The Essentials of Process Digitization Excellence

Process digitization is the key to creating a Live Business – a business able to coordinate multiple functions in order to respond to and even anticipate customer demand at any moment.


Making Room Where There Isn’t Any


The number of containers that go through the Port of Hamburg is expected to reach 18 million over the next decade from 9 million today – but there’s no room to build new roads in the center of Hamburg.





Instead, the port uses a combination of sensors, telematics systems, smart algorithms, and cloud data processing to feed real-time information through mobile apps to truck drivers. The apps tell drivers exactly when ships are ready to drop off or receive containers and optimizes their routes so the port can handle the added traffic without disrupting the city.

Source: “Port Stars: How Hamburg Is Tapping Tablets and Telematics to Tame Truck Traffic” (ZDNet, March 17, 2015).



Process Digitization Creates a Live Business

The technologies used by the port make digitizing all kinds of business processes possible, which is key to creating a Live Business – a business able to coordinate multiple functions in order to respond to and even anticipate customer demand at any moment.



Two Kinds of Algorithms Drive Process Digitization


Edge Algorithms

Edge algorithms operate at the point where customers or other users interact directly with a sensor, application, or Internet-enabled device. These 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.

Server-level Algorithms

Server-level algorithms 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 assess how creditworthy an individual is, but they also explain why a score is low or high, what factors went into calculating it, and how an applicant can raise the score in the future.




You Need a Process Model

Whenever the results of a predictive model start to drift significantly from expectations, it’s time examine the model. You need to determine whether you should dump old data that no longer reflects your customer base, add a new product or subtract a defunct one, or include new variables, such as marital status or length of customer relationship, that further refine your results.



Models Require Constant Care

Successfully digitizing a business process requires building a model of the business process based on existing data. For example, a bank’s customer records expand to include more data as the relationship develops. Predictive analytics can then extrapolate from the data what customers might do next, such as the likelihood that someone will apply for a mortgage in the next year.



Data Shouldn’t Be Perfect

While some of us retain the perfect penmanship we learned in grade school, most of us let our skills devolve to embarrassing levels. Therefore, to train an optical character recognition system to recognize and read handwriting in real time, your samples of block printing and cursive writing data stores also have to include sloppy scrawls so the system can learn to decode them.



Digital Processes Are Only as Good as They’re Designed to Be

Digitizing business processes doesn’t eliminate the possibility of mistakes and problems, but it does ensure that those mistakes and problems are easy to spot and fix.



download arrowTo learn more about how to digitize your business processes, read the in-depth report Unlock Your Digital Super Powers.


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