Digitalisation can boost the supply chain tower in real time!: Scott Read, Head of Intralogistics at Siemens UK and Ireland

31 Oct 2019

Digitalisation can boost the supply chain tower in real time!

Scott Read, Siemens Digital Industries Head of Intralogistics Innovation UK


Supply Chain networks are now more complex than ever. This complexity is generally proportionate to the number of partners and geographies involved in getting a product from its point of origin to the end customer. To add to this milieu, there are legal jurisdictions set by industry regulators and governments.

With so many stakeholders, it becomes imperative that each of them remains connected and in continuous communication. The supply chain ecosystem is very advanced and digitalised, and we hear logistics experts talk about the supply chain ‘control’ tower. It is true that with new technologies we get a bird’s eye view of movement of products from vendor to customer and every other phase of its journey. However, there are certain areas that require further digitalisation in the supply chain management, and this is especially true for smaller businesses whose customers have the common demand of fast deliveries.

The complexity of the industry puts further pressure on businesses and the only way to efficiently overcome the hurdles is smart use of technology. Connecting the supply chain will enable logistics providers to handle management of the data, including planning, problem forecasting, improving delivery reliability and ensuring intelligent handling of shipments. By managing the entire supply chain, providers can combine shipments directly helping reduce carbon footprint. There is a disconnect between data and decision making; digitalisation will help the management to act in real time, which is crucial to this business.

To achieve the best in class supply chain management, it is essential that companies have access to real time data. In this respect, IoT can enable intralogistics organisations to connect to their warehouses and depots and use the systems-generated data effectively. The captured data can help evaluate and add to the Overall Equipment Efficiency (OEE) allowing maximum performance, availability and quality of any automation machinery being used. Operations managers can assess the productivity of assets adding to the bottom line of profits.

For instance, cloud computing operating systems enable organisations to harness the wealth of data generated by the IOT with advanced analytics. Data analysts have the capability to collect information from all areas of the warehouses or depots and across networks to support management operations decisions. This not only increases visibility, but also creates key opportunities for collaboration across machines, and machines and humans. Data can be transformed into knowledge resulting in informed business choices.

Siemens IoT operating system, Mindsphere, is an example of this technology. There are many other aspects that these applications can help in, including predicting adverse weather and traffic congestion, thus managing the forward supply chain and front to end risk management along the transport chain. Such digital tools also help support the operational expenses (OPEX) of supply chain by managing usage of energy in real time, identifying areas where energy consumption can be reduced.


There is a huge range of other digital tools available to logistics companies, including 3D printing and RFIDs (radio-frequency identification). 3D printing has the potential to disrupt the supply chain by enabling warehouses to print 3D commodities and eliminating the need to have finished product stacked in warehouses. 3D printing could also be used to produce spare parts for assets on site.

Another digital tool that is most useful is Artificial Intelligence (AI). Algorithms allow the slightest of faults to be detected and collect data whether it is in the conveyor or the automatic retrieval machine. This data can then be applied to conduct predictive maintenance, saving a lot of delivery hours and money in downtime. Predictive maintenance enables a depot manager or warehouse manager to control and schedule maintenance of the defect, adding to efficiencies in the supply chain management.

Smart technology and devices have also made in-roads into the supply chain management industry, such as the IoT-enabled radio frequency identification (RFID) sensor tags and barcodes. Data collection through these technologies will drive growth, and adoption of these technologies by smaller players is imperative if they want to remain in the supply chain management business. These technologies will enhance the offering of supply chain management for managing inventories and reducing warehousing needs. This integration is expected to act as a competitive advantage for implementing supply chain analytics in reducing cost fluctuations by improving sourcing and logistics activities.

A report published by Media Watch earlier this year says that the global supply chain analytics market is expected to reach approximately US$8.89 billion by 2023, registering a 13.7 per cent CAGR during the period 2019-2023. This is an indicator of huge worth of data and its usage in supply chain management.

Supply chain management is not limited to retail and manufacturing sectors but is crossing many other industries including health care management where NHS patients rely on delivery of medicines to their homes or care centres.

However, lack of data privacy in public cloud deployment and monetary constraints among enterprise are likely to hinder the growth of supply chain analytics market during the forecast period.

 

 

Contact information

Paul Addison

PR and Government Affairs Manager

Siemens

07808 823 346

paul.addison@siemens.com

About Siemens