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Improve Business Productivity with Machine Learning


Do you remember the first time you saw a picture of a cat?

You were probably a baby, and it’s likely that you didn’t comprehend that what you were looking at was a cat. But then days and years went by, and during that time you saw many more pictures of cats, and maybe even a few real cats. You saw a lot of things that you were told weren’t cats. And one day, without being prompted, you saw a picture of a cat and thought, “That’s a cat!”

The thought process that your brain went through to successfully identify a cat is exactly the way machine learning works. With machine learning, advanced algorithms are trained – meaning they are fed vast amounts of data that has been labeled or otherwise identified – until they can begin to independently learn, identify, and predict.

As computers become increasingly capable of learning freely, reasoning, and determining the best course-of-action in real time, businesses stand to reap the rewards.

When computers first made their way into the enterprise, it radically changed everything about the way business was conducted. With machine learning, we’re now on the cusp of yet another revolution, one where computers will begin to not only augment human processes, but command them.

Machine Learning - HPE.jpg

Machine learning, which falls under the umbrella of artificial intelligence (AI), has advanced rapidly over the years and become even more accessible for businesses to adopt. Algorithms that once required time-intensive training and deep knowledge from an expert require only primitive labeling now. Machines can learn features independently, and in many cases more accurately, as greater amounts of data are introduced to the model.

While machine learning is still in an early adoption phase among enterprises, there are many ways these technologies can be used to directly impact business productivity.

Improve sales and marketing

Data from customer profiles, such as browsing activity, recent purchases, or personal details, can be used to predict the uptake of a new product or service, and forecast which products a specific customer is most likely to buy. Refining sales and marketing efforts might be the most commonly-used current application of machine learning in the enterprise, with at least 40 percent of companies indicating in a recent survey that they are already using machine learning to improve sales and marketing performance.

Boost customer satisfaction and loyalty

Machine learning algorithms can also help enhance the customer experience and deepen consumer loyalty. For example, contact centers can use machine learning techniques to route incoming calls to the right representative more quickly, helping to reduce call durations and increase the incidence of first-call resolutions. And companies like Netflix and Amazon are experts at using predictive algorithms to deliver content or recommend products that they know a specific customer will enjoy, helping to boost customer satisfaction and loyalty.

Increase employee safety

Particularly in dangerous environments such as a power plant or an offshore drilling rig, using every tool to ensure employee safety is paramount. Predictive analytics can monitor equipment health in real-time and foreshadow malfunctions or failures that might put employees at risk. Machine learning algorithms can also be trained to pore over historical data to understand which factors may have led to catastrophic safety events, or identify employee segments that are at the highest risk.

Streamline operational processes

Perhaps the largest opportunity to boost productivity with machine learning is the potential to streamline operational processes across the board. Machine learning models incorporating data from all aspects of the business can hold the key to automating entire processes and workflows. Sometimes referred to as intelligent automation, machine learning systems can incorporate both historical datasets and streaming data from things like sensors to streamline everything from quality assurance to compliance.

A recent study conducted by Harvard Business Review uncovered five common business processes that had been noticeably improved by machine techniques. The chart below demonstrates that a number of machine learning techniques can be used to improve a variety of businesses processes, with the same technique sometimes being used to improve multiple processes:



What Type of Machine Learning is Being Used for Which Business Processes.jpg

Source: Harvard Business Review, February 2016

As machine learning applications continue to proliferate and these technologies become more accessible at the enterprise level, businesses across a variety of verticals will be positioned to achieve new levels of productivity and efficiency. We’ve only just begun to understand the true potential of machine learning in the enterprise – be sure to follow me on Twitter @Bill_Mannel to stay up-to-date on all of the latest innovations! 

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About the Author


As the Vice President and General Manager of HPC and AI Segment Solutions in the Data Center Infrastructure Group, I lead worldwide business and portfolio strategy and execution for the fastest growing market segments in HPE’s Data Center Infrastructure Group which includes the recent SGI acquisition and the HPE Apollo portfolio.

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