Accepted Value Costing, Lean Value Stream, Agile Dynamic Budgeting, Value-based Decision-making, Proportional Cost Allocation, Activity-based Cost Driver, Product Owner Measure Business Value

Accepted Value Costing Annotated Bibliography

David Hughes
Originator of Accepted Value Costing

Accepted Value Costing^SM (AVC) is the evolutionary approach to Lean-Agile decision making. David pioneered the concept in 2014 on a multi-team Agile program at an American multi-national managed healthcare and insurance company, and then applied it at the portfolio level at the leading American commercial mortgage real estate services company through 2017. Since then, AVC has reached maturity through use by hundreds of Agile teams at-scale with financial, investment management, banking, and service firms. AVC presentations and workshops have been delivered at Agile conferences since 2018.

AVC At-a-Glance

Focuses thinking about money in terms of valuable outcomes instead of tracking expense for planned outputs.

A lightweight, cost-effective approach for identifying low-value/high-cost epics and eliminating them from the value stream at the earliest possible moment. AVC recommends Roman Pichler's product vision board as part of the AVC process for defining and continuously refining an epic hierarchy.

Time-phased epic analysis using sliding windows of time reveals the cumulative effect of continuous Agile decision making for epic expansion, contraction, or stagnation.

Time-phased epic analysis is perfectly suited to the Kanban Method, especially when driving the operations review in Enterprise Services Planning. AVC directly supports Kanban practices at maturity levels 3 and 4 for implementing feedback loops and managing flow as described in the Kanban Maturity Model. Click here to view the AVC-KMM integration graphic. Visit the KMM LinkedIn page for more information. Watch the lightning talk at Kanban North America 2018 to learn more.

Originally created to implement the Scaled Agile Framework's Lean Budgeting approach.

Scales from the individual team level for product owner decision making to the enterprise portfolio level for executive decision making.

Data extracts are designed for the major Agile lifecycle managament tools: JIRA, Rally, VersionOne.

Decision Model Conclusions