Services / AI Operating Model / KPIs & Measurement
KPIs & Measurement: What changes through AI
Productivity is the simplest AI metric, but rarely the most important. Steering needs metrics that make quality, risk and business impact visible.
The shift
Productivity is the simplest AI metric, but rarely the most important. Steering needs metrics that make quality, risk and business impact visible.
From
To
- Output (volume, speed)
- Activity focus
→
- Impact (quality, results)
- Customer focus
Guiding questions
- How do we recognize whether AI really creates impact in the workflow – for customers and for results?
- How do we measure quality, interventions and risk, not just usage and time saved?
- Who is accountable for the metrics, and how do they feed into steering and governance?
The typical mistake
Confusing usage with impact. High usage figures and time savings say little about whether quality, customer value and results are improving.
What you can expect from us
- Measurement model along the dimensions usage, efficiency, quality, autonomy and interventions, risk, customer impact and business value
- Metrics per workflow with target values and owners
- Steering and reporting rhythm
- Link to governance and incentive or target systems, where desired
Seven dimensions of measurement
01
Usage
02
Efficiency
03
Quality
04
Autonomy and interventions
05
Risk
06
Customer impact
07
Business value
Would you like to align your operating model with AI?
We are glad to discuss with you where AI can create impact in your organization – and which structures, roles and rules are needed for it.