---
title: "Prescriptive Control of Business Processes: New Potentials Through Predictive Analytics of Big Data in the Process Manufacturing Industry"
type: source
tags: [prescriptive-process-monitoring, prpm, event-driven-bpm, cep, complex-event-processing, condition-based-maintenance, design-science, steel-industry, big-data, foundational-prpm]
authors: [Krumeich, Julian; Werth, Dirk; Loos, Peter]
year: 2015
venue: "Business & Information Systems Engineering 58(4): 261–280, Springer. Published online 7 Dec 2015 (volume 2016). DOI: 10.1007/s12599-015-0412-2"
kind: paper
raw_path: "raw/Process Frameworks & BPM/2015-krumeich-prescriptive-control-business-processes.pdf"
doi: "10.1007/s12599-015-0412-2"
sources: []
key_claims:
  - "Foundational early-PrPM paper. Proposes a concept of prescriptive *control* of business processes via event-based process predictions, predating most of the prescriptive-process-monitoring literature catalogued by Kubrak et al. 2022. Cites Gröger et al. 2014 as concurrent."
  - "Articulates Event-Driven Business Process Management (ED-BPM) and Event-Driven Predictive Analytics (EDPA) as conceptual umbrellas; combines Complex Event Processing (CEP) + predictive analytics + business process control."
  - "Methodological anchor: design-science research (Hevner). Case study of a German steel-producing company with revelatory design as evaluation."
  - "Four-component concept: (C1) process blueprints embedding complex event patterns into process models; (C2) induction + CEP detection of patterns within running instances; (C3) Bayesian-network forecasting of further process behaviour and KPIs; (C4) KPI-based prescriptive control via an optimisation function over time/quality/resource-consumption."
  - "5-layer enterprise system architecture: CEP Layer → Prediction Layer → Process Engine Layer → Dashboard with KPI Controller (plus EPA + Event Models + Event Rules supporting the CEP layer)."
  - "Seven derived requirements for prescriptive-control enterprise systems (sensor instrumentation; CEP engine; event model + rules; intra-process cross-event mining; embedding of prediction targets into process models; cross-correlation of context and process; KPI-driven optimisation feedback)."
  - "Process-industry specifics motivate the work: divergent/analytical material flows, production cycles, non-linear and non-controllable production outputs, customer-specific end products. Steel as paradigmatic example."
created: 2026-05-11
updated: 2026-05-11
---

# Krumeich, Werth & Loos 2015 — Prescriptive Control of Business Processes

Springer *Business & Information Systems Engineering* (BISE) research paper from the Institute for Information Systems (IWi) at DFKI Saarland University. Published online 7 December 2015 (assigned to volume year 2016 — both dates appear in citations). One of the earliest articulations of **prescriptive process control** in BPM, predating most of the literature catalogued by [[sources/2022-kubrak-prescriptive-ppm-slr|Kubrak et al. 2022's SLR]] and contemporaneous with [[sources/2014-groger-prescriptive-analytics-bpo|Gröger et al. 2014]].

## What the paper does

A design-science research artifact (Hevner) for a system architecture that takes predictive process monitoring beyond *predicting* the future to *actively controlling* it via KPI-driven optimisation. Three lenses make the contribution distinctive:

1. **Event-Driven framing** — re-uses Complex Event Processing (CEP) from financial-services & manufacturing operations as the technical substrate. Coins ED-BPM and EDPA (Event-Driven Predictive Analytics) as the umbrella concepts.
2. **Industry verticalisation** — explicitly targets the *process manufacturing* industry, particularly steel, with its characteristic divergent/analytical material flows, production cycles, non-linear outputs, and customer-specific end products.
3. **Borrowed conceptual heuristic from Condition-Based Maintenance (CBM)** — section 2.4 develops CBM as a methodological analogy for prescriptive process control.

## The four-component concept (Figure 4 in the paper)

| # | Component | What it does |
|---|---|---|
| 1 | **Process blueprints with complex event patterns** | Process models extended to embed CEP queries at decision/control points. |
| 2 | **Pattern induction + detection** | Cluster mining for significant event patterns; CEP-engine runtime detection in event streams. |
| 3 | **Event-based process forecasting** | Bayesian network (probabilistic) prediction of remaining process behaviour and KPIs, conditioned on detected complex events. |
| 4 | **KPI-based prescriptive control** | Optimisation function o(a, b, c) over time, quality, resource-consumption KPIs; selects the (most-optimal) onward process branch. |

## The enterprise architecture (Figure 5)

Five technical layers, top to bottom:

- **Dashboard with KPI Controller** — managers tune KPI weights.
- **Process Engine Layer** — Process Models · Process Instances · Simulation Engine · Optimisation Engine.
- **Prediction Layer** — Event-based prediction models (rule induction · neural net · etc.).
- **Complex Event Processing Layer** — EPA₁..EPAₙ · Event Processing Engine · Event Model · Event Rules.

Event stream flows: pre-processed events → CEP detection → predicted complex events → prediction layer → process engine → control feedback.

## Seven requirements derived from the case study

1. Sensor instrumentation of physical processes.
2. CEP engine integrating heterogeneous event streams.
3. Event models + event rules specifying detection logic.
4. Intra-process cross-event mining to discover predictive complex-event patterns.
5. Embedding of prediction targets (cycle time, branch likelihoods, exception probabilities) directly into process models.
6. Cross-correlation of contextual (sensor) and intra-process data.
7. KPI-driven optimisation feedback loop from prediction outputs to process engine.

## Position in the wiki's prescriptive-process-monitoring lineage

This paper is an early ancestor of the prescriptive-process-monitoring literature later catalogued in [[sources/2022-kubrak-prescriptive-ppm-slr|Kubrak et al. 2022's SLR]]:

| Year | Source | Contribution |
|---|---|---|
| 2014 | [[sources/2014-groger-prescriptive-analytics-bpo]] | Concept of "recommendation-based BPO" using process warehouse + association-rule mining. |
| **2015** | **This paper (Krumeich et al.)** | **CEP-based prescriptive control architecture for process manufacturing; 4-component concept; 7 requirements.** |
| 2022 | [[sources/2022-kubrak-prescriptive-ppm-slr]] | SLR consolidating the field; covers 36 included papers from 2014–2021. |

## Limitations

- **Single case study** — German steel manufacturer. Generalisability to discrete-manufacturing / service-industries explicitly flagged as future work.
- **Revelatory rather than evaluative** — design-science evaluation is conceptual (descriptive utility) + single-case demonstration. No quantitative end-to-end deployment.
- **Bayesian-network prediction model** — chosen for tractability + interpretability; not benchmarked against contemporary deep-learning PPM alternatives (Evermann 2017, Tax 2017 had not yet been published at the time).
- **Optimisation function** kept simple (weighted sum); does not address multi-objective Pareto frontiers, stochastic dominance, or risk-aware KPI weighting.

## Connections

**Concepts:**
- [[concepts/prescriptive-process-monitoring]] — early canonical reference.
- [[concepts/event-driven-bpm]] — *introduces ED-BPM and EDPA in the wiki*.
- [[concepts/predictive-process-monitoring]] — embedded prediction component is PPM-as-subroutine inside PrPM.
- [[concepts/business-process-simulation]] — simulation engine in the process engine layer.

**Methods:**
- [[methods/process-discovery-methods]] — complex-event-pattern mining as a discovery variant.

**Sources cited that exist in the wiki:**
- [[sources/2014-groger-prescriptive-analytics-bpo]] — concurrent PrPM-vision paper.
- [[sources/2018-dumas-fundamentals-of-bpm]] — BPM lifecycle foundation.

**Syntheses:**
- [[syntheses/prescriptive-process-monitoring-lineage]] — *anchor source for the lineage*.
- [[syntheses/ppm-landscape]] — referenced as PPM→PrPM bridge.