Rising Cost Pressures Force Construction Sector to Reassess SaaS Models

Software-as-a-Service (SaaS) has become integral to the construction and infrastructure sectors, facilitating a wide range of functions from project management to financial planning. As developers, engineering, procurement, and construction (EPC) contractors, consultants, and asset owners engage in multi-billion-dollar projects, cloud-based platforms are now essential at nearly every phase of the project lifecycle. These platforms include Common Data Environments (CDEs), Building Information Modelling (BIM) collaboration tools, field management systems, document control, digital quality assurance, environmental, social, and governance (ESG) reporting, workforce management, and financial planning applications, predominantly offered through subscription-based SaaS models.

Evolving Cost Structures in SaaS

Initially regarded as a flexible pay-as-you-go solution, SaaS has transformed into one of the most significant recurring expenses in digital transformation budgets, often exceeding the growth of the businesses themselves. This financial burden encompasses annual licensing fees, implementation costs, charges for scope changes, customization, and pricing based on tenant and environment usage, along with compute-driven overages. As organizations expand and data volumes increase, additional costs related to performance, storage, and computational power also arise.

The global technology market is experiencing pressures that further exacerbate these costs. A sector-wide correction known as the “SaaSpocalypse,” characterized by declining SaaS earnings and valuations, has led many vendors to shift from traditional subscription pricing to consumption- and outcome-based models.

Regional Economic Pressures

These global trends coincide with regional economic challenges. The ongoing US-Iran conflict has disrupted supply chains, tightened liquidity, and compelled companies, particularly in capital-intensive sectors, to meticulously evaluate every aspect of operational expenditure.

Adinath Kadam, a financial planning and analysis (FP&A) systems architect based in the United States, emphasized that the cumulative impact of SaaS subscriptions has become increasingly difficult to overlook in capital-intensive sectors. He noted that for long-term projects, the recurring overhead associated with SaaS compounds over the project lifecycle.

Kadam stated that executives are now reassessing the balance between long-term SaaS commitments and other digital investments, including artificial intelligence (AI), automation, digital twins, and cloud-native analytics. He remarked that the focus has shifted from the utility of SaaS to whether the economics of perpetual subscription models remain viable in an environment where cost discipline, data control, and operational resilience are paramount.

Challenges in Transitioning Away from SaaS

Despite the appeal of reducing SaaS expenditures, contractors and project owners face significant hurdles when attempting to migrate from established platforms. Kadam explained that implementations can take 18 to 24 months, costing millions of dollars and requiring extensive scoping, configuration, and change management. By the time a system is operational, workflows, reporting structures, and employee roles are often fully integrated, creating a heavy reliance on existing SaaS platforms, even when more cost-effective alternatives are available.

Exploring Cloud-Native Alternatives

The shifting economic landscape is prompting some organizations to consider cloud-native architectures for specific business functions rather than relying solely on proprietary SaaS platforms. Kadam identified financial planning and analysis (FP&A) as a particularly suitable function for migration, as its workloads primarily involve aggregating financial and operational data rather than requiring intensive computational processing.

FP&A workloads typically consist of high-volume transactional data, such as sales, costs, payroll, and operational metrics, supplemented by a limited set of descriptive data. These workflows necessitate frequent recalculation of derived metrics like margins, growth rates, and variances across multiple planning cycles.

Kadam noted that from a data engineering perspective, FP&A workloads are more focused on aggregation than on computational intensity. Performance bottlenecks often arise from repeated data movement and unstable transformations rather than complex algorithms.

A cloud-native FP&A architecture can also accommodate the heavy reliance of FP&A teams on tools like Microsoft Excel, enabling finance teams to manage multi-million-row datasets while maintaining familiar workflows and avoiding premature transitions to complex data warehouses.

The Role of AI in Financial Decision-Making

Looking ahead, Kadam anticipates that artificial intelligence will significantly influence financial decision-making within construction and infrastructure firms. He suggested that integrating AI with cloud-native data warehousing could redefine FP&A workflows, making financial analytics more accessible and responsive.

Kadam explained that an intelligent FP&A system would allow users, including those without technical expertise, to pose questions in natural language and receive immediate, data-driven insights. This democratization of financial insights reduces reliance on specialists and fosters a fundamentally different relationship between finance teams and their data.

Source: www.zawya.com

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Published on 2026-06-28 16:31:00 • By the Editorial Desk