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Once in a while, new technologies that change the world and disrupt many companies spring up. One such technology is Machine Learning. There is a lot of buzz around machine learning, and the hype is actually justified. This technology can be applied in so many areas. Recently, Machine Learning (ML) has been constantly gaining tremendous recognition in two key business areas, improvement in scalability and operation efficiency. It’s turning into a massive growth because of the need for faster computational processing and easy availability & accessibility of data to name a few. As Storage Area Networks continue to grow at astronomical rates and the lack of technical support services (the list can go on) there are plenty of reasons to justify the need for this “new” technology. This is just a tip of the iceberg though, as machine learning can offer so much more to businesses. We will explore many of these techniques in this article.

What is Machine Learning (ML)?

Machine learning (ML) is a technology that makes use of algorithms that implement statistical techniques which enables computers to learn from data. This learning gives computers the ability to make predictions and decisions using the data without being explicitly programmed. With machine learning (ML), computational tasks whose programming were previously difficult can easily be accomplished.

The process involves the system looking for specific pattern in a data-set and using it in making decisions. This data can be instructions, examples or direct experience. The main aim is to enable the computer to automatically learn from its experience without any human assistance or intervention and adjust its actions appropriately.

Machine Learning (ML) can be classified into two categories, supervised and unsupervised. Supervised machine learning algorithms predict future outcome by applying what it has learned from the past to new data by using branded examples. The system can also modify its model by comparing the intended output with its output and thus using the errors generated to effect the required modification. As opposed, the unsupervised machine learning algorithms doesn’t need to implement the use of labelled examples. It’s effective in defining hidden structure from data that isn’t labelled.

Ways Machine Learning Can Benefit Your Business:

  1. Analyzing Sales Data: The noticeable increase in digital interaction has increased the growth in sales-data. This allows sales team to make use of several metrics ranging from A/B testing, social media platform and website visits. Though some setbacks have been noticed when it comes to analyzing this data. Machine Learning (ML) can be used to speed up the rate of sales data gathering and analysis. Some systems implement machine learning which helps sales teams to be able to connect with best leads. Thus enabling them to direct their resources on those leads with the greatest potential
  2. Hire The Right People: When jobs are being posted, it tends to attract a huge number of interested candidates who may be required to submit their application. It takes a lot of time to go through these applications in order to ensure that the right candidates are selected for the job. With the aid of Machine Learning (ML), one can easily go through a huge chunk of applications easily & efficiently. It also helps in shortlisting the right candidate with the required experience and credentials. Also the use of Machine learning in hiring processes means that human bias can easily be overcome and this will ensure a transparent shortlisting and hiring process. With this, candidates are sure to be selected if they truly merit the position based on the required criteria.
  3. Fraud Detection: Based on research conducted by Association of Certified Fraud Examiners, at least 5% of the revenue generated each year by the average organization is lost due to fraudulent activities. Using an algorithm than can learn and understand pattern of previous data, any irregularities or mismatch in pattern can be easily detected when carrying out similar process and alert can therefore be initiated to inform the company of a suspicious move. This has found its use in combatting tax evasion, cyber-security and transaction fraud.
  4. Increasing Customer Satisfaction: Adopting the use of Machine Learning (ML) in customer service, customer’s loyalty and impressive customer experience can easily be achieved. This is made possible by the machine which try to analyze the previous customer experience and based on this analysis the system will assign the customer to the most appropriate customer service personnel that best suits them. Using machine learning in this process, the time and cost invested in handling customer relation can be considerably reduced. Most organization tend to have adopted a predictive algorithm that can recommend to customers based on their past experience the products that best suit their needs.
  5. Improves Precision of Financial Rules and Models: The financial sector are greatly adopting the use of Machine Learning (ML). Amongst the benefit it has enjoyed includes loan underwriting, portfolio management, fraud detection and algorithmic trading. According to an Ernst and Young report titled ‘The Future of Underwriting’, Machine Learning can benefit financial sector in analyzing and detecting some suspicious anomalies and nuances. This will help to enhance the accuracy of financial rules and models.


A lot of organizations are adopting the use of machine learning to automate processes and therefore boost productivity. With the application of Machine Learning (ML) in the business processes, businesses can easily recognize new patterns and trends in diverse and large datasets. Interpretation of business interaction can be effectively carried out by automating analysis of data which were conventionally carried out by a human (think about the “time” aspect” too). Businesses can now deliver new, differentiated and personalized services and products. All of this can give a business competitive advantage, ensuring it is atop its industry.

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