iTech Data Services

Why Choose Machine Learning (ML) Data Capture?

Read Time: 3 minutes

Machine learning (ML) is an innovative technology that “learns” by adapting algorithms in response to newly-identified patterns and trends.

For example, let’s say you have a search engine algorithm that runs the search bar feature on your bird watching website. Users are searching for the terms “grey bird” and “gray bird.” And behind the scenes, you know that users are expecting the same type of search result when they query these two phrases. An artificial intelligence-powered machine learning technology can modify the search engine algorithm to equate these two terms.

While human gatekeepers can be used to confirm that a machine learning recommendation for algorithm change is sound and valid, this isn’t always necessary. Artificial intelligence technology can be paired with machine learning to automatically approve and implement modifications that fall within a particular scope.

Machine learning is good for more than just updating search engine algorithms. Machine learning-powered data entry technology is changing the way that companies capture and process large volumes of data.


Why Choose Machine Learning Data Capture Technology?

Machine learning (ML) data capture technology brings many benefits and as such, it has proven to be a game changer at many levels. Consider the following.

ML-powered data entry software can work endlessly, without breaks. This allows you to process massive volumes of data on a 24-7 basis, without the need for a coffee break or a mental break. And don’t underestimate the need for a mental break in the case of manual data capture projects. The latter can be mentally exhausting due to the boring, repetitive nature of data entry. This translates into a high potential for human error.

Data capture software with machine learning capabilities delivers a high quality at relatively low cost, especially when compared to manual data entry processes.

Machine learning capabilities improve the accuracy of data capture software over time. It gets better and better the more you use it. The same will also ring true for your ROI.

Organizations will also save money when it comes to manpower. With manual data capture, you need at least three people to capture and (accurately) process a single set of data. Two data entry specialists capture the data in digital form. Their two data sets are then compared by a third party and any discrepancies are subsequently identified and addressed. This process is every bit as inefficient and time-consuming as it sounds.

Data capture software is far faster and more efficient than the best, most experienced human data entry specialists. And the costs are lower since you don’t have to pay three people to capture and process a single set of data. When you add machine learning capabilities to the software, you increase accuracy and speed too.

Data capture software is highly scalable. Platforms with machine learning capabilities are highly adaptable. This translates into exceptional ROI and superior performance that surpasses what you might see with a run-of-the-mill data capture SaaS offering.

Scalability is important for organizations that may experience growth in the foreseeable future. You will have the flexibility and agility to process higher volumes of data without having to hire more data capture specialists; nor will you need to search out a new data capture software solution as data volumes change.

You’ll see lower overhead costs in the short term and in the long term. As mentioned above, software accuracy improves over time since you have machine learning technology identifying patterns and trends that may easily evade a human analyst. The software’s algorithm is adjusted accordingly, resulting in faster, more efficient data entry processing. Greater speed and efficiency translates into cost savings that business leaders can always appreciate.

Some ML-powered software platforms boast a 90 percent time savings over manual data entry processes. It is also not uncommon to see claims of an improved accuracy rate of around 98 percent. This translates into far better cost-efficiency on a short term and long term basis.

The use of a cloud-based platform can reduce overhead even more significantly thanks to its scalability and security, among other factors. For this reason, it is prudent to seek data capture processing solutions that leverage cloud technology.

Harnessing the Power of ML Data Capture Outsourcing Solutions

At iTech, we offer comprehensive data capture outsourcing solutions. Our machine learning data capture, cleaning and unification technology is “trained” in much the same way you might teach a human data entry specialist. We evaluate the client’s data and then provide the machine learning algorithm with very specific instructions on how to handle that information during the data capture process. This may include:

  • How to define “normal” data;
  • How to handle normal data versus anomalous data; and
  • When to summon a human to intervene in the data entry process.

This approach allows us to achieve a high degree of accuracy, speed and cost-efficiency with our machine learning data capture solutions. If you’re ready to harness the power of ML data capture technology, contact the team here at iTech. We’re excited to show you how this innovative technology can be a game-changer for your organization’s bottom line. Oh, and, by the way, we’re amazing too.

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