Construction
The Challenge
A leading construction company in Europe was grappling with severe payroll operational issues impacting the morale of employees. Delayed salaries and erroneous transfers across subsidiaries impacted over 6,000 staff members across 4 subsidiaries.
The already overworked payroll processing team was experiencing increased stress each day, leading to attrition within the team, and creating reputational risk for the organization.
Location
Europe
Industry
Construction
4
Subsidiaries
6,000+
Construction
Attempted Solution before Scout
Consultants requested for an additional
1,200 hours
for Manual Discovery Workshops
The company engaged one of the top consulting companies to overcome the operational shortcoming.
The consulting firm went about this in a traditional manner, conducting discovery workshops through manual interviews. These workshops demanded an additional 1200 hours from the already overworked business teams, leading to attrition. This manual approach didn’t add any real value and intensified the problem.
Enter
The CFO and CHRO then 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. The AI analyzed how payroll teams interact with various applications, mapping out how and why work happens the way it does within the payroll team.
This led Scout to discover a key insight: the root of the problem was outside the payroll team.
Within just
2 weeks
Scout's AI model uncovered a critical insight - the problem lay outside the payroll team
Scout’s AI to “find and fix”
Step 1: Find
As the first step, the AI decoded the work patterns of the payroll team and connected them to business activities, simply by analyzing interactions between the team and their software. It then automatically classified these work patterns as either core payroll activities or non-core activities.
Based on this analysis, within two weeks, Scout’s AI model provided the following insights:
40%
time was spent on core payroll apps and activities
Contrary to popular belief, only 40% of the team’s effort was spent on core payroll apps and activities. This startling statistic pointed to a massive work recall gap across the team, highlighting the disparity between the team’s understanding of how work is being done and how work was actually being done.
60%
time was spent on manual follow-ups
The AI also determined that the remaining 60% of the time was spent on manual follow-ups, managing data across 1500+ spreadsheets, and creating custom reports for management.
Scout’s AI model then further inferred the reason why the payroll team spent so much time on non-core activities – information silos and disconnected systems. These bottlenecks were forcing the team to incessantly toggle between different applications, ultimately resulting in a loss of productivity to the tune of 3,300 hours annually.
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 standardization and user training
Submit timesheets on time
Leadership kicked off a focused awareness and training program for everyone across the organization to ensure that people submitted their timesheets on time.
This led to 100% timely submission of timesheets which significantly reduced the stress on the payroll team’s bandwidth, allowing them to focus on core payroll activities.
Standardize data inputs
The leadership enforced standardization of data inputs, which reduced the effort and time spent on organizing and validating the input data received by payroll teams.
Standardize management reporting
Leadership also made a concerted effort to standardize management reporting which resulted in a reduction of time spent on generating customized reports.
Deep Fixes
Systemic and long-term fixes planned across the organization
Build an integrated Payroll system
The root cause of all issues was that there were significant digital gaps in the overall process; and these were predominantly because systems did not talk to each other, and because data was duplicated/fragmented.
Scout also provided detailed insights into the cost of unintegrated payroll systems and also, the disconnection debt in the organization.
Based on these insights, the leadership kicked off a transformation program, to build an end-to-end workflow system by integrating information inputs, business process rules, and reporting & compliance.
This led to a 95% reduction in digital gaps, 100% payroll accuracy and a 26% reduction in employee attrition in the payroll team.
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
Strategic Payoff
In summary, Scout was able to drive the following business outcomes
Significantly improve how employees experience work and improve their morale
95%
reduction in digital gaps
100%
improvement in payroll accuracy
26%
reduction in employee attrition
How AI connects interaction data to business outcomes
Scout lights up the ‘dark side of the moon’.
Your business generates billions of data points from team-machine interactions. Scout, our AI model, deciphers this interaction data to reveal 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 to address these challenges, paving the way for improved outcomes.
