Using Star data at different levels in an organisation #
Star data is most effective when it is understood, shared and used at different levels within an organisation. The approach to using Star data may differ at different levels but the aim is always to learn and improve the outcomes of the people being supported.
Some levels in an organisation where Star data may be used are:
- Practitioners and the people they support – to understand where someone is on the Journey of Change and agree priorities and next steps
- Managers and practitioners – to support reflection, supervision, and ongoing practice and service improvement
- Senior leaders and external stakeholders – to see overall patterns across the organisation and support learning and improvement at scale
- Implementation leads – to oversee and strengthen how the Star is introduced, embedded, and used consistently
- Other teams (e.g. training, development, data and insight) – to support learning, impact reporting, and effective use of Star data.
Using Star data well is a whole organisation project and one that requires engagement and an understanding of what the Star is, how it works and what it measures at all levels.
Star data is most valuable when it’s used close to where it’s collected. When practitioners and the people they support use the Star together, and when Service Managers review that data, there’s rich context to help make sense of what the readings really mean. At this level, detail and nuance are still visible.
Star data can also be helpful at organisational or strategic levels, but the further it moves from the point of collection, the more care is needed in interpreting it. Patterns should be explored alongside other data and informed by conversations with practitioners and managers who know the work and the people behind the numbers.
Regular use of Star data also strengthens data quality. When Team Leaders or Service Managers routinely review Stars, they can spot issues early — such as Stars being completed too late or readings that don’t reflect the scale descriptions — and offer support to improve consistency. This shared use creates natural checks and balances, making the data more reliable and useful at every level.
The best way to report on Star data #
There are three types of reporting that we recommend when we look at Star data, and these are available as ready-made reports within Outcomes Star Online:
- Implementation reporting
- Snapshot reporting
- Distance-travelled reporting
These different types of reporting serve different purposes but used together can help ensure good quality Star data can provide insights for service learning and development as well as service evaluation.
Implementation Reporting
Helps to monitor Star use and ensure data quality
Implementation reporting allows a service to measure against the service guidelines that they have developed to ensure that the Star has been implemented well in a service to allow for good quality and meaningful Star data.
Implementation Reporting looks at:
- How many Stars have been completed – checking that first and review Star are being done
- When Stars are completed – looking alongside the service guidelines as the timing of Stars is important and can affect their accuracy
- How Stars are being completed.
Snapshot reporting
Helps to focus resources where needed, identify training needs and tell a story
Snapshot reporting looks at the distribution of readings across the Journey of Change in each Outcome Area when looking at one specific Star reading.
Snapshot reporting can be used in a variety of ways:
First Stars
By looking at everyone’s first Stars across a cohort the service can see what people’s needs where when they first started support in the service. This can be used to answer a variety of questions:
- Are first Stars accurate?
- Do the people we are supporting match our referral criteria? Are we getting the right people through the door?
- In which area do people have highest support needs?
- Is the service supporting people in the areas that they need support in?
- Does the support given match where people tend to be on the Journey of Change when they start support?
A Snapshot report of people’s first Star can also be useful to look at alongside a Distance-travelled report for the same cohort. The Snapshot of people’s first Stars is saying ‘this is where people started’ and then the Distance-travelled is saying ‘and this is the progress they made’. This allows an organisation to really explain the journey the people they support have gone on.
Last Stars
A Snapshot report could also be used to look at everyone’s Last Stars and ask questions like:
- Are people getting to the Journey of Change stage that we would expect?
- Are we supporting people long enough?
- Are we referring them onto the right services based on where they get to on JOC?
Latest Stars
A Snapshot report can look at people’s latest Star:
- Where are the people we are currently supporting on the Journey of Change in each area?
- Where should my time be distributed across my current caseload?
- What activities would be useful for the people we are currently supporting?
- Do current action plans match where people are on the Journey of Change?
Snapshot reporting is great when being done across the organisation – at that caseload level, as well as across services and the whole organisation. Needs can be looked at over time, as well as across different cohorts.
Distance-travelled reporting
Helps to develop service delivery, improve outcomes for the people being supported and evidence outcomes
Distance-travelled reporting is looking at where people have progressed, maintained and dropped back in each Outcome Area between a baseline (e.g. 1st) and comparison (e.g. last) Star. We recommend using percentages when looking at distance travelled.
The Distance-travelled report is useful for both service learning and evidencing outcomes. Looking at a Distance-travelled report can allow and organisation to ask questions such as:
- What is this report telling you?
- Why might this be?
- How can we respond to this?
Including narrative for a meaningful picture #
Practitioners and Service Managers can provide valuable narratives to make sense of Star readings at an individual or for reports at cohort level. For example:
- Why readings may have moved backwards due to circumstances changing
- How the scope or funding of the service affects the change that is possible in a particular outcome area
- How external factors such as changes in policy, housing or employment opportunities may have affected start points or change
- Why one service is showing different start points or change on the Star than another – e.g. due to the geographic area, the nature of referrals or the availability of different services.
This type of contextual information, presented alongside reports – whether as case studies or broader cohort level information, will greatly improve the meaningfulness and learning that can be derived from the data.
Reporting against expectations #
One of the most useful ways to use Star data is to report against the services expectations. Using Star data in this way allows an organisation to ask better questions of the data and helps them to learn from their Star data. Because each service using the Star has its own context, remit and approach, it makes sense that each service needs to set their own expectations around their Star data. It is possible to apply the same approach to Star data at different levels, from whole organisation to a specific service, caseload or even an individual service user.
By reporting against expectations, a service can:
- Highlight where the data is different to those expectations.
- Use any differences as a starting off point to try and understand why this might be.
- Pinpoint any implementation issues with the Star in your service
- Highlight broader questions around the people you are supporting and the support you are providing.
- Use Star data and learning to continue to improve outcomes for the people being supported.
| What to look at | What you can learn |
| Starting points | Whether first Star readings are a good baseline for your Star data – or whether a more realistic baseline is achieved on second Stars when a practitioner has started to develop a relationship with a service user. Whether people are entering your service with the expected and appropriate levels of need, perhaps relating to the funding you receive or the remit of your commissioned service. Whether the initial Star readings seem accurate (ie if practitioners are completing first Stars correctly). |
| End points | Whether the final/review Star readings being recorded seem accurate (ie if practitioners are completing final/review Stars correctly). Whether people leaving your service have achieved the expected outcomes in key outcome areas. |
| Key milestones in the journey | Whether people are making the progress that you would expect and if they are likely to achieve the end points you think are likely across different outcome areas. Not all areas may have ‘interim’ milestones – it will depend on the nature of your service and the people you support. |
Comparing cohorts #
More learning can be gained from reports by comparing data across different cohorts
This could be:
- Comparing data from different time periods
- Comparing people with differing support needs
- Comparing people with different demographics
- Comparing outcomes across services or area
Comparing different cohorts allows you to ask questions like:
- Is there other evidence that one cohort achieves better outcomes than others?
- Does practice differ between cohorts and could there be an opportunity for shared learning?
- Do some groups of people need more support in areas than others?
- What can we do to ensure that all people get the targeted support that they need.
Outcomes Star Online allows you to filter the ready-made reports to support comparison across cohorts.
Reporting with multiple Star versions #
It is common for an organisation to use more than one version of the Outcomes Star when supporting a range of people with different needs. However, when reporting on the readings in completed Stars, it is not possible to report across different Star versions. This is because different versions of the Outcomes Star are designed for people with different needs, underpinned by different Journey of Changes and include different Outcome Areas.
However, there are some high-level trends that can be reported across different versions of the Outcomes Star. Please note, currently the facility to report these high-level trends across Star versions is not currently available with Outcomes Star Online.
Looking at starting points
The percentage of people with significant needs in at least 1, 2 and 3 outcome areas:
NB. The % of ‘All clients’ is skewed towards the Star with more client readings (i.e. the Homelessness Star above). To calculate the likely level of need given equal numbers of readings for each version, take the average % (i.e. 90% for at least 1 area at 1-3).
Looking at change
Looking at the number of Outcome Areas in which each person progressed in, and then calculating the proportion of all people who moved forward in at least one, at least two and at least 3 outcome areas.
NB. When the versions of the Star differ in whether they have a 10- or 5-point scale, ‘moving forward’ should be defined as moving forward by at least one Journey of Change stage (e.g. moving from 1-2 on a 10-point scale would be counted as no change).
Reporting on Star data by time-period #
The key decision to make – what do you want your data to show?
When reporting by time period, you will need to decide what you are interested in demonstrating in that time period and what data needs to be included.
There are different ways a time period can be applied – for example, you may want to look at Star readings only for those people who have joined and left the service in the time period. Or, perhaps you are interested in demonstrating peoples’ progression up to a specific point in time, but for people whose support is ongoing.
Creating a report, with a time period applied, that is right for you partly depends on how people join and leave your service. For example, if you have a defined ‘term’ for specific groups, your decisions will be more straightforward. If you have a rolling intake, defining exactly what change you want to show relevant to a time period is more complex.
- When you know what you want to demonstrate you can define:
- What Stars you will use as your baseline
- What Stars you will use as your comparison
- Whether these need to be inside your time period or outside of it.
Some options for how Star data can be reported on by time-period are listed below.
| Option | Example question | What to include | Key points |
| Looking at change that has taken place within the time period | What change has taken place in the last 6 months for people receiving support? | Include the Earliest and Last Stars within the time period. | • Shows only change that took place within that time period. • Misses change recorded before or after the time period. • If the time period is very narrow, the sample size may be too small. |
| Looking at change that has taken place up to the end of the time period | For people we supported in the last quarter, what total progress did they make from when they started support up to the end of the quarter? | Include the First ever Star and the Last Star in the time period. | • Shows all change that occurred for people up to a specific moment in time. |
| Looking at the total change for people who started and ended with the service within the time period | What percentage of people progressed in each outcome area between their first and final reading in the last financial year? | Include only people with both a First ever and Final ever Star recorded within the time period. | • Shows a definitive picture of change for that period. • Includes only people who joined and left the service within the time period. • Different from Option 1, which can include people who were with the service longer than the specified time period. • If the time period is very narrow, the sample size may be too small. |
| Looking at change started and achieved within the time period | For those who started support last September, what progress did they make by July? | Include only First ever Stars and Last Stars. | • Shows change started within the time period and achieved before the end of the time period. • Can include people who are still with the service and may achieve more change later. • Unlike Options 1 and 2, it does not include people who joined before the time period began. • Unlike Option 3, people can go on to achieve more change after the time period. |
| Total change achieved up to the end of the time period | Looking at those who ended support last year, what progress did they make? | Include only people with a Final ever Star within the time period, using their First ever Star as the baseline. | • Shows the total change those people achieved. • Different from Option 2 because it only includes people who left the service within the time period. • No further change can be recorded for them by the service. |
| Total change that has taken place within the time period | What progress has been made by people in the last quarter? | Include only service users with a Final ever Star within the time period, using their Earliest Star in that time period as the baseline. | • Shows the total change those service users achieved within the time period. • Misses any change recorded before the time period. |
Caseload reporting #
Regular reporting on caseloads can be really helpful in an organisation. It ties into the importance of using Star data across an organisation and can really help get buy into the Star from practitioner as they see the usefulness of Star data.
Caseload reports can be used in supervision sessions, team meetings, peer-to-peer support or whatever practice support sessions an organisation implements.
Using Implementation reporting, Snapshot reporting and Distance-travelled report, reporting on caseloads can:
- Review individuals
- Look at caseload as a whole
- Provide a basis for discussion
The benefits of reporting on caseloads
Caseload reports can highlight the needs of people being supported and identify gaps in resources and support
Reporting at this level also gives an opportunity to add a narrative to Star data – leading to a richer and more powerful dataset
It can also flag issues around Star completion, check accuracy of readings and check actions are appropriate to a person’s Journey of Change stage. This can in turn help identify any training needs for the practitioner.
Evidencing outcomes with Star data #
If an organisation has good quality data then there are lots of ways they can present it and draw on it to evidence the great work that is being done.
Star data can be used to attract funding and to demonstrate the effectiveness of funding.
It can also be used to increase awareness of an organisation and to encourage campaigning.
Top tips for evidencing outcomes with Star data
- Identify your target audience and report in more or less detail depending on that audience
- Choose a format to suit that audience (this might be a website, blog, PDF, infographic)
- Explain what the data is showing. Not everyone will be familiar with the Outcomes Star and the data, so you need to explain to the audience what the data is based on and what it shows
- Include case studies and statements to make the data more meaningful for the reader
Describe how the organisation will use the data to develop services and continue to support people
If you are reporting to commissioners discuss Star data with them in advance and what it can be used to show to ensure what they are asking for is meaningful.