Post Date : June 28, 2021
The word “cognitive” comes from the Greek word for “knowledge” (gnosis). Significantly, it has a “co” in the front, implying the notion of collaboration. In our current age of information, knowledge is most powerful when shared between multiple parties (objects) to arrive at good decisions.
There is plenty of room for improvement in making those decisions. We need a cognitive approach when it comes to logistics & supply-chain optimization. If we get it right, there is an opportunity to transform the business. If we embrace the revolutionary possibilities presented by developments in artificial intelligence (AI) and machine learning, we can anticipate problems and manage disruptions before they even occur.
What is Cognitive Logistics?
Logistics is not at all a new term or jargon in today’s era. We have been operating, storing, and transporting the goods since ages. What is new, is basically the enormous data, information, insights, and experience from operating globally and across modalities. We have been able to transform the logistics by freeing it from legacy data systems, manual document handling and poor visibility. Cognitive Logistics is a holistic combination of Art & Science; a coupled framework of people, process and technology influenced by external and internal stakeholders, environment.
During this pandemic, we have witnessed once again that Logistics proves to be the backbone of the economy. The real heroes are the drivers (truck, trailers, van, train, planes etc), last-mile delivery executives, warehouse champions who are working day and night to ensure that all of us would receive the essential items in a well stipulated time. What makes it possible? We have not realised because our forefront players are busy delivering and fulfilling the requirements. With the experience of same-day shipping, real-time problem resolution, and the new normal in consumer interactions is the speed with agility. Accomplishing it requires organizations to create cognitive supply chains that augment human capabilities with advanced technology and analytics. We have come miles forward in terms of technology, automation, digitization, and transformation (real-time tracking, driverless port cargo operations, route optimization, supply chain modelling etc).
Key enablers of Cognitive Logistics
The beauty of Logistics lies in its flexibility, agility, and responsiveness. The supply chain model (for ex. Hyperlocal market, in case of retail and customer centric and bespoke in B2B) and reflexes of the logistics are the key success factors.
Following are the factors propel to a cognitive logistics and supply chain:
|Logistics Operating Models||Resource Skill Sets||Process Centric – Digital Technology|
| 1. Shift from traditional transactional model to hybrid model|
2. Hybrid Model – Global Business Services Model: Global, Regional and Local to boost service and cash inflows.
| 1. Paradigm shift from functional expertise to functional plus digital expertise|
2. Programme transformation and management approach
| 1. Forward and backward integration|
2. Collaboration between Commercial and Operational side (KPI’s)
3. Structured data with cognitive analytics and automation (IoT etc)
Unlike transactional logistics, a cognitive logistics will be a digitally led, yet process-centric – as opposed to being merely digitally enabled. This new model (commercial + operational) is evolving, as digital technologies with embedded analytics converge to capture, store, process, and share data. Scalable, more flexible operating models as well as new skill sets are natural enablers of this evolution.
Why Cognitive Logistics
The key pillars on which logistic success lies are – Agility, Visibility, Responsiveness, Customer Delight and Cost effectivities. To achieve these organisations are working largely on cost savings and process improvement initiatives. This broadly includes process mining, automation, reducing carbon footprints projects and many more. All these led to sustainable model readiness towards next gen logistics and supply chain. The cognitive (self-learning) logistics framework is based on the Cognitive Logistic Object (CLO) concept which represent any entity involved in logistic operations augmented with cognitive capabilities. These are also enriched with social-like (behavioural) capabilities and therefore, CLO builds on the Social Internet of Things (SIoT) concept. Such capabilities allow the seamless ad-hoc interaction between logistic entities even if managed by different operators.
- Outcome driven model and framework – It can reduce the order-to-ship cycle time from three days to less than a day, for example. By contrast, transactional supply chains might just concentrate on cost-cutting. This club’s cost-cutting with meeting SLA (OTIF etc)
- Collaborated and connected model – allowing suppliers, customers, third-party manufacturers, and logistics providers to collaborate in real-time to purchase, produce, and move exactly what the end consumer needs.
- Smart & Intelligent Logistics – with embedded business logic for end-to-end optimization and decision making, as opposed to local optimization. As an example, deployment recommendations will not just consider demand-side priorities, but also costs (transportation and penalty cost) and capacity (warehouse and transportation).
- Bull Whip Reduction – It proactively responds to real-time demand signals from points of sale so the business can change short-term forecasts, marketing campaigns, or production schedules.
This article has been authored by Vibhore Khandelwal, Manager – Strategic Sourcing and Category Management, Liberty Steel Group.
Note: This is an abridged version of the original article that was published in the June issue of the Logistics Insider Magazine. To access the full article, get your e-copy of the magazine now!