How Aelius Venture Used AI Automation to Reduce a Two-Week Workflow to One Day
Client: Aeliusventure
As the client's business grew, a key operational workflow comprising data gathering, manual review, cross-team approvals, and final reporting became an increasingly significant impediment to the organization's ability to move fast. 1. Heavy reliance on manual data handling. Every cycle requires staff to manually collect information from different internal sources, condense it into usable formats, and double-check it for accuracy before proceeding. The manual handling alone took up a large chunk of the two-week schedule. 2. Sequential approvals caused delays. Rather than proceeding in parallel, crucial milestones in the process required sequential sign-offs from numerous stakeholders, so every single delay in the chain pushed back the entire timeframe for everyone downstream. 3. Inconsistent Data Quality Because much of the process relied on human entry and consolidation, minor errors and inconsistencies were widespread, necessitating multiple rounds of inspection and correction before the workflow could be considered complete. 4. Limited visibility into process status. Without a centralised mechanism to track progress, leadership struggled to understand where a given cycle was at any given time, whether it was on track, delayed, or completely stalled. 5. Cost of a Two-Week Cycle As business expectations grew, a two-week turnaround for a fundamental operational routine became more difficult to justify. Competitors moving quicker prompted pressure to modernise, but the client's old technology and manual procedures were not designed to handle considerably faster cycles without a major overhaul. ...
Technology
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