Business data of an enterprise involves sales data, financial data, manpower data, product data and many other types, and the importance of sales data in all data is beyond doubt. By analyzing the sales data, it is helpful to find business problems, reduce sales costs and ultimately improve the sales profits of enterprises.
Key index extraction
Different industries have different emphasis on sales indicators. This article will take the building materials industry as an example to illustrate.
The sales data indicators involved are: sales quantity, sales unit price, sales revenue, unit cost, sales cost, sales gross profit, etc. The original data will also involve information such as month, city, classification, unit of measurement, and corresponding customers.
Chart and kanban making
After extracting important data indicators, you can make related kanban and charts according to your own needs. Before this, users must understand the indicators that need to be monitored.
Generally speaking, when making kanban, according to different purposes, it can be divided into three categories:
1. Basic data kanban: an overview of the global situation
Everyone is familiar with this kind of kanban, which is mainly composed of a series of basic charts including maps, bar charts and pie charts. Used to view basic data such as sales revenue and sales cost in different regions, times and categories. The following figure is a kanban generated according to the sample data of building materials industry:
From this billboard, we can read the basic sales information of this company: Jilin Province is a big sales province, with a total income of more than 30 million in the first half of the year. The sales effect was the best in March, and the sales of conventional series multilayer composite products were the best.
It should be noted that this billboard is measured by sales revenue, and business personnel can adjust it according to their own needs or reporting objects.
2. Problem analysis kanban: looking for reasons
Basic kanban meets the needs of users to view data. If you want to solve problems with data, you need to analyze specific problems, establish targeted kanban, and conduct exploratory analysis according to the functions provided by DataHunter.
If you want to see the relationship between sales revenue, cost and gross profit of different categories of goods, you can create a new kanban and generate a two-axis chart:
It can be seen that the sales revenue of multi-layer composite categories is obviously greater than the cost, and the corresponding gross profit is also particularly high.
If you want to know more about which provinces and cities have the highest gross profit and when, you can create a new chart based on the original kanban, as shown in the following figure:
Next, drill down the gross profit list from the city and time dimensions respectively:
▲ Drill by city dimension.
▲ Drill by date dimension
▲ The drilling results show that,
I finally know: Ryan has the largest gross profit in April.
The above is a simple exploratory analysis process.
3. Early warning monitoring kanban: quick response
There are many application scenarios of sales data monitoring and early warning: for example, focus on monitoring goods with good behavior, and if abnormalities are found, immediately check the reasons to prevent major losses; Another example is to focus on monitoring commodity inventory, and adjust it in time if there is insufficient inventory in a certain area.
For a simple example, a scatter plot is generated according to the cost and profit of different types of products, and two reference lines are set with average profit and average cost respectively, so that the whole graph is divided into four quadrants, which can focus on monitoring products with high cost and low profit or high profit and low cost, and find out the reasons and react to changes in time.
(The picture above was made by DataHunter. )