Scout helped a Big 4 Consulting firm in achieving a remarkable 40% reduction in time-to-close for a G500 CPG leader through process optimization and automation


The Challenge

A major Global 500 CPG company, boasting a workforce of over 120K employees, encountered critical challenges within its global supply chain finance functions. These issues manifested as increased workloads resulted in errors and miscalculations, low adherence to service level agreements (SLAs), and a concerning rise in operational costs that posed a substantial threat to revenue.

The company urgently needed to address these challenges to safeguard its financial stability and operational efficiency.






Attempted Solution before Scout

Business leaders needed to investigate 2000 sub processes in under

2 months

Business Leaders of the CPG company attempted to study the processes by interviewing process teams and by examining existing documentation.

Soon they realized that they needed expert help and technology-driven analysis to investigate 2000 L4 sub-processes and 15 L2 processes within the packed timeline of 2 months.

The Big 4 consulting firm was then tasked with an in-depth process study that would reveal

• the areas of manual touchpoints,
• identify process inefficiencies, and
• recommend digital transformation change initiatives.


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The consulting firm leveraged a synergistic approach that combines its domain expertise and technology-led exploration to achieve a comprehensive understanding of processes. This methodology eliminates potential human biases, providing a holistic 360-degree view.

They evaluated and onboarded Scout to find and fix these problems.

Scout's AI model could be quickly put into action because it didn't need complicated integration with current systems and was able to cater to the customer’s application stack. The AI analysed how finance teams interact with various applications, mapping out how and why work happens the way it does within the supply chain finance team.

This led Scout to discover a key insight: significant effort spent on non-core apps (MS Excel, Outlook) across processes.


2 weeks

Scout's AI model discovered a key insight - significant effort spent on non-core apps across processes

Scout to “find and fix”

Step 1: Find

As the first step, the AI decoded the work patterns of the supply chain finance teams and connected them with business activities, by analyzing interactions between the team and their software. It then automatically classified these work patterns as either core process activities or non-core activities.

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Do You Know How Your Teams Get Work Done?

Based on this analysis, within two weeks, Scout’s AI model provided the following insights:

3000+ Excel files were used with around 20% of that effort being repetitive and predictable data entry.

Scout’s AI model then further inferred the reason why the teams spent so much time on non-core activities – information silos and disconnected systems.

20% of the user’s day (~27000 hours per year) was spent on toggling between apps, logging into various applications, and managing files and folders, ultimately resulting in a loss of productivity and context.

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How Much Time Does Having Too Many Apps Really Waste?

Step 2: Fix

Based on the above insights, Scout’s AI model recommended two levels of fixes:

Quick Fixes

These were ‘no-code’ fixes based on standardisation and user training
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The consulting firm recommended standardisation of data available across several MS Excel sheets to reduce the effort and time spent on organising and validating the data processed by the finance team.

Deep Fixes

Systemic and long-term fixes planned across the organisation.
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Scout highlighted the root cause of all issues: that there were significant digital gaps in the overall process; and these were predominantly because manual effort spent processing information from various Excel sheets, removing duplicates, maintaining/renaming sheets across several folders associated for different countries.

The consulting firm has identified and presented a prioritized list of processes that need to be automated to improve process efficiency and save manual effort and costs.
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Design an integrated system:
Design an integrated system:
Scout also provided detailed insights into the cost of unintegrated systems & applications and, also the disconnection debt in the organization.

With these insights and aiming to unify the experience across multiple applications and documents, the consulting firm has built a roadmap for a digital transformation initiative to implement an integrated system to seamlessly gather inputs, validate data and complete process requests.

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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.

Business outcomes

In summary Scout was able to drive the following business outcomes
Reduce manual touch points by automating



Reduction in time-to-close by


Increase in % of automated tasks by


Increase in accuracy of
financial reporting by


Finding excess capacity of


FTEs in processes

How AI connects interaction data to business outcomes

Your business generates billions of data points from human-machine interactions. Scout, our AI model, deciphers this interaction data to unveil what often remains unseen—the hidden challenges your teams face at work and how they affect business outcomes, whether it's cost optimization, revenue growth, customer or employee experience, or business continuity.

The AI then provides data-based recommendations for the necessary interventions to address these challenges, paving the way for improved outcomes.

We call this lighting up the ‘dark side of the moon’.
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The 'Dark Side Of The Moon' In Enterprises

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