Machine Learning. Artificial Intelligence. We hear these terms all the time, but it can be quite difficult to sort through the buzzwords and fluff (and there’s a lot of fluff) to determine if it’s an investment your business really needs to make. Let’s start off by talking about the costs. Apart from the software itself, you’ll have to potentially pay for third-party implementation services and licensing fees. This doesn’t even include the costs to retire any legacy systems, transfer data, training, and the loss of time from internal resources.
If your business is running fine without machine learning, you might be asking, “Why do I need to even make such a daunting investment when everything is fine as it is?”. I’m sure you said the same thing when you had a flip phone and smart phones first started entering the market. I’m sure blockbuster said the same thing before Netflix. Although these comparisons can be helpful, you still want the facts and the numbers. That makes perfect sense considering the level of investment something like machine learning would be for your business.
I recently came across an article by Forrester which evaluated the financial and organizational benefits of machine learning experienced by several companies utilizing SAP products. This article separates itself from others because it shares the quantified benefits that these companies received, not just random buzzwords. If you want to take a deeper look at it, you can check it out here. If you want to read it, you’ll have to put in some basic info like your email. However, if you’re someone who wants to learn more about the financial outcomes of implementing machine learning, this is a great article to get started.
The Age of Machine Learning is Upon Us
Machine Learning is here and here to stay. According to the article, “62% of global business and technology leaders are implementing or expanding their implementation of machine learning today, and another 24% plan to implement it in the next 12 months”. Machine learning is no longer something you can ignore and I’m sure your competitors aren’t ignoring it either.
One of the examples the article highlights is from an American energy provider and it’s call center. Machine Learning provided the employees with increased certainty in to why exactly each specific customer was calling. This significantly reduced the number of calls that were actually reaching the contact center. A Service delivery manager shared:
“And out of the 16 million calls we get, we’re hovering around 1 to 1.2 million calls in a year that we would have effectively reduced. That’s a significant chunk of change, close to $2.4 million in savings.”
As he said, that’s a significant chunk of change. At a total cost of 2 dollars per call, reducing the amount of calls that make it to the call center is a necessity. What about the less quantifiable benefits of machine learning in this use case? Higher employee satisfaction, efficiency, and higher customer satisfaction.
In a more advanced use case of machine learning, the same American energy firm utilized machine learning to predict customer intention and recommend products and actions to customers. Before machine learning and predictive analysis, around 5% of calls resulted in a sale. After implementing predictive analytics, sales doubled with over 60% of new sales being attributed to predictive analytics. If you’re in a position where your competitor knows exactly what the customer needs and when they’ll need it, you’re going to be at a massive disadvantage. Of course you can make assumptions like those yourself without the use of machine learning, but how long will that take you? How many resources are you investing to find information that your competitors are deriving in seconds?
If your still on the fence about machine learning and if it’s necessary for your company, I really recommend checking out the full article. Later in the week, I plan to write another blog post on some of the key challenges the interviewed companies were facing and some of the key results that machine learning provided them. If you’re interested in that I recommend you check back on Thursday! If you’re someone who’s interested in learning more or you have a specific question about your own business, I’d recommend dropping it here. You’ll be able to find answers from other people involved in SMBs just like yourself.
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Is machine learning really as important to SMB’s as most articles tend to argue? Let me know your thoughts below!