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Why It Fails?

When organizations go online, they have to decide which e-business models best suit their goals. A business model is defined as the organization of product, service and information flows, and the source of revenues and benefits for suppliers and customers.

Automation is uniquely difficult because its complexity extends beyond your company's walls. Your people will need to change the way they work and so will the people from each supplier/distributor/customer. Only the largest and most powerful manufacturers can force such radical changes down their throats. Most companies have to sell outsiders on the system. Moreover, your goals in installing the system may be threatening to them, to say the least.

  • Internal Resistance to Change
  • External Resistance to Change
  • Many Mistakes at First
  • Historical and Accurate Data
  • Skilled Manpower
  • Continuous Training and Upgradation
  • Planning and Implementation
  • Management Support

Resistance to change: Operations people are accustomed to dealing with phone calls, faxes and hunches scrawled on paper, and will most likely want to keep it that way. If you can't convince people that using the software will be worth their time, they will easily find ways to work around it. You cannot disconnect the telephones and fax machines just because you have a software in place.

Many mistakes at first: There is a diabolical twist to the quest for software/automation acceptance among your employees. New systems process data as they are programmed to do, but the technology cannot absorb a company's history and processes in the first few months after an implementation. Forecasters and planners need to understand that the first bits of information they get from a system might need some tweaking. If they are not warned about the system's initial naiveté, they will think it is useless.

In one case, just before a large automotive industry supplier installed a new supply chain forecasting application to predict demand for a product, an automaker put in an order for an unusually large number of units. The system responded by predicting huge demand for the product based largely on one unusual order. Blindly following the system's numbers could have led to inaccurate orders for materials being sent to suppliers within the chain. The company caught the problem but only after a demand forecaster threw out the system's numbers and used his own.

That created another problem: Forecasters stopped trusting the system and worked strictly with their own data. The supplier had to fine-tune the system itself, then work on reestablishing employees' confidence. Once employees understood that they would be merging their expertise with the system's increasing accuracy, they began to accept and use the new technology.

Historical and Accurate Data: Computers work on the GIGO principle – Garbage In Garbage Out. Any computer system is only as good as the data/information that it is feed. Inaccurate data or not enough data both are one of the invisible causes of failure of information systems.


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