What type of forecasting would best help in predicting demand accurately for planning purposes?

Quantitative data analysis is the best method for predicting demand accurately because it relies on numerical data and statistical techniques that can analyze past demand patterns and trends. This approach allows organizations to make informed, data-driven decisions based on measurable factors such as sales history, market trends, and other relevant metrics. By applying mathematical models and forecasting methods, businesses can create projections that account for seasonal variations, economic conditions, and other quantifiable variables.

In contrast, qualitative data analysis, while useful for understanding subjective factors such as customer sentiment or market conditions, does not provide the same level of precision that quantitative methods can offer. Market research surveys can gather insights and opinions, but these are often less structured and harder to analyze numerically. Supplier capacity reviews focus on the operational aspects of fulfilling demand but do not directly inform demand forecasting. Thus, while each option has its value in the broader context of supply chain management, quantitative data analysis stands out as the most effective approach for accurate demand forecasting in planning.