Read Part 1 here.
Q&A Part 2
JW: What are the main supply chain flows that supply chain executives should look to address?
JJ: Traditionally, there are three main supply chain flows that benefit from automation:
- Physical flow (flow of goods from, e.g., from a DC to a retailer, the most visible and tangible flow) – some more obvious than others, such as parcels delivered to your door or raw materials arriving at a plant. To address these issues, the industry is getting ready (or is ready) to adopt drones, automated trucking, and automated guided vehicles (AGV). But to achieve true end-to-end physical delivery, major infrastructure and regulatory changes are yet to happen to fully unleash the potential of physical automation in this field. In the short-term, however, let’s not forget the critical paper flow associated with these flows of goods, such as a courier sending Bills of Lading to a given port on time for customs clearance and vessel departure, a procedure that often leads to unexpected delays
- Financial flow (flow of money) – here the industry is adopting new technologies to palliate common issues, e.g., interbanking communication in support of letters of credit
- Information flow (flow of information connecting systems and stakeholders alike and ensuring that relevant data is shared, ideally in real-time, between, e.g., a supplier, a manufacturer, and its end customers) – this is the information you share via email/spreadsheets or through a platform connecting you with your ecosystem partners. This flow is also a perfect candidate for automation, starting with a platform to break silos or for smaller transformation with tactical RPA deployments. More ambitious firms will also want to look into blockchain solutions to, for instance, transparently access information about their suppliers and ensure that they are compliant (directly connecting to the blockchain containing information provided by the certification institution such as ISO). While the need for drones and automated trucking/shipping is largely contingent on infrastructure changes, regulations, and incremental discoveries, the financial and information flows have reached a degree of maturity at scale that has already been generating significant quantifiable benefits for years.
JW: Can you give me examples of where Capgemini has deployed elements of an autonomous supply chain?
JJ: Capgemini has developed capabilities to help our clients not only design but also run their services following best-practice methodologies blending optimal competencies, location mix, and processes powered by intelligent automation, analytics, and world-renowned platforms. We have helped clients transform their processes, and we have run them from our centers of excellence/delivery centers to maximize productivity.
Two examples spring to mind:
Touchless planning for an international FMCG company:
Our client had maxed out their forecasting capabilities using standard ERP embedded forecasting modules. Capgemini leveraged our Demand Planning framework powered by intelligent automation and combined it with best-in-class machine learning platforms to increase the client’s forecasting accuracy and lower planning costs by over 25%, and this company is now moving to a touchless planning function.
Automated order validation and delivery note for an international chemical manufacturing company:
Our client was running fulfillment operations internally at a high operating cost and low productivity. Capgemini transformed the client’s operations and created a lean team in a cost-effective nearshore location. On top of this, we leveraged intelligent automation to create a touchless purchase/sales order to delivery note creation flow, checking that all required information is correct, and either raising exceptions or passing on the data further down the process to trigger the delivery of required goods.
JW: What are the key success factors for enterprises starting the journey to autonomous supply chains?
JJ: Moving to an autonomous supply chain is a major business and digital transformation, not a standalone technology play, and so corporate culture is highly important in terms of the enterprise being prepared to embrace significant change and disruption and to operate in an agile and dynamic manner.
To ensure business value, you also need a consistent and holistic methodology such as Capgemini’s Digital Global Enterprise Model, which combines Six Sigma-based optimization approaches with a five senses-driven automation model, a framework for the deployment of intelligent automation and analytics technology.
Also, a lot depends on the quality of the supply chain data. Enterprises need to get the data right and master their supply chain data because you can’t drive autonomy if the data is not readily available, up-to-date in real-time, consistent, and complete. Supply chain and logistics is not so much about moving physical goods; it's been about moving information for decades. A bit of automation here and there will not make your supply chain touchless and autonomous. It requires integration and consolidation first before you can aim for autonomy.
JW: And how should enterprises start to undertake the journey to autonomous supply chains?
JJ: The first step is to build the right level of skill and expertise within the supply chain personnel. Scaling too fast without considering the human factor will result in a massive mess and a dip in supply chain performance. Also, it is important to set a culture of continuous improvement and constant innovation, for example, by leveraging a digitally augmented workforce.
Secondly, the right approach is to make elements of the supply chain touchless. Autonomy will happen as a staged approach, not as a big bang. It’s a journey. Focus on high-impact areas first, enable quick wins, and start with prototyping. So, supply chain executives should identify those pockets of excellence that are close to being ready, or which can be made ready, to be made touchless, and where you can drive supply chain autonomy.
One approach to identifying the most appropriate initiatives is to plot them against two axes: the y-axis being the effort to get there and the x-axis being the impact that can be achieved. This will help identify pockets of value that can be addressed relatively quickly, harvesting some quick wins first. As you progress down this journey, further technologies may mature that allow you to address the last pieces of the puzzle and get to an extensively autonomous supply chain.
JW: Which technologies should supply chain executives be considering to underpin their autonomous supply chains in the future?
JJ: Beyond fundamental technologies such as RPA, machine learning has considerable potential to help, for example, in demand planning to increase accuracy, and in fulfillment to connect interaction and decision-making.
Technologies now exist that can, for example, both recognize and interpret the text in an email and automatically respond and send all the information required; for example, for order processing, populating orders automatically, with the order validated against inventory and with delivery prioritized according to corporate rules – and all this without human intervention. This can potentially be extended further with automated carrier bookings against rules. Of course, this largely applies to the “happy flows” at the moment, but there are also proven practices to increase the proportion of “happy orders”.
The level of autonomy in supply chain fulfillment can also be increased by using analytics to monitor supply chain fulfillment and predict potential exceptions and problems, then either automating mitigation or proposing next-best actions to supply chain decision-makers.
This is only the beginning, as AI and blockchain still have a long way to go to reach their potential. Companies that harness their power now and are prepared to scale will be the ones coming out on top.
JW: Thank you, Joerg. I’m sure our readers will find considerable food for thought here as they plan and undertake their journeys to autonomous supply chains.
Read Part 1 here.