Understanding the importance of supply chain analytics
The system that encompasses the flow of goods and services from the point of origin to the point of consumption, including sourcing and procurement, is called a supply chain. It is a network between the business, suppliers, and end users, originating from raw material sourcing to the final product or service delivery to the customer. The supply chain plays a huge role in the customer experience factor, which is what most businesses focus on today, along with profitability. Achieving high rates of operational efficiency in supply chain management (SCM) is critical for business success, especially in the post-pandemic scenario. Organisations are always looking for ways to improve sales and optimise deliveries while reducing costs and increasing the overall speed of their supply chain.
Supply chain analytics is the investigation and analysis of all data regarding procurement, inventory management, order management, logistics, transportation, etc., across the complete cycle of the supply chain. Bottlenecks and issues in any part of the supply chain will affect the business and customer experience. Hence, insights drawn from this analysis help organisations understand and streamline processes to improve efficiency and finetune forecasting for better decision-making. Usually, organisations rely on Enterprise Resource Planning (ERP) software or specialised supply chain management solutions with in-built dashboards and customisable reports.
The types of supply chain analytics
Supply chain analytics provide complete, real-time visibility into end-to-end SCM operations by uncovering hidden patterns, generating insightful summaries, and presenting this information through visualisation for better understanding. It can process data from multiple supply chain streams and even integrate sentiment data from social media and location intelligence to improve demand planning. Procurement and spend analytics is a part of this as it helps understand buying patterns and related insights. It provides decision-makers the much-needed flexibility to make necessary trade-offs in the SCM process to enhance customer experience.
Typically, it includes demand planning, sales and operation planning, inventory management, risk management, order management, etc., that help streamline procurement workflows significantly. Improved efficiency in these aspects results in sizeable cost savings and wastage reduction.
The four primary types of supply chain analytics are:
Descriptive analytics: This involves the analysis of historical data to understand patterns for the same data across different periods. It provides trustworthy visibility across the complete supply chain to specific questions such as ‘How has inventory changed over the last quarter?’ or ‘Which supplier deliveries are running late?’.
Predictive analytics: This is a risk mitigation strategy that helps predict future scenarios as to what can happen based on present data. These projections suggest an impact on business performance and help organisations become proactive rather than reactive to situations. It helps answer queries of the type - ‘How will this new regulation impact my logistics?’.
Prescriptive analytics: This combines descriptive and predictive analytics to arrive at the best possible strategies to achieve desired goals. It helps businesses derive maximum business value through optimised solutions to avoid any SCM disruptions. It is the key to answering questions such as ‘When should I launch this new product?’.
Cognitive analytics: It employs the best analytical techniques like artificial intelligence algorithms, machine learning, and natural language processing to answer complex questions, with speed and accuracy. It helps systems become smart over time to weed out inefficiencies, enhance predictions, respond better to dynamic customer needs, and enable product innovations.
Why supply chain analytics matters
Let’s look at a few specific areas where and how supply chain analytics helps businesses.
Sales: Supply chain analytics can help make more accurate sales forecasts for better SCM planning. It helps match demand and supply to meet the dynamic spikes and falls based on changing customer needs and seasons. It directly impacts customer experience significantly as it improves order fulfilment services. It can also help identify slow-moving stocks, and even suggest where certain products sell better, and alternate suppliers where required.
Transportation: This is an integral part of the SCM that can affect all other aspects. Supply chain analytics help understand the transportation delay patterns with cause and cost impact to facilitate impactful solutions. Speeding up material movements to match demand variability helps businesses improve cash flow. These aspects are linked to procurement streamlining by identifying alternate suppliers and negotiating better contracts and deals with them. Collectively all these steps will increase the working capital for businesses.
Inventory management: Managing inventory is always a problem unless it is backed by intelligent supply chain analytics. Too little or too much inventory impacts various aspects of the business. Predictive analytics help balance the inventory with better sales planning. It provides intelligent triggers for Stock Keeping Units (SKU) that are running low aligned to the supplier lead time. It adds value for better warehouse planning and improves order management and fulfilment.
Overall, supply chain analytics provides benefits through short-term and lasting benefits at every stage of the supply chain. The valuable, actionable insights provide businesses multiple opportunities to improve workflows, identify risks, foresee immediate and future problems, and cause a significant impact on the bottom line. It helps them become more customer-centric and move to a data-driven decision-making process to turn profitable.
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