help in analyzing the satisfaction of customers and their loyalty to turning and promoting the company.

References for Strategic Business Intelligence

Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2017). Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems, 25, 29-44.

Balducci, B., & Marinova, D. (2018). Unstructured data in marketing. Journal of the Academy of Marketing Science, 46(4), 557-590.

Dai, H., Dai, B., & Song, L. (2016, June). Discriminative embeddings of latent variable models for structured data. In International conference on machine learning (pp. 2702-2711).

Saura, J. R., Herráez, B. R., & Reyes-Menendez, A. (2019). Comparing a traditional approach for financial Brand Communication Analysis with a Big Data Analytics technique. IEEE Access, 7, 37100-37108.

Tsirogiannis, D., Binkert, N. A., Harizopoulos, S., Shah, M. A., Sowell, B. A., Kaplan, B. D., & Meyer, K. R. (2017). U.S. Patent Application No. 15/478,177

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