IDOL mumbai university supply chain management logistics important question

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   M.COM SEMESTER - IV (CBCS)

BUSINESS STUDIES (MANAGEMENT)

SUPPLY CHAIN MANAGEMENT LOGISTICS

IDOL mumbai university supply chain management logistics important question


Q.5 Explain in detail forecasting in SCM and the need for the same in business.

ANS:

Forecasting is the process of making predictions based on past and present data. Later these can be compared (resolved) against what happens.

  • ·        For example, a company might estimate their revenue in the next year, then compare it against the actual results. Prediction is a similar, but more general term.
  • ·        Forecasting might refer to specific formal statistical methods employing time series, cross-sectional or longitudinal data, or Supply Chain Management and Logistics alternatively to less formal judgmental methods or the process of prediction and resolution itself.
  • ·        Usage can differ between areas of application: for example, in hydrology the terms "forecast" and "forecasting" are sometimes reserved for estimates of values at certain specific future times, while the term "prediction" is used for more general estimates, such as the number of times floods will occur over a long period.
  • ·        Risk and uncertainty are central to forecasting and prediction; it is generally considered good practice to indicate the degree of uncertainty attaching to forecasts.
  • ·        In any case, the data must be up to date in order for the forecast to be as accurate as possible. In some cases the data used to predict the variable of interest is itself forecast.
  • ·        Data-driven forecasting provides more accurate predictions, but qualitative data also plays a significant role in supply chain forecasting and has proven to be just as effective.
  • ·        In many cases, ecommerce brands use a combination of both quantitative and qualitative forecasting methods to get as close to accurate predictions as possible.
  • ·        However, qualitative forecasting methods come in handy when there is a lack of data. Oftentimes, new businesses or innovative products rely on qualitative forecasting methods to make predictions. Here are the most common qualitative forecasting methods used in ecommerce supply chain forecasting.

1. Market research:

Market research is a best practice for any business, whether it’s selling a product or even a service. For ecommerce sales, market research can be used to predict supply and demand, and help determine whether or not there is strong demand for a product that will support profit goals. Market research can be executed internally by marketing or sales experts, or businesses can hire a third-party that specialize in market research. There are different tactics used, from developing stakeholder surveys, conducting a thorough competitive analysis, or even interviewing experts in a specific field or industry.

2. Delphi method:

The Delphi method consists of market orientation and judgments within a small group of experts or advisors, which is then sorted, grouped, and analyzed by third-party experts.

The opinions of the experts are gathered individually to avoid the influence of others’ options, which differs from a panel discussion or focus group. The gathering of opinions is outsourced to a third-party, which analyzes the opinions and information shared. Once reviewed closely, the information is then summarized with an emphasis on different patterns or trends before handing the findings over to the business to review. This method has proved effective and dependable for long-term forecasting.

3. Historical analysis:

Historical analysis uses the sales history of a product having a parallel relationship with a present product to predict future sales. It can be utilized to predict the market’s response to a new product or product line. For instance, if you sell vacuums, you would look at past performance on your highest selling vacuum models. Then, you would compare whether or not the features for the new vacuum are similar yet offer something new and improved in terms of settings and options.

Historical data can also be collected by looking at your competition’s high-selling products and comparing similar products in your line to determine demand when possible.

4. Panel consensus:

The panel consensus method brings together members of a business across all levels to establish its forecast. It is an open process that allows all the participants to express their opinions and predictions based on what they know.

For example, you could work with your ecommerce customer service team to identify which products are being returned most often and why, or work with your sales team to get insights on what customers are asking for.

 

 

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