---
title: Intervention Policy (PrPM)
type: concept
tags: [prpm, ppm, intervention, policy, causality]
sources: ["[[sources/2022-kubrak-prescriptive-ppm-slr]]"]
created: 2026-04-20
updated: 2026-04-20
---

# Intervention Policy

In [[concepts/prescriptive-process-monitoring|prescriptive process monitoring]] (PrPM), an **intervention policy** specifies *when* an intervention is triggered, *to which* running cases it is applied, and *how* the candidate intervention is chosen. The policy is orthogonal to the prediction model and the catalogue of candidate interventions — it is the decision rule sitting on top of both.

[[sources/2022-kubrak-prescriptive-ppm-slr|Kubrak, Milani, Nolte & Dumas (2022)]] elevate intervention policy to one of six first-class dimensions of their PrPM framework (alongside performance objective, performance metrics, intervention types, modeling techniques, and data inputs).

## Axes of variation

**Frequency** — how often does the policy fire?
- *Continuous* — an intervention is prescribed for multiple (possibly every) step of an ongoing case. Typical in "guiding" recommender systems.
- *Discrete* — an intervention is triggered only when a specific condition is detected (e.g., predicted negative outcome above a threshold). Typical in alarm-based systems.

**Purpose** — what is the policy's logic?
- *Optimizing* — trigger an intervention so as to improve a KPI. Sub-split:
  - *Correlation-based* — pick the intervention that historically co-occurs with the best outcomes (e.g., [[sources/2014-groger-prescriptive-analytics-bpo|Gröger et al. 2014]]).
  - *Causality-based* — pick the intervention that is *causally* estimated to improve the outcome (uplift trees, CATE estimation; Bozorgi et al. 2021; Shoush & Dumas 2021).
- *Guiding* — prescribe recommendations based on similarity to historical traces, without an explicit KPI target (nearest-neighbour recommenders).

## Common trigger types

- **Threshold on predicted probability** of a negative outcome (alarm-based; Teinemaa, Fahrenkrog-Petersen et al.).
- **Set of rules** over process / resource attributes.
- **Maximum expected metric improvement** — assign intervention to the case/resource pair that maximises predicted KPI delta.
- **Cost-aware alarm** — fire only when expected benefit exceeds intervention cost (Fahrenkrog-Petersen et al. 2022's *Fire now, fire later*).
- **Similarity to past successful traces** — pure guiding.

## Why the distinction matters

A method with an excellent predictor but a poorly designed policy will waste interventions (firing when it shouldn't) or miss opportunities (not firing when it should). The predictor answers *what will happen*; the policy answers *what to do given the prediction, the cost of acting, and the limits on resources*.

## Causality and second-order effects

The Kubrak SLR names **causal, second-order-aware policy design** as the most promising research direction. Correlation-based policies can recommend interventions that would occur *anyway* in the successful cases (selection bias) or that conflict with implicit process restrictions (as [[sources/2014-groger-prescriptive-analytics-bpo|Gröger et al.]] observed with material-machine compatibility). Causal methods (uplift modelling, counterfactual reasoning; cf. [[concepts/causal-process-discovery]]) aim to estimate the true effect of intervening, and second-order analysis considers how an intervention on one case affects contemporaneous cases through shared resources.

## Resource constraints

Practical policies must account for resource availability — Shoush & Dumas (2021) combine probability-of-undesired-outcome with resource availability and intervention cost before prescribing. Without resource-awareness, a policy can fire more interventions than can be executed.

## Related

[[concepts/prescriptive-process-monitoring]] · [[concepts/predictive-process-monitoring]] · [[concepts/causal-process-discovery]] · [[concepts/interventionist-theory-of-causation]] (philosophical grounding: Woodward's causes-as-handles view is the metaphysical counterpart of PrPM policy design) · [[concepts/operational-support]] · [[concepts/mape-k-loop]] (the Plan stage of MAPE-K is the APM analogue of a PrPM policy)