Achieving Operational Excellence in CPG Through Advanced Analytics and Network Visibility Control Tower

• Supply Chain

Operational efficiency is the key to staying ahead of the competition in the dynamic and fast-paced Consumer Packaged Goods (CPG) industry landscape. Today, businesses are pressured to slash operational costs, preempt disruptions, speed up product deliveries, and keep customers happy. Consequently, optimizing every aspect of the supply chain isn’t just a goal— it becomes a top priority for companies.

One of the most powerful ways of doing this is by improving visibility, i.e., getting real-time insights across the complete value chain, from procurement and manufacturing to last-mile customer delivery. Using advanced analytics, CPG organizations can streamline different operational components, including procurement, capacity utilization, customer service levels, inventory management, stock-keeping unit (SKU) rationalization, and warehouse efficiency.

In this article, we’ll explore the relationship between each of these parameters and the impact of advanced analytics and artificial intelligence (AI) on their performance across the company.

Key Operational Metrics: Are They Interconnected?

Improving visibility across the supply chain and tracking individual components helps us understand how they influence each other. Let’s look at how these six CPG supply chain parameters are interlinked:

Procurement and Upstream Replenishment

Also known as the fundamental starting points in any supply chain, procurement and upstream replenishment play important roles in maintaining a steady and sufficient availability of inventory. Gaining visibility into order lead times, costs, fill rates, strategic dependence, and supplier performance allows companies to easily tackle supply chain disruptions and strengthen relationships with suppliers.

Capacity Utilization

The capacity of warehouses, manufacturing facilities, and logistics infrastructure helps decide how proficiently a company can meet customer demands. If parts of the supply chain are overloaded or underutilized, it can cause bottlenecks or excessive capacity.

For instance, a congested warehouse increases operational costs and causes delays that only get worse with time. On the other hand, a facility’s underutilized capacity increases storage expenses without improving fulfillment times.

Customer Service Levels 

For any company to sustain high service levels, it must ensure timely delivery of the right product to the right location in the right quantity. Parameters like demand allocation, warehouse efficiency (including manpower and machine efficiency), and inventory availability can help achieve this.

For example, operation failures in a warehouse can cause shipment delays, and low inventory availability leads to low order fill rates. These lead to poor service levels and lower customer satisfaction, often resulting in penalties and customer churn.

Inventory Availability

Stocking up on the right products in the right amounts as inventory in different locations is crucial to help meet demand without the risk of overstocking or understocking. When companies have access to inventory visibility across the entire supply chain, they can instantly respond to customer demand changes or disruptions caused in any part of the network.

SKU Rationalization

This is the process of carefully analyzing a company’s product portfolio or SKUs in terms of which ones are worth keeping and which should be removed partially or completely from the inventory. Storage costs, product lifecycle, profitability, sales correlation amongst different SKUs, and sales performance are some of the factors considered while optimizing SKUs.

With SKU rationalization, companies can focus on the products that perform best, which boosts profits and makes operations more efficient.

Warehouse Efficiency & On-Time Deliveries

A company can deliver products at the right time only if its warehouse is functioning smoothly. Inventory management, capacity utilization, and order management directly impact the efficiency of a warehouse.

Inefficient warehouse management delays order processing and delivery timelines get missed. On the other hand, effective warehouse management systems provide real-time visibility into stock levels, order picking, and shipping to ensure on-time dispatches.

Now that we’ve seen how each of these CPG parameters are interconnected, let’s look at the role of advanced analytics and AI in improving visibility and driving performance.

How Does Advanced Analytics Improve Network Visibility and Performance?

CPG companies can convert raw data into data-based solutions by incorporating advanced analytics and optimizing these connected parameters. One such technique is building a Visibility Control Tower.

Popularly known as supply chain control towers, these are cloud-based solutions that provide real-time (subject to clients’ data refresh frequency), end-to-end visibility across an organization’s complete network—manufacturers, suppliers, and business partners. By offering up-to-the-minute insights, organizations can manage what they earlier could not see, plan for unknown variations, anticipate risks, and mitigate disruptions before they become arduous.

A visibility control tower involves 4 major steps— descriptive analysis, causal analysis, predictive analysis & prescriptive analysis.

Let’s dive in and understand the role of each of the following steps in driving success for CPG organizations:

Dynamic Decision-Making with Descriptive Analysis

Descriptive analytics is the first stage of data analytics, primarily focused on interpreting historical data to uncover trends, patterns, and insights. It answers the question: “What happened?” by summarizing large datasets through statistical techniques, data aggregation, and visualization tools like charts, graphs and dashboards. This is primarily used to understand performance, track key metrics, and make data-driven decisions. While it does not predict future outcomes, it provides a clear view of what has happened, thereby helping organizations optimize operations and strategy.

Root Cause Identification with Causal Analysis

By using the latest analytics and AI technologies to find core performance issues, companies can focus on solving problems and put their efforts into what matters most. For example, if there’s a dip in customer service levels, causal analysis can be used to identify the causes of low service levels – whether it is procurement delays, inaccurate demand planning, poor inventory management, or warehouse inefficiencies.

Proactive Management with Predictive Analytics 

As the name suggests, predictive analytics helps CPG companies predict future demands and inventory requirements while identifying potential supply chain disruptions. Organizations can leverage historical data and pattern recognition to easily predict which SKUs are going to be in demand (and hence which SKU’s will be soon going out of stock), when and where they will require extra capacity, and when equipment needs maintenance. This provides more adaptability in responding to demand shifts, fewer inventory gaps, and more efficient use of company resources.

Decision Support with Prescriptive Analytics

Using advanced optimization technologies, prescriptive analytics can be used to find solutions to clearly defined problems for various use cases, which allows companies to focus on addressing hurdles and boost overall performance. One practical use-case of prescriptive analytics is optimizing warehouse workflows to find the best truck routes for lower lead time and recommend ideal inventory quantities in the network based on demand forecasting.

Are these solutions applicable in the practical world? Read along to know how a leading conglomerate benefited from a Visibility Control Tower and Advanced Analytics.

Visibility Control Tower for Capacity Utilization and Fill Rate Insights: A C5i Case Study

A leading global food and beverage company wanted to bring visibility for the overall state of Direct Store Delivery (DSD) network with real-time insights into capacity utilization and service level. The objective was to identify opportunities to help decongestion and support future targeted growth.

Leveraging C5i’s Supply Chain Analytics solution and Discovery, a GenAI-powered augmented analytics platform, C5i took the approach of building a DSD Visibility Control Tower to track utilization and customer fill rate (CFR) across the network.

The result? Better visibility for DSD network capacity, notable performance improvements, and effective management of the inventory and shipments.

Watch the demo here

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