Smart Ways to Use Machine Learning to Improve Your Company
Machine learning, by now, is a widespread idea that has revolutionized the ways in which routine operations used to take place. Modern advancements in the ML domain have forced individuals as well as enterprises to think in a different dimension by utilizing and incorporating the power of machine learning and saving time. Moreover, the concept of MLaaS (Machine Learning as a Service) has enabled everyone to get access to machine learning to some extent without really worrying about the underlying engine that exhibits it.
In this blog post, we will look at some smart and impressive ways in which you, as an enterprise, can effectively make use of machine learning in order to improve and optimize your day-to-day operations and consequently save much manual effort and time.
A general overview of modern ML applications
We all know that data is an essential prerequisite behind every machine learning application, and in today’s era, we all are producing huge volumes of data and are surrounded by it. Given the advancement in information technology and the pace at which computing machines are increasing their computation capacity, researchers have found some really interesting and eye-catching ways in which machine learning can be applied to achieve a common good.
When you use Facebook or Amazon, do you notice any sense of personalization? Indeed, we do! This is because Facebook and Amazon have implemented a machine learning technique commonly known as recommendation systems which capture your interests and choices based on your past activities.
Hence, the experience that you have of an application is entirely different from another person who has other preferences and choices. YouTube, Pinterest, SoundCloud, and other similar systems also embed the same idea within their applications to give a personalized touch.
Not just recommendation systems, but ML has been remarkable in healthcare analytics as well; be it a disease diagnosis prediction or a medicine suggestion, machine learning has deep grounded its roots. When it comes to financial technology, machine learning is again playing a significant role in the areas of anti-money laundering (AML) and fraud detection.
One extremely interesting (under research) application of machine learning is being developed by some researchers at Carnegie Mellon University who claim the possibility that human faces can be reconstructed from voices. Pretty cool, no?
Machine Learning for Your Enterprise
Knowing about the game-changing applications of machine learning in services and researches, it is natural to think of taking inspiration from them and use their conceptual parameters in order to benefit from them for your own enterprise. You can develop some smart ways in which your business, as well as your in-house enterprise processes, can get easily streamlined to a vast percentage.
How much your business can sustain these ideas entirely depends on its nature. Of course, if the problem your business is trying to solve is indeed AI-driven then you can definitely consider ML approaches for you to automate those as well, but again, that is completely dependent on your business problem. However, there are a lot of ideas in which you can use ML within the enterprise to automate processes and eventually save time.
Following are some of the cool ways in which ML can help you improve your company’s lifestyle and culture.
Employee attendance using facial recognition
Back in the days when there was very limited access to technology, companies used to take manual attendance of employees on sheets of paper. A little further, attendance sheets were replaced by attendance systems where employees fill in the necessary information each against the given date and time. Sooner than later, we moved towards card-based attendance systems and then to fingerprint identification systems. But wait, we haven’t stopped there!
Now that we are living in the era of artificial intelligence, companies have started implementing techniques where there is literally zero manual effort and employees just have to pass in front of a camera, and the attendance will be marked automatically using facial recognition machine learning algorithms.
Meeting minutes using voice to text translation
Daily meetings are an essential part of every enterprise; be it internal collaboration meetings or client meetings, we do those all around. In order to keep up the best with what was discussed during the meetings, we often document meeting minutes and they undoubtedly serve the best purpose of recapping everything that was discussed. What if we automate this process? Voice-to-text translation systems are now very common. We can reduce an additional focus overhead using these systems, focus on the actual meeting agenda, and let the system do the hard work of keeping up with the meeting notes. Sounds interesting, right?
Monthly reports using text summarization
Just like how we used voice-to-text translation for documenting meeting discussions, we can extend that a step further and apply machine learning techniques that would take in a piece of text and generate its summary for you. There are numerous useful applications to this technique. Starting from meeting notes, you can extend this idea for generating weekly and monthly progress reports, sales growth reports, customer retention reports, research synopsis, and what not.
Employee satisfaction surveys
Apart from the general implementation side of things, you can also utilize the power of machine learning to maintain a healthy culture and a productive environment within the company. You can start off with conducting expectation and satisfaction surveys among the employees and then use this information to conduct sentiment analysis on this data. This way you would know an overall company atmosphere, which departments are happy with their work, which category of people are looking for a change and multiple other situations. You can then use the results of sentiment analysis to address the issues within the company and maintain a healthy and uniform environment overall.
Sales growth predictor
Sales, undoubtedly, is the most important factor in a company’s growth. Here also we can enable machine learning to configure the sales team in mimicking multiple growth strategies and predict the relevant sales matrices out of those strategies. This won’t be an easy task as it may have various data non-availability issues and the model might need to be treated extremely delicately so that it aligns with the company’s philosophies and outreach strategies. Nevertheless, the idea of using ML for predicting sales growth is a huge fascination in itself.
- Automatic inter-department teams generator (based on requirements, team bonding, deadlines, etc.)
- Healthy food recommendation (based on personal preferences)
- Personalized employee training and growth
- Bonus predictors (based on performance and relative growth)
- Predicting customer retention
- Smart hiring
For the majority of the ideas mentioned above, the cool part is that you do not necessarily need to recreate the wheel. This is the power of MLaaS and we just should be good enough to plug these services as per our use cases.
So here we are. Pretty interesting to know that machine learning can essentially be applied in a variety of ways for a better experience and company culture overall. We hope that this was an informatory read and look forward to how you interpret these ideas in order to develop a cool and time-saving environment within your company.
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