What key data do home furnishing dealers need to master in order to make a profit? For home furnishing dealers, carrying out refined management and comprehensive data aggregation and analysis is an inevitable trend. Achieving it all at once may be difficult, but management can be improved step by step by starting with some simple foundational data.

Dealers rely on downstream customers for their business, and only by clearly understanding customer-related conditions can they act with precision:

1. Exactly how many customers are there at present? There must be an accurate figure, and telephone verification is the simplest and most effective method.

2. Divide current actual customers into three categories: large, medium, and small. How many customers are there in each category?

3. Among the total customer group, what proportions have high sales quality, average sales quality, and poor sales quality?

4. From the perspective of customer relationships, what proportion of customers have good relationships, average relationships, and poor relationships?

5. How many blank outlets are there at present? For these uncovered outlets, are they newly opened stores or stores that previously cooperated but have now stopped cooperating?

6. How many customers have unresolved historical issues? Problems with new product distribution, display, and settlement are often continuously obstructed by historical issues.

Fully master product information from cooperative manufacturers:

1. Among the manufacturers you cooperate with, how many SKUs are there in total?

2. Among all SKUs, what proportion are best sellers, what proportion have average sales, and what proportion have poor sales, including slow-moving items?

3. Up to the present, what is the actual sales amount of each manufacturer? This data must be summarized once a month.

4. Up to the present, how much capital is actually tied up by each manufacturer? This includes advance payments remitted to manufacturers, the value of inventory goods, and various prepaid expenses.

5. Up to the present, what is the amount of products pending return, exchange, or other handling for each manufacturer?

Data that affect dealer decisions on shipping and purchasing:

1. What is the total warehouse area, and after deducting aisles, loading and unloading areas, and office areas, how much actual storage area remains?

2. Within the storage area, what are the respective proportions of normal goods, goods pending return or exchange that cannot be sold normally, gifts, promotional materials, miscellaneous items, and large equipment?

3. How long does it take to complete a full inventory count of the warehouse? This should be compared on an annual basis. Strictly speaking, under the same area and same volume of goods, inventory counting time should decrease year by year.

Management of supplier receivables and receipts:

1. As of now, what is the total amount of receivables?

2. Of the current receivables, how much belongs to receivables normally agreed in contracts, and how much arises from human factors or industry customary factors?

3. Among receivables, what proportion can be normally collected at maturity, and what proportion is troublesome or overdue for too long?

4. What is the ratio between receivables and total sales, and how does it compare with the same period last year?

Business team data management:

1. Within the business team, what proportion of employees maintain stable performance, and what proportion fluctuate greatly in performance?

2. In employees' actual work status, what proportion can keep up with company development, what proportion need stronger management and supervision to keep up, and how many are basically already within the scope for elimination?

3. Based on historical resignation data, separately count how many employees stayed with the company for less than half a year, how many for half a year to one year, how many for one to two years, and how many for more than two years.

All of these data points are basic operational data, and collecting them is not complicated. The data themselves cannot directly solve problems, but they can help the owner have a clear picture, reduce ambiguity, provide a basis for analysis and judgment in relevant decisions, and reduce gut-feeling decision-making. Soonfor ERP systems center on enterprise management and use information science and technology to automate management, supply chain, production, sales, and other activities. They establish a management system that integrates processes across upstream and downstream parts of the enterprise, helping businesses simplify complexity, realize digital management, promote industrial upgrading, reduce costs, and win more business opportunities and profits.
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