Get started
Insights

Test automation in supply chain management and logistics: three use cases

Test automation in supply chain management and logistics: three use cases

Introduction

According to six key trends impacting global supply chains in 2022, government and industry leaders are seeking to rely less on regional and international supply chains by building resilience and boosting domestic capabilities, that’s for one. Secondly, industry players are more than ever interested in getting over the reliance on third-party solutions, aiming for more flexibility and better cost control. Finally, supply chain providers are ready to double down budgets on introducing advanced technologies because they need greater process visibility. Here are how things are: 

«Only 2% of companies have visibility into their supply base beyond the second tier.»

For the most part, to bridge this gap, supply chain providers can use quality management systems, circumstance monitoring, and data collection and analysis to stay on top of changes or mishaps that occur during transportation. We’ll break up some possible use cases for test automation in supply chain management — to provide insight into potential hurdles and encourage business leaders to explore worthwhile ideas.

1. Robotic Process Automation (RPA) Implementation

RPA definition is pretty much self-explanatory. Used for automating repetitive manual tasks to single out human errors and anomalies, RPA  has a few application areas:

  • Order placement and processing — from product selection to payment processing to order placement confirmation. 
  • Email communication, such as complex notification systems keeps all stakeholders and parties in the loop.
  • Inventory management, opening opportunities to data-based restocking and storage management decisions.
  • Analyzing and selecting vendors — including quotation requests, and cross-checking credits, and requirements helps enterprises making informed partnership decisions.
  • Supply and demand planning  — while this is a bit of a stretch, with the help of artificial intelligence and machine learning supply and chain providers can use their own collected historic data to allocate their resources in the future.

As one can expect, RPA implementation is an extremely complex process to begin with. When it crosses paths with a multifaceted supply chain and logistics industry, with multiple parties involved at different stages, difficulties in implementation orchestration are bound to happen. 

Putting bots, sensors, and cognitive learning software systems together will require rigorous testing. 

However, supply chain industry players eagerly go for RPA because of its tangible benefits. Enterprises who are already in report increased scalability and reductions in resource count as high as 38%.  

 It’s clear that revamping many key business processes might seem a substantial risk, but you don’t have to jump headfirst into uncharted territory. Explore what traditional test automation can offer in your particular case, and advance from there. Handling the mentality shift needed for introducing a test automation framework might need outside assistance — preferably with an experienced quality assurance partner.

2. Third-party risk reduction

Third-party risk management is a process with no final destination, meaning that whoever is responsible should regularly evaluate third-party members of your supply chain and the risks they pose to your company. Those risks might include:

  • Supply and demand risks, which disrupt your timing and potentially ruin your plans and relationships with clients and business partners.
  • Environmental risks, which means any external, political, environmental, and social-economic issues that might cause harm to your business operations. 
  • Business risks that occur when key links of your supply chain fallout for whatever reason, urging you to take extra steps to keep your processes uninterrupted.

Out of all strategies aimed to keep third-party supply risks at bay, leveraging your data to monitor and predict risk events takes the cake. Solutions like service portals, IoT sensors on containers, automated reports on inventory levels, and more can help keep you improve your supply chain visibility and track the freight carrier metrics.

But, for the numbers to be displayed on your screen or a system dashboard whenever you need them, the data you collect has to be consolidated, cleared, and sorted out automatically. To implement such a sophisticated data-driven analytics tool, your delivery will need to execute thousands of test cases daily to ensure the stable data flow from multiple sources, and its accuracy.

By adopting a custom test automation framework, which is an approach to QA automation on your business’ terms, you can harness the power of business intelligence to evaluate risks, saving efforts on tons of functional, performance and security testing.

3. Government regulatory compliance

Regulatory compliance in supply chains refers to adherence to laws and requirements set forth by local or national governments that oversee the actions involved in the sourcing and manufacturing of products. There are quite a few strategies to achieve compliance in the supply chain sector, like checking your vendors’ and suppliers’ qualifications when establishing connections or enhancing the internal company’s ethics. In the end, all of them are targeted at improving supply chain visibility and minimizing the risk of acquiring an unreliable partner. 

 

However, when an enterprise and its network reach a certain development milestone, compliance automation enters the picture. To its benefits, one can attribute fuller organizational control, improved speed of making decisions, and better assessment of your vendor relationships, not to mention the accumulated data you can later use for analytics. At the same time, implementing automation at such a scale with the ever-changing regulations is as time-consuming as it is complicated when you already have so much on your plate. 

What is more, McKincey survey showed that supply chain digitalization increased the need for digital skills, but only a striking one percent of companies possess sufficient talent.

 
So, even if you go for an established SaaS solution, chances are its integration will still require a sizable chunk of your tech manpower and man-hours, taking up to a few years. Instead, you can start small by simply automating some tests and freeing up extra opportunities to focus on the quality of your services. 

How test automation framework improvised working pipeline for a logistics provider: a featured case study

Redwood Logistics, a contract logistics partner that develops web-based solutions for companies across a variety of industries, set its quality goals to increase its confidence in software releases by expanding its testing coverage and performing more “exploratory testing”.

To modernize the provider’s environment, enable business growth, and support a series of business acquisitions, the Forte Group team assigned a cross-functional, on-site product team to quickly and iteratively improve the product suite.

Outcome 

  • A modern test automation framework that enabled efficient automated test creation for both UI and API level tests
  • Migrated legacy projects into Azure Cloud and Azure DevOps
  • Integrated an effective way to track, measure, and analyze all testing workflows within Redwood delivery teams
  • Improved stability and scalability through automated testing

Read the entire case study here.

Buckle up for more supply chain industry disruption

In response to the changing industry standards and requirements, many supply chain providers are taking steps to automate early in the process. Because as costly as it is, Logistics 4.0 solutions are the future and the main pedal pusher for the rapidly (pun intended) evolving logistics and transportation sphere. At the same time, you don’t need to pour limited resources into expensive innovations right away — it’s enough to automate smaller areas that bring core value to your business. Test automation, as a process or as a whole framework, is applicable in RPA, supply chain compliance, and third-party risk mitigation.  

You may also like...

Data Engineering as an AI Enabler in Custom Software Development

1 min By Forte Group

DevOps 2.0: From Operators to Enablers

3 min By Matias Caniglia

Scaling Up: How Managed Product Services Support Business Growth

3 min By Forte Group
More Insights