Is Data-driven Insights Important For Supply Chain Management?

The sustainability of a business is often impacted by the volatility of supplies and fluctuation in demand forecasts. This is mostly due to the planning which was done using the data from the past. Also, the planning is not done after considering the dynamic parameters.

The pandemic situation highlighted the importance of the supply chain management of essential commodities. Once the lockdown was put to an end, companies who had invested in digital platforms already could achieve closely aligned components such as completion of production, stock availability, the supply of raw material, transportation, etc. with ease. With supply chain analytics, they were able to meet the demands of their customers.

Supply chain analytics, which includes descriptive, predictive, cognitive, and prescriptive analytics, can be used for solving problems, mitigating risks, and also to foresee scenarios depending on both internal and external data. Supply chain analytics will also help respond to the needs of a customer on a timely basis.

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Vital tasks such as inventory planning, manufacturing, sourcing, warehousing, sales, and logistics are interlinked with one another via a well-organised supply chain analytics system which is capable of transforming the performance of a supply chain altogether. Dynamic insights drawn via customer analytics has to be imposed so that viable plans concerning production planning and distribution can be generated.

In India, various manufacturing companies have their factories scattered in multiple locations with thousands of retailers and distributors scattered too. Hence, forecasting and planning can get complicated.

With the pandemic situation, slowly few businesses have already started understanding the correlation between investing in supply chain analytics, reduction in working capital, and increasing business. A few businesses have been able to cut down on their inventory carrying expenses, avoid rerouting or overstocking of products from actual destinations to new destinations with the help of supply chain analytics.

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