Support for the rationalization of indirect operations through the use of AI Bookmark has been added
Support for the rationalization of indirect operations through the use of AI
Initiation and testing of AI use starting from PoC
With slowing corporate growth and long working hours identified as problems in recent years, responses to management issues such as the enhancement of services in the market and the securing of human resources in the face of population decline have led to attention being focused on AI. Improving the efficiency of operations by having AI support intellectual work allows management to allocate more resources to dealing with key issues that require increased attention.
- Cost issues of indirect operations (responding to inquiries as an example)
- Effects of AI-based improvement of operations
- Illustration of AI-based improvement of operations
- AI implementation starting from PoC
- Contact us
Cost issues of indirect operations (responding to inquiries as an example)
As a company’s operational processes become more diverse and complex, inquiries addressed to HQ departments (corporate functions such as helpdesks) tend to become both more numerous and more difficult to respond to. Even HQ departments that, unlike a helpdesk, are not explicitly tasked with handling them often receive various types of inquiries, which can be expected to lead to cost issues. Meanwhile, a situation in which the business departments making inquiries are always required to explicitly request that HQ department personnel respond to said inquiries may lower the productivity of the business departments’ core operations.
Effects of AI-based improvement of operations
Utilizing AI in the ever more complex operational processes of companies can be expected to improve efficiency and reduce costs. This applies not only to inquiry-related operations, but also to various other operations involving intellectual work.
Illustration of AI-based improvement of operations
The possibility of AI-based solution of issues is examined after first extracting the issues currently affecting operations. The illustration below describes a process of responding to inquiries, in which personnel at the department that receives inquiries respond to them and search for materials such manuals and regulations to prepare their responses. Once the issue that time is spent on such work has been identified, an AI that responds to inquiries or searches for materials related to the inquiry at hand is introduced, leading to a significant reduction in personnel workload and a realistic solution to the issue.
As with responding to inquiries, no matter what the operation in question, it is important to begin by properly identifying operational issues in order to clarify how AI can be of use.
AI implementation starting from PoC
Before implementing an AI into production, it is essential to first verify the effects of such implementation by conducting a proof of concept (PoC) demonstration. Beginning at the PoC stage, Deloitte Tohmatsu assembles a team of operational specialists and experts on AI and machine learning to construct an actual prototype AI and provide effective advice.