A sales prediction using the data visualization.

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During December 2019, which product has a higher amount of average quantity sold?
LC-3006
C-6001
LK-4001
BL-2001
Which product has a higher amount of average quantity sold in November 2019 compared to November 2018?
O-8005
LC-3006
LK-4001
BL-2001
Which product shows an obvious decreasing trend in the last quarter of 2018 in terms of the average quantity sold?
BL-2001
C-6001
LK-4001
O-8005
Make a sales prediction using the data visualization.
The company has a concern that the sales department may try to increase the sales revenue in December to receive more bonuses. Based on the average quantity sold in each month in 2018 and 2019, do you have the data to confirm whether this is happening? If you do have the data, what data is used to make this confirmation? If you do not have the data, what additional data is needed to make the confirmation?
Analyze product inventory using data visualization.
Starting in 2020, the company decides to use the change in average quantity sold between December 2018 and December 2019 to predict the inventory level the company needs for each product in 2020. Which products will require a higher inventory level and which products can maintain a similar inventory level?
Explain the advantages of using a data visualization tool for audit analytics.

Sample Solution

Product Sales Analysis

1. December 2019:

  • Average Quantity Sold: Calculate the average quantity sold for each product in December 2019. Compare the values to determine which product has the highest average quantity sold.

2. November 2019 vs. November 2018:

  • Calculate the average quantity sold for each product in November 2019 and November 2018.
  • Compare the values: Determine which product shows a higher average quantity sold in November 2019 compared to November 2018.

3. Decreasing Trend in Q4 2018:

  • Analyze the average quantity sold for each product in October, November, and December 2018.
  • Look for a downward trend: Identify if any product shows a consistent decrease in average quantity sold during this period.

4. Sales Prediction:

  • Analyze historical sales data: Examine the sales trends for each product over time.
  • Consider external factors: Consider any external factors that may have influenced sales, such as economic conditions, marketing campaigns, or seasonal trends.
  • Use forecasting techniques: Employ forecasting methods like time series analysis or regression analysis to predict future sales based on historical data.

5. Sales Manipulation:

  • Compare sales data for December 2018 and 2019: Analyze if there are any unusual spikes or patterns in sales during December 2019 that could indicate manipulation.
  • Consider additional factors: Examine other factors that could influence sales, such as marketing campaigns, promotions, or changes in customer behavior.

6. Inventory Level Prediction:

  • Calculate the change in average quantity sold: Determine the percentage increase or decrease in average quantity sold between December 2018 and December 2019 for each product.
  • Predict inventory needs: Use this percentage to estimate the change in inventory required for each product in 2020.

Data Visualization

Use data visualization tools to create charts and graphs that help visualize the data and identify trends:

  • Line charts: To show trends in sales over time.
  • Bar charts: To compare sales quantities across different products or time periods.
  • Histograms: To analyze the distribution of sales data.

Advantages of Data Visualization for Audit Analytics

  • Enhanced Understanding: Data visualization can help auditors quickly understand complex data and identify patterns or anomalies.
  • Improved Efficiency: Visualizations can help auditors identify potential areas of concern more efficiently, reducing the time and resources required for audits.
  • Enhanced Communication: Data visualizations can be used to communicate audit findings effectively to stakeholders, including management and regulators.
  • Improved Decision Making: Data visualization can help auditors identify risks and make more informed decisions about audit procedures and sampling.

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