Event Report: Taking on the Challenge of Next-Generation Business Process Reengineering (BPR) Realized Through AI-Based Operations Design

Here we would like to present three specific case studies into AI-enabled BPR.

The first case study is into the automation of internal inquiry handling work using AI internally at ABeam Consulting. While a broad range of inquiry handling work exists at ABeam, we often found that similar inquiries have to be handled over and over manually, so the workload on the people responsible was persistently high.

On the part of the users making such inquiries, this also meant having to wait for responses each time via email or chat. In many cases their own work stalled while awaiting replies. As a first step towards a solution, AI Helpdesk was introduced to deal with the frequent work of responding to inquiries to the Accounting Department. As a result of this measure, progress was made on automating responses and, comparing the number of human responses to before the introduction of AI, this number was cut to 20% or less of the total. This realized operational streamlining for both employees responsible for handling inquiries and for users (see Figure 1).

The second case study was an attempt by a certain semiconductor manufacturer to improve productivity in its development operations overall. That demand for the addition of new features to software and the development of wholly new software will increase in future is considered to be a certainty. Amidst labor shortages, dealing with such conditions creates strong demand for improving the efficiency of development through the automation of operations and labor saving measures.

Development operations involve a variety of processes, including planning, design, development and testing. Of these, focusing on the design work that places the greatest burden on veteran employees from among these areas, as a result of promoting the use of AI, the company achieved 15% year-on-year labor savings.

The third case study is that of the trading department of a general trading company. The preparation work for commercial negotiations at this department progresses through a number of processes beginning with drafting reports when needed based on price movements or news about commercial materials through to drafting scenarios of how negotiations could go. As a result of making full use of AI to automate this series of tasks, the department cut up to 88% of its work volume.

Here, we would like to go into a little more detail on the use of AI Helpdesk in handling internal inquiries at ABeam Consulting, as was touched on in Case Study (1) in Section 3.

The work of handling internal inquiries is work that is required at many companies. A wide range of inquiries exist at such companies, from highly specialized ones to day-to-day checks and questions. With that said, it is a fact that there are many inquiries that are on a level that could be solved by checking documentation such as manuals or rules. The work burden on those responsible for dealing with these inquiries thus remained quite high.

While we provided resources such as online FAQs, searching such FAQs itself generated work for users. There were also examples where even if a user inquired with someone likely to be able to provide an answer, going back and forth over email meant that it could take days to get an answer.

The urgent challenge of combining both reductions in workload for people responsible for dealing with such inquiries and improved work efficiency for employees lay behind the development of AI Helpdesk.

One important feature of AI Helpdesk is that it supports both FAQs and documents such as manuals and instruction documents. For this reason, as long as AI Helpdesk has FAQs or other information, users can make inquiries 24 hours a day, 365 days a year, and get instant answers (see Figure 2).
Because processing inquiries can be completed using Microsoft Teams, which is used on a daily basis, the fact that this can be done without dividing the work up across multiple means of communication improves employee convenience.

In practice, as a result of introducing AI Helpdesk, some 80% of overall inquiries are currently resolved through automatic responses from AI Helpdesk. The system is thus producing suitable results, with only some 20% of inquiries now needing human responses.

We have also seen outcomes that we did not anticipate before implementing AI Helpdesk. The number of inquiries made has more than doubled year-on-year due to the ease of asking AI things on Teams compared to inquiring with a person, as before.

Analyzing the details of usage logs, however, we found that users previously did not inquire directly with responsible departments, but, rather, searched the documentation themselves or asked people near them. In other words, the latent need for automatic responses from the system itself already existed, and this doubling of inquiry numbers is not just down to the ease of inquiring with AI.

From the perspective of streamlining operations, AI Helpdesk has also been useful not only in reducing the time spent handling inquiries by responsible departments, but also in streamlining work on the user end. Comparing before and after introduction of AI Helpdesk, despite the number of inquiries itself more than doubling, the number of human responses is down to 39% of the figure from the previous year, a reduction of more than half. We can see this as the initiative having greater than anticipated benefits.

As another case study into AI-enabled BPR, we would like to take a look at the coordination between ServiceNow* and AI Helpdesk.

ABeam Consulting provides IT maintenance and operations outsourcing services that include inquiry and fault handling and feature upgrades for 280 companies globally. Taking the end of support for this platform as an opportunity, we upgraded to the platform provided by ServiceNow.

In doing so, by positioning AI Helpdesk as a touchpoint with users at the gateway to ServiceNow, we are able to promote self-solution of problems by end users and can expect improved usability. This produced the effect of limiting the number of inquiries handled by ServiceNow and helping to streamline operations and minimize total costs for the operations side as well.

By seamlessly linking ServiceNow and AI Helpdesk, we were also able to unify inquiry checking and the inquiry point of contact for users, thus enabling us to provide an easier-to-use system.

*ServiceNow: A platform that converts various operations at companies into digital workflows to automate and streamline them