Reference no: EM131937674

Article : How Lufthansa Capitalized on Big Data for Business Model Renovation By Hong-Mei Chen and Roland Schütz.

Article Review

Everywhere we go, everything we say, everything we buy leaves a digital trace that is recorded and stored. In this big data era, it is important for enterprises to derive values from big data to create competitive advantage and pull away from their competitors.

McAfee & Brynjolfsson (2012) found that data-driven companies are, on average, 5% more productive and 6% more profitable than their competitors. However, merely having more or better data does not guarantee the success of big data deployment. Chen, Schutz, Kazman, & Matthes (2017) investigated how Lufthansa has managed big data pipeline and discovered big data value, and found Business-IT alignment as the success factor of big data adoption at Lufthansa.

Becoming a data-driven organization is a complex and significant challenge for managers. In addition, while firms often tend to consider and tackle big data and analytics as an IT department issue, it extends far beyond this. Organizations need to "strategically align" all resources to tackle this issue systematically (Vidgen, Shaw, & Grant, 2017). This week's article by Chen et al. (2017) will help you draw practical insights into how to leverage big data to create business value.

Learning Objectives of Article review:

Discuss how big data and analytics can help organizations create business value.

Formatting instructions: How to format your review essay

1. Provide at least 1" margins, at least 12-point font, and at least 1.15-line spacing.

2. Number all the pages.

3. Length: The maximum length of the essay is 4 pages, excluding references.

4. Use headings and sub-headings.

5. Have three paragraphs in Section 3.

6. Place references at the end of your review essay.

Structure of your review essay

Your review essay should have the following four sections. Use headings for all sections. Below I provide the body of text you should write in each section.

1. Introduction

A good introduction encourages readers to read your essay with great interest and prepares them to understand it better. You want to establish common ground, a shared understanding between reader and you about the topic you will write in the following sections. Then, you will concisely introduce what the focused topic is, and how your essay is organized to inform readers. This section is usually a single paragraph. Do NOT place the summary in the introduction and conclusion sections. If you do so, the level of achievement will be lowered.

2. Summary

Assume that you are giving someone who has never read the article enough detail so that they could have a summary of the article. Your summary should NOT be a mere copy of paragraph or the bulk of quotes from the article. You should provide a concise, comprehensive summary in your own words. In this section, please show me that you really read and comprehended the article at a level where you can cogently cover the most important parts succinctly.

3. Practical implications

In this section, you should provide practical implications about how you would deploy big data and analytics as a manager. Big data deployment is not merely a technical issue but demands alignment among business, organizational, and technological dimensions of the strategy triangle (Vidgen et al., 2017). In this section, you should discuss how you would achieve alignment among these three dimensions to create business value from big data deployment. This section should have three paragraphs as follows.

In the first paragraph, from a business perspective, you should

1) identify a particular use case that employs big data and analytics to create business value in the context of your organization, and

2) discuss how that use case can create business value in the context of your organization.

You can find the example of use cases in this week's article by (Chen et al., 2017).

In the second paragraph, you should state how you would develop the organizational dimension which supports the use case you proposed. For instance, you can think about how you would cultivate data-driven culture, and facilitate such a change. You can consider introducing a new incentive system to reward employees who demonstrate data analytics capabilities. Other factors you can consider include how to structure data analytics team to promote cross-functional cooperation and organizational agility.

In the third paragraph, you should state how you would lay out technological infrastructure components. Our textbook (Pearlson, Saunders, & Galletta, 2016) lists four categories of software tools typically used for business analytics (see p.266).

You should pick one of those four categories, name specific software products, and discuss how the software products support your use case to create business value. The tools can be an enterprise product or open source product. In doing so, you would need to consider data requirements and the value you want to create from data.

4. Conclusion

You wrap up your review. State overall contributions of the article, theoretically and practically. You should also write what more you would like to know. This section is usually a single paragraph.