In a conversation with David W. Gould, Chief Customer Officer at EncompaaS, we delve into the transformative potential of AI in pharmaceutical rebate contract management. EncompaaS is revolutionizing the industry by leveraging next-generation AI technologies to automate processes, streamline data management, and provide real-time insights. Through innovative solutions, EncompaaS aims to empower pharmaceutical companies to navigate complex contractual relationships, maximize revenue potential, and ultimately contribute to improving human health and productivity.”
1. Can you tell us a bit about EncompaaS and its mission in the pharmaceutical industry?
The one thing we know best about pharmaceutical manufacturing is that time to success and time to failure are the two most important metrics driving business processes and outcomes. The relationships and processes large pharmaceutical companies must manage are extremely complex and often hard to navigate. The relationships between manufacturers, pharmaceutical benefit managers, payers, and the healthcare delivery system are based on complex contractual relationships. And, without the ability to connect the dots between contractual terms and business performance, the complexity of relationships becomes even harder to manage for a successful business outcome for all parties involved.
The EncompaaS platform uses next-generation AI technologies to find, enrich, and organize structured, unstructured, and semi-structured data into a normalized data quality foundation. This enables automated governance at scale, ensuring information is de-risked, and preparing the highest quality data to fuel upstream processes.
EncompaaS’ mission in the pharmaceutical industry is to revolutionize the way rebate and other business contracts are managed to provide the best possible outcome. We do this by leveraging our unique policy engine that drives AI to analyze all regional, national, and government rebate contracts, create standardized policies, and eliminate manual processes at scale. This allows pharma manufacturers to understand their rebate position – including correlations and rollups – in real-time so they can maximize the revenue potential of every rebate contract.
2. What are some of the most common challenges pharmaceutical companies face in managing rebate contracts traditionally?
Contract Managers typically spend a significant portion of their jobs manually searching through thousands of pages of complex rebate contracts to find specific language, passages, or data points to input into spreadsheets. Some words and data could be in handwritten notes scrawled in the margins. This is the experience that many, if not all, contract managers endure when managing business outcomes for the rebate programs they manage. It’s an incredibly tedious and time-consuming job for highly skilled and educated workers. Because of its precision-driven nature, many contract managers get bogged down in managing the details rather than being able to focus on better business outcomes for their organizations. This leads to a great deal of frustration and job disappointment.
3. How do these challenges impact revenue and operational efficiency?
The sheer scale, breadth, and complexity of rebate contracts (often numbering in the tens of thousands) often leads to inefficiencies in productivity and data management, impacting crucial aspects like time-to-information, distribution, and competitive advantage. For an industry so driven by time to success and time to failure, these challenges impede, if not block, the manager’s ability to respond quickly, accurately, and with the insight required.
4. How does AI technology address the issues faced by pharmaceutical companies in rebate contract management?
AI technology is prevalent all throughout the clinical side of the pharmaceutical manufacturing business. It is not a new concept, but it is extremely well integrated into clinical advancements. On the business side, AI, in this case, Intelligent Document Processing, enables pharmaceutical contract managers to automate an incredibly tedious and time-consuming process. It saves teams hundreds of hours by automating document processing and the extraction of insights from complex contracts and master agreements. AI and powerful analytics provide key answers to questions regarding product performance, business relationship status, and competitive advantage.
5. Could you provide examples of how AI-driven solutions have helped companies mitigate errors and improve decision-making?
Case study example:
A global pharmaceutical organization sought to understand and analyze the effect of vendor rebates on a drug’s net revenue across tens of thousands of master contracts and amendment documents. The sheer volume of data, inconsistency in its format, and time required for human processing led them to seek a technology solution to streamline this process.
EncompaaS was selected to transform the way rebate contracts were managed with advanced AI-powered Intelligent Document Processing. A Proof of Concept was completed, whereby a model was built and trained with exemplar contracts to automatically extract rebate information from different formats, such as text and tables, and correctly reproduce the data in a reporting dashboard for comprehensive analysis.
Using EncompaaS, the pharmaceutical organization has successfully automated a critical task, enabling the business to assess with accuracy the performance of vendors and the net effect of rebates on a drug’s revenue. The insights gained will support them in making informed business decisions on drug pricing and sales targets and in assessing the true profitability of a drug. This means saving tens of millions of dollars every year in their rebate program.
6. What specific features does the EncompaaS platform offer to streamline rebate contract management?
EncompaaS harnesses Intelligent Document Processing to effortlessly analyze all regional, national, and government rebate contracts — and automatically extract data with speed and accuracy. The EncompaaS solution extracts literally hundreds of data points from contracts and amendments and allows that extracted data to be visualized and better understood from a “persona” point of view. For example, the EncompaaS analytics dashboards can be configured and visualized with a specific point of view or a specific swath of business perspective. For example, a product manager can track actual product sales to a specific dosing or delivery system against contracted terms. Pharmaceutical sales reps can understand the tiered sales structures defined in a business contract. With advanced analytics and customizable dashboards, it allows rebate managers to 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 about your data, spot risks and opportunities faster, make rapid commercial decisions, and maximize the revenue potential of every rebate contract.
7. How does your platform leverage AI to provide accurate, real-time data and insights?
EncompaaS leverages Azure OpenAI and Supervised Machine Learning, to automatically inspect all live rebate contracts (including master agreements, amendments, and associated documentation) with speed and accuracy.
EncompaaS scans the content of contracts, intelligently extracts key information such as Contract Value, Dates, Parties, Products, and applies it as structured metadata on the contract itself. This metadata can then be used for searching, sorting, filtering, and reporting in a consistent way across all contracts, wherever they are stored.
Your most valuable contract and sales data can then be presented in highly visual dashboards, providing live, up-to-date landscape views that contract teams, rebate managers, and sales representatives can harness for informed decision-making on current strategies, rebates, and market data.
8. What are the primary benefits that pharmaceutical companies can expect from adopting AI-driven rebate contract management solutions?
- Eliminates manual processing
- Improves Accuracy
- Ability to understand your rebate position in seconds
- Empowers teams to focus on strategic tasks instead of manual tasks
- Enhances vendor relationships through improved transparency
9. How do you envision the role of AI evolving in pharmaceutical rebate contract management in the coming years?
EncompaaS sees a couple of key trends emerging that will rapidly advance the state of rebate management. First, organizations will not need to intensely train extraction models with large volumes of samples. Advances in Open AI and the ability to create Small Language Models (SLMs) on the fly will reduce the time it takes to establish and test models used to extract and visualize information. Small Language Models offer the ability to minimize “training” software as well as provide even higher degrees of confidence and ultimately accuracy of response. Second, tools like Microsoft Copilot will drive the “autonomy” of model development, giving large pharmaceutical companies the ability to understand their business position against contracted language faster and more accurately than ever before.
– Are there any emerging technologies or trends that you believe will further enhance the capabilities of AI in this field?
Tools like CoPilot will also reduce the time it takes to gather requirements for AI-driven model development, thereby speeding the implementation process of getting the models exactly right.
10. How does EncompaaS ensure smooth integration of its platform with existing systems and processes within pharmaceutical companies?
The EncompaaS data quality layer automates sensitive, private, and repetitive documents, ensuring accuracy. In a matter of weeks, our low-code solution will be provisioned in your Microsoft Azure cloud, providing direct access to all contract repositories. In addition to mitigating content risk, your sensitive data never leaves your control or firewall.
11. What does the implementation process typically look like for clients adopting your AI solution?
The implementation process is similar to any other software implementation process. Being able to document requirements and then represent those requirements into a data schema that allows for deep understanding of complex questions is the number one challenge. The requirements are somewhat similar, but not necessarily alike, for all pharmaceutical manufacturers. So the ability to identify those requirements and define behaviors through policy are the two key challenges faced by every organization.
12. Given the sensitive nature of pharmaceutical data, how does EncompaaS address security and compliance requirements?
With EncompaaS, data never leaves the manufacturer’s Azure tenancy. In addition to our own data security functionality, such as security trimming and access control, EncompaaS leverages the world class security infrastructure of Azure, which meets all security standards, such as SOC 11 and ISO.
13. What kind of support and training does EncompaaS offer to its clients to ensure they maximize the value of the platform?
We offer a comprehensive training and enablement program for data extraction and visualization. At our largest customer, users are taught to leverage our built-in analytics engine by creating highly personalized dashboards that visualize and present data in the way the contract manager wants to see it. We also offer a managed service offering that allows the manufacturer to rely on EncompaaS consultants to do the work on behalf of the company.
14. Is there anything else you’d like to add about the transformative potential of AI in pharmaceutical rebate contract management?
As stated earlier, AI is already deeply embedded in the technology fabric of every large pharmaceutical manufacturer. Where AI offers the most promise is at the personal level. It truly is the first technological advance that touches individuals as well as systems. We think a lot about the highly educated personnel who come to work at large pharma and the ways in which they can support the mission, which is, across the board, to make humans more healthy, productive and thrive longer. There is no greater mission in professional life. We see AI as the pathway to transform individuals at their desks by removing the tedium and drudgery and allowing the best and brightest to focus more on that mission and how their companies can better deliver on its promise to the medical system. In our minds, AI is the lynchpin for achieving that aspiration.
