Prepare an 11- to 15-slide Microsoft^® PowerPoint^® presentation for the senior management team based on the business problem or opportunity you described in Weeks 3 and 4.( The Week 3 & 4 information is provided below.)

Include on the slides what you would want the audience to see (include appropriate visual aids/layout). In the Speaker Notes section, include what you would say as you present each slide. If any source material is quoted or paraphrased in the presentation, use APA citations and references.

Draw on material you developed in the Week 3 and 4 assignments.

Include the following in your presentation:

• Introduction slide
• Agenda slide
• Describe the organization, with a brief description
• Explain the business problem or opportunity
• Analyze why the business problem is important
• Identify what variable would be best to measure for this problem and explain why
• Apply data analysis techniques to this problem (tell which techniques should be used: descriptive stats, inferential stats, probability) and explain why
• Apply a possible solution to the problem/opportunity, with rationale
• Evaluate how data could be used to measure the implementation of such a solution
• Conclusion
• References slide (if any source material is quoted or paraphrased throughout the presentation)

Format your assignment consistent with APA guidelines.

____________________________________________________________________________________________________________

Week 3: Challenges and Opportunities in Komar’s: Part 1:

Company Description:

I work at Komar’s, a warehouse that supplies and sell stock to renowned companies such as Wall Mart, Kohl’s, TJ Max, and JC Penney’s, as well as stores from across the globe. Our company receives a large number of customers during the festive season, so obviously the volume of sales during this festive season is expected to increase dramatically. Therefore, our firm must prepare well by increasing the volume of stock to cater for the expected increase in demand during the Christmas through to New Year festivities.

Business Problem:

Our company can only increase the volume of stock by using an effective system that will not result in increased losses. Therefore, we must rely on the data of the stock sold during the festive seasons in the past years. The sales statistics derived from the other years will help to project the sales for this year. The main problem of the business is to collect accurate sales data for the past years and to analyze that data accurately. The company will also need to know the taste and preference choices of the consumers during this season.

Research variables:

The data collected will mainly be qualitative and quantitative data. The main quantitative research variables identified from the business problem includes the volume of every commodity sold during the festive season and their respective costs. The common commodities sold during the festive seasons will be a subject of study. The main reason to identify the common commodities sold during the festive season is that our clients consume festive related commodities during these periods. The qualitative variables will include the taste and preference of our esteemed customers during the festive season.

Methods of data Collection:

The methods used to collect data will mainly focus on collecting the qualitative as well as the quantitative data from previous sales years. Since the company keeps the records of its stock and sales, one primary method of collecting the sales information will be a review of the business records. Therefore, the primary method of collecting data will be a review of reported sales.

This method will involve a review of transaction records such as shipping and receiving invoices, sales slips and sales tallies (Black, 2009). The method of reviewing these documents should have a very high degree of accuracy. Accuracy is an important factor since the process will involve reviewing of large volumes of paper, which may be prone to human errors.

The main identifiers in this process will be the name of the commodity, the date of the transaction and the price of the commodity. During data collection, comparison with the data recorded in the annual reports will make the process of error identification easier.

To collect the information about the preference and taste of the consumer, methods such as questionnaires and interviews will be applicable (Black, 2009). Requesting the frequent customers to give their feedback on their experience in the stores as well as possibly having them fill out a questionnaire form which can help to determine what types of merchandise they prefer to purchase during the festive seasons. It would also be possible to reach frequent customers through the telephone, or internet blog site for the purpose of retrieving statistical information about their preferred choices.

Our company has an online sales platform where customers place their orders online. The platform allows them to place their orders in advance. This platform would be another valid source of information concerning the taste and preference of the consumers. It would be easier to have customers review the services they receive from our company as well as get their views on the commodities they would expect to find in our stores. From the same platform, it would be easy to collect the information concerning the most common commodity, and quantity ordered by the consumers.

Validation of the Data Collected:

The data collected should have a high level of precision since it will be mainly used to focus the market trends. To ensure the data on sales made and the prices of the commodities sold during the festive seasons in other years, comparison of different documents will be very important. For example, it would be a better to compare the goods sold to the consumers and the goods supplied to our stores during a certain period. This method will help to determine if the sales are collect (Australian Bureau of Statistics, 2015). For example, the volume of the commodities sold must always tally with the volume of commodities received from the suppliers.

Comparison of different documents will also serve to minimize the number of errors during the data collection process. For example, comparing the information recorded in the invoices and receipts would help to identify a mistake in the case of any.

Ensuring that the employees who will conduct the interview receive a high level of training before the exercise will help to minimize errors (Buttle & Maklan, 2015). They should receive adequate training on communication skills, data collection, and data recording techniques.

Knowing that the Data is valid:

The methods described above will only help to minimize the chances of making errors during the data collection process. However, a close supervision and scrutiny of the whole process are imperative. Before analyzing the data, the company should ensure that all the data from the sales record tally is correct. The company can use different people to collect the data and then compare the results to determine its consistency. Since all transactions in the company get recorded on the computers, it will be easier to compare the data collected with the one stored in electronic form. Therefore, consistency of the data will be the only way to determine that the data collected is valid and correct. After ensuring the validity and consistency of the data, the other task will involve identification of valid methods to analyze that data. Such methods may include the use of well-known statistical software such as SPSS. Such software has numerous and valid tools to manipulate and analyze the data correctly (Anil & Ismail, 2014). Therefore, the results derived from consistent data analyzed using valid methods will be valid.

References:

Anil, M., & Ismail, B. (2014, November). Regression Methods for Analysing the Risk Factors. Elsevier, 66(6), 587-592.

AustralianBureauofStatistics. (2015, June 17). Australian Demographic Statistics. Retrieved October 13, 2016, from http://www.abs.gov.au/ausstats/[email protected]/featureart…

Black, K. (2009). Business Statistics: Contemporary Decision Making. Boston: John Wiley & Sons.

Buttle, F., & Maklan, S. (2015). Customer Relationship Management: Concepts and Technologies. Routledge: London.

__________________________________________________________________________________________________________________

Week 4: Business Decision Making Project: Part 2:

Types of descriptive statistics that might be best for summarizing the data:

By the use of descriptive statistics, our company would be able to summarize the data collected from different places or from different customers by the employees. This way the company would be able to identify the different items that were bought more in each place and plan well on the production in this festive season. The core reason is to get the average number of the items sold to customers in our different distribution points. To get to this, we will take the statistics of different products supplied at each specific store and then get the average of each which will determine our production during this festive season.

In the descriptive statistics, there are different ways of summarizing data. This ways would include calculating the mean, median and mode. This three methods would be helpful at our research. At first instance, the trained employees will be send at all points where our company supplies its products. They will get the statistics of the different commodities that was supplied at that place for the last three years. They will have to put the numbers in tabular form for each product in each specific year. For each product they will have to observe the trend during the three years. Then they will write a report for each product whether there have been an increase or a decrease in the purchase of the product during those consecutive three festive seasons.

All the trained employees send to the field by the company to get the statistics of how its products have been supplied for the past three years will return to the company where the analysis will take place. We will take each products data from the various points and add them together. This way we will be able to calculate their means. It is from the mean of this product the company would deduce the numbers to produce this time. We will also take the keen look at the trend of each product during the past three festive seasons to identify whether that product have been increasing its purchase or it has been dropping during the years. The product whose supply was increasing in each year will mean that we will have to produce it at a higher number compared to what we produced on 2015. The product whose purchase was dropping or seem to maintain a certain number, we will discuss on whether to produce the same as 2015 or increase the production a bit since also population we have increased a bit and this can increase its purchase.

Analyze the types of inferential statistics that might be best for analyzing the data:

In inferential statistics, a conclusion is made from the data. The company will use the data to deduce what the customers might need and the number of the products they might buy during this festive season. The comparison of the products supplied during the previous festive seasons will serve greatly in this research. Using our data that was collected from various points, we will make the inferences and predictions on the market during this time.

There are different types of inferential statistics. Here are the ones that will be much useful for the case of our company:

• The t-test.
• The Analysis of Variance.

The t-test will enable the ability to compare two variables. In our case we have two variable, that is, a.) the customer and b.) the product; and therefore this method becomes useful here. Using this method, we will be able to get the product that was bought more by the customers. This will enable us know exactly which product to produce more using the available material and labor putting time into consideration. We will also be able to know at which place each product its purchase is high so that we can arrange on the transportation. Knowing the product which needs to be produced in more, the company will be able also to assign its employees in different production areas.

This type of inferential statics enables one to make a comparison on three variables. Our three variables are the past three festive seasons that we need to analyze their data so that we can get the exact quantity of production that we have to produce during this season. There are two types of “The Analysis of Variance”. These are, one-way Analysis of Variance, which compares multiple groups on the same variable. This will enable us to relate how different products are bought at different stations, and identify which product should be supplied more at each point. The other one is the factorial “Analysis of Variance”. This one the results of multiple independent variables on one dependent variable. The independent variables at our case will be the stores where the company supplies its products while the dependent variables will be the particular products. The above types of inferential statistics will enable determine the quantity of the production which we should produce during this festive season.

Analyze the role probability or trend analysis might play in helping address the business problem:

Trend is the change that is observed on a population over time. Probability is the likelihood something has for it to occur. Observing keenly this two things, the trained staff will be able to come up with the exact quantity of production that the company requires to produce during this festive season.

What the trained employees should do is that they should take all the findings they have gathered from the various supplying regions, and try to observe the trend that has been there for those three consecutive festive seasons. They figure out which products have been having a rising trend in terms of purchases. For such products, it means that the company will have to produce more of it than the 2015 number. To get the exact quantity the company is going to produce, the staff should determine what has caused the changes that have been taking place, that is, the change that has been taking place, and by how much. This way they will give out an exact feedback. There is also those products whose purchase have been dropping during this three previous festive seasons. The trained personnel should also know the approximate number by which it has been dropping, so that the company can be able to reduce the production of those items by a specific number. For those products that have been maintaining a certain number of purchases, the company should consider producing the same number or slightly higher assuming that population have increased and so the purchase will increase.

References:

Wigginton, J. E., & Abecasis, G. R. (2005). PEDSTATS: descriptive statistics, graphics and quality assessment for gene mapping data. Bioinformatics, 21(16), 3445-3447.

Lowry, R. (2014). Concepts and applications of inferential statistics.

Bordens, K. S., & Abbott, B. B. (2002). Research design and methods: A process approach . McGraw-Hill.

Weiss, N. A., & Weiss, C. A. (2012). Introductory statistics. London: Pearson Education.