The hidden costs of the digital factory: Rethinking manufacturing expenses

The global economy is shifting rapidly, with digital resources driving innovation and growth in ways never seen before. The increasing importance of intangible digital assets, such as data, software, and artificial intelligence, is reshaping regional economies, breaking traditional geographical constraints, and fostering new hubs of economic activity. A recent study by Olegs Cernisevs, Doctor of Science and CTO of Blackcatcard, focuses on these intangible resources and highlights the necessity of integrating digital innovation into economic region theory. 

Olegs Cernisevs, Doctor of Science and CTO of Blackcatcard

One of the key findings is that intangible resources are also bound to geography. In the modern world, manufacturing is no longer associated with tangible costs like raw materials, transportation, warehousing, and labour. However, with the rise of digital transformation and the increasing reliance on intangible inputs like data, artificial intelligence, and intellectual property, cost structures are evolving. Traditional cost models must be re-evaluated to reflect this shift accurately.

Traditionally, manufacturing costs were categorised into fixed and variable expenses, such as:

• Fixed costs: machinery, factory rent, and infrastructure.
• Variable costs: raw materials, transportation, and energy consumption.

The integration of intangible inputs in manufacturing introduces new variable cost factors that differ significantly from traditional tangible resource expenses. These include:

• Research and development (R&D): The costs of developing new algorithms, AI models, and automation software are becoming significant expenditures for manufacturers embracing digital transformation.
• Digital infrastructure: Cloud computing, cybersecurity, and data storage are essential for maintaining seamless production processes reliant on digital resources.
• Intellectual property and licensing: Companies must allocate budgets for acquiring or protecting patents, trademarks, and proprietary software necessary for modern manufacturing.
• Talent acquisition and training: With automation and AI becoming central to production, skilled labour for operating and maintaining these systems has become a crucial cost factor.

With the rise of intangible inputs, cost distribution is shifting. Fixed costs now include investments in cloud infrastructure, cybersecurity, and proprietary digital systems. Variable costs expand to licensing fees for AI tools, digital subscriptions, and continuous workforce upskilling, etc.

The integration of intangible resources has also reshaped logistics and supply chain dynamics:

• Lower physical storage costs: As digital assets replace physical components in manufacturing, warehousing expenses decrease.
• Reduced transportation costs: The use of digital designs and AI-driven processes minimises the need to transport materials.
• Greater predictability in supply chains: AI-driven predictive maintenance and data analytics improve operational efficiency, reducing downtime and unexpected costs.

As industries transition to digital-driven manufacturing, a hybrid cost model integrating both tangible and intangible cost structures will emerge. Companies must adopt flexible financial strategies to accommodate this shift, ensuring that investments in digital assets are balanced with traditional manufacturing needs. By re-evaluating cost structures in light of intangible inputs, manufacturers can optimise expenses, enhance efficiency, and remain competitive in an increasingly digitalised global economy.