A Guide to Leveraging Data to Optimize Each Link in Your Supply Chain

A chain is only as strong as its weakest link. Any weaknesses or inefficiencies in an organization’s supply chain inevitably hurt the other areas along its route, causing delays, frustration, and lost profits.

Leveraging data analytics has become a powerful strategy for businesses looking to streamline operations, reduce costs, and improve efficiency. In this comprehensive guide, EnterBridge will provide supply chain professionals and business leaders with the tools and knowledge needed to harness the power of supply chain data analytics to achieve their objectives. Discover the best strategies to optimize each link in your supply chain using data.

How Supply Chain Analytics Can Help Your Business

Supply chain analytics is the process of collecting, cleaning, and analyzing supply chain data. This provides actionable insights that can help businesses drive growth and improve efficiency by offering a clearer understanding of what’s happening in every link of your supply chain. 

With a bird’s eye view of your operations, you can quickly identify bottlenecks, inefficiencies, and opportunities for improvement. This creates numerous benefits for a business, including:

Eliminate Silos

Supply chain data scattered across various systems can lead to inefficiency and incomplete understanding of operations. With analytics, you can integrate data from different sources into a single platform, eliminating silos and providing a holistic view of what’s happening.

Meet Customer Expectations

Analytics allows companies to predict and adapt to changing customer demands, ensuring a consistent and satisfactory service. In some cases, this means giving customers what they want before they even know they want it, such as through offering new services. From the supply chain side, this would manifest in different purchasing and sourcing decisions to fill these gaps, as well as by simply avoiding slowdowns that could lead to items being out of stock.

Increase Sustainability

By providing detailed visibility into every step of the supply chain, analytics enable businesses to make informed decisions that save costs and reduce environmental impact. This can range from optimizing transportation routes to save fuel and identifying sustainable suppliers to minimizing overproduction and waste. Analytics can also assess the environmental impact of various aspects of the operation, allowing companies to prioritize their sustainability efforts and make data-driven decisions toward achieving their environmental goals.

Exploring Different Types of Data Analytics in Supply Chains

Supply chain analytics can be grouped into three main categories: descriptive, predictive, and prescriptive analytics. Each type plays a unique and crucial role in supply chain management.

Descriptive Analytics

Descriptive analytics is the initial stage of data processing that creates a summary of historical data, often in a visual format. This type of analytics helps businesses to track performance over time and compare it to certain standards or goals. It provides valuable context and a basis from which more nuanced analysis can be carried out. This type of analytics typically includes techniques such as data aggregation and data mining.

Predictive Analytics

Predictive analytics leverages a variety of statistical techniques, such as machine learning and data mining, to analyze historical data. The aim is to make informed predictions by seeing what has happened in the past. A good example of this would be how it helps supply chain managers foresee potential delays in their logistics or distribution network. It can also be used to predict customer buying behavior, allowing businesses to stock more or less of an item based on predicted need, or even look into buying new products based on customer habits.

Prescriptive Analytics

The most advanced form of analytics, prescriptive analytics suggests actions based on the outcomes from descriptive and predictive analytics. By leveraging machine learning algorithms and AI, prescriptive analytics can help businesses make proactive, data-driven decisions that can lead to improved performance, reduced costs, and increased customer satisfaction.

How Data Analytics Enhances Supply Chain Optimization

Harnessing the power of data analytics can lead to significant enhancements in supply chain operations. It can help increase the visibility of operations, allowing key decision-makers to quickly identify and rectify any potential issues. It also aids in capacity planning and delivery schedules by predicting trends and patterns, as well as enables real-time tracking of goods and materials, allowing businesses to respond proactively to any potential risks or disruptions in the supply chain.

Steps to Implement Data Analytics in Your Supply Chain

When incorporating data analytics into your supply chain, you should follow a few simple steps to make the process as painless as possible and create the best outcomes. These typically include:

Assess Current Data Sources

The implementation of data analytics in any supply chain begins with the assessment of current data sources. Start by identifying all potential sources of relevant data, since knowing which sources to use for your data will affect the results of your analysis. These may include internal systems such as order management, inventory, or CRM systems, as well as external sources such as supplier databases or market trend reports. The more comprehensive your data collection, the more accurate your analytics will be.

Define Objectives and Key Performance Indicators (KPIs)

Charts and statistics are meaningless without context. Therefore, set precise objectives and KPIs that align with your business goals. These could include measures such as fill rate, order accuracy, and inventory turnover depending on what you hope to achieve from your optimization efforts.

Select Suitable Analytics Tools

Analytics tools can automate and streamline the process of data analysis, making it easier to uncover valuable insights. The plethora of analytics tools available on the market can be overwhelming. However, you can narrow things down by looking for tools based on user-friendliness, scalability, and the ability to integrate with existing systems. Tools such as Tableau or Power BI can provide powerful insights into your supply chain data.

Data Collection and Integration

Data collection and integration can be a challenging task considering the diversity of sources and platforms. However, technologies such as cloud computing and data warehousing can help you centralize your data, facilitating easier access and analysis.

Apply Data Analytics Techniques

Once the data is collected, cleaned, and integrated, it's time for analysis. That means examining, transforming, and modeling data to discover useful information that can support decision-making. The analysis should be performed with the goals of your supply chain in mind to ensure that the insights gained are relevant and valuable. Implementing techniques and tools like machine learning, predictive modeling, and regression analysis are also quite useful.

Fine-Tuning Each Supply Chain Link With Data Insights

Data analytics can fine-tune various aspects of your supply chain. By taking into account the information you gain from your analysis, you can better pinpoint the areas where things fall short in each of the links along the chain and begin making improvements. Some potential areas to look at would be:

Sales Inventory

Predictive models can use past data to improve and synchronize sales forecasts, inventory levels, and operations planning to meet market demands efficiently. These models are constructed based on what has happened in the past, using computing power to find patterns and draw conclusions that the human mind would likely miss.

Sourcing

One of the easiest ways to cut costs is by finding a good supplier. Data analytics can look at your data related to where you source your products and suggest new methods or suppliers that will allow you to save more money. Ideally, your analytics tools will be able to find ways to avoid compromising on quality while doing so.

Manufacturing

By looking at the data, your analytics tools can find new ways to streamline manufacturing processes. This could mean new ways of making existing products that reduce waste, new prototyping techniques that are more cost-effective, strategies to reduce downtime, and more.

Warehousing

Predictive modeling can even be used to improve how your stock is stored. For example, moving the products that are most often bought and need restocking to an optimal location within a warehouse can save small amounts of time whenever that product needs to be fetched or restocked.

Transportation

Transportation solutions are one of the easiest things to optimize with data analytics. By looking at your current quotes, fuel costs, delivery times, and more, your tools can find new and innovative ways to shave off travel time with things like more efficient routes and better vehicle upgrades.

Point of Sale

Data collected at the point of sale can inform supply chain strategies in a few ways. By taking into account the selling experience for customers and identifying pain points or other issues some of them experience when buying from you, you can go on to improve the process to make it easier and more satisfying.

3 Ways to Utilize Your Supply Chain Data

Your supply chain data can be leveraged to benefit your business in several ways. Here are three useful ways to use your data most effectively:

Improve Supply Chain Visibility

Improved visibility through data analytics provides a complete picture of your supply chain operations and enhances transparency. It offers a clear understanding of the journey of a product from the point of origin to the point of consumption. Through techniques like real-time tracking of products and personnel, you can more proactively resolve issues and keep efficiency high.

Inform Business Decisions

Data analytics can offer significant insights that influence crucial business decisions, ultimately expediting growth. By analyzing patterns and trends in supply chain operations and customer behavior, businesses can anticipate market changes and adjust their strategies accordingly. A real-world example of this comes from McKinsey’s look at Amazon, where around 35% of all sales in 2017 came from their data-driven recommendation engine.

Measure Performance Over Time

By employing data analytics tools, businesses can quantitatively assess their supply chain's performance over specific periods. This longitudinal analysis enables businesses to measure their progress against defined KPIs and reveals trends that might not be perceptible in shorter-term observations.

Overcoming Challenges and Implementing Solutions

Like any new initiative, implementing supply chain analytics comes with its share of challenges. Failing to properly integrate data is a common one, but this can easily be overcome with more thorough cleaning or by updating your existing systems. 

You’ll also need to train personnel to be able to use these new tools since a lack of knowledge or experience can often lead to resistance to implementation. You might also run into the issue of struggling to embed the insights you learn from your data into your organization, but this can often be fixed through better communication – by communicating the need for this technology to decision-makers, by helping the experts better explain their findings, and by stressing how working with these insights can benefit the business.

Elevate Your Supply Chain With EnterBridge

Your journey to supply chain optimization powered by advanced data analytics begins with EnterBridge. Our tailored solutions allow you to navigate through the complexity of your supply chain, providing you with the essential insights needed to make informed decisions. Schedule a call now and let us help you optimize your supply chain.