What’s happening in supply chain management: Part 2

By Maureen Aylward

Supply chain management is a critical component of many businesses. It is also a field that is changing, adopting new technology, and finding new ways to implement processes and ideas. We asked our Zintro experts to tell us their success stories and outline the tactical considerations, strategic approaches, and technology they are using or see as emerging trends in this area.

Aitha PK, a senior operations research analyst, says that a common problem for large manufacturing organizations with geographically wide distribution is the need to rationalize economies of scale in production within a large and complex supply chain network. “Most industries face conflicting pressures to take advantage of significant production economy of scale on the one hand and be customer responsive through fast and lean distribution systems on the other,” he says. “It’s a strategic approach to consider economies of scale in designing a supply chain network.”

Aitha PK says that once a supply chain network is designed, tactical considerations include having optimal procurement, production, distribution, and inventory plans that simultaneously calculate, for example, the production mix at plants and distribution quantity. “Businesses have to look at the transport mode selection between suppliers and plants, plants and warehouses, warehouses and markets, and inventory stocking of raw materials and finished goods at plants and warehouses,” he says.

Aitha PK likes the Decision Support System (DSS), which he says can help with different strategic decisions like facility locations, line (technology) selection at each facility, and tactical decisions like product mix on each line, quantity to be supplied from each plant to warehouse, and warehouse to market.

“The DSS can have user interface developed in Java/ASP.net with the backend as a relational database management system. These DSS systems are developed and deployed for strategic and tactical planning. In order to achieve good accuracy and reduce run time, models need reasonable assumptions to simplify the problem,” says Aitha PK.  “At the tactical level, making middle level mangers understand the optimization logic behind the production and distribution plan remains a challenge.”

Unnikrishnan, a vice president of business development and operations, reports that companies are outsourcing supply chain analytics. “As the expertise of outsourcing providers has improved and confidence in that expertise has grown, companies are outsourcing increasingly sophisticated functions, such as specialty design and manufacturing,” he says. “A handful of forward-looking companies are off-shoring the analysis of supply chain data to help them make better operating decisions. By tapping into the analytical skills of low-cost countries with a well-educated workforce, such as India, companies get valuable insights from data that had once been too voluminous or too complex to deal with quickly in a cost-effective manner in-house.”

Unnikrishnan points out that unlike traditional outsourcing and off-shoring, which can carry a degree of operational and financial risk and sometimes disappointing results, outsourcing supply chain analytics is virtually risk-free. “It’s relatively easy to implement, requiring no exchange of people, processes, or systems. It’s also flexible. Instead of being locked into multi-year contracts, most companies subscribe to a data analytics service on an as-needed basis,” he explains. “Outsourcing providers in India are able to spread one highly skilled, low-cost expert across three or four accounts for greater leverage than an individual company could achieve on its own.”

Ralph Brander, a logistics and supply chain expert, says that pinpointing the supply chain pain and understanding its root cause is the only way to successfully solve supply chain problems. “One common challenge I see is that organizations tend to focus on end result numbers without fully understanding the drivers of those indicators,” he says. “One way to avoid focusing only on the numerical indicators is to map processes along the supply chain that have an impact on the end indicator. Another consideration is to understand the result and behavior that the business is trying to achieve by measuring and reporting on the indicator as compared to the goal.”

Brander worked with a company to determine why the on time percentage for receipts was low and how that percentage could increase. “We used the percentage as a key performance indicator, and goals to improve year-over-year performance were provided to management who could affect the change,” explains Brander. “The challenge was identifying the true desired results and measuring them to determine the root causes of late products and then attacking those issues.”

Brander looked at the desired results and decided that inventory reduction, improved in-stocks, and resulting sales would provide the greatest cash improvement for the company. “We looked at the full supply chain from vendor to shelf to determine the root causes of late deliveries and how to improve store level in-stocks. We found that store level in-stocks were highly impacted by the delivery schedule more than in-store behavior,” he explains. “We addressed these issues and had a measurable impact both in-stocks and sales. There were several systemic issues that we corrected to allow the supply chain to function correctly and smoothly, improving performance and confidence levels.”

Vijay Hanagandi, an operations research engineer, says that mathematical programming (also known as optimization) is a key technology differentiator that he uses in his supply chain applications. “Optimization involves translating the supply chain problem into a mathematical problem and solving it using algorithms to arrive at optimal solutions,” he explains. “Supply chain network optimization is a classic application of this technology where, traditionally, people used heuristics and simplistic rules to solve complex and critical problems. Optimization technology allows me to define the distribution network mathematically, ask complex questions, and arrive at optimal results. These results are not only mathematically sound but also practical and implementable as they can be configured to take into account day-to-day business constraints.”

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