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Risky business: Outdated supply chain management systems

By Jessie Chimni, vice president of North America Consulting Services, Bristlecone
EETimes Supply Network
(06/23/2008 3:36 PM EST)





Supply chains in the electronics industry are more fraught with risk than ever. The rise in outsourced manufacturing and packaging, along with highly demanding OEM customers, and lean inventory levels within the supply chain, have combined with unexpected disruptions such as earthquakes in Taiwan to jeopardize the steady flow of goods at established prices. In order to plan for and respond to these disruptions, more organizations are investing in supply chain risk management initiatives.

Most of their risk management efforts focus on minimizing the volatility of component supply and pricing, using multi-sourcing to reduce dependence on any single vendor for critical components, and ensuring contract compliance to drive predictable pricing. Companies also strive to improve logistics and delivery reliability and to reduce supply network costs.

However, many of these companies overlook the most obvious risks that may be bubbling within their very own supply chain management systems, hidden from view. These systems were often put in place years ago and are likely to suffer a deteriorating performance over time, producing planning recommendations that do not reflect the most current conditions for the company or the global economy at large. This steady erosion in the system's performance is a risk most companies never even recognize because they expect their supply chain planning and execution systems to perform as well as they did when they were first implemented

Some of the most common problems with out-of-date supply chain management systems include the following:

  • Demand planning solutions use multiple statistical models to predict demand, but most organizations don't have deep statistical modeling capabilities. As the business environment changes statistical models don't keep pace. Forecast accuracy gradually worsens, leading to recommendations that increase supply chain risk.

  • Supply chain planning systems typically rely on multiple optimization algorithms. Creating them or updating them requires deep expertise in operations research, which many organizations also lack. When the assumptions behind the sophisticated planning algorithms change, the algorithms are no longer in sync with the environment, resulting in sub-optimized or even incorrect planning recommendations.

  • Data within every information system deteriorates over time. With this decline in the quality of data, supply chain deployment can potentially hide supply side problems, creating a potential for unexpected disruptions in the future. The systems which were once accurate can make wrong recommendations or lead to incorrect decisions.

  • Most supply chain planning systems require so much work to maintain that planners may get bogged down with details and have no time to devote to the critical task of identifying and reducing potential supply chain disruptions. Creating the analytics to accurately forecast such disruptions requires a level of expertise which many organizations don't have.

Organizations that are able to address such issues proactively will see the highest return on risk management spending, since the best way to avoid a supply chain disruption is to anticipate it ahead of time. There are two possible approaches to averting these future problems. Companies may hire dedicated persons with these skills within the enterprise, or they can retain an outside consulting firm that provides knowledge process outsourcing, or KPO services for the capabilities listed above. Unlike the more common practice of outsourcing relatively low-skilled jobs, KPO outsourcing covers more advanced, specialized work.

Regardless of whether companies outsource this work or keep it in-house, however, they must seek out people who have expertise in multiple areas, including statistical modeling, optimization algorithms for supply chain planning, analytics and data cleansing, as well as an understanding of how to apply these technologies to supply chain management. Such a set of skills may be hard for a company to recruit and retain. In addition, these skills are very specialized and probably cannot be found in one person.

Supply chain consulting organizations with KPO capabilities that can bring sophisticated technical expertise offer a good alternative to hiring a dedicated staff. Working closely with the demand planning team, these consultants can continuously assess the existing statistical models and refine them to ensure highest performance on forecast accuracy. Since these resources work with any given client for a half or one third of their weekly hours, the client gets the benefit of such skills at a lower cost and on-demand.

In addition to providing expertise in the specific supply chain technologies such as statistical modeling or optimization algorithms, consultants or in-house workers are also needed to provide many decision-support services, such as supply chain exception processing, insightful analytics and continuous data cleansing. These services ensure that supply chain planners are spending the majority of their time on more high value tasks, while the tedious day-to-day task of exception processing and data cleansing can be managed by a dedicated staff.

While companies often set themselves up as lean geographically-dispersed operations to remain competitive, that same structure can leave them particularly vulnerable to supply chain disruptions. In today's ultra-competitive business climate, even little blips in normal supply chain functions can have serious consequences. It may be hard to comprehend how a company's current supply chain management system, which was designed to anticipate and avert risk may end up being a source of risk. But unless these systems are continuously optimized by skilled staff, they will be of little use in helping a company navigate a supply chain disruption.

By taking a deeper view of their current systems and ensuring that they have the capability to continuously leverage advanced analytics and optimize statistical/optimization models, they can reduce their risk and reap sustainable benefits, so that they are ready to respond to those unfortunate, but inevitable events that disrupt the flow of raw materials and finished products.

About the author: Jessie Chimni is vice president of North America Consulting Services for Bristlecone, a supply chain consulting firm. Bristlecone brings expertise across the entire spectrum of supply chain including demand planning, supply planning, network collaboration, sourcing and analytics. Bristlecone also provides supply chain-focused KPO services.

Jessie Chinmi can be reached at: Jessie.chimni@bcone.com

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