During tough economic times, many companies are forced to cut their labor force in order to survive.
However, these same companies still have work that needs to get done and now have to figure out how to operate with less staff.
Regardless of the industry you are in, this is a great time to look into automation through AI/ML.
One of the most common questions we get from clients is where to even get started as that task can often seem daunting. The advice we always give is – start small. Although you could probably think of dozens of automation opportunities, it’s important not to try to do them all at once. Start with the low hanging fruit. Pick a use case that is relatively easy and could provide some immediate ROI. Think of things like repetitive clicks, basic data entry, uploading forms, etc.
At NLP Logix, we always recommend first doing an assessment of the entire organization’s data, as the basis for an automation plan. This gathering of the data also expedites the training of the machine learning models, in addition to providing a benchmark to measure the return on investment.
Our approach to these projects is to work closely with our clients to understand their data and workflows.
We are able to leverage our knowledge of mathematics, software development and machine learning engineering, however we need our client’s help as the subject matter expert in their business to build a successful AI/ML solution.
Once you are able to tackle these types of automation projects, you should be able to calculate the ROI by hours saved or increases in efficiency. This will also give you a good sense of the processes involved in order to automate and apply Machine Learning.
From there, you can expand the scope of your automation efforts. Maybe you started out only automating 40% of your data entry, now you can look at how to get that number to 60% or higher. Or perhaps you successfully automated part of your workflows in one line of business, now you can repeat the process in other departments.
These are all great ways to get started with implementing automation within your organization. From there, you can start to look at more advanced AI/ML solutions like predictive modeling, advanced analytics and using Natural Language Processing (NLP) for unstructured data.
Interested in hearing more about Automation?
We’ll be sharing our insights into Automation and how companies can leverage Machine Learning to their advantage. Keep an eye out for weekly posts in our Automation Insights series.
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