# Logic model, theory of change & SMART objectives

The reviewer scores the **causal logic**, not the activity list. This file is the depth behind the SKILL.md "Logic model & SMART objectives" section.

## The logic-model chain

The W.K. Kellogg framework: **INPUTS → ACTIVITIES → OUTPUTS → OUTCOMES** (outcomes split short / medium / long-term). Inputs and activities are what you control; outputs are what you produce; outcomes are what *changes in the world* as a result.

| Column | Question it answers | Example |
|---|---|---|
| Inputs | What we invest | €450k, 4 FTE, 3 partner SMEs, training curriculum |
| Activities | What we do | Run 10 cohorts of a 12-week digital upskilling program |
| Outputs | What we produce (countable) | 200 people trained; 1 open curriculum published |
| Outcomes (short) | What changes at 0–6 months | 70% of trainees apply ≥1 new skill on the job |
| Outcomes (medium) | What changes at 6–18 months | 140 secure a digital-sector role or progression |
| Outcomes (long) | The ultimate change | Regional digital-role fill rate 62% → 80% |

Fill it left-to-right, then **read it right-to-left** to test the logic: does each outcome plausibly follow from the output before it? If a link requires a leap of faith, name the assumption or fix the design.

## Theory of change — the "red thread"

A theory of change is the **same causal claim made visible in every section**. The problem you state, the activities you fund, and the way you measure success should all be the same story:

```text
Needs:      SMEs can't fill digital roles (38% report unfilled roles, Eurostat 2025).
Mechanism:  Because the local pipeline lacks job-ready, certified candidates.
Design:     So we run cohort-based, employer-co-designed upskilling to certification.
Evaluation: Therefore we measure job-readiness, placements, and regional fill rate —
            the exact indicators implied by the mechanism.
```

If the evaluation measures something the mechanism never claimed (e.g. "satisfaction" when the theory was about placements), the thread is broken and the reviewer sees it.

## Output vs. outcome — five contrasts

The single most common scoring failure. Outputs use verbs of *doing*; outcomes describe a *changed state* with a baseline and a timeframe.

| Output (what you did) | Outcome (what changed) |
|---|---|
| Held 100 workshops | At 6 months, 200 participants sustain [behaviour] vs. baseline |
| Trained 200 people | 140 of 200 secure a digital-sector role by month 12 |
| Published a toolkit | 3 partner orgs adopt the toolkit in their own programs by month 18 |
| Conducted 50 outreach visits | SME enrolment rises from 12 → 45 per quarter |
| Produced 4 reports | 2 sector bodies cite the findings in revised guidance |

Rule of thumb: if you can count it the day the activity ends, it is an output. If it requires the world to have changed, it is an outcome.

## SMART objectives — Bad → Good

Specific, Measurable, Achievable, Relevant, Time-bound. Every objective needs a **numeric target** and a **date/timeframe**.

```text
Bad:  "Improve employability of participants."
Good: "By month 12, ≥140 of 200 enrolled participants (70%) secure a digital-sector
       role or progression, verified by a follow-up survey."

Bad:  "Increase awareness of the program among regional SMEs."
Good: "By month 9, raise quarterly SME enrolment from 12 to ≥45 (3.75×),
       tracked via the enrolment CRM."

Bad:  "Disseminate results widely."
Good: "By month 24, secure documented adoption commitments from ≥2 sector bodies
       (letters of support attached) covering ≥9,000 SMEs."
```

If an objective has no number or no date, it is not yet SMART — push back before drafting the budget around it.
