Peer Responses – Reply to at least two
of your classmates, with the following:
Provide your peers feedback on their
post and compare your findings to theirs.
Research and summarize an article
related to decision analysis tools and the current technology.
Discuss how will AI (artificial
intelligence) will assist in decision analysis
Address the competitive advantages
or disadvantages the use of technology could have on the
organization.
A different article for each peer
response is required. The article must be within the last 2 years to be
considered current.
1.5 page response to each
Peer post 1:
Working in phone sales has led to the launch of new
electronic services being offered by the company which involved the decision
analysis process to deliver the product to customers. Verizon recently began
spreading their own alternative option for qualifying addresses for home
internet service. This method runs off data connectivity and speeds rather than
satellite, so comparing speeds and other metrics directly with the competition
is difficult. In order to educate people about the new service and determine
the best approach to increasing consumer interest, data was collected and
analyzed within the company.
Background
Verizon launched its new service and began gradually
gauging potential interest throughout 2023, this presented a learning curve as
the service was not and still is not as widely available and entering a highly
competitive market space can become tricky. In order to get the best possible
reception from consumers to this new service offered, data analysis was
utilized to determine the ideal market entry strategy and how to best
incentivize consumers to make the switch to Verizon Home Internet services.
Currently Verizon has taken collected data and analyzed it
for growth trends and forecasts. Continuously collecting data in order to
better understand the target market and deliver a service that can be of use to
consumers, who may not even be active Verizon customers. Tracking and being
aware of trends is a major benefit in utilizing data analysis for Verizon. Camm
et al. (2024) define trends as “the result of long-term factors such as
population increases or decreases, shifting demographic characteristics of the
population, improving technology, changes in the competitive landscape, and/or
changes in consumer preferences” (Camm et al., 2024). Population fluctuations,
changes within the competitive landscape, and improving technology are all
factors that Verizon needs to consider and monitor while seeking expansion into
the internet space.
Verizon is tracking population density and growth in areas
they wish to provide their services to and where they see opportunities for
product/service growth. The primary strategy taken as a result has been to
offer services in areas where the competition is not actively servicing or
where connectivity seems to be a major concern. This provides a needed service
to new areas while also making the product more widely available. Although
competitors struggle in some areas utilizing satellite or fiber internet options,
Verizon utilizes their cell service and data to run their internet routers
making for expanded opportunities over the competition. Identifying these areas
is done through research and a data analysis of comparing availability with the
competition based on geographic and demographic need and the utilization of
coverage map data.
Similarities
Another service based industry that can benefit from data
analysis is the healthcare industry. Similar to Verizon identifying areas with
a need, healthcare providers need to make sure large areas of the population
are able to get coverage and the care they need. Analyzing population,
demographics, average area incomes, and comparing coverage or availability from
competitors helps the healthcare industry identify a need for a service and
determine the best course of action at the time. An article by Muenning (2017)
points out that, “Decision analysis is highly dependent on the accuracy and
completeness of model inputs, as well as the assumptions that the analysts
make. This is especially true when making recommendations or going through
options within the healthcare industry” (Muenning, 2017).
Benefits
One benefit that Verizon has through their data analysis
that healthcare providers do not necessarily see is that the costs are more
consistent and predictable between available options, allowing that to be a
data metric that provides insight into where a need may be that could
capitalize on affordability. Whereas, within the healthcare companies it is
important to conduct thorough research of individual profiles to determine the
ideal course of action to minimize any losses and prevent sticky situations. Muenning
(2017) also points out that oftentimes a cost-effectiveness analysis is
conducted in tandem with more traditional data analysis approaches to yield
accurate results (Muenning, 2017). While for Verizon identifying population
levels and comparing coverage availability of what is offered by the
competition in that area leads to coverage opening in new areas and guides
recommendations being made to customers.
Another way a company could utilize data analytics is
through monitoring marketing campaigns, content creation and receptivity to
content, product development, and sales strategies. Loew (2023) highlights that
Coca-Cola watches and is constantly updating their internal data analytics to
try and identify what appeals to their consumer base. Seeking new methods to
bring in customers without costing them opportunities with loyal consumers
(Loew, 2023). Similar to how Coca-Cola wants to retain while also expanding
their customer base, Verizon is utilizing data analytics and marketing
campaigns to collect data helping to determine if customers are willing to get
involved with Verizon Home Internet, even if they are not an existing Verizon
customer. The data can show which campaigns helped boost sales or peak
interest, while monitoring trends with both new and existing customers.
Disadvantages
Although the healthcare industry does utilize data
analytics in numerous scenarios, healthcare is an industry that has to account
for a lot of uncertainty and potential disruptions to the expected results.
Similarly Verizon is working through the uncertainty of the capacity at which
they can sell and provide internet service to customers without causing
disruptions to the existing cellular networks in the area. There are external
variables that may disrupt the accuracy and flow of available data collection that
skew forecasted results.
Another limitation to Verizon’s approach is it becomes very
dependent on what the competition starts doing in response to Verizon offering
services to areas where other providers currently do not. While Coca-Cola does
run campaigns and track marketing techniques, they have less limited
availability and their campaigns are not currently focused on competitor’s
availability to consumers. Being a newer service provider Verizon began by
targeting areas that had limited options, leaving them little to no competition
while becoming more established.
However, the data collected may have to shift
as Verizon seeks to become a more commonly used internet provider. Instead of
analyzing areas that are going to have Verizon as either the primary or only
option, the current approach needs to gradually shift towards the larger market
and gather interest in the product from people using major network providers
that rely on satellite reception for their connection. The limited data being
analyzed will need to increase to include potential consumers’ reception to marketing
campaigns or incentivized offers to both new or existing customers for making
the switch. This will help better understand the direction the service could go
and how it will hold up against competitors when they operate in a market that
has active competition rather than existing as the only option for some people
based on location.
Conclusion
There are numerous benefits to the utilization of data
analytics within many industries. Playing a role in industries ranging from
healthcare, food and beverage, and even internet providers. Being aware of the
data and analyzing it to show expected trends, cost-effectiveness of solutions,
or general reception to any product or service changes can help businesses
better identify which approaches work best to yield optimal results. For
Verizon entering the internet market, data analysis helped identify competition
in the area, customer reception to marketing, and areas that didn’t have other
coverage options to target consumers for market entry. While beneficial for
market entry, as they seek to expand their coverage to more consumers Verizon
may have to adopt some of the practices Coca-Cola utilizes in order to grow
interest in the product and place themselves in the top competition for
internet providers.
References:
Camm, J. D., Cochran, J. J., Fry, M. J., & Ohlmann, J. W.
(2024). Chapter 9 Time Series Analysis and Forecasting. In Business Analytics (5th ed.).
essay, Cengage.
Loew, L. (2023, July 18). Council post: Being data-driven is likely your best bet. Forbes. https://www.forbes.com/sites/forbeshumanresourcescouncil/2023/07/18/being-data-driven-is-likely-your-best-bet/?sh=754e34bd6bb0
Muenning, P. (2017). Decision analysis. Decision Analysis – an overview | ScienceDirect
Topics. https://www.sciencedirect.com/topics/earth-and-planetary-sciences/decision-analysis
Peer post 2
To address the business problem of reducing
turnover rates at Wize Guys, various research design methods and techniques can
be applied. Jangwoo and Hyun-Woo (2019) “…several factors lead to a high
turnover rate in the restaurant industry: 1) the current thriving economy
(i.e., more available job opportunities), 2) employing teenagers (1.6 million
teenage restaurant workers)3, and 3) employing a high proportion of students
(27% of restaurant employees are enrolled in school)”. In the restaurant
industry, two major groups of teenagers/college students are usually part-time
and ones that quit and full-time workers who rely on this job.
·
Descriptive Research: This method
involves gathering information about the current turnover rates at Wize Guys,
including turnover reasons, employee demographics, tenure, job roles, etc.
Descriptive research helps in understanding the existing scenario without
manipulating variables.
·
Exploratory Research: Exploratory
research aims to explore potential factors contributing to high turnover rates,
such as work environment, job satisfaction, compensation, career advancement
opportunities, etc. It helps in identifying underlying issues and generating
hypotheses for further investigation.
·
Causal Research: Causal research
aims to establish cause-and-effect relationships between variables. In the
context of reducing turnover rates, causal research can help determine which
factors directly impact turnover and how changes in those factors affect
employee retention. For example, does increasing compensation lead to lower
turnover rates? Does improving work-life balance result in higher employee
retention?
·
Experimental Research: Experimental
research involves manipulating variables to observe the effect on the outcome.
While it may not be feasible or ethical to conduct experiments directly on Wize
Guys employees, interventions or initiatives could be implemented in specific
locations or departments to test their effectiveness in reducing turnover
rates.
·
Qualitative Research: Qualitative
research techniques, such as interviews, focus groups, and surveys, can be used
to gather insights from current and former employees regarding their
experiences, reasons for leaving, suggestions for improvement, etc. This can
provide valuable qualitative data to complement quantitative analysis.
·
Quantitative Research: Quantitative
research involves collecting and analyzing numerical data. This could include
analyzing turnover metrics, employee satisfaction surveys, performance
evaluations, etc., to identify patterns, trends, and potential solutions for
reducing turnover rates.
·
Decision Analysis: Decision
analysis techniques, such as decision trees or cost-benefit analysis, can be
used to evaluate different strategies for reducing turnover rates. This
involves assessing the potential costs, benefits, and risks associated with each
option to inform decision-making.
“The restaurant industry has a staggering
rate of turnover with data showing an average churn of around 75%–a percentage
that has been rising following the pandemic. This is more than 1.5x compared to
all private sector workers where turnover is around 46%” (Notch, 2024).
From this website, they say that the average is 75% which is pretty high. It’s
hard to get people to stay in the restaurant business unless they are treated
well.
In the case of Wize Guy’s goal to reduce
turnover rates, a combination of descriptive research to understand the current
state, exploratory research to identify potential factors, causal research to
establish relationships, qualitative research to gather insights from
employees, and decision analysis techniques to evaluate solutions would likely
be most effective.
References:
Jo, Jangwoo
and Joung, Hyun-Woo (2019) “Do Part-time Employees Matter in the
Restaurant Industry?,” ICHRIE Research Reports: Vol. 4: Iss. 3, Article 2.
Available at: https://via.library.depaul.edu/ichrie_rr/vol4/iss3/2
Notch.
(2024, January 5). How to Fix High Restaurant
Employee Turnover | notch. https://notch.financial/blog/restaurant-turnover-rate/#:~:text=The%20restaurant%20industry%20has%20a,employees%20leave%20their%20restaurant%20jobs%3F
