How do traditional enterprises achieve digital transformation?

Overcapacity, excess products, excess services, low business dimensions, and fierce industry competition...these are the problems that traditional manufacturing companies are currently facing.

In this current situation of survival,sap partner hk only by changing business methods and management structures can enterprises adapt to changes in the current market environment and achieve further development.

The goal of digital transformation is to improve enterprise operating efficiency, achieve high-quality industrial development,sap hcm optimize the existing economic structure, and build a digital economic system. Enterprise digitalization is a big wave and a new opportunity for traditional enterprises.

Enterprise digital transformation needs to go through five stages

1. Business digitalization

The so-called business digitization means that enterprises move all original offline business process management online, and the intermediate process products or results can be digitally recorded and formed into data.sap consulting Help enterprises achieve interconnection.

Taking the order management scenario in manufacturing as an example, the lack of business digitalization will cause the following problems:

When traditional manufacturing companies conduct order management, they use traditional Excel tables to manually record order information. When there are too many orders, it is easy to make mistakes and miss orders, and subsequent verification of orders is very troublesome. The order data of some large companies are scattered, making it inconvenient to search for statistics and summarize them. Getting up is time-consuming and labor-intensive.

How do companies in the informatization stage carry out this process?

Task allocation in project management will replace paper documents and improve management efficiency. Project management allows you to submit project information online and view the basic status, production status and other data of each project in real time to improve management efficiency.

2. Process integration

Since the business process of an enterprise involves multiple links, informatization is difficult to achieve overnight and is often built step by step based on systems or modules. If different systems and modules cannot communicate with each other in terms of information exchange, they will become isolated islands, greatly reducing operating efficiency. Therefore, systems need to be connected. This is called process integration.

Taking the after-sales work order management scenario as an example, the lack of process integration will cause the following problems:

When traditional enterprises manage orders, the traditional processing method through offline or WeChat communication is inefficient and prone to problems such as missed orders and repeated processing, which seriously affects the quality of after-sales service and customer satisfaction.

The business process of an enterprise in the informatization stage is like this~

Customer service, factories, and express delivery parties can enter the system anytime and anywhere through the WeChat service account or scan the QR code to submit and process work orders, which is convenient and fast. When a work order is submitted, processed, or not processed by the deadline, the system will automatically notify the corresponding role through the WeChat service account to reduce the processing cycle and ensure that the problem is handled in a timely manner.

At the same time, the system supports data visualization analysis, which can conduct data analysis and mining on the entire after-sales service process, and automatically count customer service workload, after-sales problem distribution, after-sales problem number trends, processing time of all parties, and ranking of the number of express & factory after-sales problems. Provide data support for enterprises to help them identify problems and improve service quality.

3. Data visualization

The project is perceptible and adjustable. Enterprise business is visualized, data is traceable, and the entire project cycle can be monitored, managed, tracked, etc. This process requires the enterprise to contextualize the business and then digitize the scenario, and it also tests the enterprise's external compatibility and collaboration.

In the manufacturing industry, enterprise data is recorded on documents, and there is a lack of intuitive data analysis. It is difficult to analyze production data to assist management in making decisions.

Enterprises in the informatization stage can realize data analysis visualization.

For example, automatic data verification can be performed to improve product production accuracy. After the materials are received, the data is automatically updated.

The system can also integrate data and conduct horizontal comparative analysis of days, months, quarters, and years through dashboard chart components to determine business conditions.

4. Refined management

The iteration of management is from coarse to fine. In the manual offline management stage, due to the obvious efficiency bottlenecks and capability boundaries, the recording of business information cannot be refined, resulting in business decisions that cannot be refined. By using more advanced system tools, refined business decisions become possible.

There has always been a lack of refined management in traditional manufacturing. Take inventory management as an example:

In warehouse management, traditional manufacturing industries have long relied on manual statistics to manage warehouses, which is time-consuming and contains many errors and omissions, leading to chaotic warehouse management and seriously affecting the efficiency of the enterprise.

Enterprises in the informatization stage can achieve refined management and have accurate and clear inventory quantities.

For example: Enterprises can clearly understand the status, content and application details of each purchase application to facilitate later traceability. They can also achieve system-wide management of inbound and outbound, with accurate and clear inventory quantities.

5. Intelligent decision-making

Without digitalization, managers lack necessary data and information and can only rely on experience when making decisions. After the enterprise has accumulated a large amount of data through the previous stages of transformation and iteration, it can conduct more constructive experiences through the digital system. Entering the stage of intelligent decision-making.

For example, the multi-dimensional data analysis module provided by the engineering project management system makes data information a good helper for enterprise management decision-making through proportions, comparisons, trends, etc., and provides reliable support for the strategic and executive decisions of middle and high-level enterprises. No longer rely on human experience to determine the direction of business development.