Five Challenges in Rebate Management and How to Overcome Them

I recently read a report that said global use of medicines has grown by 14 percent over the past five years, with a further 12 percent increase expected by 2028, bringing annual use to 3.8 trillion defined daily doses.

With rebates impacting over 25 percent of pharmaceuticals, this translates into a monumental challenge for the industry. At the heart of this challenge lies pharmaceutical rebate management, a critical process that can make or break a pharmaceutical company’s bottom line.

However, in my experience, managing rebate contracts effectively is no small feat.

From the sheer complexity of contracts to data quality issues, tedious manual processes, overwhelming scale, and demanding stakeholder expectations, rebate contract managers face many obstacles. These challenges not only consume valuable time and resources but also increase the risk of errors and missed opportunities.

In this article, I’ll explore the five key challenges I’ve experienced working closely with rebate contract managers and how AI-powered rebate management software can transform this critical business function.

Challenge 1: Complexity

Rebate contracts are incredibly complex. Generated from hundreds of different sources, no two contract rebates are alike. For example, certain clauses which might be on page 24 of Regional payer A are on page 78 of Regional Payer B.

Nevertheless, you have to go through each of those contracts manually to find the information, highlight it with a marker, and then get that highlighted information into an Excel spreadsheet to analyze. Some of these contracts can number in the hundreds of pages – take 340B which is about 300 pages long. They all contain the same sort of information, but they’re expressed differently and are in different places.

This painstaking process requires a solution that can efficiently streamline rebate processing and handle the nuances of pharmaceutical supplier rebate management.

Challenge 2: Data Quality

Data quality is a persistent issue in pharmaceutical rebate management. A lot of pharma contracts have been converted to PDF poorly, which makes it very hard for an OCR scan or a Kofax machine to get the information into a state where key data can be extracted from it.

Another issue that’s highly prevalent is that these contracts and the information relating to these contracts, such as amendments, are not always in one location. They’re often strewn all over the place in file shares such as SharePoint and other records management repositories, creating silos that hinder efficient rebate management. That means the ability to discover this information and bring it together into a common source is a huge business challenge.

The ability to centralize and normalize this data is essential for organizations seeking to implement the best rebate management software. AI-driven solutions can help bring order to the chaos, enabling smarter decision-making.

Challenge 3: Tedium

The third key challenge is tedium – this is a hard job. In my experience, I would say that 98% of rebate contract managers all have college or university degrees. While working at a large pharmaceutical manufacturer is a prestigious position, the reality is that for eight hours a day, five days a week, these professionals are armed with a highlighter leafing through contracts trying to figure out ways to get certain information out of the contract and into an Excel spreadsheet. (I know this because I’ve been working with 10 contract managers over the last 18 months, and above all else, that’s the hardest part of their job.)

By implementing AI-powered pharmaceutical rebate management software, manufacturers can automate repetitive tasks, allowing rebate contract managers to focus on higher-value activities and eliminate inefficiencies in rebate processing.

Challenge 4: Scale

The sheer scale and volume of pharmaceutical rebate management contracts is overwhelming. No two contracts are the same, and most organizations are using contract lifecycle management solutions to generate contracts, or the payers are using CLM solutions to generate contracts back to you. The reality is there’s no standard contract used, and that makes the magnitude of having to complete this job extremely difficult.

If you’re a medium or large pharma company, you’re probably managing between 5,000 and 50,000 contracts with multiple amendments that are being renewed on a very regular basis, so the scale of being able to put your arms around that cannot be done anymore by hiring interns, putting 50 people into a room and getting a great result.

Without the support of rebate management software to handle these vast volumes, achieving accuracy and compliance is an uphill battle. AI can address this by processing large datasets quickly and consistently, enabling rebate teams to scale effectively.

Challenge 5: Stakeholder Management

Stakeholder expectations add another layer of complexity to pharmaceutical rebate management. When I met with one of the divisional vice presidents who was authorizing a rebate contract transformation project, I asked him why he was interested in doing this. He replied: “When I ask my team to give me an answer, I can’t give them two weeks to find the answer to a question, I can’t even give them two days. Sometimes I’m in a meeting and I need to know what the value is from a specific contract. That’s why I want to automate the solution.”

The challenge further compounds when you have product managers, revenue managers and salespeople, all wanting to understand what the terms of the contract are, so they can relate this information back to their Salesforce automation systems for example.

How AI can revolutionize rebate management

Leveraging AI to analyze and visualize contracted agreements can streamline the management of rebate contracts, offering a more scalable solution that removes the heavy lifting.

Here are some of the ways AI can help you overcome these common pain points and benefit your pharmaceutical organization.

It helps automate repetitive tasks

If you’re sitting at your desk for 40 hours a week doing manual, repetitive tasks, that’s a process that can be automated using AI-powered rebate management software. At EncompaaS, we can automate document processing and the extraction of insights from complex contracts and master agreements, eliminating manual processing and saving your teams thousands of hours.

It helps you efficiently extract more accurate data

Just like your formularies won’t cure 100% of the population taking them, if the FDA found out that 80% of the people taking them were being cured or treated successfully, that’s a really great business outcome. Similarly, AI can help you automate the extraction of key contract data with great accuracy (over 90%) and at a much faster rate, eliminating human error and streamlining pharmaceutical supplier rebate management processes.

It fast tracks data-driven decision making

The better data you have, the better decisions you can make. If you’re making misinformed decisions by having inaccurate or incomplete data, that’s incredibly risky. AI can not only help you extract accurate contract data, but it can do it in real-time so it’s always up to date. By leveraging AI, time to information is greatly accelerated compared to manual contract landscapes updates, which take thousands of hours to complete every quarter. What’s more, by getting key insight from your data faster, this creates a competitive advantage.

It enables enhanced collaboration

AI allows you to collaborate a lot more effectively on your rebate projects by identifying specific data points that multiple different stakeholders are or aren’t interested in. Everyone benefits from real-time information accuracy based on what’s important to them in their roles, whether they’re Rebate Contract Managers or Chief Legal Officers.

It enables you to leverage repeatable results

Once you have the right machine learning model established, the results you’re going to get are consistent – day in, day out. AI doesn’t ask for days off, doesn’t take a lunch break or call in sick – so once you train these models to get what you want out of them, you’re going to get a highly repeatable result of data flow that allows you to do your job a lot better.

Future Proofing Rebate Management 

At EncompaaS, we use AI to inspect complex rebate contracts and extract data with speed and accuracy, allowing you to visualize important rebate management data in seconds.

With advanced analytics and customizable dashboards, you can easily connect the dots between agreement and business performance so you can understand your rebate position in real-time, including correlations and rollups.

This means you can ask pertinent questions of your data, spot risks and opportunities faster, make rapid commercial decisions, and maximize the revenue potential of every rebate contract.