Demand forecasting can be defined as the process of predicting sales and consumption of pharmaceuticals so that they can be purchased in appropriate quantities in advance. It should be the goal of all supply chain managers to strike the right balance between demand and supply as this could have significant implications on overall success of the organization.
An excess supply of medicines may mean high storage costs and financial losses due to expired medicines. Conversely, demand that exceeds available supply may mean loss of current and potential clients to your direct competition.
Below are 5 key principles that can improve accuracy of forecasts for pharmaceuticals.
Focus on demand rather than customer orders
There is a fine margin between what demand is and what customer orders are. The former refers to the medicines the customer is willing and able to purchase, while the latter is the actual quantity of medicines a client buys at a given period. Organizations should focus on actual demand rather than customer orders. This is because customer orders are influenced by a myriad of factors that may greatly distort the forecasting process.
For instance, a drug wholesaler may make an unusually huge order of Panadol tablets not necessarily because the dispenser’s demand has increased but because he anticipates a shortage of the same.
Alternatively, a wholesaler may order a significantly lower amount of ibuprofen tablets just because the distributor is experiencing stock outs. In a third scenario, customer orders may be returned due quality issues.
Based on these reasons it is therefore not advisable to anchor forecasting on customer orders but rather on actual demand which can significantly differ.
Forecasts are almost never accurate
Unfortunately, regardless of whether you use the most sophisticated statistical techniques or the most accomplished industry experts, forecasting is almost always inaccurate. During the course of doing business, circumstances and minds change which in turn affects buying decisions.
As someone once said, the only thing constant in life is change and so is the demand for health products. Therefore, the goal is to just ensure that forecast errors are kept at a minimum through constant review of the forecasting techniques in use.
Some pharmaceutical companies make the mistake of basing their forecasts on their goals rather than the actual demand. This is a mistake as pharmaceutical forecasts should be based on data.
Read also: How to create highly efficient pharmacy teams (5 quick tips) – African Pharmaceutical Review
Always include an estimate of error
Since forecasts are estimates, it is inevitable that some form of error may creep in during the forecasting process. Careful statistical analysis of the variability of demand should therefore be carried out to determine the error estimate (monetary terms).
If a huge estimate of forecast error is detected, then it is advisable to review the forecasting steps. Alternatively, a restructure to accommodate the uncertainty of demand your medicines may be experiencing can be carried out.
Forecast pharmaceutical classes rather than a single drug
Pharmaceutical supply chain managers should focus on forecasting pharmacological classes rather than a single medicine. This concept of forecasting based on groups rather than single items is referred to as risk pooling.
The thinking is that, the low forecast items shall be offset by the high forecast items meaning the overall risk is lower than the average of all risks in the pool. For instance, it is better to forecast for antihistamines as a group rather than individually forecasting for cetirizine, there is less error that way.
Alternatively, one can as well pool risk by forecasting for a group of customers ordering the same item, rather than forecasting an individual medicine for an individual customer.
Short-term forecasts are better than long-term forecasts
Have you ever wondered why financial institutions charge more interest in long term loans rather than short-term ones? This is because in principle, long term plans are more prone to error since they are more likely to be derailed by chance and change.
For instance, someone who had a four-year demand forecast of certain classes of pharmaceuticals in 2018 may realize their numbers were inaccurate since they did not factor in the COVID pandemic. It is therefore advisable to do shorter-term forecasts and do appropriate forecast accuracy reviews to reduce estimate error.
Pharmaceutical supply chain managers are also encouraged to push for shorter lead times as this reduces the forecasting horizon and increasing accuracy of the forecast.
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