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Production planning: how production forecasting makes life easier

Posted by Bala Deshpande on Thu, May 09, 2013 @ 09:14 AM

Some manufacturers of luxury products, even though they do produce in mass, tend to follow to a build-to-order process. For example, it is known that BMW customers can change the specification of their car up to 6 days before their car gets produced! Other luxury car manufacturers also do it this way. However for a large number of manufacturers that produce commodity goods, build to order is not the preferred production planning model. production planning for build to order products resized 600

They follow the Build-to-stock (BTS) model. Here products are manufactured based on demand forecasts. The main challenge in BTS models is to keep inventory levels optimized: too low an inventory will lead to stock-outs and loss of business and too high an inventory leads to excess costs for storage, potential damage losses, not to mention wasted labor hours. The solution to this problem is to predict likely demand so that you only produce needed levels. Production forecasts will prevent excess inventory and opportunity loss due to stockout, but the issue here is how to forecast demands accurately.

If demand can be accurately forecasted then creating a forecast production schedule is fairly simple. The BTS model is like a train schedule (supply schedule) for which the number of passengers (forecast demand) for each time period can be gleaned from historic data. Most commodities from processed foods to industrial supplies are BTS-type products to minimize opportunity loss. BTS can be regarded as push-type production. In the industrialized society of mass production and mass marketing, forecasting mass production has encouraged standardization and efficient business management such as cost reduction. 

The challenge is that there are many small manufacturers do not possess the resources or skills in-house to efficiently develop forecasting models to use in their production schedules. Additionally, their production resources are also highly constrained. One of our SMB customers has only 6 machines and 20 workers to produce their core products. They can neither afford to let any machines be idle nor waste precious cash on unwanted overtime hours if the demand for any of their product lines is likely to be lower than expectation.

Most production management time is usually spent in addressing real time or fire fighting issues and critical cost saving activities, such as accurate production forecasting get the short shrift. Clearly production forecasting tools and technology has been available for a while. But most of these tools are beyond the reach of small manufacturers. An entry level ERP system which provides these features will cost upwards of $30,000. Most SMBs in manufacturing cannot afford these productivity enhancement tools. 

Today, many high quality predictive analytics and forecasting tools are available freely as open source products. But SMBs do not have the expertise to best utilize these tools. Further, each SMB has unique needs and some amount of customization is always needed. What is needed is a cost effective solution which combines some amount of technical consulting and some amount of IT and is available on a SaaS or PaaS basis.

Read our case study on how one SMB manufacturer is effectively using custom forecasting for production planning.


Download Production Planning Case Study


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Topics: cost forecasting, time series analysis, production forecasting

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