Case Study: Team Dependency

Insights into Team Dependencies and Team Structures increases productivity by 15%

Team structure(s) heavily impact the performance of engineering projects.

Where teams are new, projects are large, or where team members work across multiple projects, agile management approaches are needed.

However, team structures and co-working are often only outlined or recorded when set out in initial planning and do reflect the reality of complex collaborative working.

Without up-to-date and accurate data on team working, the evidence to support decision-making and increase productivity is all too often non-existent, limited, or severely lagging.


Providing an means to monitor, review and evaluate team structures and dependences based on what is actually completed, not just planned.

To capture all influential relationships, this needs to go beyond the work of individuals or within teams to include both formal and informal cross-team co-working and collaboration.


KADlytics’ tools monitor the digital engineering work of the entire team – both as a whole and as individuals.

This is mapped against the work of related teams to generate a work graph of the entire system, identifying teams of people and teams of teams related by their work that transcend pre-planned structures.

Analysis of this ‘work graph’ empowers us to identify workflows and hidden structures, uncovering the ‘real’ inter-team and inter-personal dependencies within and across projects or even companies.

KADlytics dependency map, capturing dependencies between systems and teams across the project hierarchy and system architecture


Our maps give managers a real-time and evidenced-based understanding of what is actually happening within their projects (as-practiced), rather than as-planned.

Placing this data at the fingertips of decision-makers empowers them to make the right decisions, investigate the effectiveness of their teams, and learn from past successes to improve in the future.

Amongst many capabilities, managers can evaluate the roles of team members, cohesion of teams, team configurations and levels of inter-team dependency, letting them determine if their structures are well suited to the reality of work.

By focusing on individual teams or workers, they can identify gate keepers, who should attend meetings, or who should be moved to increase productivity elsewhere.

By reorganising data and seeing the effect to the resulting workgraph, managers can evaluate the impact of change from leavers or reallocations, and form better plans for future work.

Our case study resulted in a 15% improvement in performance and productivity for a multi-disciplinary team of 40.

Association dashboards, allowing understanding of progress and relationships of related systems across teams and the project timeline