7 Directions to Achieve Lean Management Step by Step
In recent years, it seems that everyone talks about the concepts of production intelligence and big data when they are chatting. So it is not strange that almost every enterprise has joined the army of intelligent production revolution. However, they often neglect the most important thing —lean management, and the road to achieve intelligent production seems to be in trouble.
So how can we get rid of the misunderstanding of lean management? And then how to let data become the productivity that leads the enterprise’s intelligent production?
1.Why we need lean management
It is derived from lean manufacturing and it maximizes organization value by increasing customer satisfaction, reducing costs, and improving quality.
The goal of Lean Automation is to automate the production process, while most companies just focus on manufacturing automation.
2. Why lean management becomes hings of little value
Lean management is in full swing in foreign countries. However, the road of implementing lean management for domestic enterprises is not so flat. The main reason is that domestic enterprises have fallen into three major misunderstandings, making lean management become a tasteless “chicken rib”.
- Misunderstanding of thought and culture: When implementing lean management, enterprises often think that lean thinking is only a matter of leader, and does not need to be decentralized to all levels of the enterprise;
- Misunderstanding of direction and attitude: Lean management advocates sustainable development, the purpose is to achieve continuous improvement, and may not produce obvious benefits in a short period of time, which makes many enterprise managers mistakenly believe that lean management is not important;
- Misunderstandings of rules and changes: Traditional management models tend to set standards, while lean management requires both rules and innovation;
These three misunderstandings will bring many problems to company’s management and operation, which will make the business results show a tortuous decline, and finally deviate from expectations and plans.
3. Lean management “one enterprise to one policy”
James P. Walker, who puts forward the concept of lean management, has a core concept: “Lean management is not good or bad, only suitable and unsuitable.” The vitality of lean management lies in innovation, while the innovation of management mode can’t just copy someone else, lean mode management within the company needs to be changed accordingly.
4. How data help realize lean management?
The process of lean production includes procurement, R&D, production, marketing, logistics and many other processes. The data flow and information flow generated are considerable, and the data will generate data management problems. In order to better manage data, let the data be base of lean management, and a lean analysis application model is proposed for this purpose.
4.1 Systematic management thinking
Any software system has three parts of input, process, and output, with the input as the data stream, the process as the workflow, and the output as the information flow.
Combining with the data analysis report refinement management system, from the perspective of demand management, report management and indicator system, we use professional report development platform such as FineReport, from requirements acceptance to report development, report release, report operation and maintenance, etc. Develop a management indicator system to solve the problem of redundant reporting confusion;
4.2 Lean 110
Lean 110 means that every one second of the delivery period should be implemented. Every 1 cent of the cost must be planned, and the quality control should be zero. In response to this strategic goal, we have improved in terms of cost, quality and delivery.
We can use FineReport to establish order delivery cockpit, from purchase delivery to production delivery, customer delivery monitoring and management, in order to achieve the purpose of integrated production planning, procurement planning, marketing plan;
4.3 Target gap analysis
The gap is the problem, through the value stream analysis to find process management defects, and then propose improvement measures. Taking the production plan indicators as an example, the reporting system can correlate the factors related to the production plan to monitor the continuous progress of the entire production process;
4.4 Lean scene management tool
The traditional mode of scene management is basically based on manual inspection by human resources. This mode is easy to miss the problem and has little effect. Lean scene management can use the mobile terminal report to timely feedback the on-site production situation.
4.5 Value stream analysis
In traditional value thinking, the goal of production is to continuously increase the output value, while the core of lean thinking is to avoid all waste, that is, to require employees not only to have value-added work, but also to actively identify waste;
4.6 Lean meeting system
According to the lean management idea, we often rely on the data foundation of the reporting system, and establish a decision-making conference system, then let the report feedback the data, thereby greatly improving the efficiency of the conference, such as the automated conference report of equipment developed by FineReport;
4.7 TPM full production maintenance
Taking equipment production and maintenance as an example, the real-time data of the equipment is graphically displayed through the data analysis system, we use these data to monitor the operation of the equipment. At the same time, the trend of the equipment can be estimated by analyzing the running status of the equipment, and then the equipment maintenance plan is formulated.
Lean management is the only way to intelligent production, and it is important for company to achieve data transformation.
On the other hand, the lean management combined with data can produce greater value, everything leaving Lean management of data is empty talk. Only if enterprises apply data to various modules of enterprise production management, can data truly become the productivity that leads the transformation of intelligence.
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