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Understanding Supply Chain Analytics – Supply chain Management

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Let’s understand the challenges of supply chain management and how analytics can come handy in improving and solving those challenges in a subtle way.
Understanding Supply Chain Analytics
We will understand the aspect of using data driven decision making for various levels of supply chains.
We know there are suppliers, manufacturers and distributors involved in the supply chain management function till consumers consume those products or services
Initial idea of supply chain started from Ford Motor company which used to control the mining of iron ore on one side and distribution of finished cars on other side.
They followed an integrated form of supply chains and because of this high level of integration supply chain was very much efficient but faced a problem of “lack of flexibility”…Hence the supply chain become popular as supply chains supplying only T Model cars.
Then came the Toyota concept where Toyota developed a pool of vendors and started incorporating flexibility into their supply chains. Over a period of time most of other industries like electronics, consumer durables and even FMCG Segment started adopting Toyota model of Supply Chains
Late in the 20th Century or in the beginning of 21st century we have this IT revolution and this gave birth to another big revolution.
This model of supply chain was given name as dell model of supply chain. Dell used power of Information Technology for delivering their products in a highly customized fashion and this model became very popular because of competition and Increased expectation of customers.
Birth of Supply Chain Analytics
Through the power of IT Dell was able to deliver a high degree of customized products to their customers.
In last two Decades, there are very rapid changes which are happening in the business environment and at the same time, there are rapid changes happening in the technological environment driving an information overload.
Currently this has led to Integration of supply chain analytics to better process the heavy load of information’s and thereby facilitating our operations.
Role of Supply Chain Analytics
Supply chain analytics plays a very key role in enhancing the performance of supply chain by improving supply chain visibility, managing volatility, and reducing fluctuations in cost.
Visibility- It is very important because of a focus on developing customer experience … In case of supply chain involving critical products like medicines and equipment supply chain visibility becomes extremely important. Customers are Interested in Knowing the current status of their orders and therefore visibility became a critical factor for supply chain management as such to provide the customer with a better customer experience .
Volatility- Volatility demands flexibility. Flexibility can be achieved with the help of tools provided under supply chain analytics. Real-time data analysis helps in inculcating flexibility into supply chains.
Reducing Fluctuations with regard to cost-Stock-outs & Excess inventory both alike creates a fluctuation in the cost of the product. Supply chain Analytics helps in mitigating such fluctuations.
Understanding Supply Chain Analytics
Key Focus of Supply Chain Analytics
a) A smarter Logistics system to improve supply chain visibility with the help of data-driven decision making
b) Efficient and effective inventory Management to keep the profitability of supply chains unharmed. Idea is to eliminate stock outs and a problem of excess inventory.
c) Real time data of inventory with the help of Information Technology for a smarter Inventory management.
d) Analytics thereby will help in reduction of costs pertaining to sourcing and logistics by Optimizing logistics and sourcing activities with the help of real-time data.
Types of supply chain analytics
Descriptive analytics
Provides visibility and a single source of truth across the supply chain, for both internal and external systems and data.
Predictive analytics
Helps an organization understand the most likely outcome or future scenario and its business implications. For example, by using predictive analytics, you can project and mitigate disruptions and risks.
Prescriptive analytics
Helps organizations solve problems and collaborate for maximum business value. Helps businesses collaborate with logistic partners to reduce time and effort in mitigating disruptions.
Cognitive analytics
Helps an organization answer complex questions in natural language -in the way a person or team of people might respond to a question. It assists companies to think through a complex problem or issue, such as “How might we improve or optimize a process?”
Features of an Effective Supply Chain Analytics
Connected- Being able to access unstructured data from social media, structured data from the Internet of Things (IoT) and more traditional data sets available through traditional ERP and B2B integration tools.
Collaborative.Improving collaboration with suppliers increasingly means the use of cloud-based commerce networks to enable multi-enterprise collaboration and engagement.
Cyber-aware. The supply chain must harden its systems from cyber-intrusions and hacks, which should be an enterprise-wide concern.
Cognitively enabled. The AI platform becomes the modern supply chain’s control tower by collating, coordinating and conducting decisions and actions across the chain. Most of the supply chain is automated and self-learning.
Comprehensive. Analytics capabilities must be scaled with data in real time. Insights will be comprehensive and fast. Latency is unacceptable in the supply chain of the future.

Less than 10% of the data available to supply chains is effectively used by businesses. And most are virtually blind to the 80% of data that is dark and unstructured. That’s where Supply Chain analytics comes in for a help.
Insights from Supply Chain Analytics help us gain end-to-end supply chain visibility so that we can proactively predict, assess, and mitigate disruptions in minutes, not days. Supply Chain Analytics is therefore a Life changer for our supply chains.

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