Gross to Net Benchmarking Survey – Initial Trends: Forecasting Accuracy

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In the life sciences industry, gross to net (GTN) is the management process at the heart of the pricing and contracting lifecycle. Within this process, manufacturers forecast demand and accrue for rebates, chargebacks, and any other adjustments to the price charged for a product’s sale.

HighPoint is currently conducting a Gross to Net Benchmarking Survey with the goal of gaining insight into current process trends for life sciences manufacturers. Preliminary results have yielded some useful insights, which we’re sharing in an ongoing series of blogs. Previously, we reviewed the initial trends for organizational size and structure. In this installment, we take a look at forecasting accuracy.

Respondent demographics

The following trends are based on a sample of 15 small, medium, and large life sciences manufacturers and reported annual revenues. As the sample size builds up, we expect the statistical significance of the results to increase; however, the initial data can provide some directional trend information for decision makers.

The current set of responses are distributed relatively evenly across branded, generic, branded generic, and biotech manufacturers. Biopharma and medical device companies have lower representation. Of the initial set of respondents, 60 percent report having a role of associate director or above.

Survey questions regarding gross to net forecasting accuracy

HighPoint’s benchmarking survey requested manufacturer perspective on the following six aspects of gross to net forecasting accuracy:

  1. Does your organization have a formal forecast review process?
  2. What are the number of levels for final forecast approval?
  3. How does your organization measure forecast accuracy?
  4. What are management expectations related to forecast accuracy?
  5. Over the past 3 years, how have historical forecasts varied from actuals?
  6. How does your organization deal with uncertainty in the forecasting process?

Initial insights

1. Does your organization have a formal forecast review process?

As expected, overall, the majority of respondents reported having a formal forecast review process:

  • 89 percent of all respondents
  • 100 percent of large pharma respondents

 

 

 

2. What are the number of levels for final forecast approval?

90 percent of all respondents reported having up to 6 levels of approvals; however, the trends vary based on organization size:

  • Small organizations:
    • 67 percent reported having 1­ to 2 levels of approval.
    • 17 percent reported 3 to 4 levels.
  • Large organizations:
    • 100 percent reported having 3 to 6 levels of approval.
      • 67 percent reported having 3 to 4 levels.
      • 33 percent reported having 5 to 6 levels.

 

3. How does your organization measure forecast accuracy?

Responses show a clear distinction between how large and small pharma approach reviewing forecasts for accuracy:

  • Large pharma:
    • 67 percent have a formal process to review the forecasts if the variance is beyond a pre-defined threshold.
    • Only 33 percent have a formal process to review on a regular basis.
  • Small pharma:
    • 33 percent have a formal process to review forecasts on a regular basis; while an equal proportion (33 percent) manages the process informally.
    • 17 percent have a formal process to review once forecast variance goes beyond a certain threshold; while another 17 percent have no plans to track forecasting accuracy in the near future.

 

4. What are management expectations related to forecast accuracy?

Survey responses reveal an overall lack of consistency in executive expectations for forecast accuracy:

  • Across both large and small pharma, an equal proportion of respondents report that they are not aware of any executive expectations.
  • Nearly 45 percent of respondents report that either there are no stated accuracy expectations from management (11 percent) or they do not know what the expectations are (33 percent).
  • On the other end of the spectrum, nearly 45 percent report that management expects actuals to fall within 0 to 4 percent of forecasts; of these, the majority report expectations for forecast accuracy within 0 to 2 percent.

 

5. Over the past 3 years, how have historical forecasts varied from actuals?

Despite stated expectations of high accuracy, the average performance across all organizations is relatively mixed:

  • Approximately 56 percent of organizations understated their forecast.
    • 67 percent of small organizations
    • 33 percent of large organizations
  • 33 percent of respondents were not aware of historical performance.

 

6. How does your organization deal with uncertainty in the forecasting process?

Responses show a clear indication of how organizations deal with managing uncertainty:

  • 78 percent of organizations report producing only one forecast number but make a note of downside and upside risk. This includes 100 percent of large organizations and 67 percent of small organizations.
  • Only a small subset of organizations (16.6 percent) report performing extensive, scenario-based forecasts.

 

Preliminary conclusion

Initial benchmarking results are very consistent with informal observations across the industry:

  • Forecasting accuracy is a much talked about topic; however, there is great variation in terms of implementing processes that lead to more accuracy.
  • Although the sample size is limited, the survey responses suggest a systematic correlation between management expectations and what actually happens.
  • Consistent negative variance of actual vs. forecasted results suggests forecasts are usually optimistic, which may be leading to non-optimal utilization of cash reserves.
  • Management expectations are fairly tight regarding forecasting accuracy; however, the typical mix of complex manual processes and unsophisticated gross to net forecasting tools does not support the level of accuracy required.

To learn more about gross to net trends and best practices for life sciences companies, contact Neelabh Saxena.

Tags: Life Sciences, pcma, gross to net, gtn, forecasting accuracy, pricing and contracting

   

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