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1. Departmental "Silos" Create Conflicting Goals
When a company's director of inventory keeps tabs on safety stock, the head of production maximizes uptime at the plant, and the procurement manager drives down costs with a key supplier, you'd think that company would be in pretty good shape. But when a company monitors supply-chain performance solely by using departmental metrics, it may end up driving locally minded "silo" behavior at the expense of the overall smooth functioning of the chain.
The director of inventory, for example, might pull a day of safety stock out of the system to reduce carrying costs. That might go a long way to help him meet his departmental targets — but it could also jeopardize the company's ability to respond to an unforeseen spike in customer demand. (Some companies, such as Sun Microsystems, go so far as to align their incentive programs with broader operational metrics.)
Even when metrics are in synch across the company, departments may fail to communicate properly, or fail to exchange critical information altogether. Sales and marketing, for instance, may offer discounts on certain products to drive demand, but without informing the manufacturing department. When manufacturing notes the increase in sales, it might ramp up production in the belief that demand has risen. (Demand has risen, of course, but only temporarily, and not at a price that the company plans to maintain.)
"You've got different people, a bunch of complex business processes, each with different objectives and tons of data, explains Mike Mansbach, a senior vice president at SeeCommerce, a provider of supply-chain applications. Without aligned metrics and good communication, "you start to have a lot of dysfunction in the supply chain."
2. Dirty Data Obscures Your View
Ultimately communication can be no better than the information that's being communicated. So when databases are poorly connected, or when they're updated on different schedules, it can be nearly impossible to get a comprehensive view of supply-chain performance.
"If you make a decision before getting a full view from all your systems, it could be turn out to be disastrous, " says Mansbach. Many companies, he adds, have gone to the opposite — and costly — extreme of "maintaining legacy systems simply because they don't know whether they are valuable. They're collecting data at very high costs in maintenance and licensing fees and labor that has little value." (To combat the problem of "too much data," some companies have turned to new methods of enforcing data-growth and data-retention policies.)
That dirty data — even seemingly minor inaccuracies like misspellings, typos, and missing information in database fields — can actually subtract value by throwing forecasts and calculations well off the mark. That's especially true when dirty data is duplicated or fed into further calculations, creating the "bullwhip effect," in which the amplitude of the error increases as you move further down the supply chain.
"Perhaps the biggest problem with forecasting accurately is data cleansing," says Katrina Roche, COO at Evant, a planning and replenishment software provider. "Data integrity and validation," agrees Kim Perdikou, CIO of Juniper Networks, a provider of Internet systems, is an inescapable "part of the maintenance."
In the early '90s, when companies began to automate business processes, much data cleansing was done manually. Some still do, notes Roche, describing one case in which "it took one customer six months to cleanse all their data." Many software providers, such as Evant, have developed tools using mathematical algorithms that help cleanse data automatically, by cross-referencing disparate data sets, synchronizing overlapping information, correcting inconsistencies, and removing spikes and "outlier" information that might throw off forecasts. Adds Roche, "We ran the same data through our system in a matter of hours."
3. Your Inventories Are Out of Whack
"Many of the companies we work with have some level of inventory problem," says Mansbach of SeeCommerce, "but they're usually not sure exactly where the problem is."
Poor visibility and poor communication are obvious candidates. Managers who don't have good visibility into customer demand, notes Jim Fuller, controller of global product services at Cisco Systems, often obey the natural "cover your back" instinct, especially when they can't afford having a part out of stock. The lower the visibility, the higher the level of safety stock — and the higher the cost of carrying it.
If demand for a given item is particularly volatile, of course, that item might require a higher level of safety stock. And if it can be obtained at a huge discount (with reasonable assurance that it won't become obsolete) then it may pay to stock up.
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