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Case Study

How a 200-Person Financial Services Firm Achieved 78% Cost Reduction with BetterWrk

A mid-market financial services company was drowning in manual reconciliation, disconnected systems, and approval bottlenecks. BetterWrk deployed AI-powered discovery and automation to transform their operations in 5 weeks.

78%
Cost Reduction
in order-to-cash
14→3
Days Cycle Time
79% faster
5 wk
Implementation
from start to live
$1.2M
Annual Savings
validated ROI

The Challenge

This 200-person financial services company faced a common mid-market problem: critical business processes had grown organically over years, layering manual workarounds on top of disconnected systems. What should have been straightforward operations had become slow, error-prone, and expensive.

Their order-to-cash cycle — from receiving a customer order to collecting payment — took 14 days and required 6 handoffs across 3 departments. Each handoff introduced delays, manual data re-entry, and reconciliation errors. Staff spent hours each day on work that existed only because systems didn't talk to each other.

Previous attempts to fix the problem had failed. A traditional consulting engagement produced a 120-page assessment over 4 months but led to no operational changes. An RPA implementation automated individual tasks but couldn't handle the exceptions that made up 30% of transactions.

Before BetterWrk

  • x 14-day order-to-cash cycle with 6 manual handoffs
  • x 8 disconnected business systems with no integration
  • x 23 manual processes identified as automation candidates
  • x 30% of transactions required manual exception handling
  • x Previous 4-month consulting engagement produced no changes

The BetterWrk Approach

1

Discover for Insight — Week 1

ProcessScout connected directly to all 8 business systems — ERP, CRM, billing platform, document management, and 4 supporting tools. Instead of interviewing staff about what they thought happened, BetterWrk's AI analyzed what the systems actually showed.

The 5-pillar diagnostic identified 23 automation opportunities and quantified the Ghost GDP — manual work that existed only because of process gaps. The discovery phase alone identified $360K in immediate savings from process eliminations that required zero automation.

2

Validate for Integrity — Weeks 2-3

BetterWrk's expert team manually verified every finding. AI had flagged 23 opportunities; human validation confirmed 18 were viable and identified 2 additional opportunities the AI had missed due to undocumented tribal knowledge.

Each recommendation was validated with statistical confidence intervals and linked to specific system artifacts — not opinions or estimates, but verifiable data showing exactly where money was being lost and how to stop it.

3

Automate for Impact — Weeks 3-5

BetterWrk deployed Autonomous Workflow Orchestration across the highest-impact processes first. Unlike traditional RPA which broke on exceptions, the AI agents could reason through the 30% of transactions that required judgment calls — routing them to the right person only when genuinely needed.

Order-to-cash dropped from 14 days to 3. The 6 manual handoffs were replaced by automated orchestration with human checkpoints only at compliance-critical junctures. The system went live in week 5 and was fully autonomous by week 6.

The Results

After BetterWrk

  • 78% cost reduction in order-to-cash operations
  • Cycle time: 14 days → 3 days (79% improvement)
  • $1.2M in annual savings — validated and recurring
  • 5-week implementation from discovery to live automation
  • 18 processes automated with intelligent exception handling
  • 6 manual handoffs eliminated — replaced by AI orchestration

"BetterWrk found savings we didn't know existed. The discovery phase alone paid for itself. What impressed us most was the speed — we went from first conversation to live automation in 5 weeks. Our previous consulting engagement took 4 months just for the assessment."

— VP of Operations, 200-person Financial Services Firm

Could Your Operations See Similar Results?

Every company's operations are different, but the pattern is consistent: mid-market companies are losing hundreds of thousands annually to manual processes that should run themselves.

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