Transformation Leaders

Prove whether your transformation is improving delivery.

Establish how delivery performs before the change, see where intervention is needed, and use the same evidence afterwards to show leadership what changed.

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Nave Executive Dashboard comparison for the Digital Payments teams: 85th percentile cycle time for 7 to 20 September against the two weeks before. Payments API 17 days, down 23% from 22 days; Payments Mobile 17 days, down 37% from 27 days; Payments Web 17 days, down 19% from 21 days

Before the change

Establish the baseline before you change the system

Know where you’re starting.

Before changing operating models, introducing Kanban, reorganizing teams, changing delivery practices or rolling out AI, establish how work actually flows today.

Measure

  • Cycle time
  • Throughput
  • WIP
  • Flow efficiency
  • Process-step performance

Now the transformation has a baseline rather than anecdotes.

Detect and investigate

Find where the system actually needs changing

Don’t change every team because an aggregate metric moved. Natural process limits identify meaningful signals, then the AI Investigator shows where the problem is and the work behind it.

The numbers are computed, not generated. The AI only reads them, so swap the model and the numbers don’t change.

Nave AI Investigator insights for Payments API, 3 August to 25 September 2026. Celebrate: WIP has dropped sharply from a period average of 19 to 11, and all current items are flowing within stage percentiles. Monitor: Ready for SIT is a queue with high variability, p50 is 3 days but p85 jumps to 17 days. Monitor: items 1169 and 1170 have identical timing across all stages, likely a coupled pair that should be tracked as a unit. Monitor: Awaiting Release has the second-highest average WIP (5.17) and wide variability, release cadence may be batch-driven

Intervene

Make a targeted intervention

The transformation team makes the decision.

  • Reduce WIP.
  • Remove an approval.
  • Change a handoff.
  • Alter a policy.
  • Rebalance capacity.
  • Redesign part of the workflow.

Change the part of the system the evidence points to, not the whole operating model.

After the change

Prove what changed afterwards

Show what changed, not what you implemented.

Did delivery actually get better?

Nave Value Stream comparison for Digital Payments, 7 to 20 September against the previous two, six and twelve weeks. Average throughput: Payments API 12.00 against 13.00, 15.00 and 10.17; Payments Mobile 6.00 against 6.00, 7.33 and 6.50; Payments Web 6.00 against 8.00, 9.67 and 7.00. Average WIP: Payments API 9.07 against 11.14, 12.76 and 15.12, down 40% over twelve weeks; Payments Mobile 6.50 against 8.14, 7.29 and 9.17; Payments Web 6.29 against 7.64, 8.60 and 9.51
Run the investigation again after the intervention and compare the evidence.

AI adoption

Measure the impact of AI on delivery

Your developers are coding faster. Are customers getting value faster?

AI can shorten development time without shortening the entire delivery system.

Use end-to-end flow data to establish what delivery looked like before AI adoption and measure what changes afterwards.

Services and Portfolios

One evidence base across the transformation

Your teams don’t need to use the same tool for leadership to get one view of delivery.

  1. Teams
  2. Services
  3. Portfolios
  • Jira
  • Azure DevOps

Executive visibility

Report the transformation to leadership

Give leadership evidence of whether delivery performance is changing.

The point isn’t to report more metrics. It’s to show whether the changes you’re making are improving delivery.

Nulogy uses Nave to facilitate team meetings and corporate KPI reviews.

Read the story
Portfolio dashboard: Retail Banking
Nave portfolio dashboard for Retail Banking: average cycle time 19 days 8 hours 49 minutes and throughput of 112 work items, each split by issue type (Story, Task, Bug, User Story), above the portfolio's WIP Trends and Throughput Trends from July to September 2026: work in progress climbs through July and August, drops at the end of August and stays lower through September, while throughput rises to August and falls back in September

Customer evidence

What proving the change looks like in practice

Teams use Nave to find where work is getting stuck, make targeted changes, and show what happened next.

0.521.09

Items finished a day, measured again across August.

“After implementing an action, we need to go back to the data to understand whether there really was a change.”

Joelma Castro Agile Master and Squad Leader
Read Joelma Castro’s story

3322 days

85th percentile delivery time, within a month.

“We use the Cycle Time Scatterplot and Cycle Time Breakdown chart during retrospectives to get a bigger picture of the current situation.”

Pawel Lewinski Scrum Master and Accredited Kanban Trainer
Read Pawel Lewinski’s story

Prove the change with delivery evidence.

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