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Big Data

Response to James

Hello James,

Thank you for sharing your post. I can only imagine the volumes of data that the former workplace, MTN West Africa, gathered after checking and finding out that MTN is the biggest mobile network in Africa. Similar to most, if not all, large corporations, customer data is used to the advantage of the organization and to also extend benefits to the customers (Grable & Lyons, 2018). You mentioned how MTN did this in your post, where the company used the data to create products and services aimed at enticing customers to remain loyal to the brand. I would like to add that with so much data, an organization may find it challenging to utilize the same to the fullest (Ohlhorst, 2012; Loshin, 2013). For example, an organization could be tempted to focus on current information provided by analytics, yet information such as sales from the last 5-10 years can be useful in discerning customer behavior. If there was an economic slump 5-10 years ago and the organization found itself in a similar situation, past data can help the organization predict what the sales would be based on the patterns observed in the past. This prediction can help the organization to brace itself better and make the necessary changes to accommodate the inevitable.


Grable, J. E., & Lyons, A. C. (2018). An Introduction to Big Data. Journal Of Financial Service Professionals72(5).

Loshin, D. (2013). Big Data Analytics: From Strategic Planning To Enterprise Integration With Tools, Techniques, NoSQL, and Graph. Elsevier.

Ohlhorst, F. J. (2012). Big Data Analytics: Turning Big Data Into Big Money (Vol. 65). John Wiley & Sons.


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Big Data

Hello, I need help responding to a classmate’s post for session 5 topic Using Big Data. Thank you

Big Data

Big Data

James’ Post

Using Big Data

After reading through the “Big Data” article by Grable and Lyons (2018), It was clear that excessively large amount of data is produced and stored by businesses and government daily. Advancement in modern technology has contributed immensely to the production of data every minute. Businesses and governments are maximizing the value of this big data. The two points that I will like to discuss were organizations maximize the use of big data are consumer/customer orientation and sales and operations planning.

According to Racela (2014), customer orientation is a “business philosophy that leads to superior performance and firm profitability”. Customer orientation brings about creativity, innovation, and performance in businesses. Organizations use the resource-advantage of big data collection with the help of user behavior analytic to manage the big data (Grable and Lyons, 2018). From experience, the giant multinational telecommunication company (MTN – West Africa) I worked with before relocating to the U.S. uses this concept of big data to predict their customers and create innovation. Based on the analysis of customers’ behaviors the organization can roll out new products and services now and then. Examples of such products and services are mobile banking, CUG lines, Mobile bundles, credit transfer, internet services, etc.

This process leads me to talk about sales and operation planning. According to Thome, et al. (2012), sales and operation planning is a tool that unites different business plans into one integrated set of plans. Its goal is to balance supply and demands, and to link together the strategic plans and the operational plan of the organization (Thome, et al., 2012). Some of these strategic and operational plans used by the organization that I worked with involves making out-band calls to customers and giving them orientation on new products and services that best suit their needs. The company also used incentives, promotions, free offers, etc. to entice their customers, and get them to start using the products and services. The customers liked it and continued to patronize the company.


Grable, J., & Lyons, A. C. (2018). An introduction to big data. Retrieved from

Racela, C. O. (2014). Customer orientation, innovation competencies, and firm performance: A proposed conceptual model. Procedia social and behavioral sciences 148(2014) 16-23. Retrieved from

Thome, T. M. A., Scavarda, F. L., Fernandez, S. N. & Scavarda, J. A. (2012). Sales and operations planning: A research synthesis. Int. Journal of production economics. Retrieved from

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