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Dunelm PowerBI Help

Dunelm PowerBI Help

Owned by Alex Gooding
Last updated: Sept 27, 2019
7 min read

These charts are designed to help each team to be more aware of their work, identify improvements and create more accurate predictions.

Charts like this won't give you answers, but they should help you ask better questions!

 

BurnUp / 'Landing Zone'

Purpose: Show the likely range of dates that a piece of work is likely to finish.

Primary audience: Stakeholders and team

Uses:

  • Can be used for a team but more likely for a Fix Version or Epic

  • Adjust assumptions about scope and throughput rate to see how this might effect the dates

  • Review history to see if throughput or scope have had any expected changes

Settings:

  1. Toggle between count of Issues or Points (if you have done estimating)

  2. Select the date range - either manually here or with the slider

  3. Adjust the rate at which the scope line is flattened out.

    1. The projected scope is based on assumed adjustments to the historical rate and the rate of scope growth. Higher numbers will flatten out the projected scope. The number refers to the rate at which the scope projection is decreased by..

    2. There is a upper and lower scope increase to give you a range

  4. Adjust projected completion rate. This shows the range of completion rates, based on historical completion rate.

  5. The manual override enables you to make assumptions about throughput rate.. and it overrides the historically based rate in (4). You might use this if there is not yet any history for the fix version / epic

  6. Decide on what your 'Definition of Done' state is

  7. Use the slicers to select Project, Fix Version, Components or Labels. These filters in this section persist across all charts.



Epic Progress

Purpose: Show relative size and progress of the Epics .

Primary audience: Stakeholders

Uses:

  • Communicate progress and priorities at a level that most stakeholders are going to be able to engage with

    • Story-level is probably too low granularity for most people outside of the team

  • See if team focus is scattered across too many Epics - possibly reduce WIP

Settings:

  1. Shows proportion of the backlog that is un-estimated issues

  2. order by either

    1. Rank: The Rank (priority) in the backlog

    2. % Complete

    3. Size

  3. Slice by any of these criteria

 



Completed work / day (by type)

Purpose: See the mix of work being done by a team - showing Issue Type

Primary audience: Stakeholders and Product Owners

Uses:

  • Review if it is the optimal balance of work being done

  • Decide if adjustments need to be made in the prioritisation of work coming to the squad

Settings:

  1. Change the date range (or use the slider) to select dates that issues were closed

  2. Use the slicers to select Project, Fix Version, Components or Labels. These filters in this section persist across all charts.

  3. Toggle between count of Issues or Points (if you have done estimating)



 

Control chart (Scatter plot)

Purpose: Use to identify outliers and trends in cycle times

Primary audience: The team

Uses:

  • Useful input to retrospectives to review the trends and patterns

  • Identify outlier stories and see if there is a pattern or underlying cause

Settings:

  1. Shows the median for this data set

    1. This can be compared over time to see if trends are changing

    2. Note: we are looking to add trends, but this cannot be done with 'native' PowerBI

  2. Choose date range (

    1. Power BI doesn't enable us to show dates on the X-axis, and so we have had to use number of days in the past, from today.

  3. You can filter out the big outliers, as this can flatten the chart for the majority of stories ( logarithmic scales not yet available in PowerBI)

    1. Caution: your choice of Max cycle time will reduce the dataset and therefore change the Median time and 85th percentile

 

Lead time Histogram

Purpose: Predict how long it will take to finish a new story.

Primary audience: Team, Delivery managers

Uses:

  • Identify outliers (very long lead time) and investigate root causes

  • See what the 85% is (not yet on this chart -coming in later version, may need non-PowerBI functionality)

    • Can then say that the squad is able to turn around 85% of work within x days. This can be compared over time

  • See how predictable the squad is. Tighter spread of columns indicates more predictable

Settings:

  1. Shows the number of stories that took x days (cycle time) to get across the state(s) selected in 2

  2. Select what you want to measure cycle time across

    1. e.g. how much time stories spent in development

  3. You can see one more more issue types

  4. Decide if you want to remove outliers

  5. Select data range

 

Item Ageing Detail

Purpose: Identify work that has become stuck or forgotten whilst in the selected state e.g. In progress or 'ready for deployment'

Primary audience: Team and Delivery manager

Uses:

  • Identify work that needs to be resolved (either done or discarded)

  • Y axis

Settings:

  1. Choose the state which you are interested in

  2. Narrow search by one of the slicers

  3. Y-axis shows the number of days that each item has been in that state

 



Throughput History Trend

Purpose: Shows the number of stories of total story points completed each week over time, with a trend line.

Primary audience: Team

Uses:

  • See how the items being completed is trending over time

  • Show the team how volatile their completion rates are changing

Settings:

  1. Relative date selector

  2. Slice by any of these criteria

  3. Turn trend lines on/off

  4. Shows the average through-put per week for the time period selected

  5. Change to ‘Points’ or Count

 

Planned Vs Un-Planned

Purpose: Shows the ratio of planned (stories) and un-planned (defects, other) work over time.

Primary audience: Team

Uses:

  • Show the team how many of their time is being spent on un-planned work

  • Show the team how volatile their completion rates are changing with respect to planned and un-planned work

 

Settings:

  1. Relative date selector

  2. Slice by any of these criteria

  3. Turn trend lines on/off

  4. Change to ‘Points’ or Count

  5. Shows the average through-put per week for the time period selected for Stories, Defects and Other work item types

 

 

Defect Percentage Trend

Purpose: Shows how the percentage of all work completed, which is un-planned, changes over time

Primary audience: Team

Uses:

  • Allows the team to look back at heavily un-planned periods and to try and analyse what was the cause in order to stop it re-occurring

  • Allows the team to look for patterns of increases in un-planned work

Settings:

  1. Relative date selector

  2. Slice by any of these criteria

  3. Turn trend lines on/off

  4. Change to ‘Points’ or Count

  5. Shows the average amount of work each week that is made up of un-planned defects

 

CFD

Purpose: Shows the flow of work through the team’s various states over time

Primary audience: Team

Uses:

  • Allows the team to

    • Check their flow

    • Determine bottlenecks in their system

    • Predict future blockers

Settings:

  1. Relative date selector

  2. Slice by any of these criteria

  3. Show/Hide certain backlog statuses

 

Lead Time By Phase

Purpose: Allows the team to define their preparation and delivery lead time definitions and see how they trend over time

Primary audience: Stakeholders, Team

Uses:

  • See how the different lead times trend over time and allow action to be taken where appropriate to help maintain/decrease it.

  • Shows the ratio between the preparation and delivery aspect of delivery

Settings:

  1. Relative date selector

  2. Use this filter to select the team’s 'Delivery Lead Time' statuses

  3. Use this filter to select the team’s 'Delivery Preparation Time' statuses

  4. Slice by any of these criteria

 

 

85th Percentile Lead Time

Purpose: Shows the trend of the 85th percentile of lead time for different work item types

Primary audience: Stakeholders, Team

Uses:

  • The 85th percentile gives the team a good idea for outwardly telling stakeholders how long it takes an item to be completed

  • The visual is broken down into different work item types so the team can see how long planned and un-planned work takes respectively

Settings:

  1. Relative date selector

  2. Use this filter to define the ‘Lead Time’ definition for the team

  3. Slice by any of these criteria

  4. Turn trend lines on/off

  5. Shows the 85th Percentile lead time over the selected date rate (in days)