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First Learnings in Applying GenAI to Value Stream Management

Publisher IDC
Published May 27, 2025
Length 8 Pages
SKU # IDC20068545

Description

This IDC Perspective discusses the current state of value stream management (VSM) and AI intersection (primarily in the form of large language models [LLMs]) and how organizations can plan and prepare to leverage AI and VSM in the future. Value stream maps represent detailed “pictures” of business and digital processes that have served as a cornerstone of lean thinking and process optimization for years. These same maps, when loaded into GenAI tools, can be transformed into active decision-making tools that can perform optimization analytics far beyond the capabilities of humans alone. While the intersection of GenAI and VSM is in its very early stages, the potential for continuous improvement and competitive advantage is in reach in the short term. The following four areas will be explored with input, comments, and thought leadership from interviews with four industry experts:How value is created by applying GenAI to VSMThe power of GenAI value stream simulationApplying GenAI to optimize VSM flow metricsTips for GenAI prompting“Value stream management has a rich history of helping teams optimize value streams through rigorous value stream mapping. Now, the data from the value streams can be loaded into AI tools to perform dynamic VSM optimization with much greater speed and depth,” says Bob Multhaup, adjunct research advisor for IDC’s IT Executive Programs (IEP).

Table of Contents

8 Pages

Executive Snapshot

Situation Overview

How Value Is Created by Applying GenAI to VSM

Optimize Business Outcomes

Optimize IT Software Development Life Cycle

Optimize Flow Metrics

Other AI/VSM Opportunities

The Power of AI Value Stream Simulation

Building VSM Digital Twins

Training an LLM to Optimize a Digital Twin

Using AI to Understand Causality

Applying GenAI to Optimize VSM Flow Metrics

Deep Dive into Flow Metrics

Tips for GenAI Prompting

Advice for the Technology Buyer

Learn More

Related Research

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