Delivering Digital Technology to the Supply Chain – LogiSYM September 2019

[vc_single_image image=”10760″ img_size=”large” qode_css_animation=””]With recent advances in new technology, the promise for supply chain transformation can now be realised. The combination of technology to track, monitor, analyse and suggest is enabling the management of supply chains to change fundamentally. With ever greater complexity across the supply chain, this advance in technology is necessary, whether it is supporting personalisation, immediate delivery, or new business models such as product as a service. This move to digitally transform has moved from a technology discussion to a business discussion, as the amount of money being invested in these areas demonstrates.


Digital Transformation is not a single technology

Digital transformation is not a single technology, but a combination of multiple technologies. The fundamentals of cloud, analytics, social and mobile are being enhanced by what we term innovation accelerators – these being Robotics, Augmented Reality / Virtual Reality (AR/VR), Internet of Things (IoT), Artificial Intelligence (AI), Additive Manufacturing and Next Generation Security. It is when these technologies are combined that we see the real benefits of moving to digital. These technologies are maturing at a rapid rate, and are now being seen across many enterprises, deployed, at scale across the entire supply chain.

If we look at technology spend for digital transformation, what is crucial to understand is that the focus is not on a particular technology, but on a group of technologies that are implemented together to deliver an effective business change. Whilst digital transformation (known as DX) is impacting all industires, it is manufacturing that is spending the most, both across the shop floor, but also across the supply chain. In 2019 IDC predicts that discrete manufacturing spend will be $221.6 billion and process manufacturing $124.5 billion. For both industries, the top DX spending priority is smart manufacturing, supported by significant investments in autonomic operations, manufacturing operations, and quality. The DX use cases – discretely funded efforts that support a program objective – that will see the largest investment across all industries in 2019 will be autonomic operations ($52 billion), robotic manufacturing ($45 billion), freight management ($41 billion), and root cause ($35 billion).


Start with data

Fundamentally the digital transformation of the supply chain starts from data. The promise of delivering data driven decision-making is now a reality, as real time visibility to the location and state of materials across the supply chain can be seen. This in turn can be used to optimise the supply chain through simulation models, and contribute to creating the digital twin of the supply chain. The creation of a digital twin of the supply chain process has been set as an “end goal” for many organisations as they go through their digital transformation exercise. Why the end goal?, because a digital twin requires data from every part of the process, and a model created that mimics the actual process – once you have the digital twin in place, then true optimisation can be applied, in addition to the use of advanced analytics / machine learning / artificial intelligence to moved from what has happened, and what is happening, to what will happen. The digital twin represents the end state as all data, and all models of the process are in place.

The business case for digital is also very real. From analysis of the financial performance (Figure 1) of 400 global manufacturing organisations, these organisations were split into digitally mature, digitally determined, or non-digital. Their financial performance was measured in an index going back to 2013, and what can be seen is a clear business improvement in both profit and revenue compared to their semi-digital and non-digital competitors over the last 5 years.


Applying this to supply chains

Looking specifically at the supply chain. The focus of the digital supply chain is the convergence of multiple data sources, effective analytics and automated decision support.

This in turn supports the entire end to end supply chain, coupled with the flow of materials, money and information.

Getting into the specific areas of change we see three key themes, which contain a number of specific “digital” use cases.

Some of these are the application of digital technologies to existing business processes, and some are “new” and cut across traditional business processes, taking full advantage of the new technology:

Capabilities based procurement
– Sourcing intelligence
– Digital supply base management
– Supplier network monitoring
– Vendor engagement
– Automated kanban

Extended Planning
– Demand and consumption signal intelligence
– Real time demand matching
– Extended S&OP
– Integrated supply chain
– Thinking supply chain
– Inventory intelligence

Logistics Automation
– Smart warehousing
– Transportation optimisation
– Global trade automation


These specific projects are the ones that we predict that are going to be able to be implemented based on the new digital technologies. However, these will also require a timeline to be implemented. As a guide these can be looked at across three time horizons:



IoT and Analytics are key foundational technologies

Key technologies to focus on for the immediate focus are IoT and analytics. Every project starts with the data, so being able to gather data is key. The IoT project should also consider the communication network, storage and security in gathering, and sharing the data. Coupled with this is the focus on analytics. With ever increasing complexity, the need to be able to visualise the data is key.

So developing key skills in business intelligence and analytics will be essential. Once this has been mastered then progress can be made towards the application of AI and machine learning which will start to be realised in the midterm and long term focus.

The promise of digital technology is clear, however we do see many organisations struggling to move forward and implement at scale, Keys issues that need to be addressed are:

  • No integrated roadmap. Very often business and IT have their own plan for deployment of technology with neither talking to the other.
  • Establishing the ROI for the project. The challenge of rethinking the business process to fully integrated the new technology is essential. The business process should be reimagined incorporating the new technology and the return on investment measurements be adjusted to account for new metrics, such as customer engagement.
  • Skills. With new technology the challenge of having skills in-house is complex, consider the longer term and think about whether to develop skill in-house or move forward with a partner who can provide the skills.
  • Security. Security is paramount. With a digital supply chain collecting data across multiple sources outside of the enterprise, bringing the data back into critical systems needs to be secure. Do not skimp on the budget on security.
  • Scale. When starting the exercise through proof of concepts (POC), ensure that there is the infrastructure to scale the POC across the enterprise, with minimal extra investment.


Addressing these key issues and identifying the solutions to your outcomes, as a series of connected technologies, rather than just one, will give you a path forward in what can be appear to an overwhelming area.

Adoption of game-changing technologies by competing organisations and supply chains has already started to change the playing field. It is now time for organisations – large and small – to get serious about their supply chain digital transformation, because your competition is.Chris Holmes
Chris Holmes is Managing Director for IDC Insights Asia/Pacific responsible for leading the Retail, Energy, Manufacturing, Health, Government, Telecommunications, and IT Spending groups. He is responsible for setting the direction of the research and managing the delivery teams. His research focuses on industry transformation, the application of new technologies to enhance business processes, and cross-industry learning.

Prior to joining IDC, Dr. Holmes worked at the Singapore Institute of Manufacturing Technology (SIMTech). Here, he pioneered the use of technology road mapping across Singapore, working with start-ups to multinationals, to help companies match their business needs with technology. Before relocating to Singapore, he worked in the aerospace sector in the United Kingdom and focused on process efficiencies.

– Doctor of Engineering degree from Warwick University, United Kingdom completed while working for the Warwick Manufacturing Group (WMG)
– Master of Philosophy degree from the University of Glamorgan (currently University of South Wales), United Kingdom
– Frequent keynote speaker at industry conferences[vc_single_image image=”9766″ img_size=”200×200″ qode_css_animation=””][vc_single_image image=”10729″ img_size=”medium” qode_css_animation=””][ult_layout layout_style=”4″ list_style=”6″ s_image=”0″ s_excerpt=”0″ s_categories=”0″ s_metas_o=”0″ s_metas_t=”0″ quick_view=”0″ taxonomies=”post_tag” price_font_weight=”” atcb_font_weight=”” title_font_weight=”normal” title_font_style=”normal” title_text_transform=”capitalize” metas_font_weight=”” excerpt_font_weight=”” filter_font_weight=”” tab_font_weight=”” pagination_font_weight=”” d_i_filter=”219″ title_font=”Lato” title_font_size=”12pt”]