How Machine Learning Influences Decision-Making For Small Businesses

Have you ever wondered why businesses want to hop onto the Machine Learning bandwagon? Like the distinguished GAFA (Google, Amazon, Facebook and Apple) technology giants, every business is looking out for technology advances to establish their business. In the case of smaller businesses, they tend to doubt whether it is possible to implement machine learning as a part of their business cycle. And the answer is Yes!

What Is Machine Learning And How Does It Help In Decision-Making Processes 

Machine Learning is an application of AI that focuses on automatically learning from common patterns and depends on algorithms that can access critical data and derive insights used for businesses. The goal of machine learning lies in making computer systems able to learn automatically without human support, though it is categorized into various algorithm types as follows:

• Machine Learning Algorithms That Need Supervision

This algorithm is used when the data is labelled or classified. The data sets are labelled based on the previous data which after analysis, the supervised machine learning algorithm generates a function that is capable of predicting future outcomes.   

• Machine Learning Algorithms That Need No Supervision

These algorithms are used to train the data sets which are not classified or labelled. These unsupervised machine learning algorithms generate functions to define hidden structures from data sets. In this case, the system does not process the outcomes but derives insights from unlabeled data sets.

• Machine Learning Algorithms That Need Partial Supervision

These algorithms use both supervised and unsupervised machine learning as they deal with labelled as well as unlabeled data sets. These algorithms are used to improve accuracy as labelled data sets demand skillful resources to learn from or to get trained whereas unlabeled data sets do not require extra resources to learn from or to get trained.

• Machine Learning Algorithms That Are Reinforced

This machine learning algorithm category makes use of trial and error search which allows the machines to automatically determine various behaviors. This, in turn, maximizes productivity and performance with the reward feedback for the agent, known as the reinforcement signal.

Thus machine learning processes large amounts of data sets and delivers faster and accurate results. Machine learning can be well combined with cognitive technologies, IoT and Artificial Intelligence to identify and predict advances in the technology forefront.

Machine Learning has numerous potential benefits. As algorithms that are trained to learn from existing data sets, to derive patterns and insights from the patterns, it helps businesses make decisions and remain competitive.

How Is Machine Learning Influences Small Businesses In Decision-Making

Size and Complexity Of Data Sets Well-Managed By Machine Learning Algorithms:
Machine Learning provides immense value to businesses with large volume and variant data. This leads to high storage optimization techniques and increased computational processes. This in turn drives the need for analyzing the available data sets by machine learning algorithms which ensures highly accurate data processing and faster outcomes. 

This is not made fully possible by humans alone in being able to uncover complete value from the raw data derived, be it unstructured raw data from online customer behavior, their purchasing decisions online, transactions in various businesses and many more.

The large sized data sets along with its sophisticated nature can be processed by machine learning algorithms with minimal or little human assistance. This is how small businesses can make decisions with machine learning techniques. 

Machine Learning related infographics: Machine Learning- Deciphering the most Disruptive Innovation

On-time Predictive Maintenance:
Manufacturing industries are reported to lose around $50 billion every year with major downtime and repair overheads. Machine learning helps in taking required measures by first collecting parameters of operations and analyses the behavior.

Automated Decisions For Increased Efficiency:
In addition to the complexity and size of data sets available to be processed, many businesses also take advantage of automation technology to increase the efficiency of operations. The reason behind slow decision-making by businesses is due to complex business processes or work overload which can considerably reduce productivity and operational efficiency.
In such cases, machine learning framework analyzes business data sets, analyzes trends in major processes, automates decisions, and also in generating critical business approvals.

Human Intervention Least Required:
With the ability to automate decisions without requiring human intervention at all times, as machine learning has reached the peak of informing decision-makers in businesses what their decisions ought to be on the basis of correct suggestions derived from patterns in history, machine learning algorithms speed up the ability of businesses to accelerate their decision-making that further accelerates critical workflows and operations with maximized efficiency.

Image Recognition Impacts:
Machine learning also enables image recognition. The image recognition market is reported to reach $39 billion, which is 2.5 times the size it is now by 2021.
This is due to an increase in businesses trying to implement machine learning to leverage its core advantages. The use cases, for instance, are the QR Scanners. It recognizes codes to respective objects. A lot of industry verticals benefit from Image Recognition techniques.

Customer Satisfaction :
Product recommendation along with findings of market segmentation provide a deep understanding of how machine learning provides insights into gaining high customer engagement and sell their products/ services to their targeted audience.
This illustrates the difference between businesses advertising their products/ services and making proper customer recommendations that engage their targeted audience much more efficiently than otherwise. 

Machine Learning As A Major Investment:
The technology giant, Amazon’s investment in machine learning to use driver-less cars is an example of how it used machine learning algorithms to speed up the click-to-ship time. Software-based startups are valued more than machine-based systems that lack their hardware counterparts. These factors add to more businesses adopting machine learning.
Machine learning is said to draw 80 percent of the total investment from AI which was between $8 and $12 billion initially. Machine learning is thus a major investment preferred to other systems.

Content Personalization:
Netflix saves $1 billion each year by implementing machine learning for personalizing content according to customer requirements, according to a report published by Neil Hunt to inform investors about the use of algorithms and the impacts.
The streaming giant is able to draw out significant ROI by growing its customer base via implementing machine learning algorithms. 

Enhanced Security For Well-Organized Business Processes:
Cyber attacks are dominant and machine learning algorithms detect and prevent such attacks. This is identified by the ability of these algorithms to detect deviations from processes and behavior patterns in history.  
Spamming is yet another issue being addressed by these algorithms by filtering inbound traffic and thus avoiding spamming and phishing attacks.
In a nutshell, machine learning enhances performance and productivity in addition to detecting and preventing fraudsters and malicious activities in businesses. Machine learning algorithms make use of patterns and methods that are futuristic and can be relied on by helping businesses enhance performance and avoid risks