Pavan Bagai, Chief Operating Officer Abstract
In the current economic environment, revenue leakage from the Order-to-Cash cycle represents an opportunity for freight carriers. Identifying and preventing such leakage can realize missed revenue opportunities that exist at different stages of the order-to-cash cycle – billing, audit, rating, pricing, invoicing and collections. Analytics can assist freight carriers in identifying and plugging revenue leakage, resulting in additional revenue – also termed as positive revenue.
A top US freight carrier added millions of dollars to its revenue by implementing a solution that combines BPO and analytics to identify positive revenue opportunities and improve process efficiencies. The solution has three integrated components – revenue augmentation, process reengineering & automation, and continuous monitoring & reporting. With the help of this solution, the carrier was able to equip its order-to-cash cycle with better controls and transform it into a more effective and efficient process.Positive Revenue Analytics in Order-to-Cash Cycle
On the face of it, the US freight transportation industry is facing such challenges as volatile fuel cost, overcapacity and driver retention. However beneath the surface, the industry is known to be saddled with inefficiencies, particularly in the order-to-cash cycle. The prolonged recessionary environment has further magnified the process inefficiencies and brought it under the glare of the Board and the management. This has brought the focus of transportation carriers on preventing revenue leakage as well as maximizing return from each shipment. There could be several points of revenue leakage in order-to-cash cycle. If carriers are able to identify and plug such vulnerable points, it could result in realizing positive revenue opportunities.Overview of order-to-cash Cycle
A typical order-to-cash cycle for a freight transportation company involves multiple steps, as shown in the diagram below, from the point of receiving order, to delivery, to revenue collection. Positive revenue opportunities can exist at any point in this cycle.
Positive revenue opportunities
Order-to-cash cycle (Illustrated for transportation industry)
The order-to-cash cycle diagram clearly indicates that different handshakes are involved at different stages in the cycle. Missing even one step during any of the stages could lead to incorrect revenue calculation.
- Missing critical information during data entry
- Incorrect field entry
- Insufficient / inefficient bill entry audit
- Inaccurate base rating
- Missing an accessorial or other charge
- Process inefficiencies
- Missing critical information or a valid correction
- Process inefficiencies
- Inaccurate invoice creation
- Insufficient / inefficient invoice audit
- Process inefficiencies
Incorrect invoicing of higher-than-actual values does not pose a major threat because such errors typically get reported by the customers. In contrast, a lower value invoice could result in revenue losses and therefore it becomes critical to track and rectify such errors. Such process inefficiencies could also result in delayed payments, rework costs and high overall service delivery time; eventually leading to order rejections and customer dissatisfaction.
Order and bill entry
This is the first step in order-to-cash cycle and it becomes even more important to control revenue leakage at this stage. An error that finds an entry into the central data system at this point, either through wrong entry or otherwise, might have a more severe impact at latter stages of the order-to-cash cycle.
There have been instances of billing errors and related rework resulting in loss of approximately 0.5 - 3 percent of the total revenue1.
The reasons for errors creeping into the system at this stage could be as diverse as system flaws and human errors.
- Degree of complexity - number of scenarios to be considered
- Inadequate training
- Production pressure on bill entry agents
- Redundant entry fields
- Time consuming search method for incomplete information
- Non-standardized template of bill of lading
- Human errors
- Communication errors
Identifying the reasons for errors is as important as controlling the margin of error at this stage. Carriers have been using audits of sampled data as a control measure. However, the effectiveness of audit can be increased only if the size of the sample size is enlarged; which eventually has a direct impact on cost. The challenge therefore is to capture and correct maximum number of errors while keeping the costs low. A solution that leverages the integrated capabilities of analytics, process reengineering and risk management has proved to be highly effective in reducing errors at the order and bill stage. It enables carriers to devise and implement predictive audit strategies, simplify data entry processes, formulate predictive rules and apply effective search techniques. Further cost optimization can be achieved by leveraging global delivery model for audit team.
|Billing Error Rate Reduction*|
|A leading transportation carrier was facing revenue losses because of high error margins at the bill entry stage.|
Root Cause Analysis and Six Sigma approaches were implemented to identify the reasons for errors and improvement opportunities.
Error rate reduced by ~20%.
Rating and application of charges
In addition to applying the charges for basic services, carriers also add accessorial and other contractual charges for optional services. A complex pricing system adds multiple steps and this could increase the risk of calculation error. The error can eventually result in revenue leakage, delay in payments and rework cost. The most likely reasons for error at this stage are wrong data entry and cumbersome pricing techniques.
Audit arrangements similar to the solution at the order and bill entry stage can also be effectively used to reduce the margin of error at this stage. Analytics can augment audit process in two ways – predictive modeling to develop preferential queues and developing tools to identify errors and apply corrections.
|Automated business rules for application of accessorial charge for a leading transportation carrier.|
Applied advance analytics to automate audit of accessorial charges.
Resulted in 0.5% increase in annual revenue on sustainable basis
Updates and corrections during freight movement
It is highly unlikely that the invoice created at the ‘rating and application of charges’ stage remains sacrosanct when the shipment is on the move. The invoice is subject to modifications as per the information received from drivers, fleet managers and terminal coordinators while the shipment is in transit. For example, shipments may be inspected at terminals of less-than-truckload players and there may be instances of misstated information getting detected at this stage. Such updates need to be executed to ensure the accuracy of charges. Analytics can be used to track error patterns and this information can then be used to reduce invoicing error. It can also be used to estimate the probability of a shipment to go through a revenue correction procedure.
|Higher Correction* |
|Predictive analysis for a major transportation company in the US was done to increase correction-revenue at the terminal.|
Resulted in increase of correction-revenue by ~50%.
The EXL approach
Invoicing and collections
An incorrect invoice, at times, may cost a carrier more than the total amount charged. Analysis of data related to invoicing and collection can provide critical insight into payment and collection patterns, which is helpful in preventing instances of incorrect invoicing and improving invoice accuracy. If the feedback and insight gathered at this stage are passed on to the earlier stages in the order-to-cash cycle and effective preventive measures are implemented then revenue leakage can be stopped at multiple stages in the order-cash-cycle.
|Invoice Rejects Analysis*|
|Reject invoice data for a major transportation company in the US was analyzed to identify the root cause.|
Identified over 200 reasons for invoice rejects and an error pattern particular to a shipper.
Improved invoice quality.
Error reduction by 80-90% for select shippers.
EXL uses its proprietary patent pending methodology, MicroAnalytixTM for data analytics and modeling. The methodology includes use of different analytics tools like MATLAB, CART & MARS and SPSS along with an EXL proprietary tool kit. The analysis process is driven by Lean and Six Sigma (DMAIC) approaches. The use of structured methodologies like these facilitates development of accurate, stable and effective solutions.
Positive revenue opportunities can be realized by adopting a three-pronged approach - improve effectiveness, efficiency and control. The solution is supported by a framework consisting of deep domain expertise, robust analytics processes & tools, and dual-shore cost effective delivery model.
Enhancing effectiveness through revenue augmentation
The EXL approach to recovering positive revenue
Creating long-term sustainable revenue enhancement involves analysis of order-to-cash cycle processes and identification of the points of missed opportunities. Such missed opportunities are validated on out-of-time and out-of-sample data. Implementing a correction procedure on the validated opportunities can generate benefits though revenue augmentation.Enhancing efficiency through process reengineering and automation
Efficiency enhancement can be achieved by creating a foundation for sustained lean operations and a platform for positive revenue recovery. Lean Six-Sigma capabilities are leveraged to identify the problem areas and ascertain the root cause. This information is applied to customize a solution by opting for a combination of the following three elements.
Enhancing control through continuous monitoring and reporting
- Eliminate redundant processes
- Automate manual processes wherever possible
- Optimize effort required by redesigning process and information flow
It is vital to establish continuous monitoring and reporting mechanisms to ensure that the right information is available to the right person at the right time. This can be achieved through design and development of analytical reports and dashboards to control performance within different processes of order-to-cash cycle.