2075_Rams_Forecasting_Benchmark_blog_img-508328-editedThis post is the second in a four-part series on how pharmaceutical companies can elevate their forecasting operations.

The pharmaceutical industry is facing an increasingly challenging environment with looming biosimilar launches, tighter access and pricing controls, and saturation within primary care markets. Forecasting as a functional area is affected by these changes, given the range of decisions that forecasts inform.

ZS recently conducted an extensive benchmarking study with around 30 forecasting leads across the globe from small and large pharmaceutical organizations. The focus of this study was to understand how forecasting fits within an organization, along with key trends and opportunities. The results from this benchmark research provide forecasting leaders with valuable insights on the challenges and opportunities facing them. Here are three of the most important takeaways:

1. Forecasters are adapting to meet changing needs. Forty-three percent of respondents indicated that their teams forecast for orphan or rare diseases, which is twice as many as in our 2015 benchmarking study. This is driven by a shift in focus across the industry toward highly specialized markets. Another 45% of our respondents indicated working on forecasts that include biosimilars, two-thirds of which are working on forecasts that include biosimilar launches by competitors as opposed to their own biosimilar launch.

Given the limited biosimilar launches within most individual markets, forecasters will have to acquire additional data to research uptakes in other markets and develop new analogue libraries with price-elastic erosion curves. In addition, the rapid changes in managed care access is requiring forecasters to build payer- or channel-level forecasts to inform their short-term planning accurately. Our research indicates that 65% of forecasters are already using forecasts that include payer- or channel-level segments.

2. There’s consistency and transparency in forecasts. Forecasting processes within an organization and the associated coordination challenges are the least satisfying part of a forecaster’s role, and one that 90% of forecasters ranked as a high priority for change. There’s a unanimous drive to create consistent forecasts across the organization using tools and processes that lead to better collaboration and transparency. However, 60% of all respondents indicated that they don’t have standardized processes and tools, leading to inconsistency in reporting across teams. This inconsistency creates strain across teams during product launch, when regional affiliates and their global counterparts collaborate to develop detailed launch forecast plans.

This is a great opportunity to develop consistent tools and processes, something that best-in-class organizations already do. However, organizations that do this successfully also recognize the importance of establishing a forecasting center of excellence (formally or informally). The role of this group is to introduce new tools, standardize processes, share best practices, provide trainings, etc., and to have some degree of ownership of forecasting as a strategic capability within the organization.

3. Forecasters are embracing the future. Around 70% of our respondents are exploring artificial intelligence and machine learning approaches to improve their forecasting accuracy.

While the success of these approaches is yet to be determined, there’s clearly an appetite to look beyond traditional techniques to improve accuracy. This could be driven by another increasingly important trend among organizations to bridge the forecast against actual sales. In our studies, we see an increase of nearly 20% more participants (from 36% to 55%) being required to bridge forecasts against actual sales to track accuracy. In particular, short-term forecasts that inform tactical planning decisions are held to higher accuracy standards (within 5% of actual sales).

While accuracy is important in the short term, long-term strategic forecasters are embracing uncertainty in their reports and discussions. Seventy-five percent of our respondents communicate uncertainties in their forecast through ranges and scenarios with senior business stakeholders. Around 40% of these respondents take it a step further and discuss the key assumptions that are driving the most uncertainty. This lets them prioritize their efforts and investments on the key assumptions and data sources that matter to their forecast, and eventually to their business decisions.

The changes in the industry are presenting new challenges to forecasters and exacerbating existing ones. These changes also are presenting opportunities to adopt new tools, embrace new approaches and standardize processes. Some organizations have identified these needs and are ahead of the curve, turning their forecasting lens inward to the forecasting work that’s required to prepare for an evolving and uncertain future.


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Topics: forecasting, Pharma, insights, artificial intelligence, AI, machine learning, artificial intelligence & pharma, pharma landscape, ZS research, forecasting in pharma