New Zealand Police Automates Case Intake and Routing on Appian

Appian, a leading low-code automation software company, has announced that New Zealand Police is using the Appian Platform to reshape its case management approach, citing early results that reduced turnaround from 2+ weeks to 4 hours. The case study describes an environment in which case workflows were previously managed independently across three regional units using Microsoft Outlook, a model that created duplicated effort and constrained collaboration across New Zealand Police’s 12 policing districts.

According to the case study, the Frontline File Management Team previously manually triaged cases, identified priority matters, and routed work to the correct Police District, a process the organisation described as time-consuming. The new capability, built on the Appian Platform, centralises incoming emails and case data, automates workflows, and enables nationwide access, allowing staff to work from a common system rather than regional inbox-driven processes. The system also surfaces the correct case assignment rule based on offence code, location, and keywords, and matches work to appropriately trained staff.

Operationally, New Zealand Police reports that since deployment, case backlogs have fallen from roughly 4,000 to under 50 on most shifts, and staff can now collaborate in real time regardless of location. The organisation also states it can respond to public enquiries faster and more accurately, reflecting how automation and shared visibility can improve both throughput and the quality of frontline responses.

Benefits for Enterprise Process Teams

Appian and New Zealand Police describe a shift from regionally managed Outlook workflows to a centralised intake and workflow model that applies rules and enables real-time collaboration across districts. That shift can be relevant to CIOs and process owners looking to standardise front-door operations, such as customer service, shared services, and HR case handling.

New Zealand Police also emphasised decision support and planning, noting that demand had been difficult to understand before, but now has analytics that support intentional decision-making and help deploy staff where needed most. This is a key point for technology executives because the outcome is not only faster processing but also measurable operational visibility that supports staffing and service-level decisions.

The case study further frames the change as moving staff away from repetitive administrative work and towards meaningful case assessment, an approach many SAP teams are similarly pursuing as they modernise workflows around core systems.

What This Means for Mastering SAP Insiders

Faster intake automation reduces costs and boosts service responsiveness. For technology executives, the New Zealand Police results provide concrete metrics, including a reduction from up to two weeks to four hours and backlogs from 4,000 to under 50, that can help justify funding for workflow orchestration that sits around ERP and standardises how work enters the enterprise. Day to day, this shifts teams from manually reading, sorting, and forwarding requests to managing exceptions, refining routing rules, and monitoring throughput with operational analytics.

Market momentum is shifting towards process orchestration that bridges unstructured work and systems of record. Appian positions its platform as AI-powered process automation, and the New Zealand Police example shows that rules-based routing and centralised data intake can deliver measurable improvements even before advanced AI use cases become the primary story. In practice, SAP professionals will spend more time designing end-to-end processes and integration touchpoints and less time building one-off mailbox workflows and local spreadsheets.

The evaluation focus will shift to governance, routing accuracy, and operational transparency. New Zealand Police explicitly cited inconsistent file management before the change, so buyers should prioritise standardisation features (shared queues, consistent assignment rules), analytics for demand visibility, and controls that support distributed teams collaborating in real time. For SAP landscapes, the best practice is to keep the system of engagement handling intake, triage, and status communications while synchronising the appropriate master/transaction references into the ERP. This reduces SAP customisations while still improving cycle times.​