Through in-depth mining and analysis of invoice data, enterprises can comprehensively analyze key areas such as sales, procurement, finance, and operational efficiency, and accurately locate advantages and disadvantages, thereby providing strong support for scientific decision-making. This article will break down in detail how to use invoice data for business operation analysis, help enterprise managers unlock the business value behind the data, and promote the steady development of enterprises.
Invoice data contains rich details of business operations, from transaction amounts to customer information, from product categories to time dimensions, each data can provide clues for business business analysis.
Through more detailed analysis, the advantages and problems in enterprise operation can be accurately located, and strong support for decision-making.
1. Sales analysis
(1) In-depth excavation of sales trends
When analyzing sales trends, not only summarize sales according to the regular time dimension, but also introduce year-on-year and month-on-month analysis.
For example, calculate the year-on-year growth rate of monthly sales compared to the same period of the previous year to clearly show the growth trend of the enterprise in different periods; Through month-on-month analysis, compare sales changes in adjacent months to find out the impact of market fluctuations on sales in a timely manner. At the same time, combined with external and internal factors such as market environment, industry dynamics, and corporate marketing activities, the reasons for changes in sales trends are deeply interpreted.
If you see a sudden increase in sales in a month, you can see if there were new products, promotions, or favorable changes in the market during the month.
Year-on-year growth rate formula:(Current Sales – Sales in the same period last year)÷ Sales in the same period last year × 100%, helping you compare the growth trend in different years and the same period, excluding seasonal factors.
Month-on-month growth rate formula:(Current Sales – Previous Sales)÷ 100% of the previous sales × to capture short-term market fluctuations in a timely manner.
Example:
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An e-commerce company automatically generated sales trend dashboards through financial analysis software and found that sales in Q4 2023 increased by 180% month-on-month, and further comparison found that the year-on-year growth rate was only 75%. Combined with market data, it turned out that competitors launched promotions during the same period, resulting in the diversion of growth dividends. Based on this, the company deployed differentiated marketing in Q4 2024 in advance, achieving a year-on-year increase of 120%.
(2) Precise positioning of sales areas
Don’t let sales area analysis stay in the extensive cognition of “Beijing, Shanghai, Guangzhou and Shenzhen contribute 80% of performance”. For sales region analysis, in addition to counting the sales amount of different regions, it can also calculate the sales growth rate and market share of each region.
- Through the sales growth rate, identify potential markets with rapid growth, and give priority to investing resources for development;
- Through market share, understand the competitive position of enterprises in various regional markets, and analyze whether the products do not meet the market demand or there are problems with marketing channels in areas with low market share.
In addition, it can also be further subdivided into regions, such as refining provinces to cities, tapping the sales potential at the city level, and providing a basis for enterprises to formulate more accurate regional marketing strategies.
Regional sales growth rate formula:(Regional Current Sales – Regional Previous Sales) ÷ Regional Previous Sales × 100%
Market share formula: Sales in this region ÷ Total sales in this region × 100%
Example:
Transform invoice address data into thermal maps with the geographic visualization capabilities of BI systems. A chain catering company found that the market share of second-tier city B was only 3%, but the sales growth rate was as high as 45%, far exceeding the average of first-tier cities. The strategy was immediately adjusted to add 10 new stores in the city, and regional performance increased by 200% within half a year.
(3) Customer stratification and behavioral insights
In customer analytics, customer value models are built based on the frequency and amount of customer purchases, such as RFM models (Recency – last purchase time, Frequency – purchase frequency, Monetary – purchase amount).
- R (last purchase): The closer you get, the higher the score
- F (Frequency of Purchase): The more times you do, the higher the score
- M (purchase amount): The higher the consumption, the higher the score
Based on the RFM score, customers are divided into different levels, such as important value accounts, important retention accounts, important development accounts, important retention accounts, etc. Develop personalized marketing strategies for different levels of customers. For important value customers, provide exclusive discounts, priority services, etc.; For important customer retention, through return visits, gifts, etc., understand the reasons for customer loss and try to recover.
At the same time, in-depth analysis of customer purchasing preferences, not only focusing on the types of products or services purchased, but also analyzing the combination pattern of purchase. For example, some customers often purchase specific products at the same time, and companies can launch package products based on this purchase combination to increase customer unit price and customer satisfaction. In addition, by analyzing the customer’s purchase time pattern, such as some customers are accustomed to buying during specific time periods, enterprises can strengthen marketing promotion during these time periods.
Example:
A beauty brand connected invoice data through a CRM system and found that the top 10% of key value customers contributed 60% of sales. For such customers, exclusive membership days, customized gift boxes and other services have been launched, and the repurchase rate has increased by 35%; Push limited-time discount coupons to important retention customers (low frequency and high consumption), and successfully recover 40% of lost customers.
2. Procurement analysis
(1) Multi-dimensional evaluation system of suppliers
The analysis of suppliers cannot be limited to the level of supply ratio and price. Establish a supplier evaluation system to conduct comprehensive evaluation from multiple dimensions such as quality, delivery time, service, and price.
Supplier Composite Score = Quality Score ×40% + Lead Score ×30% + Service Score ×20% + Price Score ×10%
Evaluate the supplier’s product quality through feedback on product quality in invoices (e.g., returns, exchange records); According to the comparison of the invoice issuance time and the contractual delivery time, the on-time delivery rate of the supplier is counted; Evaluate the service level of suppliers through communication records with suppliers and after-sales service. Regularly update supplier assessment results, eliminate underperforming suppliers, and optimize supplier structure.
Example:
A manufacturing company set up an automated scoring module in its ERP system and found that Supplier A had a low price but only 60% on-time delivery, resulting in multiple production line shutdowns. Decisively reduced its procurement ratio from 30% to 5% and replaced it with a supplier with a higher overall score, resulting in a 25% increase in productivity and an 18% reduction in hidden costs.
(2) Optimization of the cost structure of procurement categories
In the procurement category analysis, in addition to focusing on the proportion of categories and procurement trends, the procurement cost structure of the category can also be analyzed. For example, for raw material procurement, analyze the proportion of raw material prices, transportation costs, warehousing costs, etc. in the total cost to find out the key links of cost control.
At the same time, pay attention to the substitution of procurement categories, evaluate whether there are more economical and high-quality alternative products, and reduce procurement costs and supply risks. In addition, through the life cycle analysis of procurement categories, reasonable arrangement of procurement plans to avoid inventory backlog or shortage.
Total cost of raw materials = raw material price + transportation cost + storage cost
Example:
A food company found through the analysis of the supply chain management system that the transportation cost of a certain raw material accounted for as much as 32%. By switching to railway transportation and optimizing the warehousing layout, the proportion of this cost was reduced to 15%, and the annual cost savings exceeded 2 million yuan.
3. Financial analysis
(1) Analysis of revenue structure and profit quality
In revenue analysis, not only operating income and profit margins are calculated, but also the source structure of revenue can be deeply analyzed.
useBusiness sector contribution rate formula(Revenue of this business segment ÷ total revenue × 100%) Dismantling the source of revenue. Split revenue by product, customer, channel and other dimensions to understand the contribution of different business segments to revenue. For business segments with a high proportion of revenue but low profit margins, analyze the reasons for high costs and consider whether to adjust business strategies.
At the same time, pay attention to the sustainability of revenue, and analyze whether the driving factors of revenue growth come from the expansion of new customers, the repurchase of old customers, or the short-term positive market environment. By analyzing the aging structure of accounts receivable, the quality of income is evaluated to avoid inflated income.
Example:
A technology company found that hardware sales accounted for 45%, but the gross profit margin was only 12%; while the software service business accounts for 30%, and the gross profit margin is as high as 65%. adjusted the strategy in a timely manner, increased investment in software research and development, and the overall gross profit margin increased from 28% to 37% the following year.
(2) Tax compliance and planning optimization
In tax analysis, in addition to focusing on the tax burden, it is also necessary to delve into the compliance of invoices. Check whether the issuance and acquisition of invoices comply with tax regulations to avoid tax risks caused by invoice problems.
Set up compliance verification rules in the electronic invoice system, and use tax planning tools to compare tax calculation methods:
General taxation: Tax payable = Output tax – Input tax
Simplified tax calculation: Tax payable = sales × levy rate
Analyze tax treatment methods under different business models to find space for tax planning. For example, rationally use preferential tax policies to optimize business processes and reduce tax costs. At the same time, establish a tax risk early warning mechanism to detect potential tax risks in a timely manner through real-time monitoring of invoice data.
Example:
A construction enterprise found through calculations that a project can save 15% of taxes by simplifying tax calculation, which alone saves 800,000 yuan in tax expenses.
4. Operational efficiency analysis
(1) Optimize inventory turnover rate
In the inventory turnover analysis, not only the overall inventory turnover rate is calculated, but also the inventory turnover rate can be calculated separately by product category, batch and other dimensions.
Inventory turnover formula: Cost of goods sold ÷ Average inventory balance
For products with low inventory turnover, analyze whether it is a lack of market demand, product quality issues, or a backlog caused by improper marketing strategies. By comparing the sales quantity and the purchase quantity in the invoice data, predict future inventory demand and formulate scientific procurement plans and inventory management strategies. At the same time, pay attention to the loss of inventory, analyze the causes of loss, and take measures to reduce the cost of inventory loss.
Example:
A garment company found through WMS system monitoring that the inventory turnover rate of a certain series of clothing is only 60% of the industry average. Immediately launched the clearance promotion, increased the inventory turnover rate to the industry average, and reduced the inventory backlog cost by 1.2 million yuan.
(2) Efficient management of accounts receivable
Formula for accounts receivable turnover days: 365÷ (sales revenue ÷ average accounts receivable balance)
On the basis of the analysis of accounts receivable turnover days, the customer distribution of accounts receivable is further analyzed. Find out the customers with large amounts of arrears and long account periods, and focus on tracking and collection. Establish a customer credit evaluation system and adjust credit policies according to customers’ credit status.
For customers with good credit, the account period can be appropriately extended to improve customer satisfaction; For customers with poor credit, shorten the account period or require advance payment to reduce the risk of accounts receivable. At the same time, analyze the recovery methods of accounts receivable, optimize the collection process, and improve the efficiency of fund recovery.
Example:
A trading company used the receivables management system to automatically warn of overdue accounts, stopped shipping to customers with arrears of more than 90 days, and initiated legal collection procedures, shortening the average collection cycle from 60 days to 45 days, and increasing the capital turnover rate by 33%.
Through detailed analysis of invoice data, enterprises can comprehensively and deeply understand their own operating conditions, identify problems in a timely manner and take targeted measures to improve them, and enhance their competitiveness and profitability.
