The challenge
The Prince’s Trust has to be able to financially forecast and plan with the same urgency and accuracy as any large corporation. It was therefore vital that they started making use of their existing systems and data to deliver the business intelligence required to effectively fund their programmes and make decisions. Multiple areas for improvement had been identified within the finance and fundraising teams, but the outputs they wished to achieve were yet to be clearly defined.
“The best laid plans o’ Mice an’ Men, / Gang aft agley”- was the illustrious Scottish poet correct? Whilst the prophetic words of Burns are often accurate, in this case at least, Clarasys and the charity were able to collaborate to mediate the forecasting concerns of the organisation.
The vision
Financial data from multiple teams needed to be effectively mapped together in a BI (business intelligence) system to allow for improved forecasting and reporting.
The approach
- Scope definition: worked with the charity to define the most valuable areas of business intelligence, which were specifically centered around forecasting and reporting on income.
- As-is process mapping: through workshops and interviews the as-is processes and associated pain points were gathered. These processes were used to build the future process state and system architecture for a proposed business intelligence and data warehousing tool.
- Requirements gathering: an agile approach was adopted and the team created a prioritised list of user stories. Following feedback and iterations, it became clear that there was a distinction between the short and long term. Thereafter these requirements were categorised and prioritised accordingly.
- Roadmapping: the combination of user stories, processes and a road map were created to ensure the charity could carry out the identified improvements and requirements in the future.
The results
In the short term a number of ‘quick wins’ were identified that would drastically shorten the manual work involved the charity’s processes.
In the long term a solution was proposed that would incorporate a business intelligence tool, driven by a data warehouse and data extraction process. Five potential systems were identified as data storage points that would need to feed data into this new system, including existing CRM and accounting systems. A backlog of requirements and user stories were documented which to be taken to potential vendors, and a road map was developed.
