---
id: ch7-vidzeme-monitoring
type: spine
title: "Worked example: Vidzeme turns a monitoring gap into a measure plan"
readingTime: 3
standalone: true
core: false
teaser: "Vidzeme had no systematic way to monitor its own development programme. Its policy brief maps that gap onto finance, legislation and training, then sets targets for 2028."
parent: null
diagram: fig-vidzeme-monitoring
recallQ: "In the Vidzeme case, which gap is the plan built on, and which measures close the legislation and training parts of it?"
recallA: "Vidzeme had no systematic territorial monitoring of the VPR Development Programme: data was fragmented and indicators inconsistent. Formal data-sharing agreements and mandatory annual reporting address the legislation and governance side; permanent specialist posts and data-literacy training for municipal staff address the training side."
highlights:
  - "Gap: no systematic territorial monitoring of the VPR Development Programme 2022–2027"
  - "Challenges sorted into data, cooperation, technical, financial, legal and engagement groups"
  - "2028 targets: multi-level data governance, an AI-driven geospatial platform, regional analytics capacity"
  - "Open-call studies (EDQMS_VR, D2D) fed the evidence base"
status: accepted
concept: from-policy-gap-to-intervention-logic
lang: en
lens: latvia
depth: standard
formalism: none
visuality: balanced
lengthBand: standard
genre: worked-example
state: edited
carriers: prose|table|diagram
---

The Vidzeme Planning Region (VPR) in Latvia leads PoliRural+ pilot 8. Its starting point is a plain gap: **no systematic territorial monitoring of the VPR Development Programme**. Below, the region's policy brief (D7.3, Annex 8, 11 June 2025) is read through the four steps of the [gap-to-intervention-logic method](#c/from-policy-gap-to-intervention-logic).

## Step 1: what already exists

The brief's strategic alignment table works as the policy inventory. It lists Latvia's Regional Policy Guidelines 2021–2027, the VPR Sustainable Development Strategy 2030, the **VPR Development Programme 2022–2027**, the regional Smart Specialisation Strategy (seven high-value clusters), Latvia's CAP Strategic Plan 2023–2027, the Green Deal, the Digital Decade 2030, Cohesion Policy, Horizon Europe and Digital Europe. The plan builds on the existing programme. It does not create a new one.

## Step 2: the gaps, by type

| D3.1 gap type | What the Vidzeme brief reports |
|---|---|
| Data and method | Data fragmented across institutions; RAIM (the Regional Development Indicators Module) integrates data incompletely; inconsistent indicators; little parish- and county-level statistics |
| Legislation and governance | Frequent legislative changes; insufficient data sharing; fragmented strategic documents |
| Finance | Limited municipal capacity to finance digital infrastructure |
| Training | Shortage of qualified data analysts; low municipal capacity with digital tools |
| Engagement | Low trust in institutions; little feedback to residents |

## Step 3: measures

- Standardise monitoring: unified data-collection protocols, **mandatory annual reporting cycles**, **formal data-sharing agreements**
- Launch **VPR PATHWATCH**, a centralised, AI-driven monitoring system with geospatial and mobile access
- Create permanent specialist posts and train municipal staff in data literacy and AI
- Bring citizens in through a mobile app, for accountability
- Position VPR as a national model and build a Baltic monitoring network

PATHWATCH is a recommendation in the brief, not a running system.

## Step 4: targets

The brief sets three targets **for 2028**: integrated multi-level data governance, an AI-driven geospatial monitoring platform that moves "from retrospective reporting to predictive analysis", and regional analytics capacity. These are time-bound, so they meet the T in SMART. To make them fully SMART, each still needs a measurable indicator and a baseline. An illustrative chain (constructed here, not taken from the brief): training sessions (measure) → municipal staff trained (output) → municipalities reporting on the unified protocol each year (outcome) → regional programme decisions made on current data (impact).

The evidence came partly from PoliRural+ open calls. InnoMatrix carried out the **EDQMS_VR** outreach study on economic development quality monitoring, and NovoFutura ran **D2D**, a two-phase hackathon on regional development data. Chapter 4 calls this path [data to decisions](#c/data-to-decisions).

**Sources:**
- D7.3 Policy Brief No. 1, Annex 8 Accelerating Data-Driven Monitoring of the Regional Development in Vidzeme, Latvia (Executive Summary, Key Policy Challenges, Policy Recommendations, Strategic Alignment, Acknowledgements). [PDF](https://www.poliruralplus.eu/docs/349/D7.3_Policy_Brief_No.1.pdf)
- D3.1 RAP Methodology, "Policy Gap Analysis", "Choosing SMART Indicators and KPIs". [PDF](https://www.poliruralplus.eu/docs/161/D3.1__RAP_Methodology_v1.pdf)
- D6.3 Comprehensive Report on Funded Activities and Impact Assessment (EDQMS_VR, D2D). [PDF](https://www.poliruralplus.eu/docs/437/D6.3_Comprehensive_report.pdf)