Machine learning: Extracting your strategy from your data

2018 is becoming the year where everyone is putting Artificial intelligence on their key strategy list. Because AI is a nebulous term, for many having an "AI Strategy" is demonstrated by a plan to roll out a chatbot to their customers. Don't get me wrong, chatbot technology is maturing fast and can bring great value when applied in the correct way, but many organizations are missing something big here.

Data science and machine learning, the tools and technology often associated to "AI", are more mature in many ways and can transform a business at a more fundamental level. There is an underutilized goldmine of data in every business that may be hiding the answers to some important questions. I'm talking about the unstructured and logging stores generated by the sales process - your mobile app, website and call centre - every minute of every day. At best this data ends up in a graph on a specific dashboard but most often it's simply stored and archived.

Organizations have started using machine learning as part of a data science program to put this data to work. Some proven ways of using the predictive power of historic data include:

• Predicting when systems and parts will fail enabling proactive maintenance.
• Identifying fraudulent transactions and clients
• Predicting the success of a product or item and highlighting which factors make particular products popular or unpopular
• Predicting the likelihood that a discount will help close a deal or which customers are thinking about abandoning your brand
• AI-driven logistics scheduling

So how does putting your data to work become ingrained in your strategy? It's about putting data at the heart of ...