Willdan Group (WLDN) Fair Value & Analysis
Industrials · US · Market cap $1.2B
Analysis
Willdan Group (WLDN) currently trades at $80.73, while our model-based Fair Value estimate is $59.13 — implying the stock looks roughly 26.8% overvalued today. We read business quality at 95/100 (high quality), in the Industrials sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
Willdan Group, Inc., together with its subsidiaries, provides professional, technical, and consulting services through engineering, program management, policy advisory, and software and data analytics primarily in the United States. The company operates in two segments: Energy, and Engineering and Consulting. The Energy segment offers comprehensive audit and surveys, program design and implementation, master planning, demand reduction, grid optimization, benchmarking analyses, design engineering, AI data center power solutions, construction management, performance contracting, installation, alternative financing, measurement and verification services, and software and data analytics, as well as energy consulting and engineering, turnkey facility and infrastructure projects, and customer support services. The Engineering and Consulting segment provides building and safety, city engineering and code enforcement, development review, disaster recovery, geotechnical, earthquake, planning…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.