- Integration with a third party tool that did not completely fit into existing legacy systems
- Lack of training and understanding of the i2 demand forecasting tool. This could have been a direct effect of inexperience on the tool
- It could have also been a direct result of making projections that were too far ahead in the future
- Changing market, demand and time
Tuesday, September 18, 2012
Forecasting Gone Wrong: Supply Chain Disasters
As we already know supply chain management is essential for any manufacturing company. However, this simplistic ideology seems a lot more difficult to accomplish in reality. A lot of the organization’s success is significantly based on the correct implementation of the supply chain process. We have time and again heard about the benefits of forecasting and how it is extremely essential for businesses to prepare and plan for the future. Businesses use the forecasted information in many ways - predict demand in the market, understand costs and profits. Forecasting tools are also good predictors of what products should and should not make it to market. The question really is – Are these tools reliable or is there any quality check to ensure correct implementation of these tools?
While SCM and forecasting have a lot of benefits, there are severe consequences that companies face when it is not done correctly. For example, in 2001 Nike, announced profits worth $97 million. This figure was $48 million below their forecasted projection. There was a startling difference between the two figures and Nike held i2’s technologies responsible. The forecast was supposed to reduce Nike’s expenditure on materials such as rubber, canvas etc. Not only did the company spend more on the materials, they also ended up making more of the wrong shoes. So now, Nike had to spend more resources, time and money managing inventory for shoes that were not being sold.
There were a number of reasons that led to this disaster in supply chain. Some of the reasons I believe are:
With advancement in technology companies seem to be too quick to jump on the bandwagon and adopt new systems. Investing sufficient time to train and understand these systems and how they integrate with the current systems is key to success. In the case of Nike, I believe that it should have adopt SCM technologies in a phased approach. Nike should have brought in the new technologies in concurrence with existing mechanisms of forecasting. While this might have taken more time it could have drastically saved them from this loss. Are there any proven best practice to prevent such disasters in forecasting? If not, what would be the best check points or red flags that organizations should be aware of to spot such failures?