The supply chain industry has been massively impacted due to restrictions laid down by the pandemic. Even though advancements in technology help effectively deal with its consequences, it will still be a long time before everything comes back to normal. Meaning organizations should create and implement strategies that will help them to effectively navigate supply chain disruptions.
The global supply chain challenges that plagued organizations across multiple industries throughout the past couple of years are continuing this year. To deal with supply and demand issues effectively, one of the tools that organizations should leverage is data analytics.
Many severe disruptions are currently having a negative impact on supply chains, resulting in a ripple effect across global inventory management. Even if it is assumed that these disruptions decrease as well as access to sea and airfreight revert to pre-pandemic levels, it will still need some time for things to return to normal.
As organizations seek to enhance critical supply chain capabilities by adopting more advanced digital enablers, they should start investing in technologies that will empower them to automate key processes within the supply chain industry.
Today, the customers are becoming more demanding, leading to the supply chains to change and evolve at a faster pace. Modern operations are focused on technology as well as innovations, which is making the supply chain more complex. This leads to the question, how can organizations best use data analytics to enhance their supply chain management (SCM) efforts? Here are a few best practices they should adopt:
● Convert data into actionable insights
Most organizations have a significant volume of data, often stored in diverse systems as well as databases. This led to the supply chain that added the complexity of additional data sources generated from extended partners such as outsourcing, distribution operations, and logistics. This results in many struggling to capitalize on this data to generate meaningful insights beyond top-level metrics and descriptive statistics.
Using data analytics tools, organizations can obtain deeper actionable insights and improve the accuracy of those insights. The foundations for developing a successful supply chain data analytics strategy include ensuring that internal and external data are brought together in a structured format; ensuring that results are easily digestible; and concentrating on data projects about what actions need to be taken to move the performance needle.
Organizations should form partnerships between their analytics teams and the customers to help create explainable insights that can be easily communicated across the organization.
● Shift analytics on difference-making areas
For building a successful, customer-centric supply chain while simultaneously maximizing operational efficiency, organizations should utilize the right analytics that make data-driven decisions. Therefore, they should concentrate on a few supply chain areas such as:
1) Demand planning and inventory placement
Organizations gather millions of rows of transactional data that enable vigorous analytics on customer buying patterns. Instead, they should leverage data that will help them to build robust analytics algorithms enabling them to drive inventory placement throughout the supply chain, ensuring products are at the right place. Organizations should focus on analytical resources that help them to forecast demand patterns between product type, geographical placement as well as sales channels.
2) Efficiency of operations
Customer and order data enable supply chains organizations to maximize their assets and workforce utilization by efficiently arranging labor schedules. This helps them to ramp up resources during peaks while simultaneously scheduling equipment/asset maintenance, enabling businesses to maximize efficiency and reduce operational costs.
3) Order fulfillment path decision-making
Customers today want supply chains to be more flexible and customer-centric than ever before, providing multiple avenues for products to reach the end customers. Organizations should balance various factors that include service expectations, fulfillment costs and transportation and inventory level, helping them to determine the most viable method for fulfillment.
● Capitalize on real-time data to deal with disruptions
With the size and complexity of the supply chain growing at an unprecedented rate, it is becoming increasingly difficult for organizations to manage and respond to fluctuations across the supply chain. To successfully navigate this, supply chain managers should develop concurrent planning systems that help them to optimize demand and supply chain by incorporating advanced analytics and real-time visibility across the supply chain.