Case Study: Technical dependency

Insights into technical dependencies during New Product Development avoids rework and late changes

When designing new products or undertaking significant upgrades to existing products, it’s rarely possible to establish all dependencies in advance. Many dependencies emerge as the product develops, with evolving relationships between systems and components that create a complex web of dependencies that engineers have to navigate.

Such hidden or emerging dependencies are frequently the cause of costly rework and delays.

Automatic Dependency Detection and Mapping (ADDM) tools exist for the software industry, but until now haven’t been transferable outside of well-connected IT infrastructures to consider mechanical (or non-digital) systems.

Challenge.

Detecting forms of structural, behavioural and functional dependencies in technical systems is neither trivial nor deterministic.

Systems can have 100s of systems and components with 1000s of connections, with an architecture that evolves over time and is an emergent feature of the engineering (design) process. 

This emergence makes it very difficult to predict dependencies prior to development, while their high number also makes them difficult to capture and manage as development continues.

Approach.

We monitor the digital engineering work of the each person within a team and every asset within a project.

This lets us capture, map, and analyse evolving work graphs of activity that encompass all aspects of project working, and infer potential dependencies between engineering systems, sub-systems and components.

KADlytic’s tools infer dependencies as they appear in real-time, or can be applied to historical data to understand past projects and structures, which in turn can be used to better plan for the future.

Dependency network within the complex system architecture.

Benefits.

Our analysis automatically generates a map of dependencies for a system or product, which can in turn be used by managers to interrogate its state and characteristics.

This workgraph creates a detailed data source that supports investigation, analysis, and decision-making across purposes, as well as automated monitoring and flagging of events, record keeping, and product auditing.

Core opportunities include identification and monitoring of critical dependencies to ensure productivity and avoid delay, identifying critical paths for efficient system development and stage-gating, optimisation of system structures to support efficient working, and support scenario planning by exploring the potential impact of changes, events, and interventions.

KADlytics dependency dashboard – complexity and progress tracker