Five Technologies to Future Proof Supply Chain Inspections
The COVID-19 pandemic has jolted digital transformation into overdrive, with technology adoption enabling businesses across industries to accommodate remote work and operations. But now more than 18 months into the crisis, businesses that source globally remain ensnared by rampant order delays, factory lockdowns, persistent transit challenges, rising costs and debilitating mass shortages.
To raise resiliency and thrive post-pandemic, businesses with a global sourcing footprint must continue to accelerate the digital transformation journey. As poor quality and non-conformities can have severe impacts on business value, leading businesses will be the ones that innovate by implementing digital quality and supplier management solutions and driving real-time, data-based decision-making. This way, they can prevent risks of volatile supply and demand patterns, while still protecting essential quality and compliance measures as they rebuild their supplier networks.
However, with so many tools and platforms on the market, choosing where to go next can be a daunting task. The following are five key technologies and functions that businesses should prioritize as they digitize inspections across their supply chains.
Cloud Computing and Remote Connectivity
With inspections being done offsite and often in multiple locations, businesses need easy-to-deploy software solutions that can be operated without extensive support from the IT department and can work within their existing IT ecosystem. Ideally, the inspection solution can integrate across devices on the cloud and plug in to existing PLM and ERP solutions via APIs. In doing so, data can be centralized, removing data duplication and the errors that can come with it.
Another key feature for digital inspections is the ability to function offline or with limited internet connection. As brands diversify their sourcing footprint to new geographies, they must consider varying digital ecosystems. With so many factories and inspection sites lacking internet connectivity, platforms that require an internet connection are basically obsolete and potentially detrimental to the inspection process.
Artificial Intelligence and Machine Learning
When it comes to safeguarding a business’s sourcing footprint, the most valuable data is generated daily on the factory floors. Artificial intelligence (AI) and machine learning (ML) help businesses achieve real-time visibility of vital metrics such as product quality, compliance and supplier performance. Through the use of these technologies the supply chain team can turn data from various sources into actionable insights, empower more informed decision-making and accurately assess risk that may affect their supply chain, now and in the future.
An innovative application of machine learning and artificial intelligence for quality control is the use of voice command technology to perform time-consuming measurements. While still making headway in the supply chain space, voice tech has already proven itself to be far more than a passing technology trend.
Most digital inspection platforms in today’s marketplace use IoT-connected rulers and other automation measures. But these tools require businesses to additionally invest in dedicated devices for all factories and provide intensive training to all employees or suppliers involved in the process. When supply chains engage hundreds or thousands of parties, this becomes a costly endeavor.
Moreover, the precision between devices is inconsistent, with up to a 10% delta between two measurements, according to QIMAone data. In the long-term, such a wide margin of error presents grim implications for quality control and process efficiency.
Unless other connected devices that require additional costly investments and intensive training, measurements powered with voice recognition require minimal onboarding. Notably, there’s a low learning curve as most people are already familiar with the functions of speech recognition technology thanks to devices like Google Assistant or Amazon Alexa. By infusing the inspection process with accurate speech recognition capabilities, the inspectors, armed with just a tablet or other mobile device, can simply speak up and upload their data directly and immediately to a cloud-based system.
Predictive Quality Analytics
Predictive quality analytics (PQA) anticipates the impact of high-risk events and pinpoints root causes, leading to reduced quality issues and a stronger pulse on products and raw materials. To be successfully deployed, PQA needs clean, reliable and standardized large amounts of data collected along the supply chain – from raw material factories to assembly suppliers, warehouses and retail stores
Essentially, digitization enables easier and more effective data collection and analysis – core to supply chain decision-making, collecting insights at every touchpoint and illuminating real-time visibility from factory floor to shelf. However, while algorithms can be intricate and specialized, data must be accessible and actionable for a business’s decision-makers.
When data summaries are available and manageable in a single place, rather than across multiple systems that don’t sync up or communicate with each other, businesses can continuously ingest insights and take action accordingly. For example, through performance tracking insights, they can review individual supplier and inspector metrics to easily identify the best and worst performers across their sourcing footprint. With risk radar, they can build a risk profile for each supplier and factory, which helps anticipate problems sooner rather than later.
To complement data analytics, automation should use a balanced model that empowers suppliers with intelligent design and third-party monitoring. There are three fundamental functions of automation: risk-mitigation, decision-making and reporting.
With data-based decision-making based on AQL criteria, a platform can automatically suggest a result (pass or fail) and accept or refuse a shipment for pre-shipment inspection (PSI). Proactive alerts can be automatically triggered, along with corrective and preventative action plans to suppliers to identify the root cause and solve the issue as quickly as possible. Finally, an inspection report can be automatically issued and used in a standardized format populated with all of the data collected during the inspection.
Moreover, a digital platform can change the back-end processes for how inspections are scheduled. A “smart booking” function leverages advanced risk management to automatically assign inspections to a business’s internal inspectors or supplier’s staff. When indicators show potential integrity issues “on the ground” with suppliers, the platform can trigger an inspection with third-party experts.
By automating inspection allocation based on location, product expertise, teams’ schedules and severity of the issue, businesses maximize their resources and save time in the long term.
Whether navigating disruptions spurred by the U.S.-China trade war or the pandemic, businesses have learned that they cannot succeed alone and must prioritize supplier relationship management (SRM). Against volatile consumer demand and economic uncertainty, SRM is perhaps the single most critical differentiator that will decide supply chain success or failure.
To successfully digitize supply chain inspections and assert strong SRM, businesses must loop suppliers into a computer-based collaborative network so they can bring together entities that are autonomous, geographically distributed and heterogenous in their operations. While entities may vary in culture, values and social capital, a collaborative network brings them together on a computer network so they can better achieve common goals.
A collaborative network allows a business to bring their suppliers on board the digital transformation journey. This way, meaningful benefits are unlocked for all parties. For example, a digital inspection program can be bolstered by innovative features such as integrated inspector apps, actionable insights, automation tools, configurable workflows, API integration and interactive reporting. To strengthen supplier onboarding, many digital platforms also offer training courses on operational workflows and best practices.
In QIMAone’s annual survey, supplier communication and quality were cited as serious issues by 59% and 41% of respondents, respectively. However, compared to their peers, businesses with highly digitized supply chains cut concerns of supplier communications and quality in half, according to QIMA data. Providing collaborative training and onboarding as part of digital transformation will help businesses overcome challenges and future proof their SRM framework, instilling the supply chain with the “3Ts” of trust, transparency and teamwork.