What is supply chain analytics?

The term supply chain analytics refers to a suite of software innovations and tools that support the automation of tedious, repetitive, mechanical, replicable, and otherwise non-specialized tasks. It means harnessing technology and data to eliminate roadblocks in complex, multi-pronged operations and logistics.

Systematizing these aspects of an organization’s workflow or specific components of its workflow simplifies processes, improves accuracy, and saves huge blocks of time. It can also help businesses reduce their overhead costs and make the most of their budget.

Businesses that automate their supply chains experience several benefits, most notably, reducing manual effort on tedious tasks and redirecting it to more productive endeavors. As a result, overall productivity and efficiency get a boost.

Automating links along the supply chain

Supply chain analytics can be immensely valuable to various industries and workstreams, particularly, those where automation is the next logical step. Retail, pharma, manufacturing, logistics, reverse logistics, and eCommerce sectors, by and large, tend to widely adopt supply chain analytics as they begin to scale up.

There are typical procedural links of the supply chain that are easily automated, and thus suitable for data handling. For example, in the retail industry where products and their movement are the single source of truth, supply chain analytics can help in:

  • Generating purchase orders for product-based forecasting
  • Tracking sales from various online channels as well as brick-and-mortar points of sale
  • Generating barcodes for multiple stock-keeping units (SKUs) and ensuring that inventory operations run smoothly
  • Automatic, real-time logging in of every sale, return or exchange for the most accurate inventory updates
  • Payments, invoicing and re-ordering, and studying patterns for future automation
  • Setting and monitoring business expansion activities

What are the challenges and goals of supply chain analytics?

Considering that order management and timely order fulfillment are the end goals of a supply chain, any pain points or obstacles therein become the main targets for supply chain analytics when it comes to problem-solving.

Supply chains pertain to these four major and interrelated categories:

  • Goods/Products/Materials
  • Manufacturing, storage, and distribution facilities
  • Transportation vehicles
  • Dissemination, shipping, routes, and logistics

Supply chain modeling or simulation programs model these components and movements while also gathering data on them, and then use that data to identify areas for improvement.

The biggest challenges to successful order fulfillment that impact or are impacted by supply chains include the following:

1. The complexity and vulnerability of global supply chains

The COVID-19 pandemic amply demonstrated the vulnerability of global supply chains. It showed us that complex supply chains can be volatile, yet, we cannot depend on a single geographic area for our supplies. Against this background, orders still have to be met. In order to do so, streamlining communication among all the stakeholders is paramount to achieve on-time delivery as promised. This is where efficient supply chain analytics comes to the rescue.

In addition, global businesses have to contend with different rules and regulations, as well as different legalities in the various geographies they’re seeking a foothold. Supply chain automation confers layers of adaptability to suit a variety of markets, plus the means to devise the best distribution and marketing strategies.

2. The growing number of businesses going omnichannel

More and more brick-and-mortar businesses are moving online and increasing the number of channels through which they can sell their merchandise. Likewise, there has been significant growth in eCommerce offshoots like drop shipment. By default, businesses like these see their fair share of reverse logistics through returns and exchanges. If the supply chain is not automated, there are multiple opportunities for snafus and delayed orders, which translates to dissatisfied customers who will take their business elsewhere. A business must automate its processes in order to remain ahead of the competition.

3. Changing customer preferences

With businesses, particularly those focused in eCommerce, offering a range of services to attract and retain customers, such as free shipping, free pickup or returns, and next-day delivery, the bar for customer expectation is continually rising. As customers expect bigger and better-personalized service at every touchpoint, businesses are under the scanner for maintaining a certain standard. Supply chain automation can help them do that.

The limitations of supply chain analytics

Supply chain analytics are vastly powerful, and yet they deal with some of the most common challenges of data: handling and cataloging it correctly. Numbers mean nothing when they are not being used in the context of the problem they are trying to solve. Therefore, there is sometimes no substitute for the human eye, or the human touch, particularly in knowing what to do with the data. This is where data analysts come into the picture.

Another potential issue is that sometimes the costs of going fully automated can be prohibitive to certain businesses. Additionally, for new businesses, it can be a while before they are able to reap a return on their investment. On the analytics front, while it may be easy to manually handle data today, automating data collection and handling for large businesses can quickly become a pain point.

However, its benefits are numerous, offsetting the teething problems that come with set-up.

The major benefits of supply chain analytics

By reducing the dependence on manual labor and subsequent human error at warehouses and distribution centers, tasks like storage, picking, packing, and retrieval become faster and more accurate. The payoffs are huge in terms of time saved and shortening the order cycle.

The other benefits include:

  • Highly streamlined operations due to accurate forecasting
  • Better communication between vendors and shipping partners on the basis of a single source of truth
  • Increased transparency for all stakeholders
  • Accuracy in accounting and inventory management
  • Better audit-readiness
  • Better regulatory compliance
  • Higher product visibility throughout the order fulfillment journey
  • Easier tracking of product movement between warehouses
  • An improved order fulfillment rate
  • Having the means to continually update the buyer about the status of their orders
  • More touchpoints for customer delight

Automating your supply chain using supply chain analytics

Automation of supply chains is highly recommended, as it builds resilience in addition to stimulating supply chain diversity. Listed below are a few standard technical elements of supply chain digitization and automation.

Robotic process automation

By combining robotic process automation with machine learning, workflow automation tools can garner valuable data on vendors as well as customer buying patterns. Robotic process automation can also be used to run simulations, analyze bottlenecks, and come up with suggestions for improvements. Bots can take on due diligence tasks such as credit and compliance checks and flag any discrepancies.

Supply chain analytics can help understand the major roadblocks that hold up too many tickets or customer queries. Businesses can make use of this information to implement partial automation at the biggest bottlenecks first.

Data process automation

With automated supply chains, manufacturers can analyze vast amounts of data on their manufacturing capabilities, raw materials procurement, and product movement, all of which are useful for forecasting demand.

Inventory management software

The easiest way to automate your supply chain and logistics processes is to invest in an inventory and warehouse management system that can be integrated with a variety of fulfillment partners. Inventory management software also reflects accurate inventory levels, allowing you to streamline your purchases and keep warehouses optimally stocked. This further lowers the risk of accumulating dead inventory and blocking your working capital. It tracks breakage, pilferage, and keeps you from losing stock.

Warehouse management systems

From a warehouse employee perspective, supply chain analytics can relieve some of the pressures they face about meeting delivery timelines. Specifically, the generation of scanner-read barcodes for stocking shelves and locating individual stock keeping units makes it easy to find the right item, fast. In addition, warehouse automation can streamline and suggest the fastest route for the picklist, which may contain items scattered throughout a massive warehouse.

Warehouse managers can also benefit from automation such as smart shelves, which signal them when stocks are falling low. Smart shelves are based on Radio-Frequency Identification (RFID) technology, and consist of a tag to attach to products, a reader, and an antenna. The tags send out data via radio waves, which are captured by the reader and transmitted to the software platform for further processing. Unlike barcodes, which need to be lined up against an optical scanner to be read, the radio waves-based technology makes it possible to read the tag outside the line of sight.

The future of supply chain analytics

Supply chain automation powered by strong supply chain analytics is the future that is quickly becoming the present, particularly for companies that need to compete with larger organizations in their business area. More specifically, supply chain analytics leads to faster, smoother fulfillment which then results in customer delight and brand loyalty.

supply chain analytics diagram

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