Manufacturing is the pillar industry of my country's national economy, the leading sector of my country's economic growth and the foundation of economic transformation.
From the perspective of enterprise informatization management, the informatization level of my country's manufacturing enterprises is relatively low, and integrated applications restrict the improvement of enterprise business capabilities, resulting in slow reform of extensive manufacturing, unreasonable supply chain and industrial structure, and ultimately lead to excess capacity.
The modern manufacturing industry requires that the value chain of order - supply - production - circulation of enterprises is highly informatized. As a representative of modern manufacturing industry, DunAn Environment has made great progress in informatization construction. The enterprise informatization system is ERP/SCM/CRM. /MES and other peripheral systems have been deployed and put into use, and a large amount of data has been accumulated.
However, the correlation between these information systems is not enough, and the managers of the group cannot intuitively grasp the operation status of the enterprise through data information, and cannot simply and effectively observe the reaction caused by a certain strategy change through data. Managers of different processes at the grass-roots level cannot make real-time adjustments to production and operation based on visual data: for example, production managers can monitor productivity, plan production capacity, and optimize resources from key performance indicators ( KPIs ) such as production time, capacity utilization, and resource utilization. ; Quality management managers can improve product quality through product defect analysis; and senior management can improve ROI through more effective cost control and expense analysis.
To some extent, these troubles have also led to the lack of progress in the last mile of Dunan Environmental's informatization.
face the challenge
1. The various information systems of the enterprise are independent of each other, and the data are not connected with each other, but from the perspective of the entire enterprise of DunAn, they are interconnected. Managers must also use the aggregated data from each system when making decisions. Traditional The method is to use Excel to summarize from each system , which is inefficient and error-prone.
2. More data and less information. The information reflected in the current report is too simple to form a comprehensive understanding of the entire business process. Managers must take five or six reports, and cannot perform dynamic multi-dimensional analysis, perspective analysis, or substitute into established model operations to obtain decision-making information.
3. The enterprise chain is extremely long, reflected in the BI application, the data relationship of each chain node can be opened, providing real-time monitoring and early warning, ensuring good writing between material supply, production line operations, quality inspection, sales and logistics distribution and circulation.
Data management plan:
1. Integrate data and classify and manage according to business themes
The business intelligence solution FineBI supports the connection of multiple data sources, common relational databases, JNDI, ODBC data sources, program data sources, and SAP series data warehouse tools. And through the ETL tool, the data is cleaned, added columns, row and column transformations, read data field escapes, etc., and then extracted into the data warehouse FineCube , and can set the full volume, incremental, real-time update of cubes , etc.
The sorted data is classified and managed according to business topics, and data associations are read to prepare the data for better business services.
2. Provide fully visualized report output and OLAP multi-dimensional analysis to help business departments save costs and optimize production line management
FineBI 's analysis container is integrated with the dashboard . In the analysis container, Dunan's analysts only need to flexibly select query, filter, chart controls, and drag data columns to quickly generate reports. And by adding calculation indicators, formula indicators, adding drag-and-drop data column fields, drilling, linkage, dimension-changing analysis, and setting early warning conditions, etc.
Abandoning the SQL fetching and complex modeling of traditional analysis , it completely liberates IT personnel, and also equips business personnel. They can implement various thinking about business management and control into data analysis, such as:
Analyze cost structure and save cost
Through production cost analysis (multi-angle cost analysis, volume cost benefit analysis, proportion analysis, comparative analysis, profit analysis), the inventory management and the cost incurred in the production process are monitored to assist decision makers to find unreasonable inputs in production management and strengthen costs. ex ante control.
Optimize production line management
Decision makers at different processes in the factory can obtain real-time data and view different reports. Production managers can monitor productivity and plan production capacity and optimize resources from key performance indicators ( KPIs ) such as production time, capacity utilization, and resource utilization ; quality management managers can improve product quality through product defect analysis; and senior management can see through Improve ROI with more effective cost control and expense analysis.