73% of logistics companies have reported investing in IoT from 2017 onwards. 63% of companies report to continue investing in the future as well (Source: PwC CEO Survey 2018)
Forecasts of the logistics market generally list the 5 key drivers of change that will shape our future. Identifying these drivers of change will help companies target short and long-term investments and develop e-business.
The five key drivers of change are digitalisation, strong growth in global trade, leveraging learning software, in-market restructuring, and increased automation. This blog series addresses these forces in more detail. My third topic is the use of learning software to improve competitiveness; While the main trends are described in the charts on this blog, the article itself focuses on giving a more general picture of them.
Supply Chain Management Information System
As the digital economy expands, the manual processes of the pre-Internet era will disappear from storage. According to market research, they will be replaced by learning and specialized systems that can be integrated with traditional business management systems. The value of the software-driven transportation market is expected to exceed $ 70 billion by 2022. The market value of robotics and process automation will exceed $ 1 billion in late 2020. The proactive service and maintenance market is growing at 35% per year.
The fastest short-term growth is international e-commerce, which is estimated by most to grow by about 40% a year. Under the pressure of global competition, traders are looking for a competitive advantage by relying on their store network already close to consumers; 78% of companies consider delivery on the order date to be an important service element for them in the future.
Utilizing Different Types of Software Solutions in Logistics and Trade (Source: Zebra 2019)
Success in multichannel commerce requires new types of learning supply chain management information systems that integrate factories, hauliers, and merchants into the same supply chain. Old roles are blurred as service levels and profitability are further developed in such an ecosystem. Utilization of the store network as a delivery point for online orders is becoming more common; in-store collection is increasingly using wearable technology and voice control to increase efficiency. Traditional logistics operators are starting to provide product management services - outsourcing of product return processing is already on the rise. The factories are starting to order and deliver their products directly to consumers. Last mile deliveries start using new channels and operators; the use of autonomous transport technologies is increasing.
The general legality of information systems is that as flexibility and dynamism increase, control becomes weaker. A new type of learning is required to ensure manageability. Data analysis can ensure that the right products are on the right track at the right time in the supply chain, IoT can deliver better transparency and offset management to the supply chain, and machine learning is already adapting human resources and human resources to meet expected capacity requirements.
Consumer buying behavior is becoming smartphone driven. When purchasing is no longer committed to space and time, underlying supply chains need to adapt to more demanding, multi-channel service models.
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