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Management Do’s and Do Not’s to Support Supply Chain Analytics

Recognition of the importance and value of business and supply chain analytics has surged dramatically in the last few years among supply chain executives and practitioners.
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Editor’s Note: Dr. Tan Miller is Director of the Global Supply Chain Management Program At Rider University, College of Business Administration. This is the first of a two-part series.

By Dr. Tan Miller
July 30, 2012

Recognition of the importance and value of business and supply chain analytics has surged dramatically in the last few years among supply chain executives and practitioners.  The ever increasing complexity of global supply chains, coupled with rapid technological advances in information systems and related technologies, convinces more supply chain professionals each year that superior analytic capabilities represent a core requirement and “must have” to operate an effective and efficient supply chain.  Further, as an article by O’Dwyer and Renner in a recent issue of Supply Chain Management Review pointed out, the promise of more advanced supply chain analytics in the near future is great.

In fact, many firms have used business analytics, and more broadly speaking supply chain “Decision Support Systems” (DSS) for decades. As the use of supply chain analytics and DSS develops an increasingly prominent role and level of acceptance, there are several “management issues” that supply chain managers and executives must address.  The purpose of this brief article is to share a few key observations and learnings about supply chain analytics based on this author’s twenty plus years of employing DSS and supply chain analytics in a number of different firms and industries.

For purposes of this article, let’s define supply chain analytics (SCA) and DSS as those tools and techniques which utilize corporate data bases and other information feeds as inputs to generate supply chain plans and schedules.  SCA and DSS provide inputs to decisions ranging from short run day to day operations to long run strategic planning.  Components of SCA and DSS include data bases, and quantitative techniques and algorithms such as forecasting models, mathematical simulation and mathematical optimization.

Key Management Learnings and Observations

Regardless of the specific SCA/DSS tools and techniques employed by a firm, there are several management principles that commonly apply.  First, a supply chain group must at the minimum have a few SCA/DSS experts imbedded in the organization.  Further, these employees must be involved in, and interact regularly with employees integral to daily, short run operations, as well as longer run planning activities.  Positioning several SCA/DSS experts in the midst of daily operations generates a number of benefits for the supply chain organization.

These benefits include the following:

• SCA/DSS colleagues imbedded in a supply chain organization quickly learn and know your firm’s network “by heart”.  For example, assume these employees develop and maintain mathematical optimization models of your distribution or (better yet) your integrated manufacturing/distribution network.  Through the process of developing and utilizing these models for medium and long-term planning, the SCA/DSS colleagues become extraordinarily knowledgeable about the firm’s network.  After a period of time, these internal experts almost don’t need to run their models to predict the impact of potential network changes.  Through their constant immersion in the network’s data, these colleagues have a heightened understanding of the capacities, costs, dependencies and intertwined relationships of each location on a network.  This type of quantitative, fact-based knowledge facilitates improved decision-making throughout the organization – both in more informal, spur-of-the-moment decision situations, as well as of course in more formal planning processes.

• The presence of SCA/DSS employees in positions integral to supply chain operations raises the quality of the “thinking” and planning processes of the entire supply chain organization over time.  Operations colleagues who interact with the SCA/DSS colleagues on a daily basis come to expect and eventually demand improved decision support inputs to their daily decision-making activities.  As all employees begin to realize the benefits of improved analytic support, the organization as a whole becomes more creative and insightful as to what additional decision support will improve overall productivity.  In summary, the presence of SCA/DSS experts imbedded in a supply chain group will over time raise the thinking process of the entire organization.

Tomorrow:

Another Learning – Access to Corporate Data Warehouses


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