Goodtech
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Goodtech (GOD) investor relations material

Goodtech Q2 2026 earnings summary

Complete event summary combining all related documents: earnings call transcript, report, and slide presentation.
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Q2 2026 earnings summary17 Jul, 2026

Executive summary

  • Net operating revenue after external project costs reached NOK 132.1 million, up 4% year-on-year, with stable utilization and solid activity levels.

  • EBITDA increased to NOK 15.9 million (12% margin), and EBITA grew to NOK 10.1 million (7.7% margin), reflecting operational discipline and improved margins.

  • Profit for the period was NOK 7.3 million, up from NOK 1.7 million last year, with H1 profit at NOK 18.0 million.

  • Order intake was NOK 164 million, with an order backlog of NOK 304 million, impacted by the discontinuation of a large project.

  • The Board plans to distribute approximately NOK 60 million of excess capital to shareholders in H2 2026.

Financial highlights

  • Total revenue grew from NOK 164.6 million to NOK 171.7 million, a 4% year-on-year increase.

  • Net operating revenue after external project costs rose from NOK 126.9 million to NOK 132.1 million, also up 4% year-on-year.

  • EBITDA margin held steady at 12%; EBITA increased to NOK 10.1 million, with a 7.7% margin.

  • Other operating expenses decreased by 10% due to cost discipline.

  • Personnel expenses increased by 6% due to salary adjustments and high activity.

Outlook and guidance

  • Market activity remains healthy, though large project investments face longer lead times.

  • Recurring revenues from aftermarket and life cycle services are growing, improving earnings predictability.

  • The company is well-positioned for growth in industrial AI and digitalization, with a focus on operational excellence and selective expansion.

  • Board intends to distribute NOK 60 million to shareholders in H2 2026.

  • Diversified industry footprint provides resilience amid market uncertainties.

Criteria for supplemental dividend distributions
Strategy for growing recurring service revenues
Role of engineering context in industrial AI
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