Digital transformation of electric power companies

On November 7, 2018, TEPCO Power Grid and NTT DATA established Grid Data Bank Lab (GDBL), a limited liability partnership. Inspired by this movement, Kansai Electric Power and Chubu Electric Power also realized participation in March 2019, and the union is currently operated by a joint investment of these four companies.

GDBL seems to be trying to find business opportunities mainly in the disaster prevention plan of the local government, the store opening plan of the retail-sale business, and the acquisition of the family information of the consumer, using customer data centered on smart meters. The electricity industry, where electricity rate is essentially the only source of income, expects future growth. It’s true that big data in smart meters has potential, but there are also challenges that must be overcome to achieve results. I would like to think about this point today.

Building a business plan

Until now, the power industry hasn’t worked hard on IT. For this reason, managers are not good at IT, and tend to outsource their work (the fact that GDBL has been launched externally). When setting up a new business that uses in-house data, what is important is not the knowledge of technology, but the ability to fully understand the overall picture and individuality of the in-house data and to make a new imagination on its use value. When using smart meters, it is essential to have comprehensive knowledge of local power demand, such as the composition of households by region, the trend of home appliance sales, and the impact on the power demand of smartphones and solar power. However, in large corporations, employees have specialized in the field of vertical organization, so the number of people who can build a business grand design is quite limited.

Relaxing security policy

Information departments in the power industry tend to refuse to provide big data for processing under the premise of ensuring security. They avoid outsourcing of database management, and have their own servers owned by affiliates without relying on the cloud. This point is closely related to the management of affiliated companies and, in turn, to the places where electric power employees change jobs. In short, security and employment of information department employees are inextricably linked, and as a result, there is a problem that data analysis / use is not progressing. Even if AI is trying to learn data, it doesn’t (consciously) provide the essential data. In the case of GDBL, this tendency is spurred by joint investment with competitors.

Excessive compliance awareness

The 2013 JR East SUICA personal information provision problem, for better or worse, raised the awareness of personal information. Since the data handled by JR East cannot be identified, it falls under “anonymized information”, not legal “personal information”. Therefore, it can be said that the act was legally acceptable. Regarding the Personal Information Protection Law, whether to proceed in the direction of strengthening personal protection, or in the direction of expanding industrial and daily use, there is no excuse, but excessive compliance awareness will be an obstacle to data use. Legal compliance is good, but as far as big data is concerned, it should not be over-recognized and shrunk before taking action. The electric power industry tends to create internal rules and impose more information protection on its own than the law requires, but this practice should be avoided.

Unfortunately, GDBL has not achieved results. The IT industry has already pointed out the reasons mentioned here. The electric power industry doesn’t seem to have a good reputation at the moment. I hope that these issues will be overcome and results will be gradually improved.