The Rebate Management Journey: From Spreadsheets to Cloud-Enabled Growth Promoters

The origin of rebates can be traced back to the 19^th century. Back then, rebates were common pricing strategies employed by entrepreneurs to gain an edge over competitors and expand their market share. From gaining dominance in the market to incentivizing customers to choose a particular brand, rebates were a powerful tool in marketers’ arsenal.

This post discusses how rebate management technology has evolved, from manual computing methods to artificial intelligence managing rebate proceedings.

When businesses first started using rebates, they relied on manual books of accounts to store, maintain and track the rebate contracts and receipts. Some of the common reasons they used manual ledgers, and later spreadsheets, are:

• Automatic systems were not invented
• Unavailability of technical skills to operate computers or high-end systems
• Manual accounting ledgers and spreadsheets were cheaper to use
• Rebates programs were less complex

However, as businesses grew and rebate programs got complex, the challenges in manual management of rebate processes began to surface. Accounting and sales teams realized the limitations of spreadsheets in collaborating and handling real-time data in an increasingly complex rebate ecosystem.

In 2012, JPMorgan Chase, an American multinational bank, lost over $6 million in an incident due to manually copying incorrect information into multiple spreadsheets.

Eventually, users realized that spreadsheets were:

• Not user-friendly for voluminous data
• More prone to human errors
• Incapable of tracking changes when handled by many team members
• Unable to generate reports as there is no single source of data
• Difficult to integrate with other systems
• Vulnerable to fraud and data security issues

One of the first attempts to usher in a transformation in the rebate management system came with the adoption of the enterprise resource planning (ERP) system in rebate management.

The initial feedback from ERP users was satisfactory. They were thrilled to have graduated from manual methods to an automated system that was capable of:

• Supporting businesses of all sizes
• Improving process efficiency by eliminating manual data feed-in
• Standardizing critical processes
• Providing access to reliable data
• Offering enhanced rebate management capabilities
• Enabling collaboration
• Ensuring data security

No doubt, the traditional ERP system performed better than spreadsheets. However, it lacked the technical capabilities required to manage the ever-evolving rebate programs. In fact, many businesses, after deploying ERP systems, rate them as difficult to use.

Another challenge with ERP systems was that while most systems could handle simple rebate agreements, they could not accommodate complicated rebate structures, making it a less-than-ideal choice of technology for manufacturers and distributors.

Technologies like artificial intelligence, machine learning, cloud, and data analytics have entered the rebate landscape to streamline operations and improve efficiency. The legacy ERP systems, however, did not match the pace of technological upgrades and failed to streamline the end-to-end rebate management process.

A typical ERP system:

• Lacks the data processing capability as data has to be either entered manually or processed in external spreadsheets and then fed into the ERP system
• Leaves scope for human errors in data handling
• Lacks analytics and forecasting features to predict sales estimates, consumer trends, and profit margins
• Lacks features for accruals management in case of tiered incentives to ensure timely and accurate payments for stakeholders
• Usually has a lengthy implementation process and time-consuming data migration process
• Is expensive to deploy and often includes hidden costs like licensing, implementation, and subscription costs
• Requires trained experts for maintenance, error correction, and system upgradation
• Takes a few years to offer the promised benefits
• Prevents the collaboration of large teams as it limits the number of users who can access and avail of its facilities
• Is customizable, but the functionality is expensive and does not offer real-time data monitoring and report generation capabilities

These limitations lead to erroneous revenue projections, impacting many dimensions of the rebate management process, including sales performance, ROI calculation, and performance tracking.

Consider this real-life example to understand the impact of an ERP system failure.

Target, one of the largest retailers in the US, decided to launch its service in Canada. The retailer deployed a new ERP system and fed only the most recent data in order to eliminate the data migration problems associated with legacy systems.

Result? When the legacy system was disconnected, the entire ERP architecture collapsed. Employees could not authenticate the information from old vendors and manufacturers.

Investigations found that only 30% of data fed into the ERP system was correct, and the rest were typos, currency conversion errors, and missed inventory counts. The entire project resulted in losses worth $7 billion, and consequently, the retailer announced a withdrawal from the Canadian market in 2016.

Instances such as these nudged businesses to look for an intelligent rebate management system that could address the limitations of a typical ERP system. This was when the need for a cloud-based, AI-driven rebate management system that could automate the rebate proceedings, mitigate business risks, and streamline the entire rebate management process, was strongly felt.

A cloud-based, AI-powered rebate management platform, such as rebate.ai, is key to efficiently creating, managing and tracking rebates. This platform is all-encompassing – from eliminating time-consuming manual processes to improving operational efficiency and increasing ROI.

The rebate.ai platform:

1. Uses data-driven insights to drive financial transparency, vertical integration, performance tracking, and audit trails.
2. Automates rebate payments and accrual calculations.
3. Integrates inputs from numerous sources and offers a single source of truth for all stakeholders.
4. Allows users to create and track rebate programs in real-time, enhancing program visibility and collaboration between manufacturers, distributors, and retailers.
5. Calculates, interprets, and projects the past and future rebate earnings of each product, program, or member.
6. Supports group members with predictive rebate intelligence to improve forward-looking decision-making capability.

A look at what users of rebate.ai have to say:

Jerry Knight, President, IMARK Electrical, says, “Tredence’s rebate.ai delivered IMARK electricals’ members and preferred suppliers a competitive edge by providing information to identify product and supplier conversion opportunities in a secure and easy-to-use platform.” He adds, “It is the only authorized rebate management solution for the IMARK Group which focuses on strengthening member partnerships for accelerated growth.”

John Aykroyd, President of IMARK Plumbing, mentions, “Rebate.ai offers a dashboard that provides numerous data points that benefit members and suppliers. Members can access in-depth analytical tools that offer guidance to maximize member’s rebate earnings.”

The rebate landscape is now tech-driven. Schedule a demo with our experts to improve your rebate earnings and automate the rebate management process.