Bromcom’s MAT Vision has removed a great barrier to efficiency many of our MAT customers faced as it means data flows automatically from Bromcom Cloud MIS systems into a central warehouse and so they no longer need to manually chase schools for data and manually add it to spreadsheets. However, simply having the data in the same place does not automatically mean you can use it to make useful comparisons.

When analysing Attendance, Student Demographics and Exclusions consistency is to a large extent guaranteed by the high degree of statutory control over what and how data is recorded. For this reason much of our early BI development has been in these areas.

Assessment data in Bromcom is tied to meaningful associations such as the subject, year and term of the collection as well as the assessment type. This means that in order for trust wide assessment analysis to be possible, MATs must harmonise their subject and year names. While this requires an investment of effort, it will be more than repaid due to the better analysis and easier sharing of expertise enabled by use of common names and structures. The new Group Details page in the MIS means that making these changes is quicker and easier than before.

A consistent naming convention is a necessary condition for effective analysis in MAT Vision but not a sufficient one. Two teachers can use the same form to describe a Prediction, in Maths, in Year 11 in Autumn of grade 5 – but the underlying realities they are describing with those two judgments could still be wildly different.

Technology can only play a limited role in solving this dilemma. However, it’s important to raise here because for many trusts the process of getting data, any data, in a collated form has been so torturous that it can feel like the end of a journey. We would be doing our customers if we presented MAT Vision as a short cut to that destination. Easily collating teacher judgments from across the trust is not the end of a process but the beginning, as those judgments must be checked and calibrated before they can be relied upon to provide meaningful information.