Leveraging the Power of Predictive Analytics to Optimize Global Supply Chains
Your supply chain analytics go a long way toward optimizing your company’s global supply chain. Still, you need a sophisticated digital model to tap the correct data from Internet of Things (IoT) sensors, the Internet, retail and e-commerce register receipts and the growing Metaverse. With this analytical model constructed, you can leverage a proactive approach using predictive analytics.
Transformation Takes Time
According to Gartner, although 70 percent of businesses previously began a transformative process of creating a digital supply chain honed for optimum performance, more than 43 percent of those companies continue that development into this year. Gartner reported its findings from respondents to the survey in the “2021 Future of Supply Chain Survey.” Companies want to accelerate their path to informed, insightful business decisions, especially in light of the two-year and counting roadblock caused by COVID-19. So, how do data analytics help a business overcome mounting business costs, labor shortages, and supply shortages?
Follow the example of Schneider Electric. It integrates internal and external partner data to maintain its place in the top five corporate supply chains. Its agile application of data analytics provides the company with full visibility of its end-to-end supply chain.
What does taking an agile approach mean?
Utilizing an agile approach refers to building a data acquisition and analysis program that offers actionable insight that easily conveys pipeline problems so the business can quickly address them with a change in the process. It consists of:
• linking data to business strategy using a transformation road map,
• choosing an agile methodology for long-term implementation,
• utilizing a holistic approach to implementing and integrating the methodology, the business ensures it can leverage opportunities across the different teams and at different points within the customer journey.
• establishing a stakeholder ecosystem that enhances collaboration and renders the organization better able to predict demand and source materials and supplies,
• embracing the growing Metaverse by integrating synthetic data and IoT device data.
The agile approach makes way for change by enabling it on the fly. Integrating agile methods into your supply chain analytics can open new doors for cost reduction and product delivery improvements, whether using the Toyota method, Six Sigma, lean management, or another like-approach.
Types of Supply Chain Analytics
As IBM explains, you won’t find a single analytic type when dealing with your supply chain. Instead, you’ll find yourself faced with four types.
- Descriptive analytics
- Predictive analytics
- Prescriptive analytics
- Cognitive analytics
The second type, predictive, provides the greatest insight into simulations of business decisions. This type of analytics lets you create projections and mitigate risks and disruptions. So, while descriptive defines the current business situation and prescriptive helps solve problems as they arise, the predictive lets your business model future scenarios. Cognitive analytics helps address questions using natural language.
Steps to Digitize Your Supply Chain
It probably sounds quite complex, but in summary, you build an area of data storage, such as a data lake, that can immediately integrate various data types. This lets your organization pull in real-time data from social media to connected POS systems. Your information from IoT sensors your freight shipper uses automatically integrates into the same data lake as do other sources.
Digitalization is the key to creating a connected, intelligent, efficient supply chain ecosystem. Gartner predicts that 50 percent of large international organizations will use AI, advanced analytics and IoT in supply chain operations by 2023. In addition, collaborative robots are expected to supplement more than 30 percent of warehouse workers. Your organization manages the digitization in six main steps as described by Reciprocity.
Step 1: Conduct a comprehensive assessment of your current supply chain, including a SWOT analysis.
Step 2: Create your digital strategy, collaborating with your supply chain partners. Here you create an executable roadmap.
Step 3: Conduct a comprehensive supplier analysis to help you determine their digital readiness.
Step 4: Invest in establishing your business’s digital capabilities – software, logistics and supply chain management needs.
Step 5: Build internal support for the project. Digitizing doesn’t remove humans from the supply chain. It merely lets them focus on problem-solving and making well-informed decisions. Providing staff training to leverage the new tools makes the digital supply chain more successful.
Step 6: Analyze the digital supply chain performance for continuous improvement opportunities so your business can reveal improvement opportunities for the analytics process, providing you with better information.
Contact Starr & Associates
You can more easily get started with your supply chain digitization by contacting Starr & Associates. We understand how to utilize analytics, business intelligence and data mining tools to improve process efficiency and customer service. Let us help you.