How the Port of Hamburg Doubled Capacity with Digitization

How the Port of Hamburg Doubled Capacity with Digitization

How Process Digitization Makes the Impossible Possible The Port of Hamburg has no room to expand, yet container traffic is expected to more than double in the next 10 years to reach 18 million containers by 2025. The port uses a combination of sensors, telematics systems, smart algorithms, and cloud data processing to feed real-time mobile apps that tell truck drivers exactly when to drop off or receive containers. The app optimizes the drivers routes so the port can grow its capacity without growing its footprint. Here are SIX WAYS to follow the port's lead. Source: Sara Zaske, Port stars: How Hamburg is tapping tablets and telematics to tame truck traffic ZDNet, March 17, 2015

1. Use Process Digitization to Become a Live Business Technologies used by the Port of Hamburg make it possible to digitize many business processes, which is key to creating a Live Business one that can coordinate multiple functions to respond to and even anticipate customer demand at any moment.

2. You Need Two Kinds of Algorithms to Drive Process Digitization 1. Edge algorithms, such as speech or image recognition, make decisions based primarily on their ability to interpret input with precision and then deliver a result in real time.

2. You Need Two Kinds of Algorithms to Drive Process Digitization 2. Gather data from edge algorithms and report on both the results of data analysis and the analytical process itself. For example, the complex systems that generate credit scores also tell applicants how they can raise their score in the future.

3. Create a Process Data Model Successfully digitizing a business process requires you to build a model of the business process based on existing data. For example, a bank can use predictive analytics to try to determine what existing customers might do next.

4. Don t Take Your Eye Off the Model When the results of a predictive model start to drift significantly from expectations, it's time to examine the model. You need to determine whether you should dump old data or include new variables, such as marital status, that further refine your results.

5. Perfect Data Will Ruin the Model Data shouldn t always be perfect. For example, to train an optical character recognition system to recognize and read handwriting in real time, your samples need to include sloppy scrawls so the system can learn to decode them.

6. Keep the Humans in the Room When machines are talking to each other, humans only slow things down. In human-facing interactions, though, it's still best to digitize the part of the process that generates decisions, but to leave it to a human to check and finalize the decision.

There s more. To learn more about how to digitize your business processes, read the in-depth report Unlock Your Digital Superpowers.

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