Digital Supply Networks: New Possibilities to Efficiently Maintain Your Assets

The Council of Supply Chain Management Professionals outlines the top three drivers of planning your supply chain digitalization:

• The necessity to keep up with your customer’s changing demands
• The urgent need to automate routine operations to free up staff for more productive activities
• An “overall desire to improve business performance”

In this whitepaper, we discuss not only trendy technologies and their unique features for digital transformation success but also the challenges of their implementation and technology adoption frameworks.

Digital transformation is shaping the supply chain in different ways: boosting smart logistics (automated warehousing, autonomous trucking, remote fleet management), developing demand-driven supply chain management, and the formation of a digital thread (framework of communication throughout the supply chain).

Technologies contribute to meta changes in supply chains, such as value co-creation: supply chain stakeholders evolve customers’ expectations and generate new added values for better collaboration. As the BDO accounting firm blog stated, digital transformation in many business networks leads to the creation of a transparent “network of networks,” where data is available not only for the insiders, but supply chains are sharing information, generating new opportunities for partner organizations.

Each technology solves a different issue across an interconnected supply chain; such as the product’s complexity, precise planning, and problems concerning budget allocation. And the only effective ways to gain high-tech improvements are to clarify and be completely informed about your business and potential shipping bottlenecks.

Gartner described here the latest promising technologies in 2021. They also mentioned that people will be involved in the business processes directly, despite the deep high-tech solution integrations.

It was pointed out by Christiane Titze, VP analyst for Gartner Supply Chain that it’s worth combining new technologies to maintain business effectively. He added: “We are not able anymore to focus on the separate individual tech tools.”

He gives an example of automated services uniting ML (machine learning), AI (artificial intelligence), and RPA (robotic process automation) which are used for complex operations, but still dependent on human help. Another example in his review was logistics solutions coming in handy for smoother decision-making and building autonomous supply chains.

Flash Global, a US logistics company, stated that technologies can help simplify supply chains: “optimizing every component of supply chain stakeholders and obtain possibilities to decrease the risks associated with shipping and receiving.” They mentioned that supply chain digitalization led to enhancements in customer communication and delivered real-time “actionable” data for further improvements.

Statistics from their 2021 tech initiatives show that 54% of companies worldwide treat digital transformation as a priority, and $6.8 trillion in expected in these investments in this field from 2021-2023. Accelerating supply chain digital transformation brings new challenges such as supply chain integration into the digital ecosystem, synchronizing it with the whole digital world. For these purposes, business owners and other stakeholders need to know about the latest technology trends and how to implement them efficiently.

As McKinsey Consulting mentioned digital change is an issue for discussion in many companies. However, they calculated that the average supply chain has a digitalization level of 43% which is the lowest of 5 business initiatives that were examined.

Going digital for supply chain improvements is not only choosing the technology and integrating it into your business processes. It’s very much about having an overall company strategic vision, assessing whether the technology is sufficiently integrated into the current company structure to prevent speculative expectations.

Logistics apply technologies mainly to streamline transactional activities, support major operations, and sharpen data analyses for the sake of making business decisions. But as McKinsey stated, “It’s still a challenge to combine cross-functional data as well as forecast demand and performance with advanced analytics.” Here, we propose to follow every technology trend profile to learn more about its possibilities and applications.

Gartner refers to hyper-automation as a “business-driven approach” used by companies to identify and address the processes necessary to be automated for better KPIs, more revenue, and faster ROI. No digital transformation is possible without RPA and the complete replacement of routine human operations throughout the supply chain networks by robotics alternatives.

According to Gartner’s report, global RPA software revenue is expected to reach $1.89 billion by the end of 2021, an increase of 19% from 2020. Forrester states “one in every four information workers inside the supply chain networks receives help from software bots,” a fact that proves RPA is capturing the industry.

As a growing technology trend, RPA enables the rise of IPA (Intelligent Process Automation), the gradual elimination of paperwork, RPAaaS mainstream trends, the efficient blending of human experience, manual and digital efforts, as well as the proliferation of RPA across the components of the supply chain.

RPA improves business processes via automation, elimination of human errors, cost reduction for staff administration, securing data, and rocketing robotics multitasking. The Dubai Expo 2021 proves that every country is striving for robotics development and implementing robots in every field including the supply chain.

For many years, scientists have been implementing mathematical structures of real physical objects to make them easier to visualize in a 3-D model. As a result, network technologies of grids and sensors enable us to connect assets, reporting, and diagnostic features to the digital world. Thus, changes in real world objects that can be observed by the naked eye in real-time can be seen in a digital model. Holistic images taken from these models can help to assess the physical aspects of an asset or business process and control in.

Practically speaking, a digital twin can exist in different forms with a mixture of features. Companies are willing to include familiar technologies such as existing 3-D modeling, simulation, and asset-tracking technologies to model business processes. The result is typically better monitoring, tracking, and maintaining throughput. But there is more to digital twins than meets the eye. Here is the list of features that distinguishes real digital supply chain twins from other digital models:

• It’s a virtual model of a real ‘thing’
• The model simulates physical processes
• The digital twin is genuine and unique – a living model
• It is connected to an object, updating itself in response to the system fluctuations
• A digital twin provides the value of visual inspection, analyzed content, and predicted context changes

Here are the main blocks that may be encountered when leveraging digital twins:

• Cost. Complicated asset models, their behavior in digital real-time, and the demands for reflection accuracy can easily exhaust computing capabilities. The budget for digital twins’ creation can be huge. To maintain this technology, we should keep in mind the investments in technology platforms, model development, and high-touch maintenance.
• Precise Representation. In the near future, no digital twin will be able to present reality perfectly. To represent all physical, chemical, electrical, and thermal data of a complex object will be a real challenge. Consequently, this should be taken into account by engineers—the models must be simpler and maintain data quality.
• Data quality. If we have high-quality models, we get accurate data. It can be rather complicated because we should consider a great number of sensors in a digital twin, the working conditions, and volatile networks. As a result, engineers have to discover methods enabling them to isolate inaccurate data and to cope with faults in data streams.

Sometimes, investing in digital twins is impossible and a company is willing to represent only a few critical parameters. It’s possible to have a look at an IoT system based on sensors and usual databases, saving costs.

The cost-sensitive nature of many logistics activities may explain why few companies have been willing to make the necessary investments. For these purposes, companies create packaging and container digital twins as well as digital twins of shipments, warehouses and distribution centers, and global logistics networks.

Digital twins contribute to the visibility of parts, components, and products in transit to be tracked for the sake of supply chain strengthening, securing, and making critical supply data available for all the stakeholders.

Supply Chain Visibility (SCV) is about data management which enables you with the ability to prevent inventory shortages, delivery delays, and other supply chain disruptions. If you imagine tracking the spare parts traveling from China to a US plant, you can see a diverse number of digital tools to manage the delivery (fleet tracking systems, inside company communications, CRM for customer management). These components contribute to supply chain visibility and are components of a broader ERP (Enterprise Resource Planning) system.

An investment in supply chain visibility typically results in:

• Applying the right software to increase KPIs and solving logistical problems appearing throughout the network
• Improved customer satisfaction
• Compliance: international supply chains face steep regulatory requirements so enhanced visibility monitors shipping schedules, international transactions, and new rules and regulations
• Competitiveness: visibility helps to quickly manage inefficiencies and reduce costs

To start to improve your supply chain visibility, it’s sufficient to start with the proper technology platform, stay focused on process improvement, and look for more transparency which is enabled by API-powered networks.

An Application Programming Interface (API) serves to improve the openness and optimization of the basic supply chain functions. The effective flow of data to end-users influences the modern supply chain. Thus, an API connects two unique systems. For example, you’re using a TMS to locate, rate, and schedule carrier movements. But you are also using an order management solution to process e-commerce transactions, set up shipping, and send notifications to the customer. Building an API enables these disparate systems to interface and share data.

It’s usually best to follow a planned API integration gradually. Slow and concise implementation is a great way to make transitions easily and with fewer errors. BUYER BEWARE! There are some API developers who will recommend a TMS or OMS system to make more money and to ensure that you need ongoing training and updates to maintain the systems.

The most common mistake that logistics companies make is that they overestimate their capabilities. For command centers, this usually means using API solutions that are more complex than needed. As a result, you face higher expenses for staff training and potentially more errors.

To avoid this all-too-common problem, following a plan of gradual API integration is typically the best advice. A slow and concise implementation is the best way to ensure a smooth transition and fewer mistakes.

The autonomous trucking supply chain trend cannot exist without one basic feature: data. In March 2020, Starsky Robotics arranged the closure of its autonomous vehicle business units. Stefan Seltz-Axmacher, CEO, said “the main reason isn’t the low demand of a trend but a difficulty of great investments necessity and a lot of safety issues.”

Xeneta, an ocean and air freight rating platform, defines Big Data as a “piece of standard (transportation costs and scheduled arrival times) and extended additional information (changeable data, e.g., GPS alerts or RFID metrics).” They treat big data as extremely important for decision-making in freight transportation. Key use cases of freight big data are analytics for shipowners, data engineering, vessel performance management, and fleet situational management.

Here are some key application areas for big data:

• The ability to provide the most economical way of delivery for clients. The more information variables will be available both for the carrier and for the shipowners (ETA, vessel specification, market information, load size), the more easily they arrange the best freight transportation deal. AIS (automatic identification system) is utilized to unite and integrate big data.
• Improvements to SC operations. Big data processing can help choose the optimum operational mode: truck speed, fuel consumption, route planning.
• Obtaining references from the entities (inspectors, terminals, port authorities) to keep track of the vehicle state throughout the supply chain.

Interesting Fact

TuSimple autonomous technology believes we’ll see autonomous trucks on the roads by 2024, but now it’s just a technology system of danger avoidance able to depict the situation 360 degrees around the vehicle and 1000 meters forward to prevent danger. To recap, human-free trucking is a concept comprising AI and ML data processing and analyses for more safety and business efficiency.

In Global Trade Magazine observations show that the idea of “elastic logistics” is clearly of high importance throughout the new world of supply chain technologies. Thanks to the vibrant and flexible characteristics of conducting business in the tech environment, it’s possible to mix the technologies used to meet your companies’ initiatives of upscaling or downscaling while still taking into account volatile market demands.

The technologies addressed in this paper can be helpful to successfully customizing your supply chain solutions. Starting from tracking operations to warehouse management, and ending up with a sustainably organized product supply to disintermediate shippers. Seeing the “whole picture” of your business prior to setting goals and picking certain high-tech tools can be extremely effective when outsourcing custom software development.

To undergo digital transformation shifts successfully, stakeholders should pay attention to all the core elements of the process: understanding customer needs, a clear vision of transformational strategy, knowing the list of the processes demanding to digitize, and having tools for performance management.

To follow digital transformation with great accuracy, it’s critically important to develop the right digital strategy considering all your business needs, specify a step-by-step roadmap, and choose the proper solutions you’re going to utilize for substantial digital shifts. And only then are you able to experience the best benefits of adopting digital models like the example below.

All digital transformation trends should be implemented via a precisely designed roadmap comprising:

• Vision of the company digital infrastructure
• Retraining and education of the staff
• Deep cross-organizational communication change
• Shift to the agile manner of operations delivery

Once you make the decision to go digital and transform your supply network, you’re encouraged to ask more questions! Innovecs experts can consult you on your digital strategy design and customized solutions.