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Scenario

Today’s business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This article presents a predictive supply chain performance management model which consolidates process demonstrating, execution estimation, data mining models, and web-based interface innovations into an interesting model.

Challenges

Today, supply chains are very complex business networks that need to be managed collaboratively and optimized globally. Additionally, global business landscape is constantly and rapidly changing. Uncertainty, growing competition, shorter cycle times, more demanding customers, and pressure to cut costs are just a few characteristics of the 21st century business environment. It has become critical to measure, track, and manage the performance of supply chain processes. Performance management identifies with the utilization of procedures, techniques, measurements, and innovations keeping in mind the end goal to make a reliable connection between supply chain methodology, arranging, usage, and controlling.

Solution

When companies use standardized metrics they can join benchmarking databases and use benchmarking services to compare with best in class companies and perform gap analysis.Here analysis distinguishes weak points focuses on the production network that requires some change through process overhaul or re-building. Moreover, standardized models encourage coordinated effort and integration inside the supply chain and with outside outsourcing organizations and vendors. Such collaboration models depend on a reasonable meaning of what is rational from the associates and specialist co-ops regarding process execution.Supply chain collaboration improves competitive advantage and enables supply chain partners to achieve synergies and create superior services.

Uses 

OLAP database  (Online Analytical Processing) is the technology behind many Business Intelligence (BI) applications. OLAP is a powerful technology for data discovery, including capabilities for limitless report viewing, complex analytical calculations, and predictive “what if” scenario (budget, forecast) planning. Infact, combination of business intelligence and performance management systems can improve supply chain efficiency and accountability and reduce costs with optimized decision-making process based on monitoring of the key performance indicators. Moreover, these frameworks should empower more predictable performance management by giving significant data to the correct leaders.

Competitive Advantage 

  • Performance management (PM) supplements BI and links people, strategies, processes, and technology. 
  • KPIs are frequently utilized as a part of BI frameworks to measure the progress of various metrics against business objectives. They have turned out to be particularly prevailing for BI analysis since they give a fast and visual understanding of measurable objectives. 
  • Timely and accurate evaluation of the supply chain and individual organizations is the essential for productive working. 
  • Measuring and observing metrics against predefined objectives organizations can give increased the value of expansive volumes of information produced after some time.

Our Approach & Solution

New business climate requires novel and innovative performance management systems which have the following characteristics:-

  • Straightforwardly related with overall strategy
  • Comprehensive (considers applicable factors) 
  • Utilize furthermore non-financial KPIs 
  • Handy to specific supply chain configuration and part organizations, 
  • Plenty of KPIs 
  • Basic and simple to use 
  • Auspicious and real 
  • Exact and reliable 
  • Encourage change, not simply reviewing 
  • Articulate data at various supply chain levels 
  • Give analytical tools that offer multidimensional reporting
  • Allow a proactive management, instead of reactive
  • Give bits of knowledge into recently rising trends, opportunities, and issues 
  • Send data to certain people whenever and on any device.
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