What is machine learning and how is it used in a digital business solution? In this fast-paced video, Thomas Erl (best-selling author of “A Field Guide to Digital Transformation” and many other books) uses animation to explain how machine learning can be used to give businesses the ability to continually learn more about their existing customers, as well as insights as to how they can grow and attract new customers.
Machine learning is part of the field of data science. It introduces very powerful tools and technology that can carry out sophisticated and complex types of data analysis and can often do so almost instantly. But, as the name “machine learning” indicates, what’s really important about this type of data science technology is that it can actually learn. We are able to feed a machine learning system tons of historical data that then trains the system to better understand the nature of the data and to then better optimize how it interprets and analyzes the data for us. And, as time goes by, the machine learning system can continually be retrained to further improve what it does.
This then results in higher quality data intelligence that can be very insightful and really valuable to a digital business. So, for example, we can train our machine learning system with years and years of historical customer activity data. This provides a good starting point for it to give us some insights about customer behavior, preferences and activity patterns. These insights help us better understand how we can enhance the customer-centricity of our digital business solution to improve customer experiences and make it overall more effective.
Then, as we make these enhancements we also equip our digital business solution to collect more data about how our customers interact with us. This, in turn, increases the scope and volume of data we can use to retrain our machine learning system to provide us with better and better customer data intelligence. A machine learning system can get to a point where it knows individual customers so well that it can predict the probability of how they may respond to new products we might release or how they might react under certain circumstances.
Machine learning systems really do help us create high-end data intelligence. For many digital businesses it is essential to use this technology because their competitors are already doing so. But be careful, because it is crucial that your team has the right skills to use machine learning in the right way. If it’s not designed and maintained properly, then things like data bias and inaccurate information can find their way into what is used to train your machine learning system. And, as you might have guessed, this will then result in “data intelligence” that is perceived as being correct, but is actually flawed and can then inadvertently steer your business into the wrong direction.
Machine learning can be challenging to introduce into a digital enterprise. But it’s a worthwhile and often necessary. With a qualified team building and governing your data and your data science environment, you can truly take advantage of what machine learning has to offer.
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▶️ Please subscribe: https://www.youtube.com/channel/UCMNVDTGTs8z5WoJpeEvlbXg
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▶️ Thomas Erl’s Digital Enterprise Newsletter: https://www.linkedin.com/newsletters/6909573501767028736/
▶️Thomas Erl’s Podcast Series: https://open.spotify.com/show/1YYsRLCxJQHBgOTUSMQnJ7
▶️Books by Thomas Erl: https://www.informit.com/authors/bio/f8d115ad-20cc-4d42-ad99-7e349d34f90d
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▶️Consulting: https://transformative.digital
▶️Courses: https://www.arcitura.com
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▶️Follow Thomas on LinkedIn: https://www.linkedin.com/in/thomaserl
▶️Contact Thomas: thomase@transformative.digital
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