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.

Omnichannel click and collect

For a retailer, online growth helps physical stores only when digital orders bring shoppers through the door. Working with NTT DATA, a retailer launched a global omnichannel model with click-and-collect, iPad-based ordering and interactive screens. Today 80% of online orders are collected in store, and 60% of pickup customers buy more while there.

Omnichannel click and collect

Omnichannel loyalty in Japan: stores, app and points in one place

For a lifestyle retailer, loyalty grows when every visit, click and purchase connects to the same customer. Working with NTT DATA, a Japanese lifestyle retailer brought loyalty and commerce together in one application, connecting stores, mobile and customer data to grow sales through personalized experiences.

Omnichannel loyalty in Japan: stores, app and points in one place

お問い合わせ

Every purchase order checked against demand before it reaches the supplier

For a retail and distribution company, every purchase order shapes what reaches the shelf, what sits in the warehouse and what ends up as waste. Working with NTT DATA, the company brought procurement, demand forecasting and replenishment together in a centralised Global Purchase Order (GPO) engine, combining optimised logistics parameters, DRP projections and automated supplier orders so buying teams could move from reactive, manual ordering to a model-driven process.

利用可能性

Reduced Waste, Higher Availability. The right stock in the right place, with less overstock and fewer gaps on the shelf.

決定

Model-Driven Logistics. Replenishment decisions based on optimised logistics parameters and DRP projections.

効率性

Streamlined Stock and Replenishment. Automated purchasing that reduces manual effort across the ordering cycle.

制御

Data-Driven Adjustments. Orders reviewed and optimised before they are released to suppliers

Procurement intelligence that turns demand signals into the right orders

The company needed a more reliable way to decide what to buy, when and how much, moving away from fragmented, manual ordering where forecasts, safety stock and order rules lived in different places and purchase orders reached suppliers without a common optimisation logic.

目的

The initiative set out to optimise procurement operations and the flow of information behind them, while improving the accuracy of demand forecasts and purchase orders. The ambition was not only to automate buying, but to give the business a single, consistent replenishment logic that balances product availability, stock levels and waste.

機会

With logistics parameters and forecasting centralised in one engine, the company can replace fragmented, manual ordering with a repeatable, data-driven process. A shared model for safety stock, order logic and DRP projections gives buying teams a solid foundation to keep refining replenishment as demand patterns change.

Bringing a single ordering logic to a fragmented purchasing process

The company faced the practical challenge of turning disconnected forecasts, parameters and manual decisions into one coherent purchasing flow, without losing the flexibility buyers need to react to real-world conditions.

主な課題

Supply planning team reviewing demand forecasts while warehouse inventory shows excess stock in some products and low availability in others.

1: Demand forecasting accuracy. Forecasts did not reflect real demand closely enough, leading to purchase orders that could create overstock in some products and shortages in others.

Supply planners using different safety-stock and replenishment rules across locations without a common centralized approach to ordering.

2: Decentralised safety stock and order logic. Safety stock levels and ordering rules were not managed centrally, so replenishment decisions varied and were hard to align across the business.

Procurement team preparing supplier purchase orders without a structured optimisation step to review quantities, timing and inventory impact.

3: Orders released without optimisation. Purchase orders reached suppliers without a systematic review, limiting control over quantities, timing and their impact on stock.

Supply-chain team manually reconciling separate procurement, inventory and demand information because no integrated view supports ordering decisions.

4: Fragmented procurement information. Procurement, stock and demand information sat in separate processes, making manual ordering the default and slowing down decisions.

解決策

A centralised purchase order engine built around forecasting, DRP and control

NTT DATA designed a centralised Global Purchase Order system with optimised logistics parameters and implemented automated purchasing, forecasting and DRP capabilities, giving buyers one environment to plan, adjust and release supplier orders.

Assessed current procurement, stock and demand processes

Mapped how purchasing, stock management and demand planning worked in practice, identifying where manual steps and fragmented information were limiting order accuracy.

Designed centralised parameters and order logic

Defined common logistics parameters, safety stock levels and ordering rules, so every replenishment decision follows the same consistent logic.

Implemented forecasting, DRP projections and supplier orders

Deployed demand forecasting and Distribution Requirements Planning (DRP) projections that feed the automated generation of purchase orders for suppliers.

Enabled manual adjustments and optimisation before release

Gave buyers the ability to review, adjust and optimise orders before they are sent, keeping human judgement in the loop while protecting the model’s logic.

影響

Replenishment under control, driven by data rather than instinct

The Global Purchase Order engine turns purchasing into a model-driven process. By connecting demand forecasts, centralised logistics parameters and DRP projections with a controlled release of supplier orders, the company has reduced waste and improved product availability, while gaining higher efficiency in stock and replenishment management. Buyers now base their decisions on optimised models and data-driven adjustments, creating a more reliable and transparent foundation for day-to-day procurement.

ドラッグ