Sales Forecasting Methods: A Comparative Study with Excel-Based Analysis

Sales Forecasting Methods: A Comparative Study with Excel-Based Analysis

Priyanka Shrikhande

Student,

Indira School of Business Studies PGDM

priyanka.shrikhande@indiraisbs.ac.in

Samiksha Hirekhan

Student,

Indira School of Business Studies PGDM

samiksha.hirekhan@indiraisbs.ac.in

Abstract:

This research examines at the significance of sales forecasting is for determining operational effectiveness and business strategy. With the help of sales forecasting, firms can better plan their production schedules, anticipate market trends, manage their inventories, and enhance their financial planning. Sales forecasting offers crucial insights into future sales. Precise prediction ensure that companies may allocate resources efficiently, minimize ambiguities, and improve decision-making procedures throughout divisions including marketing, manufacturing, and supply chain administration.

The research paper offers a thorough comparison of multiple sales forecasting techniques, emphasizing both quantitative and qualitative methodologies. Relying on past data, quantitative techniques like time series analysis, regression analysis, and causal models are useful in well-established marketplaces with predictable demand patterns. However, in situations when there is a lack of historical data, such new product launches or market upheavals, qualitative methods including judgmental techniques like expert views and customer surveys are crucial.

The exploration of Excel as a flexible tool for sales forecasting is an essential component of this study. Businesses of all sizes and management experts may use Excel to execute forecasting approaches since it is a practical and affordable platform. In order to provide precise sales estimates, the article explores the usefulness of Excel-based techniques such as moving averages, regression analysis, and exponential smoothing. Excel's adaptability makes it possible for companies to use sophisticated forecasting techniques without the need for specialist software, which makes it a priceless resource for management professionals and students alike.

Real-world case studies demonstrate the actual use of these forecasting strategies, demonstrating how certain sectors and business environments benefit from particular approaches. The case studies also stress how crucial it is to choose the best forecasting technique depending on the state of the market, corporate objectives, and data availability. This research helps to improve corporate planning and decision-making by offering a framework for comparing and evaluating the strengths and weaknesses of different sales forecasting techniques. In the end, the study emphasizes how important sales forecasting is as a strategic tool and how Excel may improve forecasting accessibility and accuracy.

Keywords: Sales forecasting, strategic decision-making, management tools, Excel, time series analysis, regression, judgmental forecasting, business planning.