Supply Chain Analysis: Planning Techniques, Models & Tools

Supply Chain Analytics Tools and Models

With the help of supply chain analysis, you can see everything from the availability and price of raw materials to transportation and logistics, final products, demand, and so on. In other words, the supply chain analytics tools won’t just help you understand how your supply chain works but will also make you spot those companies with whom you can do business. For example, purchasing raw materials to create a new product or selling your products to new businesses. And the final result is the expansion of your company. There are five frequently used supply chain analytics tools:

1. Descriptive Analytics

This is the best type of supply chain management analytics that you can use to check out the past performance of the supply chain. It will tell you what has happened, so you can check if the results are matching with your plans and objectives. This method uses data mining to gather raw information from the supply chain. Summarizing it and presenting it in a compact form that will allow you get a clear image of the desired period in the past.

2. Predictive Analytics

If you want to see what might happen in the future,  you should use the predictive supply chain analytics tool. As the name suggests, predictive analytics will form potential scenarios that may take place in a month, two, or a year from now. However, it is never guaranteed that they will happen exactly as predicted by this method. Even so, you will know what to expect in a significant proportion so that you can adjust your plans accordingly.

3. Prescriptive Analytics

In case you want to see what could happen and get useful pieces of advice on what to do if future scenarios come to life. This supply chain analytics tool will help out. In other words, you will be advised what to do according to what the method predicts to happen in the future, based on the acquired data.

4. Performance Metrics

This is one of the best supply chain analysis tools, to use when you want to see how the supply chain planning and the chain itself is performing. Just do keep in mind that there are several metrics, and each of them provides a different type of information. So, you need to decide which supply chain management metrics are most useful and relevant to your business so you can keep an eye on those in particular.

5. Hybrid Performance Measurement

This is a more complex form of supply chain analysis, as it utilizes several methods in the same framework so that the business owner can make the best decisions. Thus, a hierarchy of objectives is used, together with mathematical equations and simulations that should be present. Hypothetically, what would be possible if certain conditions were met?

Importance of Supply Chain Analytics

Main purpose of supply chain management is to bring together the various players involved in a supply chain in order to deliver these products to customers as efficiently and effectively as possible. As a supply chain manager, you must regularly analyze your supply chains to identify any potential problems or inefficiencies.

• Supply chain analytics help you collect and analyze data in order to make better decisions about the supply chain and improve your business’s overall performance.
• With the help of supply chain analytics tools, you can identify and solve problems from procurement to transportation, inventory management, and customer service.

Supply chain management analysis is a part of AIMS’ CSLP (logistics courses online) and CSCE (supply chain management courses online). AIMS offers these programs through a flexible and self-paced interactive learning system.

6 Key Data Components of Supply Chain Analysis

Data is the key to supply chain analytics. Various components of the supply chain produce data that are gathered and analyzed. Here is the importance of supply chain data:

• The data helps you dig deeper into the supply chain to examine the efficiency gaps and improve the operational, financial, and managerial aspects of the logistics and supply chain.
• It helps businesses to capture and study a huge amount of information.
• The supply chain data is collected and visually displayed in the form of charts or graphs.

Organizations should know the following about their supply chain data before applying supply chain analytics tools:

1. DATA SOURCES

• Where are your data sources coming from?
• How can you ensure that the data is accurate and reliable?

2. DATA TYPES

• What types of data are essential to your supply chain?

3. DATA AVAILABILITY

• Is the data available in a timely manner?
• Can it be accessed by all members of the supply chain team?

4. DATA OWNERSHIP

• Who is responsible for collecting and analyzing data?
• Who owns this data?

5. DATA SECURITY AND PRIVACY

• How is the data being secured?
• Are there any impactful compliance requirements?

6. DATA ANALYSIS CAPABILITIES

• What tools are you using to analyze supply chain data?
• What types of reports and visualizations are you creating?

Supply Chain Analytics Examples

1. DHL

• In 2018, DHL hired qualified professionals with a doctorate in logistics and supply chain management and partnered with Riddle & Code for their supply chain analysis and customer experience through blockchain supply chain technology.
• With this partnership, DHL was able to track individual shipments in real-time.

2. SWEDISH RAILWAY

• Swedish Railway partnered with SAP to improve its ability to manage its global supply chain.
• The results gained from the supply chain analysis allowed the railway to optimize its procurement, logistics, and asset management for better efficiency.

3. E.ON

• E.ON is a global electricity and gas company that hired SAP to improve and suggest innovations in their supply chains.
• The data was collected through their IoT platform, and supply chain analysis was performed, which helped them improve their energy management and customer service.

3 Tips to Improve Your Supply Chain Analytics Strategy

The following are 3 tips to improve your supply chain analytics strategy:

1.  START SMALL

• Prioritize projects that will have the greatest impact on the organization.
• Building a big data analytics project can be costly, time-consuming, and complex. Start small with a few projects that have a clear objective, and that can be completed relatively quickly.
• This will help you to gain experience and show value quickly.

2. FOCUS ON DATA THAT MATTERS

• In order to be effective, supply chain analytics must be actionable. This means that the data must be accurate and must have a legitimate impact on the supply chain.
• While all data has value, only data that is truly relevant should be collected and analyzed.

3. BUILD A CULTURE OF COLLABORATION

• Supply chain analytics can provide value to organizations of all sizes and in a variety of supply chain environments.
• For best results, you should create a collaborative culture in which data is accessible to all members of your supply chain team.

Special Types of Supply Chain Analytics

Several special types of supply chain analytics are used to achieve organizational goals. For your better understanding, here is a brief overview of three of them:

1. Capacity Planning

• Capacity planning is a type of supply chain analysis used to match manufacturing capacity to sales demand.
• Different supply chain management analytics tools are used to create a mathematical model, and then all the data is analyzed to predict the future capacity of sales.

2. Stimulation and Scenario Analysis

• Stimulation and Scenario analysis is a type of analytics used for strategic planning to determine potential business scenarios.
• It will help you shape your company’s future and stand still during numerous crises.

3. Sales & Operations Planning

• Analysis for sales and operation works on the financial bottom line and helps you determine the most profitable production.
• This type of supply chain analysis is used to determine the sales scenario and maximize future production.