Design Thinking: this is a recognised consultative technique that is a highly effective way of kicking off a DPA initiative. Essentially it involves re-imagining what a service or customer (or employee) experience should ideally look like, ignoring any known issues - such as inherent constraints of legacy systems, current process bottlenecks etc. - that would currently prevent that ideal from being achieved. This is done through a consultative process including all relevant stakeholder groups across the business. The outputs then provide the context for the DPA project.

Business Process Management (BPM): Using the ideal outcome defined by the Design Thinking exercise as a goal, the BPM activity requires a deep dive Discovery process to understand all the moving parts, connections and dependencies across the organisation that are relevant to that outcome. Using Case Management techniques, the journey to that outcome can then be charted accurately. Workflow management, extensible layers around legacy systems, integration tools and the other technologies mentioned below can then be used to drive the automated end-to-end journey.

Robotic Process Automation (RPA): RPA technologies can have a significant role to play as part of the overall DPA initiative - but they need to be used selectively in use cases that play to their strengths. They are particularly strong at automating high volume, structured “closed” tasks that currently require repetitive manual work (e.g. manual data entry etc.) performed by clerical staff working with fragile legacy systems. Those types of processes (and those kinds of legacy systems) can often be major obstacles to delivering the desired super-efficient end-to-end journey. Working as “digital assistants” to the staff engaged on these tasks, the RPA software provides an alternative approach as it takes over the heavy lifting on these repetitive predictable tasks and performs them much faster (and typically with less errors) than staff using old legacy systems. This also liberates those staff to focus on more satisfying cases requiring judgment and human intervention.

Low Code /No Code Application Development: DPA projects generally require some new applications to be built in order to automate more complex processes that do not align well with RPA. These applications will typically relate to processes requiring analysis, assessment and decisions by experienced human operators. Low Code /No Code development platforms provide a great opportunity to digitise the expertise and judgment of senior staff, as they make app development accessible to non-technical staff by using a graphical UI rather than traditional coding techniques.

Artificial Intelligence and Predictive Modelling: AI and its associated disciplines - particularly predictive modelling - can also have a key role to play as part of a DPA initiative. For example, Service-led organisations typically have to handle large volumes of requests that arrive as emails with completed forms as attachments. Reading, assimilating, actioning and responding to these has traditionally been a time consuming and labour-intensive process. Using Natural Language Processing (NLP) and Text Analytics to read, “understand” and process the emails and their attachments, AI-driven email bots can triage these high volumes of requests, extract all the necessary information, create a “case” and route it to the right responder for immediate resolution.