How Kisharon Langdon halved its analysis time

Kisharon Langdon's digital strategy had already reached its conclusion: let each expert platform hold the data it is good at holding, and build one central layer that can answer questions across all of them. The all-in-one social care platforms they looked at were not yet good enough. The question was how to build the middle.

The intended route was Power BI and Power Automate, built in-house. Staff started upskilling and the route stalled, because a charity does not have the coding capacity to build an analytics layer across the organisation quickly enough. The deeper problem was starker than slow analysis.

Mira connects read-only to the platforms the charity already runs and uses data uploads to analyse data from teams including Finance, HR, Care, Programming, Training and Education. It maps how they fit together, so a question reaches all of them at once. Questions are asked in plain English, and every answer comes only from their own data, with a trail back to the source it came from.

Fifteen governed departmental workspaces mean each team sees its own scopes and nothing else, set once and applied to every answer.

• Ten digitally confident early adopters ran a three-month trial, trained in sessions matched to their skill level, with an internal champion as trainer.
• A DPIA was completed with their data protection officer before any data was shared, under a data processing agreement with an ISO 27001 certified supplier.
• Mira exposed gaps, duplication and redundancy in the underlying data faster than the team would have found them alone, which was uncomfortable and useful in equal measure.

Recruitment trend analysis across eighteen months of data went from one to two hours of manual spreadsheet work to roughly fifteen minutes, with trends and charts the manual version never produced. The finance team analysed a set of management accounts in about an hour and the figures matched exactly.

Two independent checks were run deliberately. An external consultancy's comparative fee and value-for-money analysis, was reproduced from the same raw data, matching apart from rounding, and is now repeatable in-house at no marginal cost. Training evaluation for the Oliver McGowan programme, 165 completions, went from largely unanalysed feedback to full analysis that updates itself as new sessions arrive.

The quality team interrogated care notes twice from one dataset, once as a service manager and once as an experienced CQC inspector. Mira returned a review structured around the CQC framework, surfacing gaps in records and differences in recording quality between staff that nobody had visibility of. It also highlighted strengths in reporting and aligned to the framework.

Analysis time across the trial was cut at least in half, before counting the analysis that was not happening at all. On the evidence, the board approved a twelve-month deployment.