Descriptive And Predictive Analytics For Mutual Fund Returns And Sales Performance For Good Harvest Investments

Problem Statement

Good harvest investments is an agribusiness organization which grows organic food and offers delivery of their products’ package to their customers. They are determined in making a better community by producing and delivering quality products. The agricultural production process is determined by various factors, hence the need for time, money, water among other resources. Some natural resources such as rainfall may inconvenience the production process. Therefore, artificial sources of such resources should be developed to ensure that the agricultural activities continue effectively throughout the year regardless of the climatic conditions.  In some cases, structures such as greenhouses might be required to elevate the production levels for the plants. All these forms of dedication are focused on improved production amounts to maximize the available resources. From a business perspective, the investors should minimize the agricultural inputs and produce maximum outputs. Good harvest has compiled all these resources for efficient and effective production and supply of their products (GoodHarvest, 2017).

Despite the production process, it is also important for agribusiness investors to learn the likes and preference of their customers. Achieving this business principle, they will be able to produce their products proportionally based on their demands. In cases of underselling products, it is the responsibility of the investors to inform their potential and existing customers of the existing products and their benefits (Agrawal & Anil, 2009). For instance, vegetables are very important for their sufficiency in vitamins, which nourish the body. Enabling the customers to learn how vitamins are important for improving body’s immunity will improve the products demand hence boosting their sales. Therefore, performing blinded business might affect the sales and demands negatively. Business indicators are also important to avoid investing in products that are not selling well in the market. This paper will focus on answering the hypothetical business question to develop inferences about sales performances and profits (Dlamini, Kirsten & Masuku, 2014).

Good harvest needs to understand the best and the worst selling products on their investments. This will help them focus on the best performing specializations. Profit levels assist the investors to quantify the level of success achieved. Customer shopping behaviours also affect levels of product sales based on their location in the shop. Some of the customers prefer to shop on the products that are closer to the exit because they’re not interested in walking around the outlet. In addition, products that are located in the visible area are likely to be bought because of the concept that a customer will see, like and make a purchase. Therefore, a business needs to understand the relationship between the location of a product on the shop and their respective sales. Based on purchasing behaviours, it is assumed that time is a determining factor, hence the need to understand what time of the year the sales are high or low in consideration with product type to make effective investment plans (Dlamini, Kirsten & Masuku, 2014).

1. What is the top/worst selling products in terms of sales?
2. Is there a difference in payment methods?
3. Are there differences in sales performance based on the location of products in the shop? How are the profits and revenue affected?
4. Is there a difference in sales and gross profits between months of the year?
5. Is the difference in sales performance between different seasons?
6. What is a relationship between rainfall and profits?
7. Is there any relationship between days of the week and total orders?
8. Is there any difference between product sales and net profit?

Research Questions

Table 1: Descriptive statistics for sales data

Table 2: Descriptive statistics for product data

Table 3: Gross sales by months

Table 1: Bar plot for average amount by payment method

On average, most customers prefer using credit as their form of payment followed by Visa and then cash. Based on the sales data, customers paid an average of $584.80, $555.85 and $404.89 using credit, visa and cash payment methods respectively.  

Products that were placed outside front had more sales on average than any other on the shop. There was no much difference between the products placed in front or at the rear side of the shop. Similarly, there was no difference in sales and net profit for product placed on the left and right side in the shop.

Table 4: Product type by total sales

Vegetables and fruits are the best performing products with the highest total sales while salad greens and juicing are the worst performing.

H₀: There is no difference between the payment methods

Table 5: Payment methods

Based on the means, there is a significant difference between the payment methods used by the customers. Credit mode of payment is the best performing and MasterCard is the worst.

H₀: There is no difference between product location on the shop and sales performance

Table 6: Sales performance by product location

There is a difference between the location of the products on the shop and the equivalent sales performance. Produced located on the outside front performs much higher than those located inside the shop. Similarly, produced placed in front and rear parts of the shop have more sales compared to those located on the right and left sides.

Table 7: Product location by net profit

Although the products located on the outside front sales more, they perform poorly based on the net profits. The products placed in front performs best based on profits made followed by those located in the rear side.

H₀: There is no difference in means of gloss sales between the months

The p-value is greater than 0.05, hence concluding that there is no difference in gross sales’ means by the months of the year at 95% confidence level.

H₀: There is no difference between total profit means between months of the year.

The p-value is less than 0.05, hence concluding that there is a significant difference in total profit between months at 95% confidence level (Larose, 2016).

Descriptive Analysis

H₀: There is no difference between means of sales by season

We reject the null hypothesis because the p-value is greater than 0.05. Therefore, we conclude that there is no difference between gross sales’ means by seasons of the year (Larose, 2016).

Table 3: Scatter plot for Rainfall amount by total profit

The p-value is greater than the significance level, hence concluding that there is no relationship between rainfall amount and the total profits made in the business. Pearson correlation coefficient indicates that there is very weak (close to no) [correlation] between profits and rainfall (Larose, 2016).

H₀: There is no difference in means of total orders by days of the week

The p-value for the ANOVA test is less than the significance level (0.05), hence concluding that there is enough evidence to conclude that totals orders are different by days of the week (Poonia, 2011).

H₀: There is no association between product class and their location on the shop.

The p-value is less than the significance level hence concluding that there is an association between the product class and their locations on the shop (Poonia, 2011).

The investors should focus on the best performing products such as vegetables, fruits and dairy to ensure that they make more profits. They should also sensitize their customers on the worst performing products to check if they improve their sales (Auld, Jones & Thilmany, 2008). Payment methods available in the shop should be maintained to better customer services. Based on the performance of the products based on their location in the shop, the investors should perform a thorough analysis to which products should be placed outside front. Probably, they might perform should be placed outside to sensitive the customers. Further analysis should be conducted to understand the specific months that make more profits so that the investors can take a business advantage.

References

Agrawal, B., & Agrawal, A. (2009). Social responsibility of business enterprises. Jaipur, India: ABD Publishers.

Auld, G., Jones, K., & Thilmany, D. (2008). O37: Factors Affecting Small Producer’s Local Food Sales. Journal of Nutrition Education and Behavior, 40(4), S38. https://dx.doi.org/10.1016/j.jneb.2008.03.049

Dlamini, B., Kirsten, J., & Masuku, M. (2014). Factors Affecting the Competitiveness of the Agribusiness Sector. Journal of Agricultural Studies, 2(1), 61. https://dx.doi.org/10.5296/jas.v2i1.4775

GoodHarvest. (2017). About Us. Good Harvest Organics. Retrieved 7 October 2017, from https://www.goodharvest.com.au/pages/about-us

Larose, D. (2016). Discovering statistics. W H Freeman.

Poonia, V. (2011). Advanced statistics. New Delhi: Vishvabharti Publications.

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