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Microsoft Commercial and Professional Services Japan

ITOCHU Corporation

Data Lake / Data Warehouse Modernization · Real-time Analytics · Sales Automation

"Half of product planning is data collection and analysis. This is the area in which FOODATA excels: our customers rate it highly and we want to make it even better," explains Tsukada. "The remaining half involves generating ideas.

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"ITOCHU's Food Company services about 10,000 manufacturers and around 3,000 retailers and restaurants," says Kento Tsukada, ITOCHU Food Company Product Manager.
"In May 2023, ITOCHU established a generative AI lab with the aim of the entire company using generative AI in a secure environment and a task force to solicit ideas for use from younger workers," says the ITOCHU ICT Div...
"The launch of ChatGPT in November 2022 was a stunning emergence of AI with the potential for many novel uses. Microsoft was quick to strike a capital alliance with the owner of ChatGPT, OpenAI
A task force launched in May 2023 to explore the potential of company-wide use of generative AI to achieve the vision.

Reported impact

Business outcome

In May 2023, ITOCHU Corporation ("ITOCHU") launched a cross-company task force to promote the use of generative AI across all businesses.

  • Compliance
  • Productivity Improvement
  • Revenue Growth
  • Speed to Market

Solution

"Half of product planning is data collection and analysis. This is the area in which FOODATA excels: our customers rate it highly and we want to make it even better," explains Tsukada. "The remaining half involves generating ideas. In May 2023, ITOCHU Corporation ("ITOCHU") launched a cross-company task force to promote the use of generative AI across all businesses. This included incorporating generative AI into FOODATA, a data analytics dashboard which the ITOCHU Food Company provides to customers. Creating a platform to analyze a massive range of disparate data and provide ideas A rapidly growing number of companies are adopting Azure OpenAI Service to streamline operations, achieve higher productivity, and solve labor shortages by leveraging generative AI internally. Further, endeavors to deliver the value created by generative AI to customers and drive new business value are flourishing. A notable example is ITOCHU's use of generative AI in FOODATA.

Data flow

Operational and business data is gathered from the customer's source systems processed in Microsoft Fabric.

Solution architecture

3 components · 3 layers
  1. Compute
    • Azure OpenAI Service Runs the large-language-model features for classification, summarization, retrieval, or conversational responses in the solution.
  2. Storage
    • Microsoft Fabric Provides the shared data platform for storing, governing, and analyzing enterprise data across teams.
  3. Orchestration
    • Azure AI Studio Provides the environment for building, testing, and orchestrating the customer's generative AI workflows.

Architecture clues

  • A rapidly growing number of companies are adopting Azure OpenAI Service to streamline operations, achieve higher productivity
  • Azure AI Studio: Provides the environment for building, testing, and orchestrating the customer's generative AI workflows.
  • Azure OpenAI Service: Runs the large-language-model features for classification, summarization, retrieval, or conversational responses in the solution.
  • Creating a platform to analyze a massive range of disparate data and provide ideas
  • In May 2023, ITOCHU Corporation ("ITOCHU") launched a cross-company task force to promote the use of generative AI across all businesses.
  • Microsoft Fabric: Provides the shared data platform for storing, governing, and analyzing enterprise data across teams.

Evidence from the source

"Half of product planning is data collection and analysis. This is the area in which FOODATA excels: our customers rate it highly and we want to make it even better," explains Tsukada.
"ITOCHU's Food Company services about 10,000 manufacturers and around 3,000 retailers and restaurants," says Kento Tsukada, ITOCHU Food Company Product Manager.
Creating a platform to analyze a massive range of disparate data and provide ideas
In May 2023, ITOCHU Corporation ("ITOCHU") launched a cross-company task force to promote the use of generative AI across all businesses.
Transparency Evidence & methodology 81/100 reference value · 89% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value81/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Microsoft

    ITOCHU Corporation customer story

    First-party
    https://www.microsoft.com/en/customers/story/1784680492304822753-itouch-corporation-microsoft-fabric-professional-services-en-japan
    Source type
    Vendor-published customer story
    Published
    Jul 26, 2024
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Jul 26, 2024 · Microsoft · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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