All Foundries

商品管理と取引

データに基づくインサイトと、セキュアで機動性の高いプラットフォームにより、グローバルな商取引を支えるトレーディングエコシステムを変革します。

顧客とマーケティング戦略

パーソナライズされたつながりある体験を通じて顧客エンゲージメントを再構築し、信頼と長期的な価値を築きます。

デジタルエンジニアリング

アイデアをスケーラブルなデジタルソリューションへと転換し、デザイン・テクノロジー・エンジニアリングの力で加速させます。

ステーション・スタジオ

デジタルイノベーションでモビリティハブを再定義し、移動中の人々と企業に、よりスマートでサステナブルな体験を創出します。

サプライチェーン＆インダストリー5.0

変化を予測し、目的を持って効率性を実現する、強靭で知的な供給ネットワークを構築します。

サステナビリティ

責任あるイノベーションを推進し、組織がネットゼロ目標を達成し、将来の世代に良い影響をもたらすよう応援します。

Physical AI

Physical AI gives machines, robots and physical operations the ability to perceive their environment, decide what matters and act in real time. Factories, plants, stores and infrastructure become systems able to sense conditions, learn from them and improve on their own, closing the gap between the physical and the digital world.

Next-Gen Infrastructure

From networks as infrastructure to connected platforms that enable critical, autonomous and intelligent operations.

Four business units, one technology roadmap after the merger

After an acquisition, a retail group ran four business units on four technology stacks. NTT DATA mapped processes, applications, ERP, CRM and infrastructure across all of them and designed a low-risk transition roadmap. The group now works from a prioritized portfolio of initiatives, with synergies identified for each unit.

Four business units, one technology roadmap after the merger

小売

A pharmacy retailer grows average ticket by 8% and lab services sales by 18%

Pharmacy and health retailers compete on the visit itself: the counter, the advice, the lab test. This retailer measured its digital maturity with NTT DATA, organized more than 16 initiatives into cross-functional work cells and tracked each result. Average ticket rose 8% and lab and diagnostic services sales grew 18%.

A pharmacy retailer grows average ticket by 8% and lab services sales by 18%

お問い合わせ

Electricity Pool Price & Bid Optimization

Electricity market bidding depends on decisions made under volatility, time pressure and imperfect visibility. For an anonymized energy retailer utility, NTT DATA structured a repeatable analytical process that connects pool price forecasting, scenario analysis and bid preparation, giving trading and energy-management teams a more consistent basis for comparing alternatives before execution.

Energy trading team reviewing electricity market scenarios with grid infrastructure visible in the background.

Market data use

More consistent bidding inputs

Scenario comparison

Alternative bid positions compared

Exposure visibility

Forecast uncertainty made clearer

Optimization foundation

Repeatable process for automation

Utility decision-makers comparing electricity bid scenarios and market exposure in a control and trading environment.

Connecting pool-price forecasting with smarter electricity bidding

A more disciplined decision layer for wholesale electricity bidding, built around forecasts, scenarios and reusable assumptions.

When pool prices move quickly, bidding decisions need more than intuition. They need a repeatable way to read market signals, test assumptions and understand exposure before committing positions.

目的

The initiative aimed to establish a repeatable analytical process that combines electricity pool-price forecasting with scenario-based bid decision support. The objective was to help trading and energy-management teams use historical market, operational and explanatory data more consistently when preparing and reviewing bids.

機会

The documented approach creates a foundation that can be extended across wholesale electricity bidding and energy management workflows. Over time, the same analytical base may support broader optimization and automation of bidding processes, provided future capabilities and measured outcomes are validated in the client context.

Making bidding decisions more consistent in volatile markets

The case required more than a forecasting model. The capability needed to fit the utility operating context, connect the right information and provide outputs that business users could trust, compare and reuse.

主な課題

Energy analysts monitoring changing electricity market conditions near visible grid and substation infrastructure.

1: Volatile pool prices
Energy-market bidding decisions depended on changing pool prices and market conditions, creating a need for structured analysis before execution.

Electricity trading desk with separated planning materials and screens representing fragmented bid assumptions.

2: Disconnected assumptions
Forecasts, assumptions and bid scenarios risked being handled in separate tools, making it harder for teams to assess exposure and compare alternatives consistently.

Utility analytics team reviewing electricity demand, weather and grid signals for pool-price forecasting.

3: Complex modelling variables
The process needed to manage multiple explanatory variables, time horizons and aggregation levels without losing consistency between operational forecasting and business planning.

Energy management desk with bid planning materials used to compare and update electricity market scenarios.

4: Manual scenario effort
The initiative needed to reduce dependence on manual scenario preparation and make assumptions easier to reproduce, compare and update as new information became available.

解決策

A repeatable forecasting and scenario workflow for electricity bidding

NTT DATA combined data preparation, forecasting logic, scenario analysis and decision-support outputs into an end-to-end workflow designed for trading and energy-management use.

Prepared market and operational data

Historical market, operational and explanatory data were prepared and consolidated to support price modelling and consistent analytical use.

Built forecasting logic

Forecasting logic was developed for pool-price evolution and relevant bidding horizons, connecting market expectations to bid preparation.

Enabled scenario analysis

Scenario analysis allowed teams to compare alternative assumptions and bid positions, linking forecast outputs to business decision workflows.

Structured a reusable decision layer

Outputs were organized for use in trading and energy-management workflows, supporting ongoing model review and a repeatable foundation for future optimization.

影響

A stronger basis for electricity-market decisions

The case supports more consistent use of market data in bidding decisions, a clearer ability to compare price and bid scenarios before execution and better visibility of market exposure and forecast uncertainty. Because no validated project-specific quantitative improvement is published in the reviewed source, the impact should be presented as qualitative and scope-based rather than as measured performance uplift.

注目の成功事例

デジタル化されたサービス管理による現場業務の強化と、コネクテッドワーカー技術による安全性の向上

すべての成功事例を見る