Monday, February 17, 2014

Delivering Business Value through Supply Chain Analytics !

Are my cost reduction programs through value engineering delivering on their promise?

How do I use predictive modeling techniques to forecast the probabilities for success in the my new product line?

Can I identify dead or obsolete stock and manage it through product aging strategies?

What is the best strategy for managing returns and does it make the best economic sense to recycle or refurbish defective products?

How to Optimize Business Performance

Managers in the rapidly evolving high tech and discrete manufacturing (HTDM) industry face tough questions like these every day. Business intelligence technology can help them find the answers - assuming the software technology can be deployed to the right people in the right parts of the organization, in a form that is easy for them to use and understand. According to experts, business decisions should be made at the lowest possible level in an organization - ideally, as close as possible to where the outcome will be executed. That's why astute companies in the HTDM industry are deploying supply chain analytics solution. When properly deployed, these solutions can extend high-quality, actionable business information to many different types of employees throughout the enterprise - as well as to external partners and customers. 

Analytics correlates to Performance

What is Supply Chain Analytics?
Supply Chain Analytics combines technology with human effort to identify trends, perform comparisons and highlight opportunities in supply chain functions, even when large amounts of data are involved. The technology helps decision-makers in supply chain areas such as sourcing, inventory management, manufacturing, quality, sales and logistics. Supply chain analytics solutions leverage investments made in enterprise applications, web technologies, data warehouses and information obtained from external sources to locate patterns among transactional, demographic and behavioral data.

The typical approach to business analytics involves creating data-marts organized by function such as customer, procurement, finance, planning and quality. Business intelligence tools are used to extract the data through standard queries, ad-hoc reports and online analytical processing (OLAP) tools - sometimes via a managed reporting environment or executive dashboard interface.

Supply Chain Analytics - Staged Representation

Managing Cost and Profitability Expectations
Cost and profitability drivers are of the utmost importance in high tech industries. With wafer-thin margins of two to three percent, managing costs is an ongoing challenge. Supply chain analytics solutions can help managers in sales, marketing, customer support, supply chain planning and financials understand and respond to key issues, such as:
  • Correctly analyzing barriers to market-entry, which vary widely with each product
  • Responding to competition within a well defined supply tier architecture
  • Dealing with the high threat of product substitutes
  • Continually driving product innovation
  • Managing product life cycles to maximize returns
Global competition and the continual rise of new technologies result in short product life cycles and the commoditization of products, exerting downward pressure on revenue. At the same time, managers have shorter time windows in which to generate revenue and profitability. Customer demand is pushing supply chain cost reductions upstream even as suppliers feel the squeeze in their own balance sheets. Investing capital into R&D is critical for creating and maintaining differentiated products, yet managers must place the right bets on their product development investments.

Conceptualizing the Supply Chain Analytics Solution

Dimensions of Supply Chain Analytics:
All of these business dynamics must be with accurate, timely information. There are many ways to deliver it with supply chain analytics solutions:

Executive Information Systems (EIS) - Executive dashboards with drilldown analysis capabilities that support decision-making at an executive level.

Online Analytical Processing (OLAP) - OLAP tools are mainly used for analysts. They apply relatively simple techniques such as deduction, induction, and pattern recognition to data in order to derive new information and insights.

Standard Reports are designed and built centrally and then published for general use. There are three types of standard reports.
  • Static reports or canned reports - Fixed-format reports that can be generated on demand.
  • Parameterized reports - Fixed layout reports that allow users to specify which data are to be included, such as date ranges and geographic regions.
  • Interactive reports - These reports give users the flexibility to manipulate the structure, layout and content of a generic report via buttons, drop-down menus and other interactive devices.
Ad-hoc reports - generated by users as a "one-off" exercise. The only limitations are the capabilities of the reporting tool and the available data. 

Advanced Analytics - Advanced Analytics and analytical processing such as correlations, regressions, sensitivity analysis and hypothesis testing. 

Implementing a Successful Supply Chain Analytics Strategy
  • Identify High Impact Control Areas 
  • Develop Strategic Supply Chain Analytics
  • Solidify the Approach
  • Build a Business Case for the Implementation
  • Conceptualize the Solution
  • Implement the solution
  • Operationalize the Solution

                                                      Managing Change: Using Analytics to Optimize Supply Chain Performance

Supply Chain Analytics solutions help organizations control, measure and improve their business strategies, plans and operations. Success depends on a combination of factors:

1. Identifying the right set of supply chain analytics to deliver maximum business value.
2. Obtaining clear buy-in from business users through a business case endorsement. 
3. Creating a flexible and scalable technology solution that is comprehensive enough to meet current and           future needs.
4. Maintaining and upgrading the solution as part of a cycle of continuous improvement.

The supply chain is a great place to use analytical tools to look for a competitive advantage, because of its complexity and also because of the prominent role supply chain plays in a company's cost structure and profitability. Supply chains can appear simple compared to other parts of a business, even though they are not. If we keep an open mind, we can always do better by digging deeper into data as well as by thinking about a predictive instead of a reactive view of the data.

So while advanced supply chain analytics is promising in terms of making our supply chain leaner, do u think supply chain analytics would be ultimate solution to solving Supply Chain Problems ? Is it really something beyond ERP and Big Data? 


[2] Building Tomorrow's Enterprise - Case study by Infosys

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