What are the challenges to installing supply chain software?

 

1. Gaining trust from your suppliers and partners.  Supply chain automation is uniquely difficult because its complexity extends beyond a company’s walls. Employees will need to change the way they work and so will the people from each supplier that a company adds to its network. Only the largest and most powerful manufacturers or retailers (i.e. Wal-Mart) can force such radical changes without repercussions.  Most companies have to sell outsiders on the system first. Moreover, one company’s goals in installing the system may be threatening to their suppliers.

For example, Wal-Mart’s collaboration with P&G meant that P&G would assume more responsibility for inventory management, something retailers have traditionally done on their own. Wal-Mart had the clout to demand this from P&G, but it also gave P&G something in return—better information about Wal-Mart’s product demand, which helped P&G manufacture its products more efficiently. In order for a company to get its supply chain partners to agree to collaborate, business leaders and supplier relations managers have to be willing to compromise and help partners achieve their own goals.

2. Internal resistance to change.  Operations people are accustomed to dealing with phone calls, faxes, spreadsheets or notes on paper, and will most likely want to keep it that way. If management can’t convince front-line operations people that using the software will be worth their time, they will easily find ways to work around it.

3. Some mistakes at first.  New supply chain 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.

 

Source: CIO.com