Globalization and Information Research
Part 1: Globalization and Information Research
A company’s management should consider several factors when establishing an expansion strategy. It is important to consider aspects such as the presence of local competitors and the strategies they employ, the level of demand for products and services being introduced, and the economic, demographic, regulatory, and political environment. An analysis of Netflix’s case highlights the various outcomes of venturing into new markets.
The Most Important Strategic Moves That Propelled Netflix’s International Expansion Success
According to Brennan’s (2018) article on Netflix, the two major factors that contributed to the company’s success were the expansion strategy adopted and methods of appealing to customers. Netflix adopted a unique approach to entering the markets. First, the company entered the markets in countries with operational strategies similar to the local market operation in the US. Interestingly, these markets provided experiences useful in entering dissimilar markets elsewhere. To appeal to customers, the company aimed to satisfy the needs of the local customers. Besides, the company collaborated with the local stakeholders and cultures in content creation. The two strategic moves enabled the company to successfully venture into over 50 countries by 2015.
Importance of the Big Data Investment and the Type of Information Netflix Derived From the Data Collected
The company invested in big data analytics to facilitate expansion internationally and overseas. The company executed its expansion strategies in phases, and the second phase involved extensive and detailed expansion. This necessitated obtaining reliable data regarding customer choices and needs to determine the most appropriate entry strategies. According to Spotfire (2014), big data analytics facilitates predicting and understanding customer behavior and needs. Big data analytics also enabled the company to obtain information regarding the channels customers use to obtain information, income and lifestyle factors, and cultural attributes, especially to determine the type of content compatible with different cultures. This enabled the company to tailor market-entry strategies to different markets.
Defining Exponential Globalization
According to Brennan (2018), exponential globalization is a market entry and expansion approach that involves employing a well-planned and strategized expansion cycle, which is implemented to expand into more countries and reach a larger customer base. The market entry is also actualized at increasing speed. This strategy has proved feasible, and other companies can adopt it in entering new markets, as Brennan (2018) suggests.
US Companies that Have Failed In Attempts of Expansion Externally
E-Bay Inc. is a multinational retail company headquartered in San Jose, California, in the US. Its entry into the Chinese market is one example of a US company case that has failed in attempts to expand into another country. The article by O’Brien (2015) points out that the main reason why the company failed in China was stiff competition from local companies, especially TaoBao. Immediately after eBay entered the Chinese market, there was fierce competition between eBay and Taobao for the available market. Jack Ma’s TaoBao won, forcing eBay out of the Chinese market in 2006. I agree with the article’s assessment of the company’s failure in the Chinese market since it provides statistics about internet users and mobile phone users and how each company capitalized on these aspects to gain a competitive edge over the other.
Market Failure and Reasons Certain Companies’ Expansion Plans Have Failed In The Past
The major factors contributing to several companies’ failure to enter new markets are fierce competition from other companies, poor market analysis before the actual entry, regulation issues, poor timing, and inadequate expansion capital. Any business intending to expand globally should keenly consider these factors.
Part 2: Hypothesis Testing
A hypothesis test to determine whether the average TiQ is lower than the industry standard of 2.5 minutes (150 seconds). Using a significance level of α=0.05
H0 = The average TiQ is equal to the industry standard of 2.5 minutes (150 seconds)
Ha = The average TiQ is lower than the industry standard of 2.5 minutes (150 seconds)
H0 : µ = 2.5minutes vs. H1 : µ < 2.5minutes
The calculated z-statistic score, the p-value (-0.6168), is less than the critical value obtained from the Z-table (1.645). Therefore, the null hypothesis that the average TiQ is lower than the industry standard of 2.5 minutes should be rejected.
A Hypothesis test to determine whether the company should allocate more resources to improve average TiQ.
According to the hypotheses tests, the company should invest more resources to ensure that the Time in Queue is less than the current industry average by installing more advanced technological systems.
A hypothesis test to determine whether the average ST with service protocol PE is lower than the PT protocol. Using a significance level of α=0.05.
H0 = The average ST with service protocol PE is equal to PT protocol
- Ha = The average ST with service protocol PE is less than with the PT protocol
H0 : PE= PT vs. H1 : PE < PT
Where; X1= 149.28, n1=853, S12=34556.46
X2 = 212.163, n2=821, S22= 36320.9
Since n1 and n2 >30, we use a Z-test
To obtain Sp,
= S p = √ = = 35421.795
= √35421.795= 188.207
= = = -6.36
Therefore, the p-value obtained is -6.36, which is less than the critical value of 1.64. Therefore, the null hypothesis should be rejected and conclude that the average ST with service protocol PE is equal to PT protocol.
Assessment for determining whether the new protocol served its purpose
The major reason the company introduced the new system was to reduce the average service time for customer service. However, the hypotheses test results indicate no difference in service time between the new protocol (PE) and the traditional protocol (PT). One can deduce that the new protocol did not serve the intended purpose. Therefore, the company should establish other ways to improve its services other than introducing new protocols.
Brennan, L. (2018). “How Netflix Expanded to 190 Countries in 7 Years.” https://hbr.org/2018/10/how-netflix-expanded-to-190-countries-in-7-years
O’Brien, B. (2015). 4 lessons learned from famous market entry failures. Retrieved from https://www.tradeready.ca/2015/trade-takeaways/4-lessons-learned-famous-market-entry-failures/
Spotfire. (2014). “Big Data Analytics: The Gateway to Success in New Markets.” https://www.tibco.com/blog/2014/03/04/succeed-at-entering-new-markets-via-big-data-analytics/
We’ll write everything from scratch
The assignment has two parts: one focused on information research and analysis, and the other is on applied analytics.
Part 1: Globalization and Information Research
Context: Companies that perform well in their country of origin usually consider expanding operations in new international markets. Deciding where, how, and when to expand is not an easy task, though.
Many issues need to be considered before crafting an expansion strategy and investing significant resources to this end, including:
the level of demand to be expected for the company’s products/services
presence of local competitors
the regulatory, economic, demographic, and political environments
Carefully researching and analyzing these and other factors can help mitigate the inherent risk associated with an overseas expansion strategy, thus increasing the likelihood of success.
As a data analyst in your company’s business development department, you’ve been tasked with the responsibility of recommending countries for international expansion. You’ll write a report to the company’s executive team with your research, analysis, and recommendations.
Write a 525-word summary covering the following items:
According to the article listed above, what were the most important strategic moves that propelled Netflix’s successful international expansion?
The article mentions investments in big data and analytics as one of the elements accompanying the second phase of overseas expansion. Why was this investment important? What type of information did Netflix derive from the data collected?
According to the article, what is exponential globalization?
Not all international expansion strategies are a resounding success, however. Research an article or video that discusses an instance in which an American company’s expansion efforts in another country failed. According to the article/video you selected, what were the main reasons for this failure? Do you agree with this assessment?
Explain some of the reasons why certain companies’ expansion plans have failed in the past.
Part 2: Hypothesis testing
Context: Your organization is evaluating the quality of its call center operations. One of the most important metrics in a call center is Time in Queue (TiQ), which is the time a customer has to wait before he/she is serviced by a Customer Service Representative (CSR). If a customer has to wait for too long, he/she is more likely to get discouraged and hang up. Furthermore, customers who have to wait too long in the queue typically report a negative overall experience with the call. You’ve conducted an exhaustive literature review and found that the average TiQ in your industry is 2.5 minutes (150 seconds).
Another important metric is Service Time (ST), also known as Handle Time, which is the time a CSR spends servicing the customer. CSR’s with more experience and deeper knowledge tend to resolve customer calls faster. Companies can improve average ST by providing more training to their CSR’s or even by channeling calls according to area of expertise. Last month your company had an average ST of approximately 3.5 minutes (210 seconds). In an effort to improve this metric, the company has implemented a new protocol that channels calls to CSR’s based on area of expertise. The new protocol (PE) is being tested side-by-side with the traditional (PT) protocol.
Access the Call Center Waiting Time file. Each row in the database corresponds to a different call. The column variables are as follows:
ProtocolType: indicates protocol type, either PT or PE
QueueTime: Time in Queue, in seconds
ServiceTime: Service Time, in seconds
Perform a test of hypothesis to determine whether the average TiQ is lower than the industry standard of 2.5 minutes (150 seconds). Use a significance level of α=0.05.
Evaluate if the company should allocate more resources to improve its average TiQ.
Perform a test of hypothesis to determine whether the average ST with service protocol PE is lower than with the PT protocol. Use a significance level of α=0.05.
Assess if the new protocol served its purpose. (Hint: this should be a test of means for 2 independent groups.)
Submit your calculations and a 175-word summary of your conclusions.