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Applying SCEM

SCEM applications necessarily vary by industry, business environment and organizational requirements. But in all cases the greatest pitfall is reacting to SCEM's elevated tracking ability rather than using it for analysis. Analytic applications counter this tendency by aggregating data from key business systems at a high level and presenting the ramifications of exceptions and the possibilities of solutions. The end result is a proactive, more efficient process.

For example, suppose the event management system alerts the transportation manager to a late inbound shipment. Then, assume the transportation system is linked directly to the WMS and order management systems, but none is feeding information to an aggregate-level system such as an analytic application. The WMS would notify the warehouse manager, who would alter the proper truckload to the affected customer. At the same time, a customer service person watching the order management systems would notify the customer of the changes. Meanwhile, the transportation manager, who saw the initial alert, could have found the inventory elsewhere to compensate for the late inbound shipment. The customer will have the order filled on time after all, although none of the several internal people reacting to the initial alert knows that. And now the customer believes the order will be late.

No time or effort would have been spent if the organization had an analytical application in place with alerting capabilities. Everyone involved would have had the alert and been able to view inventory, allocations and open orders at the aggregate level. The first, and only, decision made would have been to move inventory to fill the order. No contact with the customer was necessary. Reacting to deep transaction detail mobilized more managers than needed and may have unnecessarily upset a customer.

In addition to the example above, SCEM is most likely to yield big returns in a short period of time for organizations that need to:

1.Monitor large numbers of markets/channels, customers, vendors and products.

The sheer amount of data lends itself to event management. Managers responsible for dozens of products and hundreds of customers would be overwhelmed by day-to-day activities if forced to respond to a detailed inventory report. With analytics-enhanced SCEM, they focus instead on exceptions, such as inventory levels approaching forecast limits, service levels or days of supply.

2· Support new product launches and promotions.

With SCEM, product arrival at destination and rapid variations in demand would trigger specific events, which would trigger alerts, focussing managers to take immediate action. Orders could be expedited, inventory could be transferred, more material purchased or any number of tactics implemented to verify product in-stock or replenish product quickly and meet orders on time, capture sales and satisfy customers.

3· Track to key performance indicators.

For many companies, one of the first steps in getting processes under control and managing them is to start at monitoring Key Performance Indicators (KPIs) and analyzing the causes of out-of-range alerts. For example, company XYZ may monitor inbound transportation costs because they are increasing beyond forecast expectations. Analysis could show that inbound purchase orders are being expedited because materials are not being ordered within proper lead times, which, in turn, causes slippage in production schedules and customer shipments. An event management system might detect missed production and late shipments, but without analytics the fact that material is being ordered late and transportation costs are rising might be missed.

4· Balance supply and demand.

Today's fast-paced marketplace also requires organizations to continually balance supply and demand. Surplus and shortage have the same ultimate effect - shrinking profit. As companies improve their sales and operations planning, SCEM is becoming the best means of implementing and monitoring those plans. Add analytic applications for translating variances into improvements and this new buzzword becomes more than just another acronym for ROI.

by Deb Marabotti

Deb Marabotti is an Application Product Manager at Silvon Software, Inc., a global supply chain-focused provider of enterprise performance management applications. The company's Stratum product suite includes planning, forecasting, performance analysis and exception management functionality. Silvon's solutions are currently installed in more than 1,400 sites worldwide. Reach her at deb.marabotti@silvon.com

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