Resource Utilization Made Easy: How a Global Engineering Service Firm Optimized Revenue Trends with Kasmo’s Expertise

Company Overview 

Our client is a global engineering services firm that operates across various sectors, including automotive, aerospace, telecommunications, and healthcare. This company helps clients navigate complex modern engineering challenges. By focusing on resource utilization, enhancing operational efficiencies, and fostering innovation this company provides integrated engineering services globally.  

Challenges Faced by the Client 

Our client faced significant challenges that hindered its ability to optimize resource utilization and revenue generation.  

1. Inconsistent Revenue Trends: Our client struggled to understand the reasons behind fluctuating revenue figures. Revenue did not increase according to the rate of resource utilization. This made it difficult for the company to grasp the factors affecting financial performance. These inconsistencies also complicated forecasting and resource planning for the organization. 
   
   

• • Decrease in Revenue Even After Planned Resource Utilization: Our client had a decline in revenue, even after careful resource management and planning. This anomaly raised concerns about the effectiveness of resource allocation and its direct correlation to financial outcomes. 
    
    
  • Increase in Revenue with Low Utilization: The company observed that there were many cases where they saw an increase in revenue with low or incomplete resource utilization.   

2. Lack of Predictive Insights: The client lacked predictive analytics, which made it difficult for them to plan for future resource management. This lack of predictive analytics complicated the process for our client to understand patterns and effective resource allocation became a complex process.    

Kasmo’s Solutions for the Client 

To address the challenges faced by our client, Kasmo implemented tailored solutions designed to enhance predictive capabilities and optimize resource utilization leveraging Snowflake AI Data Cloud:  

1. Predictive Resource Utilization Tool: Kasmo developed a sophisticated predictive tool that forecasts resource utilization rates for the client. This tool helped the client analyze key parameters such as ‘Year’, ‘Month’, ‘Totalbookedhours’’, ‘Totalavailablehours’, ‘Holiday’, and ‘Leave’. These key parameters had a significant impact on the company’s resource utilization. With this predictive tool, our client gained enhanced forecasting capabilities for the next 12 months. 
   
   
2. Root Cause Analysis for How Resource Utilization Impacted Revenue Changes: Beyond forecasting, Kasmo’s solution identified key factors contributing to fluctuations in resource utilization and the impact on revenue. Our experts used regression analysis to quantify the relationship between resource utilization and revenue. We also implemented machine learning models (e.g., random forests or gradient boosting) to predict revenue based on resource inputs. 
   
   
3. Region/Location-Based Utilization Rate Impact: One of the critical insights provided by Kasmo to the company was the knowledge of how personnel and resources across different regions created an impact on their revenue. Our experts implemented models like Random Forest or XGBoost that can pinpoint regions with high resource utilization and growth potential. 
   
   
4. Forecasting Project Pipeline: Kasmo used Random Forest and Gradient Boost models to predict project growth while accounting for trends. Our experts also identified how project growth influences resource utilization rates and provided insights for optimizing resource management. 
   
   
5. Impact of Contract Renewal on Revenue: Kasmo’s experts used the historical contract end dates and information on contract renewals, extensions and cancellations to predict the impact of revenue. We used Random Forest, XGBoost to predict contract renewal and cancellation probabilities. This helped in identifying key contracts approaching end dates to prioritize for renewal and cancellation.
   
   

6. Days Sales Outstanding (DSO) Forecasting: Kasmo examined the relationship between entity-level and regional manager-level sales for the last 12 months to forecast DSO values. The forecasted DSO values can play a vital role in assessing credit risk, and improving financial planning and operational efficiency. 

7. Effect of Invoice Management on Revenue: Kasmo’s experts analyzed historical invoices Data (amount, date, client details), information on clients, payment history, and credit ratings and communication log. This helped identify customer segments based on payment behavior to identify high-value clients and classify customers into risk categories. 

Results Achieved 

The implementation of Kasmo’s solutions helped our client achieve several solutions: 

1. With optimized resource utilization, our client saw an increase in revenue, reduced operational costs, and improved overall efficiency. This helped them achieve better financial health and gain an advantage over their competitors. 
   
   
2. Better resource planning and allocation helped the client accelerate project growth, fewer delays, and better cost savings. 
   
   
3. Our client made smart and data-driven decisions with forecasting. They could make enhanced decisions on hiring and budgeting. 
   
   
4. Proactive contract end-date management ensured smoother transitions and customer retention for our client. 
   
   
5. The client could now easily deploy resources across various regions, improving efficiency and meeting demand effectively. 
   
   
6. The client could now ensure that highly skilled employees are utilized optimally.  
   
   
7. With an understanding of role-based utilization patterns and demand, our client could now align resources according to business needs.