What do spam detection, facial recognition, product recommendations and credit-card fraud detection have in common? They’re all processes becoming smarter by the second, thanks to machine learning.
Put simply, machine learning is what enables computers to gain intelligence over time and from experience. The software applies a set of rules to massive amounts of data and identifies patterns to make decisions and adapt based on what's uncovered. With machine learning, businesses can capitalize on information that would otherwise require an army of people to study, interpret and act on.
What is particularly exciting right now is that technologies from companies like BloomReach, Skytree and BigML have made machine-learning solutions readily accessible to organizations at a lower cost. Machine learning takes big data to the next step. Not only does the software do the analysis of massive data sets but it uses the patterns to change its processes in real time.
Businesses of all sizes, scopes and industries are quickly recognizing that machine learning is a valuable and attainable technology for their organizations -- something that could help them gain a significant competitive edge. Here are just three advantages businesses can tap into with machine learning:
1. Predict the future.
The human brain is great, but it can process only so much information at once -- and is prone to error. Machine-learning programs can combine tons of disparate information sources to make instant decisions based on millions of individual data points, helping to ensure that nothing is overlooked.
Consider what it takes to select a health insurance plan: the comparing and interpreting of benefits, policies and provider networks.
I worked with a health insurance client that wanted to partially automate its process for recommending a personalized plan for each unique customer.
Done manually, the process is slow, tedious and prone to oversights that could cost individuals thousands of dollars or hurt the quality of their care. But machine learning not only made this process feasible but optimal. The system could access all the data sources necessary to deliver actionable, accurate insights in a blink of an eye and then deliver confident recommendations in a fraction of the time and cost of hiring call-center support staff.
2. Be proactive.
Driven by machine-learning systems, even the smallest of businesses can do the work of giant corporations, leveraging reams of untapped data to boost performance. According to a report on disruptive technologies from the McKinsey Global Institute, advances in artificial intelligence, machine learning and user interfaces like voice recognition are automating knowledge-worker tasks once deemed impossible for machines to tackle.
For example, a process that once took a knowledge worker days or even weeks to complete, such as predicting the inventory needs of a chain of grocery stores or identifying the heart failure likelihood in hospital patients, can now be performed in moments.
This is less about replacing knowledge workers than it is about augmenting their abilities. Instead of spending weeks and valuable resources trying to gather and crunch data to support a project, employees can put a machine to work for them, accessing insights in seconds and returning their focus to moving the business forward.
3. Be personal.
Recommending the right product to the right person at the right time is an ongoing challenge for many businesses. But machine learning takes the guessing game out of the equation, predicting which products and services customers may want based on prior preferences and actions.
In addition to making smart and timely suggestions, machine learning helps businesses nurture relationships. Intelligent systems can reward repeat customers with special offers or goods or proactively reach out to customers even before they ask for help.
By arranging for a predictive, proactive and personal approach, machine learning helps businesses amplify every touch point. The result is a more rewarding customer experience and increased opportunities for businesses to unlock and capitalize on cross-selling and upselling opportunities.
There has never been a better time for businesses to embrace machine learning. The sooner a company implements this technology, the smarter its software can become, learning and evolving on the fly. Quick to adopt, in this case, means quick to adapt and capitalize on opportunities for the long haul.