Are you preparing to maintain your employability in the supply chain for the next 5 to 10 years? This example alerts you to digital transformations in a distribution centre. But the impact will be on all supply chain areas.

 

I slept for five years. I woke up in 2025 and went to visit that distribution centre of a food industry located in the metropolitan region of So Paulo. In these five years, the team reduced from 428 people to 126, and the volume embarked multiplied by three. I did the math = productivity increased more than ten times.

These are some of the changes:

1. In access control of people, vehicles and loads, the old team of four employees per shift now has only one operator. The company is part of a federated blockchain network with its suppliers. Transactions no longer depend on paper - it's all in the cloud.A deep learning algorithm reads the signs, recognizes the faces of drivers, and authorizes access to the site. The same system makes facial recognition of employees - not only in the access to the site but also at the entrance of the restaurant, areas of high-value items, administrative areas. You don't see any more security guards.

2. The separation process has also changed. The machine learning model implemented three years earlier produced a predictive model capable of predicting with 98% accuracy the profile (item and quantity) of orders that will arrive tomorrow and with 85% accuracy the profile of orders for the day after tomorrow.

With this team of separators acts with the regular workload during the night shift, avoiding peaks of activity concentrated in short periods. Consequently, there was a sharp reduction in the number of people.

3. The separation process has become much more agile with augmented reality equipment. The hand-free concept allows for increased productivity in tasks where tabs chat (voice) with WMS. The iteration is constant because the system now has cognitive abilities and listens to the operator, interprets his sentences and responds promptly. For example, in the case of a faulty product, the operator asks the system "what to do" and promptly receives guidance - remember the J.A.R.V.I.S., the iron man?

 

4. From the control room, the warehouse manager interacts with a hologram produced by the virtual reality system that captures product data and locations via sensors that transmit information online through the cloud (IoT - Internet of Things)to give visibility of people, equipment, movements, etc.

 

5. Other machine learningapplications have allowed continuous layout improvement, review of receiving, warehousing, separation and shipping processes that have produced new productivity gains.

6. The conference of assembled orders is no longer necessary as the separation process already integrates into detail the order data, separate product, docks and loading vehicles. Pre-boarding conference activity has become obsolete.

7. There is also no longer the team that allocates orders and volumes to vehicles. Another set of deep learning algorithms has already trained and tested the big data originated from omnichannel retail operations well enough and now plans vehicles and routes to perfection.

8. The team that made contact with the carriers is no longer there - a second federated blockchain environment (or via consortium) integrates the order data with the activation of vehicles. On the blockchain run two complementary systems: the smart contractand the predictive fleet system.

9. With the predictive fleet system, the supplier is notified 24 hours in advance about the type of vehicle, time and dock were to make its assets available. Fleet availability checking is automatic via systemic integration. If a carrier does not have vehicles to meet future demand, a deep learning subroutinedoes a multistage search for active links available from sensors in the fleet of logistics providers federated on the blockchain.

10. The functionalities parameterized in the smart contract,also with predictive add-ins,integrate the entire flow of accounts payable to carriers and link to the performance criteria agreed in the contracts, apply penalty and bonuses automatically. In case of doubt, the system consults the clauses of the service contracts and arbitrates the fairest decision for all parties..

11. As I passed through the forklift maintenance area, I saw the 3D printing of a part that would serve to replace a damaged one. Printing took place in 12 minutes, and the forklift was inoperative for only 23 minutes.

12. Today the company for a monthly membership fee of US$ 80.00 and is part of a digital platform that allows 3D printing of more than 10,000 pieces for different applications here in the distribution centre. With this, the maintenance costs reduced.

13. As the company implemented a cognitive intelligence model that combines dozens of demand forecasting methods,forecast accuracy rose from 72% to 93%. The quality of the stock increased, and the quantity decreased by 43%. Less inventory requires less space, which makes processes faster, requiring even fewer people, which increases (again) productivity!

14. And there are no more expedition peaks. The integration of data captured at points of sale, transferred via IoT to another blockchain,made up of companies in the food sector, allows a uniform flow of replacement - with this there are no more overtime, time banking, or idle resources in the off periods.

15. No more whiteboards with performance indicators scribbled with a pen or with sheets printed on them glued together. The descriptive and diagnostic analyticalsystem produces online indicators with different particle sizes, varied time cutouts, and accessible by each employee directly on their mobile phones. Each can customize the indicators in the way they see fit and share their insights with their peers.

16. Many other points have changed, nor have I spoken of robots, automated processes via RPA, the transformation of ERPs  

Questions for this assignment

 

(A1) Reflect on the article you have just read and identify other applications for the tech solutions presented.