All Foundries

Commodity Management & Trading

Transforming trading ecosystems through data-driven insights and secure, agile platforms that empower global commerce.

Customer & Marketing Strategy

Reimagining customer engagement with personalized, connected experiences that build trust and long-term value.

Digital Engineering

Turning ideas into scalable digital solutions—accelerating transformation through design, technology, and engineering excellence.

Station Studio

Redefining mobility hubs with digital innovation to create smarter, sustainable experiences for people and businesses on the move.

Supply Chain & Industry 5.0

Building resilient, intelligent supply networks that anticipate change and deliver efficiency with purpose.

Sustainability

Driving responsible innovation to help organizations achieve net-zero goals and create a positive impact for future generations.

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.

Retail

From satisfaction surveys to EBITDA: closing the loop on customer pain points

A department store retailer in Mexico turned a biannual NPS programme into a closed-loop customer listening mechanism, connecting feedback to pain-point initiatives and incremental EBITDA.

From satisfaction surveys to EBITDA: closing the loop on customer pain points

Retail

Unified returns management

A retailer processing more than two million returns a year moved from channel-specific workflows toward one digital returns system. The initiative connects request creation, status tracking and routing across sales and return channels.

Unified returns management

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Gas & Electricity Demand Forecasting & Scenario Simulation

For an anonymized energy retailer and utility, demand forecasting had become a strategic planning issue, not only a technical exercise. NTT DATA helped connect weather, calendar, portfolio and consumption signals into a repeatable forecasting workflow for gas and electricity, giving commercial and planning teams a clearer basis for purchasing, budgeting, scenario preparation and deviation management.

Energy utility infrastructure combining power transmission and gas operations, representing gas and electricity demand forecasting.

Gas deviation penalty savings

Approx. EUR 1M

Reduced by more than 4 points

Gas Forecast Error

Daily error below 2%

Electricity Error

Faster preparation and recovery

Scenario Readiness

Energy planning professionals working near visible power and gas infrastructure, suggesting more confident purchasing and budgeting decisions.

Forecasting energy demand with greater planning confidence

The initiative moved forecasting from fragmented model preparation toward a more repeatable business workflow. By bringing together gas and electricity demand signals, portfolio assumptions and scenario logic, the organization gained a stronger foundation for planning decisions in a volatile energy environment.

Demand volatility was making energy planning harder to manage with confidence. The organization needed to connect operational signals, forecasting models and business assumptions across gas and electricity, so commercial and planning teams could work from a more consistent view of future demand.

Objectives

Deliver more accurate and frequently refreshed gas and electricity demand forecasts, while giving business teams a simpler way to generate, recover and compare future scenarios across different time horizons and portfolio views.

Opportunity

The documented approach creates a foundation for extending forecasting discipline across gas and electricity retail portfolios. With better projections, the organization can strengthen budgeting efficiency, energy procurement decisions and demand planning, while keeping scenario assumptions easier to reproduce and update.

Turning demand volatility into planning confidence

Forecasting had to reflect the real operating context of an energy retailer, where demand is shaped by external conditions, portfolio dynamics, aggregation levels and distinct gas and electricity modelling needs.

Key Challenges

Utility field environment with electrical and gas assets under changing weather conditions, representing variable demand drivers.

1: Variable demand drivers
The initiative needed to account for weather, calendar effects, portfolio changes and different aggregation levels without oversimplifying the drivers of consumption.

Energy planning workspace with utility maps and portfolio materials, representing consistency across forecasting horizons.

2: Planning consistency
Business planning required models that could manage multiple explanatory variables and time horizons while staying connected to operational forecasting needs.

Energy planning table with scenario materials and portfolio assumptions, representing faster scenario preparation.

3: Manual scenario work
Commercial and planning teams needed to reduce dependence on manual scenario preparation, making assumptions easier to reproduce, compare and refresh.

Electricity distribution site with smart metering equipment and grid infrastructure, representing hourly electricity forecasting complexity.

4: Electricity complexity
Electricity forecasting required hourly models by access tariff and telemetered supply point, including observed and unobserved supplies.

Solution

An analytical forecasting workflow built for repeated business use

NTT DATA connected historical data, explanatory variables, forecasting models and scenario simulation into an operational workflow that could be refreshed as new information became available.

Driver-aware modelling

Quantified key demand drivers, including calendar and weather variables, so forecasts reflected the factors shaping gas and electricity consumption.

Multi-level gas forecasting

Built short- and medium-term gas-demand models at daily and monthly levels, across different aggregation levels.

Scenario simulation

Created an agile simulator using portfolio, unit-consumption and temperature assumptions, enabling teams to test and recover future scenarios.

Hourly electricity forecasting

Developed electricity-demand models by access tariff and telemetered supply point, incorporating observed and unobserved supplies.

Impact

More confident purchasing, planning and deviation management

The initiative helped lower exposure to energy-purchase deviation penalties, with approximately EUR 1 million in documented gas deviation penalty savings. The weighted daily gas forecast error was reduced by more than 4 points, and the electricity average daily forecast error was reduced to below 2%. Beyond model accuracy, the capability gave commercial and planning teams a faster, more repeatable basis for scenario preparation, budgeting and demand-related decision support.

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Empowering field operations through digitalized service management and improving safety conditions trough connected worker technologies

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