How to quantify the impact of AI in everyday operations

When organizations look at AI for document-heavy processes, the discussion often starts with technology. In practice, the real question is simpler: where do we save time or create value, and how do we measure it?

Blueprints help answer that question. A Blueprint is a reusable process pattern that combines AI, automation, and human judgment. More importantly, it breaks a complex process into clear steps — which makes both implementation and ROI measurement much easier.

The document data extraction Blueprint is one example of this approach. It shows how document-heavy processes can be structured so that savings and gains can be calculated at each step.

‍

Using the Blueprint to measure ROI

The document data extraction Blueprint structures document handling into four steps:

1. Extract data from documents
2. Check whether the data is complete and correct
3. Complement or correct the data when needed
4. Use the validated data in downstream processes

‍

‍

The strength of this Blueprint is its reusability. The same structure works for financial, legal, and operational documents. Only the extracted fields and validation rules change.

This allows organizations to start from a proven setup instead of rebuilding document automation for every new use case.

‍

Example 1: quotation handling from supplier documents

Companies working with many suppliers often receive multiple quotes in different formats. These need to be compared and combined into a single quote for the customer.

For example, in a construction business sourcing materials and components from different suppliers.

Using the document data extraction Blueprint:

• Supplier quotes are ingested automatically
• Prices, delivery times, and conditions are extracted
• Humans validate the data where needed
• Automation combines everything into one customer quote

The result is faster quote generation with less manual effort and more consistent output. ROI is calculated by adding up the savings per step and multiplying by document volume.

‍

‍

Example 2: cost-price analysis for manufacturers

Manufacturers frequently analyze cost prices using supplier documents, bills of materials, and specifications. Manual consolidation often slows this down.

With the Blueprint:

• Cost-related data is extracted automatically
• Missing or unclear information is flagged
• Validated data feeds cost-price calculations
• Results flow directly into costing and margin analysis

This leads to faster analysis and more reliable input for pricing decisions.

Again, ROI is calculated by summing time saved at each step and applying it to real volumes.

‍

‍

Measuring ROI beyond document extraction

By breaking processes into clear steps, organizations can:

• Measure savings or gains per step
• Identify where automation adds real value
• Build transparent business cases for AI and automation

The document data extraction Blueprint simply shows how this works in practice. The same step-by-step ROI logic applies to any process where AI, automation, and human judgment work together.