Category: Government council

Government council CGI leverages Scout to identify opportunities within a large local council and reduce its operational workload by 67% The Challenge CGI, a global leader in consulting and IT services with over 80,000 employees, encountered a significant challenge with one of its clients. Scotland’s third-largest historic county, employing over 18,000 people, was under pressure to uphold customer service standards while dealing with budget constraints. To address this, CGI launched a digital transformation program for the council, aimed at achieving a 5% efficiency gain by streamlining operations, reducing manual effort, and enhancing work efficiency. However, CGI faced significant hurdles in identifying and prioritizing processes for automation and improvement for the council. They needed a solution that could: Identify the most resource-intensive processes and determine inefficiencies Quantify the potential benefits of process optimization and prioritize them for transformation These objectives had to be met without placing substantial burdens on their business teams. Industry Government council Location UK 18000+ Employees Attempted Solution before Scout CGI analysed that roughly 80% of the council’s cost was spread across 20% of business functions Business leaders within the council attempted to identify and shortlist processes for transformation by holding workshops, interviewing process SMEs, and examining existing documentation. The SMEs struggled to quantify potential benefits and prioritize processes for improvement due to a lack of empirical process data. . This led the council to seek recommendation from CGI, who analysed that roughly 80% of the council’s cost came from 20% of business functions which were handled by desk-based teams. Essentially, a few key functions were costing a lot, so focusing on these areas could help in managing or reducing costs. However, manually exploring these functions would be a mammoth exercise. Therefore, CGI recommended adopting an AI solution to: Provide detailed process insights through interactive flowgraphs and auto generated documentation Identify resource intensive processes and quantify process inefficiencies within the business functions, and   Prioritize digital transformation initiatives  Enter To achieve a comprehensive understanding of processes, CGI leveraged its domain expertise and onboarded Scout to find and fix problems. The council chose the accounts payable function for the pilot. The Scout AI model was quickly put into action because it didn’t require complicated integration with current systems and was compatible with the customer’s application stack. Scout analysed how teams interacted with various applications, mapping out how and why work happens the way it does, within the accounts payable function of the council.  Within a week, Scout discovered that 70% of the team’s effort was spent on 4 major processes Within a week, Scout discovered the following key insights: 70% of the team’s effort was spent on 4 major processes. 20% higher reliance on core invoice processing apps was observed compared to other similar functions across Scout customers, indicating streamlined operations Scout to “find and fix” Step 1: Find As the first step, the Scout AI model analysed interactions in the accounts payable function with business applications and recognized repeated patterns of work. This analysis revealed which processes consumed most of the team’s effort. Scout then deep dived into the shortlisted processes and delivered the following key insights to guide the business in its transformation journey: Harvard Business Review Do You Know How Your Teams Get Work Done? Read more The intelligent document processing (IDP) solution implemented for select suppliers was found to deliver 7% savings in processing effort per invoice compared to the ones that were processed using the legacy system. 0.5% of suppliers accounted for 15% of the effort spent in the legacy system. 2.3x time was spent on invoices that required re-work versus time spent on straight through invoices. >80% of effort was concentrated on structured applications across major processes, highlighting significant potential savings through automation. Harvard Business Review How Much Time Does Having Too Many Apps Really Waste? Read more Step 2: Fix Based on the above insights, two levels of fixes were recommended: Quick Fixes Efficient supplier migration Scout identified that the effort per invoice could be reduced by 7% if suppliers were transitioned to the IDP solution. By prioritizing the top 0.5% who currently contribute 15% of the effort on the legacy system, the council could achieve substantial savings by migrating suppliers within a short timeframe. Streamlining process documentation initiative The council could reduce operational workload, standardize training, and automate the creation of process documentation across various processes and variations by leveraging Scout. Deep Fixes Systemic and long-term fixes to improve operational efficiencies. Enhance existing IDP system to match invoice lines accurately Scout highlighted that there were significant digital gaps in invoice processing; and these were predominantly due to manual effort being spent to match invoice lines and to upload invoices in the system. While the existing system automatically updated invoice headers, users had to manually match line items and send emails to suppliers for discrepancies. By enhancing the system to match invoice lines and sending out automated responses to suppliers, the council could significantly improve efficiency and save 70% of manual effort spent on processing invoices. Deploy RPA bots Detailed insights were generated in the Statements and Non-PO invoicing processes. Scout assessed a savings of ~ 40% when RPA bots were deployed to service these requests. AI driven Process Prioritization The AI prioritized the assessed process for improvement based on operational effort, ease of implementation, and potential savings. This approach facilitated the development of an automation pipeline guided by data-driven recommendations. It is important to note that in all of these recommendations, privacy was of the utmost importance – and no employee data was shared. Empathy was at the core of all recommendations and the focus was on addressing and improving the core issues i.e. Getting teams to work together across functions Fixing disconnected systems Simplifying and optimizing work processes Business outcomes In summary, CGI leveraged the Scout AI model and was able to achieve the following business outcomes: 7% reduction in processing effort per invoice by migrating suppliers to the IDP solution 67% efficiency savings across all scouted processes 65% efficiency savings on invoice processing by enhancing the existing solution 40% savings by deploying RPA bots… Continue reading CGI leveraged Scout to pinpoint resource intensive processes within a large local council to reduce its operational workload by 67%