Most exercisable business intelligence supports ER

2022-08-21
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Using business intelligence to support ERP

business intelligence is a hot spot in current enterprise applications. How to make business intelligence bring real value to enterprises is the sign of the real maturity of business intelligence applications. Business intelligence will make full use of enterprise information resources and assist decision-making by supporting business systems. Combined with a standard ERP system, this paper will briefly introduce how business intelligence supports ERP applications. I hope that the introduction of this article will enlighten the application of business intelligence in ERP field

■ development of data warehouse

since the 1990s, with the continuous maturity of data warehouse technology, data warehouse has solved the problems of multiple data sources in decision analysis, the inability to use historical data, the low efficiency of multidimensional analysis, and so on

in addition, there are two urgent needs for the rapid popularization and application of this technology: first, it completely solves the dilemma faced by enterprise decision support system (DSS). People's expectation of DSS is to use the method base, model base, knowledge base and other knowledge it provides to explore the decision support functions that ordinary MIS (Management Information System) cannot achieve on the basis of database. However, the effective interface between databases and databases is a headache for every DSS. Its essence is the lack of a platform to freely obtain the data needed for decision-making. This problem makes DSS fall into a situation where people have high expectations and are difficult to achieve. Data warehouse provides a platform for integrating effective data. The construction of DSS can be easily completed through DSS front-end display tools. Experts believe that data warehouse is the best technology to solve DSS problems

second, it solves the problem of data accumulation dilemma. Most enterprises and institutions have established information systems, including both general MIS and large-scale application systems such as ERP and CRM systems. Rich data has been accumulated in the operation of the system for many years. However, due to the limitations of the transaction processing mechanism adopted by the system, valuable information and potential knowledge cannot be found from the existing data. Data warehouse technology creates an application environment for OLAP technology and data mining technology, and helps to find deep-seated information and knowledge from business data

■ business intelligence + ERP

ERP (Enterprise Resource Planning) refers to a management platform that is based on information technology and provides decision-making and operation means for enterprise decision-makers and employees with systematic management ideas

ERP is a management information system that integrates all resources of an enterprise. In short, it is a management information system that comprehensively integrates the logistics, capital flow and information flow of an enterprise. Its functional modules are different from those of MRP or MRP II. It can not only be used for the management of production enterprises, but also be imported into ERP system for resource planning and management. For enterprises, ERP includes four aspects: production control (planning, manufacturing), logistics management (distribution, procurement, inventory management), financial management (accounting, financial management) and human resource management (planning, wages, working hours, travel)

within the enterprise, ERP is integrated with PDM, CIM and pos. from the perspective of the alliance between enterprises and customers, ERP, as a background application, should be integrated with CRM and EC at the front desk, and with the supply chain. However, at this stage, ERP system stays at the level of MIS system with comprehensive functions, especially fails to achieve the function of decision-making analysis expected by real ERP. The reason is that almost all ERP systems use transactional processing to replace analytical processing in decision analysis

The business data accumulated by ERP is relatively regular. Based on these data, data warehouse, combined with OLAP technology and data mining technology, describes non intuitive and implicit information and knowledge in an intuitive form to assist the leadership in decision-making analysis. One of the difficulties of ERP project implementation is that it is difficult to arouse the interest of enterprise managers. Enhancing the analysis and decision-making function of ERP system will undoubtedly eliminate this obstacle, which will become a strong breakthrough for ERP manufacturers to promote products to enterprises

mrp Ⅱ controls the whole production process through the timely rolling of the plan. Generally, it can only achieve in-process control. The ERP system, which combines DW and OLAP technology, emphasizes the enterprise's prior control ability. It can integrate design, manufacturing, sales and other related operations in parallel, and provide enterprises with real-time analysis ability of key issues such as quality, adaptation to change, customer satisfaction, performance and so on

■ business intelligence functions required by ERP system

business intelligence functions required by typical ERP system include:

1 Sales analysis

how to make production and operation decisions accurately and timely is a serious problem faced by the boss of the enterprise. This requires decision makers to accurately and timely capture sales information, analyze sales, and make scientific decisions on the next step of production and operation according to the historical sales situation at any time. The basic data required for sales analysis involves modules such as sales, inventory, finance and personnel, which can be analyzed from multiple perspectives such as personnel performance, accounts receivable, finance and inventory around sales orders, and provide auxiliary decision-making information such as sales trends and product demand trends. Specifically, using business intelligence system for sales analysis can help enterprises solve the following problems:

· analysis of product sales of oil box and heater in a certain period of time

· how to formulate different price strategies for the same product according to different situations

· analysis of product return

· analysis of product sales revenue and profit

· which product is ordered by which customer, how much, when and from which salesman

· salesperson sales performance analysis, salesperson recovery analysis

· analyze sales performance from multiple perspectives

According to the problems that enterprises need to solve, business intelligence system helps enterprises establish corresponding analysis topics and analysis indicators, extract the required data from the basic database of the business system, and make analysis and decision according to the pre established business model. The analysis results are intuitive and visual. Decision makers can obtain the required decision-making information from the powerful sales analysis tools of business intelligence by simply taking operations

2. Inventory analysis

the inventory analysis based on the business intelligence system can not only make one 4. Please confirm that there is no action when turning on the power: 1. When encountering the limit, users can understand the quantity, inventory cost and capital occupation of inventory items, query from different angles such as level, category, location, batch, single piece and classification, but also assist in decision-making and solve deep-seated related problems of enterprises. The basic data of inventory analysis comes from business modules such as purchase, sales, production and finance. The functions of inventory analysis of business intelligence to help enterprises include:

· finding sluggish items in a given period of time and location, and providing processing suggestions

· query the reserve analysis and reserves of a material in each location

· analysis of the revenue, occurrence and balance of a material at a certain time

· analysis of inventory funds occupied by items

· which items are in shortage or overstock

· analysis of goods turnover

· query the inventory items and costs at each stage of history

· query inventory from multiple angles and conditions

3. Purchase analysis

the business intelligence system based on data warehouse technology can realize decision analysis such as supplier credit evaluation and salesperson performance evaluation, help enterprises lay a solid foundation for smooth production, and provide a scientific basis for the positioning of final products in terms of quality and cost. Specifically, it includes:

· analysis of supply credit rating, and evaluation of supplier performance in terms of delivery date, quality, data and price

· analysis of purchase price changes

· delayed delivery of goods and cause analysis

· supplier analysis of a material

· analysis of materials supplied by a supplier

· purchaser performance analysis

· analysis of purchase quantity and purchase amount of a supplier

· the supplier's materials are rejected for analysis after inspection

· arrival material storage warehouse and location query

· supplier quotation query

· query the purchase requisition, order, receipt and warehousing of items from multiple perspectives

· purchase cost variance analysis

supplier credit analysis is a very important part of procurement analysis, which is often one of the themes of procurement analysis. The basic data of purchase analysis comes from the finance, production and inventory departments

4. Financial analysis

business intelligence financial analysis based on data warehouse technology meets the requirements of enterprise leaders to query the expenses of each business department, and realizes the decision-making analysis of accounts receivable and accounts payable. By using this function, the decision-making level of enterprises can further improve the scientific level of decision-making from the perspectives of cash flow, assets and liabilities, capital recovery rate and so on. The specific functions include:

account analysis -

· analysis of the expenditure of each department to assist in making further budget decisions

· multi angle, multi-level and multi condition three-dimensional account query

· Sub Ledger query across subjects and levels

· financial historical data query

accounts receivable analysis -

· customer debt time and details query

· time period analysis of arrears

· customer purchase amount and payment status query

· customer cash discount analysis

· multi condition and multi angle query of collection and arrears

· customer credit rating analysis

accounts payable analysis -

· querying the time and details of the enterprise's arrears to the supplier

· time period analysis of the enterprise's arrears to suppliers

· analysis of procurement from various suppliers

· query payment and arrears from multiple conditions and angles

5. Human resource planning analysis

the domestic ERP system is affected by the general environment, and the human resource module is added to the ERP system at the latest. Most of the human resource modules of the current ERP system exist for the convenience of recording the external communication with the enterprise, and few can truly realize the internal human resource management and system integration of the enterprise. The labor planning application provided by the business intelligence system based on data warehouse technology should complete the decision-making based on the detailed human resource data of the enterprise. It can carry out the statistical analysis of human resources from multiple perspectives of processors such as landfilling, and through the use of existing human resources, predict the full and shortage of labor, analyze overtime and workload, and identify ineffective work and excellent employees, Calculate the rate of return of labor in a certain period of time, so as to maximize the use of labor resources. The manpower planning analysis of business intelligence can also realize the inquiry and analysis of employees' wages from different angles, and improve the scientificity of employee benefit distribution in combination with the completed workload. Specific functions include:

· employee statistics and query by department, professional title, major, educational background, gender, etc

· comprehensive evaluation of talent ability in terms of professional title, education background, workload, etc

· multi angle employee salary query, statistical analysis of employee salary according to different perspectives

· comparative analysis of actual completed workload and working hours

· manpower workload load analysis

· analyze the relationship between personal characteristics and commonalities such as rewards and punishments received by various employees

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