Data Detail vs Data Collection Cost
Map each data element to a specific analytical decision before collecting it, eliminating storage and governance cost for information that drives no action.
CyberTRIZ analysis · Benchmarking contradiction MDM002 · one of 8,235 worked contradictions published by CyberTRIZ.AI
Regulations
Business Context
Detailed data allows benchmarking teams to segment performance, identify root causes, normalize differences, and understand how processes actually operate. However, collecting detailed information can require additional systems, instrumentation, manual reporting, storage, integration, and governance. Organizations can therefore accumulate significant measurement costs while using only a small proportion of the information collected. Reducing detail lowers cost but can leave analysts unable to explain observed performance gaps.
Benchmarking TRIZ Resolution
Data collection should be driven by analytical value rather than maximum possible detail. Organizations should exploit information already generated by operational systems and collect additional detail only where preliminary analysis identifies a meaningful need. Sampling, event-triggered capture, temporary instrumentation, and selective process-level measurement can provide deeper information without requiring permanent comprehensive collection.
Applicable TRIZ Principles
Principle 2 – Taking Out removes data elements that do not materially contribute to benchmarking decisions.
Principle 19 – Periodic Action collects specialized detail periodically rather than continuously when permanent measurement is unnecessary.
Principle 25 – Self-Service uses data already generated by processes, equipment, transactions, and information systems.
Expected Outcome
Lower data-collection cost
Greater availability of useful detail
Reduced unnecessary measurement
Better allocation of analytical resources
Decision Indicators
Early indicators include:
Large datasets contain fields that are rarely analyzed.
Manual reporting requirements continue expanding.
Analysts request additional detail before determining whether it affects conclusions.
Measurement costs increase faster than benchmarking value.
Important investigations cannot proceed because the required detail was never collected.
These signals indicate that data detail should be activated according to analytical need rather than accumulated uniformly.