Is Your Gross-to-Net Strategy Ready for Uncertainty? Economic, Market & Regulatory Factors
In the life sciences industry, pharmaceutical drug manufacturers operate in a universe of changing market dynamics, rules & regulations and competitive markets. But lately, with materials and labor woes coupled with economic volatility, they’re understandably worried more than usual about managing financial performance through a Gross-to-Net (GtN) forecast and accruals process and the resilience of their balance sheet.
With shifting regulations, ever-changing market conditions and economic uncertainty all expected in the future, organizations have strived to be more intentional about financial planning and analysis, including how they approach their GtN strategy. There is a shift towards standardizing, centralizing and scrutinizing data, processes and forecast models to pressure-test them for the unknowns ahead through scenario and sensitivity analyses.
At the same time, that can all seem easier said than done. “There’s a lot that goes into designing, developing, executing, and maintaining a strong GtN management process that accurately predicts net prices…continuously and consistently,” says Thomas Benton, Senior Manager in Cognizant’s life sciences consulting practice.
“The management of GtN processes requires an intimate understanding of the product, channel strategy, contracts strategy, data, technology, government pricing, finance, accounting, and regulations,” he said.
“This is usually not the responsibility of one individual or team and requires cross-functional participation, communication, and engagement for optimal management of GtN processes, systems, and data used to calculate GtN rates. Through our deep understanding of life sciences companies’ current challenges and issues, we have observed a continued, reinforced focus to marginalize revenue leakage by evaluating current GtN methodology for net price and GtN rate calculations,” he said.
Recently, we caught up with Tom to discuss how pharmaceutical leaders and their organizations should be approaching—and potentially automating—GtN and why your organization’s “call to action” is imminent. Here’s what to consider:
Streamlining the data ecosystem
The data powering GtN strategy has never been more expansive, transparent, and actionable. However, is your organization still using disparate data sources from various origins and source systems?
Data from disparate sources can lead to opportunities to optimize business processes, streamline workflows, and improve data verification. Upstream tools used to streamline data exchanges and strengthen business assumptions, systems, and overall processes can be invaluable during the GtN forecasting process.
“Whether it’s historical demand or utilization data, you want to ensure a complete, accurate, and consistent picture is provided that helps predict better outcomes in the future,” he said, adding that this upfront effort saves time and resources down the line, as well as enables automation through machine learning (ML) and artificial intelligence (AI).
Whether a small or large drug manufacturer, organizations must not forget the “completeness” part: If you lack verification of basic inputs like contracts, pricing, and customer eligibility, it can create blind spots in your GtN strategy during month-end close variance analysis and anomalies within baseline assumptions for forecasting.
In today’s world, with the power of data and AI/ML, many organizations are currently thinking about the following:
- Is the data utilized complete, accurate and timely throughout the GtN systems and processes?
- Does the data used in forecast and variance analysis provide sufficient information to provide systematic verifications and automated insights?
Assessing the sophistication of your process
Think about the time your organization spends on manual processes like loading forecast data, ad hoc queries for variance analysis and creation of reporting. Are there opportunities to consolidate and simplify with a leaner, more powerful workflow to enable data-driven decision-making?
Very likely so, but it depends on the sophistication of your process, data, and the organization’s capabilities. Ideally, systems and forecast models should be advanced enough that they can be tailored for various scenarios and perform rapid analysis of outputs from changes in demand, product, pricing, and contracting assumptions. Business processes supported with complete, accurate and consistent data and information provide an optimal foundation for GtN strategy.
“Even though organizations leverage tailored processes to calculate GtN rates for portfolios and brands, the information your organization uses to analyze trends or analyze variances between forecast and actuals may be manual. If so, this is an opportunity to evaluate your processes to streamline operations,” he said. “For example, centralizing data and streamlining through Extract, Transform, and Load Application programming interfaces from point A to point B can allow resources to be allocated to higher priority, strategic activities.”
Staying ready for regulatory impacts and audits
The regulatory universe is always evolving, often in nuanced ways. Consider the Inflation Reduction Act (IRA) of 2022 , which has requirements for manufacturers to negotiate with Medicare for high spend, high priced drugs and subject to CPI-U inflationary penalties — if pricing increases faster than the rate of inflation. For example, from June 2021 to 2022, the Consumer Price Index for All Urban Consumers increased 9.1 percent, which is the largest increase in over 40 years.
“Rules, regulations, and sub-regulatory guidance all impact how a manufacturer approaches pricing and contracting decisions as they go to market and manage GtN strategy,” Tom said. “And it can get quite ambiguous because you may not know the outcome of government negotiations and pricing when you set your forecast (as it relates to IRA).”
He recommends that stakeholders at least consider—the best they can—how government pricing, regulatory developments, and socio-economic changes, such as CPI-U and poverty levels factor into the GtN strategy and inputs into long-range planning (LRP). To continue to ensure audit readiness, manufacturers must have a good internal monitoring and auditing process that is documented, followed, and routinely evaluated by the organization for updates.
Based on his conversations with drug manufacturers, he recommends assessing the current GtN strategy by addressing the following questions:
- How frequently is your organization performing assessment of your business processes directly or indirectly impacting GtN strategy?
- When was the last time your organization conducted an audit or assessment of the current operational, financial, and regulatory landscape for GtN management?
As labor shortages limit scalability and operational excellence, life sciences companies may need to reaffirm their approach to project management and resourcing.
Tom recommends organizations ask themselves two questions in particular:
- Is there adequate, timely, and cross-functional communication and transparency?
- Are there opportunities to automate manual tasks and reallocate resources to more revenue optimizing activities?
When resources are optimized, it stands to generate more value through human capital management and allocation of time toward revenue-generating or cost-cutting opportunities. A transparent and communicative culture supported by solid documentation, training and education is essential.
Staying Agile in Changing Environment
Whether times are good, bad, or somewhere in between, pharmaceutical manufacturers benefit from a holistic, centralized approach, including technological, financial, operational, and regulatory considerations for GtN management and predictability of GtN rates. With optimizations across people, processes, and technology by enabling AI/ML and enhanced processes, organizations can better prepare, predict, and manage financial performance.
And if you need guidance to get there, Cognizant can help.
1. Inflation Reduction Act of 2022, Pub. L. No. 117-169.