Shifting Production Abroad: Figures and Countermeasures 2026

Why Companies Are Shifting Production Abroad According to the DIHK Barometer 2026

High energy costs and declining competitiveness are driving around 20 percent of all surveyed companies to shift investments abroad or to specifically evaluate such a move, according to the 15th DIHK Energy Transition Barometer. The survey, which polled around 3,100 companies from industry, retail, services, and construction in June 2026, reveals a significant drop in sentiment: The nationwide barometer value fell to minus 11.5 points, down from minus 8.3 in the previous year.

A detailed analysis of the DIHK data reveals a wide divergence across sectors. While one-fifth of companies in the overall economy are evaluating or implementing relocations, this share rises to around 40 percent in the industrial sector. Among large industrial companies, 60 percent are dealing with this step. Particularly alarming for the business location: About one-third of large industrial enterprises state that they are already implementing concrete relocation measures. Regionally, skepticism is sometimes even higher. In North Rhine-Westphalia, the value dropped to minus 18.1, and in Baden-Württemberg to minus 13 for all businesses and minus 26 for industrial companies.

The survey identifies the persistent cost burden as the main driver. For nearly half of the companies, electricity costs have risen again within the past twelve months; for gas and oil, about two-thirds report higher burdens. Consequently, more than 40 percent of the surveyed companies see their competitiveness impaired—in industry, it is around two-thirds, and in retail, 40 percent. This leads to massive investment shifts: Around one-third of companies are postponing investments in core operational processes, one in four is holding back investments in climate protection, and 16 percent are delaying expenditures for research and innovation.

Who Benefits from the Permanent Electricity Tax Cut in 2026

The removal of the time limit on the electricity tax reduction under Section 9b of the Electricity Tax Act (StromStG) to 0.05 cents per kilowatt-hour permanently relieves the manufacturing sector starting in 2026, but excludes large parts of the SME sector. Originally, this measure from the federal government's electricity price package was limited to the years 2024 and 2025. With the new legislation, this limitation is lifted, burdening the federal budget by about three billion euros annually.

Around 600,000 companies in the manufacturing, agricultural, and forestry sectors benefit from the lower electricity tax. Although the DIHK demands an electricity tax cut for all companies, as well as faster grid connections and a reduction in regulatory requirements, the current legal situation excludes the retail and service sectors. Estimates suggest that only 15 percent of companies in Germany benefit from this tax relief. For the remaining 85 percent, managing volatile energy costs remains a purely operational challenge that must be financed directly from their own margins.

Why Average Costs Distort Margin Calculations

Rising costs for electricity and gas often only fully impact the annual financial statements because they are not broken down to the individual performance level in ongoing calculations. If energy costs are merely viewed as a block of overhead costs at the end of the month, there is a lack of transparency regarding which products, services, or locations are actually still operating profitably.

In many medium-sized companies, the data on consumption, tariffs, and produced units exists, but it lies isolated in different systems. The ERP system knows the unit quantities, the accounting department manages the advance payments, and the energy management system records the load profiles. If this data is only merged via manual Excel exports, a time delay occurs that makes active countermeasures impossible. When the price guarantee of an energy contract expires and the costs per operating day rise, this effect must be immediately visible in the contribution margin accounting—not weeks later in the controlling report.

How Business Monitoring Accurately Allocates Volatile Costs

Data-driven business monitoring merges raw data from all systems and models costs down to the individual invoice line to make margin losses immediately visible. Instead of working with Excel islands, a continuous P&L, EBITDA, and liquidity calculation is created. The process runs end-to-end from a single source: from import via allocation and the P&L cascade to the monthly closing and a 13- to 52-week liquidity forecast.

The cost modeling is granular. Shipping, commission, platform, and storage costs—as well as energy costs—are versioned and allocated per channel, category, and country. Every metric remains traceable back to the source: from the source field via the mapping and the tariff to the formula. The system is auditable rather than a black box and scales effortlessly, for example across 1.2 million invoices and 2 million invoice lines with a history dating back to 2020.

In practice, such a system answers concrete questions at the push of a button. If the question is: Why was the thermal bath below plan in February?, the monitoring provides the exact breakdown. Visitor numbers were stable, but energy costs per operating day rose by 18 percent after the price binding expired. At the same time, personnel costs rose by 9 percent due to external and leased staff. The exact effect on the result: minus 2.1 points compared to the plan.

How an Analysis Center Turns Cost Data into Decisions

An analysis center links scattered data into a normalized truth and provides concrete, approval-required recommendations for action based on contribution margins. Marketplaces, shops, ERP, ads, returns, inventories, and prices are pulled together and made joinable. This ends the situation where a number appears in six systems and none of them is correct.

The system operates on an approval-first principle rather than blind automation. It provides concrete recommendations with justifications for prices, reorders, or pre-orders, but nothing fires without human approval. In doing so, the center models the actual business, including multi-year seasonality, supplier lead times, and backward-calculated order deadlines. New evaluations can be created in hours, while an audit trail and a drift detector immediately report if parameters tilt.

A typical use case from hospital operations demonstrates the value of this normalization: A location has an occupancy rate of 94 percent, but the contribution margin per care day is 6 percent below the group average. The analysis center immediately identifies the drivers—in this case, energy costs and expensive external staff. The resulting, system-generated recommendation is: Re-tender the energy contract and rely more on pool staff instead of leased personnel. This turns an abstract cost increase into a controllable operational decision.