For years, the Drug Channels Institute (DCI) has been tracking what it calls the “gross-to-net (GTN) bubble” in pharma sales. This bubble is the growing difference between sales of brand-name drugs at list prices and sales at the actual prices after rebates, incentives, returns, and other reductions have been taken into consideration. DCI estimates that in 2021, the GTN bubble reached a record high of $204 billion for patent-protected brand-name drugs. When the calculation included brand-name drugs that lost patent protection and competed directly with generics, the bubble was even bigger: a whopping $236 billion.
What this means is that despite rising list prices, pharma and biotech companies are reaping less profit from their products at a time when estimates for R&D costs of new medicine – taking into consideration the cost of failures – in 2021 rose to as high as $2.8 billion.
The reasons are varied, but according to global consulting firm InformaConnect, they include:
- Escalating rebates for preferred formulary access
- Contracts for protecting prices
- Medicare “donut hole” increases
- Medicaid best-price and consumer price index (CPI)-penalty rebates
- Increases in pharma copays
- 340B drug-pricing government program expansion
- Duplicate discounts for 340B and Medicaid
In this blog, we’ll explain what GTN is, why it’s a strategically critical metric for life sciences firms, and how an essential first step for managing it is to create a clean, trusted, central repository of consolidated data that is your single source of truth for go-to-market financial decisions about pharma and biotech products.
GTN is the number computed when you take the gross revenue of a product – usually the list price, or what is commonly referred to as the wholesaler acquisition cost (WAC) – and subtract all the contract price discounts, cash discounts, rebates, and returns that are the result of collaborating with third-party partners to bring your product to market. This gives you your net revenues for a particular product SKU.
KPMG has observed average GTNs of 55% and reports that up to 35% of pharma SKUs are not profitable due to high discounts.
Why GTN is important
GTN is critical first and foremost because of financial reporting requirements. Publicly traded companies need to release regular statements containing their earnings and general performance metrics. Without a precise grasp of GTN, life science companies risk over- or understating profitability. They may have sold $1 million of a product at the list price but still must account for all chargebacks and rebates – some of which can only be estimated, as inventories in warehouses can either get sold or returned. Inaccurate estimations can result in regulatory complications – including fines – as well as dissatisfied stakeholders and loss of market reputation.
GTN is also important because most life sciences firms depend on third parties to commercialize their products. They typically work with a range of distribution companies and attempt – with rebates, chargebacks, and other incentives – to get to a profitable balance of reach and cost efficiency when bringing products to market.
But with the growing GTN bubble, things are tilting out of balance. Mergers, acquisitions, and consolidations have increased distributors’ power at the negotiating table. And rather than treating this as a serious issue affecting their bottom lines, too many life-sciences firms have treated GTN management as a tactical rather than strategic tool needed to achieve a competitive edge.
GTN challenges to overcome
The most serious challenges that are preventing life sciences firms from optimizing GTN revolve around trustworthy data, transparency, and the complexity of the GTN ecosystem.
- Inaccurate, inconsistent, missing, or siloed data: Getting all contract, pricing, and transactional data into a standardized format is difficult when data sources are siloed across different platforms. Because datasets get out of sync with each other, it’s difficult to know what numbers to trust, much less make comparisons that allow you to confidently strategize GTN actions across product lines.
- Complex contracts: Already-complicated deals are becoming even more byzantine, making it difficult to build analytical or predictive models that can accurately forecast and calculate accruals. Contracts can possess payment timing and achievement thresholds that vary considerably, challenging your ability to properly accrue and make accurate sales forecasts for products.
- Error-prone manual or spreadsheet-driven processes: No complete solution that automates the end-to-end process has yet emerged because the number of potential scenarios and dimensions is “exponential,” according to KPMG. Regulation, contracts, product languages, access, competition, and parallel trade all complicate matters. Attempting to do this by hand or even with spreadsheets has not proved successful.
- Limited transparency: Most life-sciences companies lack transparency on what they spend on GTN distribution agreements – on everything accruing from rebates and discounts to investments in marketing activities. They are spending many millions yet have no way of knowing the return on investment (ROI) of this money. Because many life-sciences firms don’t tie what they spend on GTN to performance, much less to overall company goals, GTN often represents a black hole into which increasingly large amounts are thrown. To complicate matters, GTN expenditures can vary across partners and channels, but the lack of transparency makes it impossible to understand how the inconsistencies impact sales.
- Organizational resistance: As with any major cultural change, putting technology in place is not enough to transform GTN from an operational challenge to a winning corporate strategy. Constant analyses, monitoring, and governance are required to make sure your organization is not contributing to the expansion of the GTN bubble.
GTN next steps: it’s all about the data
To be successful, GTN must be a separate corporate function that applies a holistic mix of people, processes, and technologies to what is unlikely going to be resolved by law or practice anytime soon. Create an interdisciplinary functional team that includes pricing, commercial, supply chain, tax, HR, modeling, IT, and compliance. You will need to act in sync – and be flexible and creative.
- Make sure you have a standardized, consolidated data set that represents the “single source of truth” that is used as the foundation for all G2N decisions at all levels.
- Use this data to make evidence-backed decisions about strategy and implementation, including being realistic about market segmentation.
- Create an interdisciplinary functional team that includes pricing, commercial, supply chain, tax, HR, modeling, IT, and compliance. Train them on your modeling and data. You will all need to act in sync – and be flexible and creative – to optimize GTN.
KPMG recommends the following data action items:
- Consolidate and clean data: This needs to be inclusive of all customers, products, and employee knowledge. You need to make sure your data is standardized and transparent and that you bring it together the “single source of truth” that is used as the foundation for all G2N decisions at all levels.
- Correct inconstancies in discounts and rebates: With your clean and transparent data, you should be able to see across invoices and apply discounts appropriately and accurately so you can make true comparisons.
- Monitor and eliminate high levels of unjustified price variation: Be careful that your partners don’t overuse commercial discounts and minimize discounts for so-called “long-tail” products and customers.
- Ensure that discounts or rebates you pay actually qualify for payment: Monitor and track your agreements and contracts so you don’t pay more than you should.
- Analyze and identify when discounts, rebates, and trade terms are not driving the customer behavior or financial outcomes you are hoping for.
Keep an eye on the G2N automation space
In the life sciences space, particularly pharmaceutical and biotech, GTN management is evolving into a strategic function that does much more than simply sum up manufacturers’ discounts. GTN optimization requires cross-functional collaboration and should be part of every company’s strategic vision.
With such a setup, you should be able to:
- Calculate more precise accruals
- Create an accurate forecasting model that can be easily adjusted and audited
- Perform “what-if” analyses to test different GTN strategies
The best thing a life science firm can do is to ensure that their data is clean and trustworthy and represents a single source of truth. Leveraging technology should be able to provide that. Applying artificial intelligence (AI) and machine learning (ML) to modeling and analytics will eventually untangle the GTN knot, but that solution still lies in the future.
Keep in touch, and we’ll keep you posted.