IDCC/PACE Implementation #

Implementing IDCC/PACE #

1. Create a shared scorecard #

• Use a simple 1-5 scale for each trait.
• Keep definitions visible so evaluators anchor consistently.
• Template: Google Sheets

2. Calibrate evaluators #

• Run mock evaluations on the same candidate profile.
• Compare scores, discuss differences, align on what “3” vs. “4” means.

3. Use structured interviews #

• One sharp behavioral question per trait.
• Follow up with “how” and “why” to probe depth.

4. Score immediately after interview #

• Don’t wait; memory fades and bias creeps in.
• Write one short evidence note per trait.

5. Review patterns, not just totals #

• Watch for outlier combinations (e.g., high confidence, low competence).
• Apply rules:
  • Fail = any 1
  • Poor = any 2
  • Pass = all ≥ 3
  • Great = avg ≥ 4
  • Exceptional = avg ≥ 4.5 with balance

6. Confirm with second lens #

• Cross-check questionable scores with work samples, references, or another evaluator.
• Treat red flags as signals for deeper inspection, not immediate rejection.

7. Track over time #

• Reassess periodically (no less than every 6-12 months).
• Use IDCC/PACE for promotions and development, not just hiring.

Scoring evaluation #

Score distributions across IDCC and PACE are rarely independent. Traits lean on each other, and certain combinations are naturally more likely than others. For example, it is unrealistic to see someone rated “1” in Intelligence and “5” in Competence. Competence reflects the application of knowledge, which presupposes at least a baseline level of intelligence.

Some mismatches signal risk profiles. High Confidence combined with low Competence can appear convincing but creates execution risk. High Drive without Pragmatism can result in wasted effort or misdirected initiatives. Strong Collaboration paired with weak Ethics may hide self-serving behavior behind social fluency.

Other combinations are unstable. High Drive with very low Adaptability often leads to burnout or rigidity. Exceptional Pragmatism with very low Intelligence is unlikely, since sound judgment depends on at least moderate reasoning.

When such outlier patterns appear, they should be treated as prompts for deeper evaluation. They may reveal evaluator bias, mis-scoring, or hidden aspects of the individual’s behavior.

Calibration #

One important point in applying this framework is that a failing score should not automatically trigger drastic action. A “fail” is not a judgment of a person’s worth, it’s a signal for closer inspection. It tells you that a dimension may be underdeveloped, misjudged, or masked by circumstances. In practice, that means the next step is introspection and confirmation - looking deeper at the evidence, asking better questions, and checking whether the low score is consistent across contexts. Sometimes it reveals a real gap; sometimes it exposes an evaluator’s blind spot.

Bias #

That brings us to the second caution: evaluator bias. Any scoring system is only as fair as the people using it. Confidence, competence, and even “collaboration” can be colored by culture, background, or personality differences. If you’re using IDCC or PACE formally, you need calibration - clear definitions, shared examples, and ideally multiple evaluators. This aligns standards across managers and ensures that a “3” in one department means the same as a “3” in another. Without calibration, you risk turning structure into subjectivity dressed up as numbers.

More best practices #

1. Define expectations by role

   • Not every position needs equal strength across all traits.
   • Decide which traits are critical before scoring.

2. Normalize scores across a cohort

   • Compare candidates side by side.
   • Relative patterns reveal more than absolute numbers.

3. Document calibration sessions

   • Keep notes from evaluator alignment discussions.
   • Create a living reference for what each score means in practice.

4. Protect against halo effect

   • Don’t let strength in one trait influence others.
   • Score each dimension independently.

5. Track outcomes of hires

   • Compare IDCC/PACE scores with actual performance later.
   • Refine scoring accuracy by learning from results.