Level of Digital Transformation

   When running DT or Smart Factory, many executives and managers want to know where their current level is. And they wonder to what extent they can jump up through DT in the future. Furthermore, they are also curious about the position of peers, competitors, and leaders. They don't necessarily want to be number one, but they want to know where they are now and what level they should be aiming for in the future.

   Usually, many people express their current level as AS-IS. And what they want to be in the future is called TO-BE. There must be a gap between AS-IS and TO-BE. The gap is expressed as GAP. Activities to reduce the GAP are called DT tasks or improvement tasks.

   Where are we really? In the figure below, the level is divided into four major levels.

   The first is the 'Factory Automation' step, where data is created/collected. This is the stage where data is created and collected through the physical automation of the factory. In case of an abnormality, it is notified immediately and the facility or device is adjusted remotely to significantly reduce human labor and increase productivity.

 

Level of Digital Transformation in Manufacturing Area

   The second stage is the 'smart factory' stage, where data is analyzed and used for decision-making. For example, this is the stage in which facility data is analyzed to predict abnormalities in advance, and through preemptive measures, facility availability is improved, production is increased, costs are reduced, and work hours are shortened. It is mainly applicable to the manufacturing value chain area.

   The third is the 'value chain integration/optimization' stage, which is the data integration stage. Until stage 2, it was limited to manufacturing, but from stage 3, it expands to integration with other value chains within the company as well as integration and optimization with third parties that make up the ecosystem outside the company. If internal and external value chains and data are integrated, business visibility and business processing speed are incomparably improved. In addition, data-based predictive management becomes possible. If everything is connected, it is possible to know right up to the point of delivery when a customer orders, and various predictive management such as demand forecasting and delivery forecasting are possible.

 

The Simulation of Nvidia Self-Driving Vehicles

   The last stage is the 'New Biz' stage, where data-based new businesses are made. This is the stage of creating new products or services based on accumulated data. If these data-based new businesses are successfully implemented, continuous growth can be possible centering on high added value. GE's data analysis-based engine predictive maintenance, Siemens' 'Amberg Factory', a factory that makes factories, and PLM or IIoT business are good examples.

   What is the level of our company? It is true that the level is not easy and difficult to quantify because the characteristics of each industry, organization, and individual are different. I would like to use it in terms of setting goals to move forward rather than level accuracy.

 

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