The Metropolitan Police Friendly Society (Metfriendly) is a mutual society providing savings and investments for serving and retired police officers and their families. The society, formed in 1893, offers uniquely police-friendly financial products and services. Over its long history, Metfriendly had built up a huge pool of data about clients and their products but the management team was finding it increasingly difficult to extract real insight with the limited technology available to them. With COVID-19 and Brexit placing even more emphasis on the need for reliable data, a swift decision was made to redesign and rebuild the Society’s Business and Management Information (MI/BI) capability. Within weeks an ambitious project was launched to transform the production, analysis and reporting of data across the business.
After several successful engagements, Altus had become a trusted partner to Metfriendly who knew we could quickly assemble an expert team to deliver the results they needed. Using our APEX delivery framework, Altus was able to combine our existing knowledge of Metfriendly’s business and technology landscape with specialist BI partner skills to launch the project at speed. Within a matter of days, Altus was able to deploy a team with the skills and vision necessary to turn data into insight, combined with the oversight and management required to deliver. Design was completed in weeks and just one month later the project was delivering results.
Despite the constrained timescales, our approach was methodical: i. Produce a pilot report to give confidence in the initial build. ii. Deliver an agreed set of report artefacts. iii. Explore further outputs based on analysis of the results iv. hand over the programme to Metfriendly to maintain and extend the core data solution. Whilst design was undertaken and managed by Altus, strong support was received from the business and key Metfriendly SMEs. The project built upon knowledge and skills within the society’s own IT development team who continue to evolve the solution.
The twin requirements for the project were to massively accelerate the production of MI and deliver the results in a way that users could easily explore to find real insight. Historically, those objectives would have entailed big, expensive software implementation projects but that was before cloud computing. Instead, our expert team was able to exploit the power of Microsoft’s Azure BI technology stack to bring sophisticated AI functionality to Metfriendly without huge cost or overhead.
Starting with the monthly MI report (produced manually at the time), the team set about using Azure Data Factory to automate the collection of core data. Next they turned to Azure Synapse Analytics and PowerBI to process and present the information. Business users were so impressed with the early results that they soon began using the system to dig deeper into the data. Working closely together, the Altus team and Metfriendly management began to explore and visualise the data in new ways. Using the powerful features of Synapse Analytics and PowerBI the team has begun to analyse the monetary shape of policies over their lifetime and to visualise segments of their membership in much greater detail. Painting a picture of aggregated money flows into and out of the business promises to allow Metfriendly to understand its customer base and see the sweet spots in their portfolio in ways that haven’t previously been possible.
The MI solution has exceeded all its original objectives. Critical business data is delivered faster and more accurately than ever before allowing management to make better informed decisions. But the project went beyond those objectives too. By selecting the right tools and investing in knowledge transfer, Altus ensured the society can maintain & enhance the system themselves and is accessible to the whole business, not just data experts. Altus is proud to have helped create a MI/BI Culture and Data Function, for daily insight, delivering long term goals and building a vision for prescriptive analytics in the future.
