Top 5 forecasting tips in Oncology
We recognise that Oncology can be very challenging to forecast, particularly as we’ve racked up over 10 years working in the field!
For that reason, we’ve put together 5 tips on how you can forecast more effectively.
Should you require more in-depth assistance, feel free to contact our team for more information about online training or our Onco+ Excel-based forecasting software.
You can even request a free demo here: https://jdforecasting.com/callback/
1 – All Change
Consider the stability of the market when deciding on the methodology.
Patient flow models are accurate and provide a great deal of insight, however, they’re only really necessary when there is a part or future variability across stages or lines of treatment.
2 – Devil’s in the detail
Using pre-calculated treatable patients saves a lot of time.
However, check the data and assumptions used by your data provider. They should use up-to-date sources that are local where possible
3 – Look before you jump
As with all forecasting, there are 3 key considerations that should be weighed against each other: value of the decision, accuracy required and the data available.
Before employing a patient flow methodology, rather than a more simplistic prevalence-based model, the forecaster should consider if the data supports the methodology, lots of complex algorithms do not deliver value if the inputs are largely assumption-based.
4 – Does it make a difference?
Sometimes there is an urge to forecast a variable because you can, but the more detailed and complex a model is, the less value it will often bring.
So always ask the question: Does it make a difference? A good example is the inclusion of 3rd or 4th line patients, does their inclusion make any substantial difference to the final forecast? If the answer is no, then group them.
5 – Step out of the bubble
Your product can achieve great OS, or perhaps PFS or ORR, however, the wider environment may pose some challenges.
Consider some questions:
- How competitive is the market?
- How much investment is required to penetrate a highly competitive market?
- What is the distribution of potential prescribers?
- Could the healthcare system bear the cost of the product?
