As data science comes to the forefront, more & more businesses are focusing on improving their business processes by harnessing the power of technologies like:
- Artificial intelligence
- Machine learning
- Big data
Out of these three, machine learning is a technology that helps businesses to gain insights from raw data. Specifically, machine learning algorithms are used to learn from a given set iteratively and understand patterns, behaviors, etc., all with little to no programming.
The iterative & constantly evolving nature of machine learning in improving a company’s work processes ensures that the business is always up to date with the latest trends & consumer demands. Moreover, building or integrating machine learning into existing companies’ procedures is a lot easier now because all major cloud providers offer ML platforms.
In this article, we will see how machine learning helps in improving a company’s work processes. So, without further ado, let us begin!
Machine Learning: An Overview
Before we move on to how machine learning helps in improving a company’s work processes, let’s have a basic understanding of how it works.
So, machine learning refers to the process of extracting meaningful data from raw data sets.
For instance, let’s consider an online retail store that records consumer behavior & purchases within the website. However, this is just data. But machine learning plays a vital role, enabling online stores to analyze & extract stats, information, patterns, & stories hidden within this data.
A critical factor that differentiates machine learning from regular analytical algorithms is its adaptability. Machine learning algorithms are constantly evolving. Thus, the more data the algorithm consumes, the more accurate its analytics & predictions will be!
Harnessing the power of machine learning has helped businesses to:
- Quickly adapt to ever-changing market conditions
- Improve business operations
- Acquire a greater understanding of the consumer & business needs
Machine learning is rapidly becoming ubiquitous across all industries, i.e. from agriculture to medical research to the stock market. For instance, agriculture can utilize machine learning for numerous tasks, like crop rotation or weather pattern prediction.
Moreover, machine learning can also be combined with artificial intelligence to enhance the analytical process, thus helping to improve the company’s work processes.
Top Ways Of Improving A Company’s Work Processes Via Machine Learning
Machine learning is the most impressive new development in technology. It teaches an artificial intelligence system to prepare itself. While this might sound like a sci-fi horror tale, the results are pretty promising for businesses.
Here are the top ways by which machine learning can help in improving a company’s work processes. Take a look!
- Customizing Consumer Service
The potential to improve consumer service while lowering costs makes this one of the most exciting areas of opportunity. By combining historical consumer service data, algorithms, & natural language processing, consumers can pose questions & get high-quality answers.
In fact, studies show that over 44% of consumers prefer chatbots to humans for consumer relations. Thus, consumer service representatives can step in to handle exceptions, with algorithms looking over their shoulders to learn what to do next time around!
- Improving Consumer Retention & Loyalty
Another method of improving the company’s work processes is consumer retention & loyalty.
Companies can mine consumer actions, transactions, & social sentiment data to recognize consumers who are at a high risk of resigning. With profitability data, companies can optimize the ‘next best action strategies’, thus personalizing end-to-end consumer experience. Therefore, this enhances consumer retention & loyalty, which benefits the company in the long run.
- Automating Finance
Artificial Intelligence & Machine learning can expedite ‘exception handling’ in many financial processes. For instance, when a payment is received without an order number, a person must sort out which order the payment corresponds to, thus determining what to do in case of excess or shortfall.
So, by monitoring existing life processes & learning to recognize different situations, AI & ML significantly increases the number of invoices that can easily be matched automatically. As a result, this will let the company reduce the amount of outsourced work to service centers, thus freeing up finance staff to focus on strategic tasks.
- Measuring Brand Exposure
Automated programs can recognize products, people, logos, etc. For instance, advanced image recognition can be used to track the position of brand logos that might appear in the footage of a sporting event.
As a result, corporate sponsors get to see the ROI, i.e., return on investment of their sponsorship investment, with detailed analysis, like quantity, duration, & placement of corporate logos.
- Detecting Fraud
A typical organization loses around 5% of its revenues yearly to fraud. Thus, machine learning algorithms can use pattern recognition to spot anomalies, exceptions, & outliners, thus helping detect frauds & improving a company’s work processes.
For instance, banks can use historical transactions to build algorithms to identify fraudulent behavior quickly. They can also discover suspicious patterns of payments & transfers between networks of individuals with overlapping corporate connections/ links.
Thus, this kind of ‘algorithmic security’ applies to various situations, like cybersecurity, tax evasion, etc.
- Effortless Supply Chains
Machine learning enables contextual analysis of logistics data in order to predict & mitigate supply chain risks. Further, algorithms can sift through public social data & news feeds in multiple languages for detection. As a result, this leads to effortless supply chains, which help in improving the company’s work processes.
Some other areas where Machine Learning might be successful are:
- Career Planning
For instance, if an individual with an engineering degree wishes to own a division, then he/ she needs to know what additional education & work experience must be acquired & in what order!
Also Read: Career Planning & Goal Roadmapping
- Drone & Satellite-Based Asset Management
Drones equipped with cameras can perform external inspections of commercial structures like airplanes, bridges, etc. The image can be automatically analyzed to detect any new cracks or surface changes.
- Retail Shelf Analysis
A sports company can make use of machine learning to see whether its in-store displaces at the promised location or not. In addition, it also helps see if the shelves are adequately stocked with products and if the labels of the products are facing outside!
Machine learning enables a company to reimagine end-to-end business processes with digital intelligence. The potential of ML is enormous. This is why many software professionals are presently investing in adding AI & machine learning to their new applications, thus creating efficient solutions.
However, there are some barriers to overcome. It is vital to have large quantities of data to train algorithms. Moreover, the data isn’t in one place or in a usable format in many companies. Therefore, to prepare your company for the future, the first step is to assess your existing information system & data flows to distinguish the areas ready for automation.
It is vital to note that the rise of machine learning is inevitable. Also, it is advancing into the company’s work processes at a dizzying speed. Thus, companies need to be thoughtful about how they employ machine learning to enhance their processes upon understanding the pros & cons inherent in the technology!