Predictive Analytics Improves End-To-End Visibility In Supply Chain

Predictive analytics is a technology tool that is improving the end-to-end customer experience of the retail, healthcare and transportation industry

Predictive analytics is a technology tool that  is improving the end-to-end customer experience of the retail, healthcare and transportation industry.
 
The increase in consumer demand is becoming more apparent across global markets and a variety of industries. This month, multinational retail corporation, Wal-Mart, announced their partnership with ‘actionable predictive intelligence’ platform, FourKites. According to Digital Supply Chain:
 
"The Canadian branch of Walmart has agreed a new partnership with FourKites for the development and furthering of the company’s supply chain visibility and predictive analytics capabilities"
 
FourKites platform will enable Wal-Mart to optimize their consumer experiences by leveraging insight that will clearly identify the lifecycle of their shipments. In addition, the company will be able to improve their ‘staffing levels, assignments and minimize truck waiting times’.
 
A challenge supply chains face in changing markets is visibility. On February 15th, Morai Logistics identified how predictive analytics can help create efficient processes such as forecasting and real-time visibility. Investment in technologies that offer ‘end-to-end predictive visibility’ is a route many industries are taking to improve the customer experience.
 
This article looks at the application of predictive analytics in the retail, healthcare and transportation industry. Specific focus will be placed on how the appropriate translation of big data will better the end-to-end customer experience.
 
Retail
 
Large wholesale companies have been utilizing predictive analytics to improve daily operations of their large product volumes for quite some time. However, in the past cost of technical personnel and lack of appropriate process has presented challenges with providing customers with personalized service.
 
According to Digitalist Magazine, the following improvements are achieved when wholesalers implement predictive tools to assess Big Data.
 
  • Data on customer purchases can help predict future sales.
  • Narrows and tailors product focus to the client’s needs.
  • Helps ‘detect risk’ and ‘provides insight into new product categories’.
  • Provides product recommendations to address customer inquiries.
In addition to the above efficiencies, research states that predictive analytics supports the development of loyalty programs as Big Data is translated in real-time. Therefore, addressing the need for immediacy.
 
Healthcare
 
Another industry looking to predictive analytics to improve processes and leverage Big Data is the healthcare industry. Instead of focusing on the customer experience, applying this technology will hopefully enhance patient care by taking a preventative approach.
 
Health Facilities Management magazine states that tools are needed to help asses ‘which patients will require more intense interventions than others’. Integrating predictive analytics into the supply chain will also reduce costs by providing efficient assessments on necessary materials and products. The article quotes vice president of inventory management solutions for Cardinal Health, who states:
 
"Rather than analytics being retrospective, we are trying to infer what will happen in the future. There is no denying the health care industry is looking to streamline their processes and supply chains to better service patients and the community"
 
Transportation
 
When it comes to transportation supply chains, transparency is key to creating an optimal end-to-end user experience. Even 73% of online shoppers feel more confident making purchases when they have the ability to track their delivery. Given the demands of online markets, companies are seeing the need for leveraging Big Data.
 
Referred to as ‘real-time freight visibility’, both shippers and suppliers should be aware of all particulars relating to the shipment lifecycle. Research addressing the importance of freight visibility identify four reasons and how predictive analytics can help.
 
  1. Helps 3PLs retain business and avoid late shipments by monitoring deliveries.
  2. Improves the visibility of ‘shipment status and location’.
  3. Avoid costs associated with ‘late and off-schedule shipments’.
  4. Create business opportunities by meeting visibility requirements.
Investment in technologies has been a reoccurring theme in changing markets, as the issue of visibility continues to be address. Many industries, such as retail and healthcare, are recognizing the positive outcomes that occurfrom integrating such technologies into their supply chains. 3PLs will also be able to translate Big Data into meaningful information, and use predictive analytics to meet the demands of immediacy and improve visibility.
 
 
 
comments powered by Disqus