Items stated in the management plan
Partially revisedEach line is the climb from the baseline the document states to the target it sets. The slope is scaled against the largest climb in this document. The increase shown by the dotted line is calculated from the two reported figures because the company did not provide the amount of growth.
There were clear areas for reflection regarding the allocation of management resources, customer targets and sales methods for the fiscal year ended September 2026. While the rollout of generative AI fundamentals training among large enterprises had run its course, advanced AI applications, AI agents and the transformation of business processes themselves did not spread across the market as quickly as expected. The main factors behind the failure to meet the plan were the sluggish acquisition of instructor-dispatch projects from large enterprises, slower growth in DX services and training by employee level, and slower acquisition and use of the Smart Pack for Human Capital Development.
| Item | Details |
|---|---|
| Plan name | Management policies for the fiscal year ending September 2027 |
| Plan period | Fiscal year ending September 2027 |
| Progress against the plan | Partially revised |
| Sales Target | ¥16 billion (initial earnings forecast for the fiscal year ended September 2026) → ¥15.6 billion (revised earnings forecast for the fiscal year ended September 2026) |
| Operating profit target | ¥6.38 billion (initial earnings forecast for the fiscal year ended September 2026) → ¥6.15 billion (revised earnings forecast for the fiscal year ended September 2026) |
| Plan assumptions | The company believes that AI will significantly change the way society and companies work over the next 10 years. |
| Key initiatives | Review the excessive allocation of sales resources to large enterprises, Growth strategy by market, Break through the large-enterprise market through development capabilities rather than sales capabilities — transition to a model selected for its development capabilities, Make MM and GB the centre of growth again — prioritize a model in which each customer uses multiple products, Place the Smart Pack for Human Capital Development at the centre of the MM and GB strategy, From a company that sells instructor-led training to a company that sells the right education, Do not scale back the AI strategy. Expand from “cutting-edge AI” to “AI that can be used in practice.”, AI BOAT will create a new market for “in-house corporate education.”, Increase per-employee productivity, From one-off revenue to subscriptions and multi-year contracts, Optimize the organization — scale back or withdraw from low-profit businesses and reallocate resources, Refine evaluation and compensation, and management, with a focus on operating profit growth |
| Results under the previous plan | Revenue of ¥16 billion and operating profit of ¥6.38 billion (initial earnings forecast) → Revenue of ¥15.6 billion and operating profit of ¥6.15 billion (revised earnings forecast; no actual results stated) |
| Reason for revision or withdrawal | There were clear areas for reflection regarding the allocation of management resources, customer targets and sales methods for the fiscal year ended September 2026. While the rollout of generative AI fundamentals training among large enterprises had run its course, advanced AI applications, AI agents and the transformation of business processes themselves did not spread across the market as quickly as expected. The main factors behind the failure to meet the plan were the sluggish acquisition of instructor-dispatch projects from large enterprises, slower growth in DX services and training by employee level, and slower acquisition and use of the Smart Pack for Human Capital Development. |
| Publication date | 1 October 2026 |
Items this document does not state (15)
These are items the company does not state in this document. We do not leave them blank, nor fill them in from other sources or by inference.
The reasons the company gives
The company's own explanation, not something inferred from the numbers.For the fiscal year ended September 2026, the company cited the completion of the initial rollout of generative AI fundamentals training among large enterprises, the slower-than-expected adoption of advanced AI applications and other technologies, the slowdown in instructor-dispatch projects for large enterprises, DX services, training by employee level and the Smart Pack for Human Capital Development, and its inability to achieve profit growth commensurate with the increase in sales personnel.