HMS Networks
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HMS Networks (HMS) investor relations material

HMS Networks 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 summary14 Jul, 2026

Executive summary

  • Achieved record net sales of SEK 991 million in Q2 2026, up 18% year-over-year, with 12% organic growth and strong performance across all regions and divisions, especially APAC with 35% order growth, driven by data center automation and semiconductor demand.

  • Order intake reached SEK 979 million, up 20% year-over-year, with 15% organic growth and a balanced relationship between orders and sales.

  • Strategic minority investment made in Swedish AI company Ekkono to enhance embedded machine learning capabilities.

  • Awarded EcoVadis Gold Medal for sustainability, placing in the top 5% of large companies and top 1% of the industry.

  • All divisions and regions contributed to growth, with Americas showing 28% organic growth.

Financial highlights

  • Q2 EBITA reached SEK 266 million (26.8% margin), up 59% year-over-year, with EBITDA margin at 31.2% and gross margin at 63.8%, both improved from last year.

  • Cash flow from operations was a record SEK 334 million for the quarter and SEK 584 million year-to-date.

  • Adjusted EPS rose to SEK 3.65, with profit after tax at SEK 155 million and adjusted profit after tax at SEK 183 million.

  • YTD net sales reached SEK 1,962 million (+13%), with EBITA of SEK 530 million (27.0% margin).

  • Book-to-bill ratio at 1.0, indicating balanced demand and supply.

Outlook and guidance

  • Expecting some margin pressure in H2 2026 due to longer lead times and rising component prices, especially for memory, but gross margin anticipated to remain above 62%.

  • Operating cost run rate and R&D investments expected to remain stable for the rest of the year.

  • Continued focus on securing inventory for critical components amid supply constraints and macroeconomic/geopolitical uncertainty.

H2 margin impact from memory component lead times
Strategic goals for Ekkono AI integration in OEMs
Outlook for EMEA automotive demand recovery
Indirect exposure to data center expansion
H2 gross margin pressure from component costs
AI tools impact on R&D coding efficiency
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