INTERNAL DASHBOARDS · 社内ダッシュボード

Japanese businesses producing monthly 取締役会 (board) performance reports by manually exporting data from kintone, freee, and spreadsheets into a formatted Excel report are spending 2-3 days per month on compilation that a connected dashboard delivers in minutes

Internal business intelligence dashboards for Japanese businesses — connected to kintone, freee, Yayoi, and your operational systems, with Japanese fiscal year configuration, Japanese-language labels, and Japanese numeral formatting built in from the start.

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This is for you if

Japanese retail and distribution businesses tracking daily sales by product category, channel (EC versus store), regional branch, and seasonal period need a dashboard aligned to the Japanese fiscal year (April to March) that surfaces performance against the annual plan in real time rather than at the end of the monthly reporting cycle. A dashboard connected to POS and inventory systems shows daily sales, stock turn, and category margin by channel without waiting for the end-of-month data extract. Seasonal period segmentation — including Golden Week, Obon, and year-end trading periods — can be built into the date table so that year-on-year comparisons account for the timing shift of key trading periods.

Japanese manufacturing businesses tracking production line output, defect rates, OEE (設備総合効率), inventory turns, and delivery lead time need operations dashboards connected to their production management and ERP systems. Current reporting in many Japanese manufacturing businesses requires a dedicated analyst to extract data from multiple systems, reconcile figures across shifts and lines, and produce a daily or weekly operations report in a formatted Excel template. A connected operations dashboard surfaces production KPIs in real time, allows shift supervisors and factory managers to see current output against target without waiting for the end-of-day report, and surfaces quality and lead time trends for management review.

Japanese professional services firms — consulting, accounting, and legal practices — tracking billable hours by staff member, client revenue, project margin, and accounts receivable ageing need a management dashboard connected to their practice management system and accounting platform. A dashboard that joins staff utilisation data from the practice management system with revenue and receivables data from freee or the accounting ERP gives partners and directors a complete view of commercial performance without a monthly manual build. Accounts receivable ageing by client and consultant revenue contribution by practice area are visible in real time, surfacing collection issues and revenue concentration risks before the month-end review.

Japanese e-commerce businesses selling across Rakuten Ichiba, Amazon Japan, and Yahoo Shopping need a unified channel dashboard that shows blended GMV, return rate, platform fee comparison, and product-level performance across all three platforms in a single view. Currently, most Japanese multi-channel e-commerce sellers manage three separate seller portals with three separate analytics dashboards, making it impossible to see total business performance without manually combining figures from each platform. A connected dashboard built on API connections to each platform's reporting data provides a unified view of channel contribution, margin by platform after fees, and product-level performance ranked across all three channels simultaneously.

What's broken

Japanese FY (April-March) Not Configured in Dashboard Tools

Japanese businesses using Power BI or Looker Studio are operating dashboards with a January calendar year default, meaning year-to-date and year-on-year comparisons are misaligned with the April-to-March Japanese fiscal year. A Japanese business reviewing performance in February is in month eleven of the fiscal year, but a calendar-year dashboard shows it as month two. All trend analysis requires manual recalculation to align with the fiscal year, and budget versus actuals comparisons are impossible to read directly from the dashboard without adjustment. This is not a minor formatting issue — it makes every period comparison in the dashboard unreliable for a Japanese management audience.

Kanji and Japanese Numeral Formatting Not Set in Dashboard

Japanese dashboards displaying metric labels and category names in English or romanised Japanese are unsuitable for presentation to senior Japanese management. The expectation for 取締役会 reporting and formal management dashboards is Japanese-language labels, Japanese date formatting (using either the 令和 era system or standard Japanese date format with 年月日), and Japanese large number formatting using 万 (10,000) and 億 (100,000,000) notation rather than Western comma-separated thousands. A dashboard displaying ¥125,000,000 instead of 1億2500万円 is formatted incorrectly for a Japanese board audience, regardless of the accuracy of the underlying data. Configuring Japanese number formatting in Power BI requires custom DAX measures and format strings that are not available in the default localisation settings.

kintone Data Not Connected to the Dashboard

Japanese mid-size businesses with core operational data in kintone are unable to connect kintone directly to Power BI or Tableau using a native certified connector. kintone's API provides access to app data via REST API calls, but building a reliable, scheduled connection to Power BI requires a custom API connector built in Power Query M code or a middleware integration layer. Without this connector, data is extracted manually from kintone each week — downloaded as CSV, pasted into a staging spreadsheet, and then refreshed into the dashboard. This manual extraction step introduces errors, creates a reporting lag, and means the dashboard is only as current as the last manual export, typically days or weeks old at the time of any management review.

No Cross-Channel E-Commerce Dashboard for Rakuten, Amazon Japan, and Yahoo Shopping

Japanese e-commerce sellers managing three separate platforms — Rakuten Ichiba, Amazon Japan, and Yahoo Shopping — are operating without a unified view of channel performance. Each platform provides its own seller analytics dashboard, but none of them shows how the three channels compare against each other, what the blended GMV and net margin look like after platform fees, or which products are performing across all three channels simultaneously. Sellers are manually downloading reports from each platform and combining them in Excel to produce a monthly channel comparison — a process that takes several hours per month and produces a static snapshot rather than a live view. Without a unified dashboard, decisions about platform fee negotiation, product listing prioritisation, and promotional budget allocation are made without access to cross-channel data.

What we engineer

Connect to operational and accounting systems already in use

Ignited Nepal builds internal dashboards for Japanese businesses that connect to the operational and accounting systems already in use — kintone, freee, Yayoi, SAP, and Oracle — without requiring a system migration or a data warehouse implementation before the first report is live. Every dashboard built for a Japanese business is configured with the April-to-March Japanese fiscal year, Japanese-language labels, Japanese date formatting, and 万 / 億 number notation from the start of the build.

Build the kintone data connection layer

The data connection layer for kintone is built using Power Query M code that calls the kintone REST API on a scheduled refresh cycle, pulling app data into the Power BI data model without manual CSV exports. The connector is built to handle kintone's field naming conventions and record structure, transforming raw API responses into a clean, queryable table that joins to accounting and CRM data in the same model. For freee and Yayoi, the connection method depends on the platform version and API availability; where a direct API connection is not available, a scheduled data export and automated file pickup process is configured to minimise manual intervention.

Apply Japanese fiscal year configuration at the date table level

Japanese fiscal year configuration is applied at the date table level in the Power BI data model. A custom date table defines 第1四半期 (Q1) through 第4四半期 (Q4) aligned to the April-March fiscal year, with fiscal month numbers, fiscal year labels in Japanese format, and a 令和 era date column for reporting contexts that use the Japanese imperial calendar. Every YTD, prior year, and budget versus actuals measure in the dashboard references the Japanese fiscal year date table, not the calendar year.

Design the report for formal management reporting

The report design for Japanese businesses follows the structured, label-precise formatting expected for formal management reporting. Metric labels are in Japanese. Chart titles and axis labels use Japanese terminology. KPI scorecards use 万 and 億 notation for financial figures. Date references use the Japanese date format. For clients producing 取締役会 reports, the dashboard is designed to match the layout conventions of the company's existing board pack template, so the automated export replaces the manual document rather than requiring management to learn a new format.

Build the unified multi-channel e-commerce dashboard

For multi-channel e-commerce businesses on Rakuten, Amazon Japan, and Yahoo Shopping, the unified dashboard connects to each platform's reporting API or data export and builds a single model showing blended GMV, platform fee rate by channel, net margin after fees, return rate, and product-level performance ranked across all three channels. The channel comparison matrix allows e-commerce managers to see which platform is contributing the most net margin — not just the most gross revenue — and which products are underperforming on specific platforms.

Configure role-appropriate views for each audience

Role-appropriate views are configured for each audience: 取締役会 summary view for board reporting, 部長 (department head) view for operational detail by department or product line, and 担当者 (operational staff) view for day-to-day task-level data. Row-level security ensures each user sees only the data appropriate to their role.

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What changes

Before
After
Before Japanese businesses using Power BI or Looker Studio are operating dashboards with a January calendar year default, meaning year-to-date and year-on-year comparisons are misaligned with the April-to-March Japanese fiscal year. A Japanese business reviewing performance in February is in month eleven of the fiscal year, but a calendar-year dashboard shows it as month two. All trend analysis requires manual recalculation to align with the fiscal year, and budget versus actuals comparisons are impossible to read directly from the dashboard without adjustment. This is not a minor formatting issue — it makes every period comparison in the dashboard unreliable for a Japanese management audience.
After Monthly 取締役会 report compilation is replaced by an automated dashboard export. The two-to-three day manual compilation process is replaced by a scheduled Power BI export that arrives in the right format, with correct Japanese labels and number notation, on the scheduled report date.
Before Japanese dashboards displaying metric labels and category names in English or romanised Japanese are unsuitable for presentation to senior Japanese management. The expectation for 取締役会 reporting and formal management dashboards is Japanese-language labels, Japanese date formatting (using either the 令和 era system or standard Japanese date format with 年月日), and Japanese large number formatting using 万 (10,000) and 億 (100,000,000) notation rather than Western comma-separated thousands. A dashboard displaying ¥125,000,000 instead of 1億2500万円 is formatted incorrectly for a Japanese board audience, regardless of the accuracy of the underlying data. Configuring Japanese number formatting in Power BI requires custom DAX measures and format strings that are not available in the default localisation settings.
After Japanese fiscal year comparisons are accurate in every chart and table without manual recalculation. YTD, prior year, and budget versus actuals figures align to the April-March fiscal year across the entire dashboard; management stops correcting calendar-year figures before presenting to the board.
Before Japanese mid-size businesses with core operational data in kintone are unable to connect kintone directly to Power BI or Tableau using a native certified connector. kintone's API provides access to app data via REST API calls, but building a reliable, scheduled connection to Power BI requires a custom API connector built in Power Query M code or a middleware integration layer. Without this connector, data is extracted manually from kintone each week — downloaded as CSV, pasted into a staging spreadsheet, and then refreshed into the dashboard. This manual extraction step introduces errors, creates a reporting lag, and means the dashboard is only as current as the last manual export, typically days or weeks old at the time of any management review.
After kintone data is live in the dashboard without manual CSV exports. The weekly data extraction task is replaced by a scheduled API refresh; operations data is current to the last refresh cycle rather than days old at the time of any management review.
Before Japanese e-commerce sellers managing three separate platforms — Rakuten Ichiba, Amazon Japan, and Yahoo Shopping — are operating without a unified view of channel performance. Each platform provides its own seller analytics dashboard, but none of them shows how the three channels compare against each other, what the blended GMV and net margin look like after platform fees, or which products are performing across all three channels simultaneously. Sellers are manually downloading reports from each platform and combining them in Excel to produce a monthly channel comparison — a process that takes several hours per month and produces a static snapshot rather than a live view. Without a unified dashboard, decisions about platform fee negotiation, product listing prioritisation, and promotional budget allocation are made without access to cross-channel data.
After Cross-channel e-commerce performance is visible in a single dashboard for the first time. Rakuten, Amazon Japan, and Yahoo Shopping GMV, fee comparison, and product-level performance are combined in one view; channel allocation and promotional investment decisions are based on blended margin data rather than platform-level gross revenue.
How it works

  1. 01

    Discovery and data audit.

    We document every data source — kintone apps, accounting platform, e-commerce platforms, CRM — and map what data is available, how it is structured, and what the priority business questions are. We confirm the Japanese fiscal year start date, reporting language requirements, and board report format conventions at this stage.

  2. 02

    Data model design.

    We design the Power BI data model: source tables, relationships, calculated measures, the Japanese FY date table, and dimensional structure. Japanese number formatting conventions and label language are agreed before build begins. The model design is reviewed and approved by the client.

  3. 03

    Data connections and API integration.

    We build the kintone REST API connector, freee or Yayoi connection, and any e-commerce platform API integrations. All connections are tested on the scheduled refresh cycle to confirm data currency and completeness before the dashboard build begins.

  4. 04

    Dashboard build and Japanese localisation.

    We build all report pages with Japanese-language labels, 万 / 億 number formatting, Japanese date columns, and the structural layout appropriate for the intended audience — 取締役会 summary, 部長 operational view, and 担当者 task-level view. Row-level security is configured for each role.

  5. 05

    Automated reporting and export configuration.

    Scheduled Power BI subscription emails and PDF exports are configured for the board report and weekly management summary. Export format and distribution list are agreed with the client and tested before handover.

  6. 06

    Handover, documentation, and training.

    We deliver model documentation in both Japanese and English, a user guide for each audience group, and a training session for Power BI report owners. A 30-day hypercare period covers any data connection or formatting issues identified during the first month of live use.

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Common questions

Frequently asked questions about Internal Dashboards

How do I configure the Japanese fiscal year (April to March) in Power BI or Looker Studio for a Japanese business?

In Power BI, Japanese fiscal year configuration requires a custom date table built in DAX or Power Query that defines the fiscal year as running from 1 April to 31 March, with fiscal quarter and fiscal month columns using Japanese labels (第1四半期 through 第4四半期, and 4月 through 3月). The date table must also include a fiscal year label in Japanese format and optionally a 令和 era column for contexts where the imperial calendar is used in reporting. All time intelligence measures — YTD, PYTD, and budget versus actuals — must reference the custom fiscal year columns rather than the built-in calendar year functions. In Looker Studio, fiscal year offset is available as a setting for Google-native connectors, but for kintone or freee connections, the fiscal period logic must be built into the data source query or calculated field.

How do I display Japanese-language labels, date formats, and number formats in a Power BI dashboard?

Japanese-language labels in Power BI are set at the individual visual level — column rename, measure name, and axis title configuration — rather than at a global localisation setting. Japanese date formats (例: 2025年4月1日) are applied using custom format strings in DAX measure definitions or column formatting settings. 万 and 億 number notation requires a custom DAX format string or a calculated measure that divides the base value and appends the 万 or 億 suffix as a text string; this approach requires careful handling to preserve sort order and chart behaviour. Eastern Arabic numerals (٠١٢٣٤ style) are not natively supported in Power BI and require a custom visual or font configuration for contexts where they are needed. The localisation configuration must be applied to every visual individually for a consistent result across the report.

How do I connect kintone to Power BI or Tableau for a Japanese business dashboard?

kintone connects to Power BI via a custom Power Query connector built using the kintone REST API, which provides access to app records via authenticated GET requests to the kintone API endpoint. The connector is built in Power Query M code, using the kintone API key or user authentication credentials to retrieve records from each kintone app used as a data source. Pagination handling is required for kintone apps with more than 500 records, as the API returns results in pages. For Tableau, kintone data can be connected via a Web Data Connector or through an intermediate data layer. The connection requires a Power BI on-premises data gateway if Power BI Service refresh is used from a cloud environment. Scheduled refresh is typically set to daily or twice-daily to keep operational data current without excessive API call volume.

How do I build a unified Rakuten, Amazon Japan, and Yahoo Shopping e-commerce dashboard?

A unified e-commerce dashboard for Rakuten Ichiba, Amazon Japan, and Yahoo Shopping requires connecting to the reporting API or automated data export for each platform. Amazon Japan provides Selling Partner API access for order, inventory, and financial data. Rakuten Merchant Logistics and the RMS (Rakuten Merchant Server) API provide sales and order data. Yahoo Shopping provides a store management API with order and sales data access. Each platform's data is pulled into the Power BI model as a separate query, transformed to a common schema, and combined using a unified channel model that includes a platform dimension (Rakuten, Amazon, Yahoo) and a shared product identifier. Net margin calculation requires a platform fee rate table that maps fee structures by product category and platform, applied as a calculated measure in the data model.

What dashboard tool is most appropriate for a Japanese mid-size business — kintone dashboards, Power BI, or Tableau?

Power BI is the most practical choice for most Japanese mid-size businesses that are already operating on Microsoft 365, because the licensing cost is lower than Tableau and the connector ecosystem for Japanese business platforms — including kintone via custom API connector and freee via API — is well established. kintone's native dashboard functionality (グラフ機能) is useful for operational visibility within a single kintone app but does not support cross-app or cross-system analysis, making it insufficient as a standalone business intelligence tool for management reporting. Tableau is used by Japanese multinationals and larger enterprises with dedicated data analyst teams and complex analytical requirements; for a mid-size Japanese business producing 取締役会 reports and operational summaries, Power BI delivers the required functionality at a lower total cost. For businesses whose primary reporting need is Japanese-language board pack production, Power BI with a custom Japanese-localised template is the most efficient path.

Our team

The people behind the work

Not a black box. Real specialists you can call, with their names on the work.

Niraj Raut

Niraj Raut

Founder — Ecommerce SEO
Keshab Joshi

Keshab Joshi

PPC Expert
Hawrry Bhattarai

Hawrry Bhattarai

Google Ads Expert
Arogya Rijal

Arogya Rijal

SaaS SEO Expert
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Japanese businesses spending two to three days per month on manual board report compilation are not facing a reporting problem — they are facing a data infrastructure gap. A connected Power BI dashboard with Japanese fiscal year configuration, Japanese-language labels, and automated distribution replaces the manual cycle permanently, without requiring a system migration or a new data warehouse. Ignited Nepal builds these dashboards for Japanese businesses, from kintone API connection through to 取締役会-ready automated exports. The first step is a Dashboard Diagnostic, where we map your data sources, agree the Japanese fiscal year and formatting requirements, and design the data model that makes the dashboard reliable for formal management reporting from day one.

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