Tips On Effective Demand Planning #Startups - The Entrepreneurial Way with A.I.

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Wednesday, September 18, 2019

Tips On Effective Demand Planning #Startups

#businesstips

A vital aspect of supply chain management is demand planning — identifying and forecasting trends in the demand for products or services based on past data, surveys, market research, etc. Businesses must implement effective demand planning to stay competitive in the modern market, as customer demand is more volatile than ever.

Doing so is not a trivial task, but there are ways to improve your business’s current demand planning, address errors and respond to unforeseen changes.

Use a Process Model.

As with any management efforts, having a model prepared before you begin is important in ensuring that the entire process is fulfilled. Demand planning, in particular, can go awry when a business underestimates the scale of the project or fails to communicate effectively. The exact details may vary, but generally the outline should include:

  • Collecting past data
  • Initial statistical forecasting
  • Conducting market research
  • Incorporating forecasts with qualitative data
  • Devising and communicating plans
  • Performance monitoring and data reexamination
  • Adjusting forecasts as necessary

The Right Resources.

To most effectively make use of your data, you need to be able to collate, analyze, interpret and communicate effectively. Many demand planning software tools exist to facilitate gathering data from multiple points on the supply chain as well as creating data visualizations that allow you to understand the results clearly. These tools work best alongside trained statisticians and data scientists, either in-house or external partners, that can make informed decisions on how to eliminate bias, supplement the statistical forecast with market and consumer research and devise a plan to to implement.

Go Beyond Statistics.

Demand forecasting is not the same as demand planning, but rather a subset of it. Forecasting entails statistical analysis using historical data on sales and demand, but this can leave out key factors in what creates demand. A “naive” forecast is incomplete and often reactive at best; the quantitative data should be supplemented with “extrinsic” information and qualitative judgments on how demand changes. Factors such as new products or services, promotions, similar products from competitors and correlations with demand trends in other products are often relevant, and the final plans for the supply chain should take these into consideration when moving forward.

An Ongoing Process.

Demand planning is often discussed as a discrete endeavor, but this is rarely the case. It is a holistic process that involves multiple functions and sites within the business at all steps from information gathering to predictive analysis and implementation. Moreover, demand planning does not have a strict endpoint. Rather, it should be thought of as a cycle, with forecasts and strategies being revised as new data comes in. Through each cycle, you must be ready to assess performance and respond to minimize further error.

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