- Seasonal ARIMA: This technique is well-suited for forecasting seasonal trends. It is also the most accurate of the three techniques, but it is also the most complex to implement.
Why:
I recommend using a combination of simple exponential smoothing, linear regression, and seasonal ARIMA to forecast the three content items. This approach will allow you to leverage the strengths of each technique and minimize their weaknesses.
- Simple exponential smoothing: Use this technique to forecast the number of patients treated and revenue. These two content items are likely to have short-term trends that are well-suited for forecasting with simple exponential smoothing.
- Linear regression: Use this technique to forecast the average length of stay. This content item is likely to have a linear trend that is well-suited for forecasting with linear regression.
- Seasonal ARIMA: Use this technique to forecast the number of patients treated and revenue if there is a strong seasonal component to these content items.
It is important to note that these are just recommendations. The best forecasting technique for a particular content item will depend on the specific characteristics of that item.
In addition to forecasting the three content items, you should also forecast the impact of the new competing hospital. This can be done by developing a scenario analysis. In the scenario analysis, you would consider different possible outcomes for the new hospital, such as different levels of market share and different pricing strategies. For each scenario, you would then forecast the impact on Memorial Hospital's patient volume, average length of stay, and revenue.
By forecasting the three content items and the impact of the new competing hospital, you can develop a more informed strategic plan for Memorial Hospital. This plan will help you to ensure that Memorial Hospital remains competitive and financially viable in the future.