Blog Post

The #1 Mistake Legal Ops Managers are Making with Data Entry

August 12, 2021

The #1 problem for most using data to make intelligent decisions is misallocating the majority of their time on the easiest part of the task. They spend more than 50% of their time entering the data manually versus spending that time to analyze the synthesized data.


Most firms use manual data entry for documents and contracts, firstly because it’s seemingly more convenient and secondly because they think it’s more efficient than using technology to automate this process.

Top 4 Disadvantages of Manual Data Entry

  • Quality: Ensuring absolute consistency is challenging with a manual process because people are prone to error. When performing tedious and repetitive tasks such as manual processing the margin for human error increases dramatically.

  • Speed:  Humans need breaks, machines do not. No downtime.

  • Cost:  Manual data processing is not scalable. Adding more staff to digitize contracts increases operating expenses.

  • Risk:  Security around manual data processing is more easily compromised. Classified or sensitive information stands a higher chance to be leaked.

What is the faster alternative to manual data entry?

You launch a process called “automated data processing.” It refers to processing large amounts of information with minimal manual input, then showcasing the results in a comprehensible way.

Automated data processing consists of two parts:

A) Automated Data Extraction             B) Text Classification

A) Automated Data Extraction – How does it work? 

Optical Character Recognition (OCR) is a technical term that means computers can recognise the characters within a document and convert them into machine-encoded text.

From a legal perspective, it means that handwritten documents, court notes, or any printed documents can be digitized so they can be electronically edited, searched, stored and used by other artificial intelligence techniques for analysis.

Once the character is extracted, the output is matched to a lexicon (a dictionary of characters). OCR is a mostly automated process (most fonts are fully recognised) although for handwritten documentation it requires some initial ‘training’. Now the data has been accessed (or digitized to a standard) we need to make sense of the information for it to be actionable.

B) Text Classification – How does it work?

Text classification is organising or classifying the information into interpretable groups.

There are two types of data:

Structured: Excel, SQL, CMS, customer data, transaction history – data that can be easily labelled with an identifiable field such as name, date etc

Unstructured coupled with Deep Learning: Documents, contracts, texts, emails, chat conversations, websites social media – data that takes additional training in order to be classified with specific fields. Using Deep Learning we transformunstructured data into structured data, which is where the real value from data is achieved. Deep learning is the best approach to quickly and effectively classify unlabelled and unstructured data – ie your contracts and supporting documents. Deep learning models perform automated feature extraction without any need for humans to intervene and assign a probability to classify based on a particular label. The classified data can be then stored in the repository as structured data.

Time is money in any corporate department, but when it comes to labor costs within legal – it can become an astronomical waste of money allowing highly-skilled and highly-paid labor perform tasks that take them away from the heavy lifting tasks they were hired for in the first place. 

If you had to calculate how many hours were lost uploading data manually how much could your organization save in labor costs?


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About the Author:

Exigent is a legal and technology services provider breaking industry boundaries and raising the bar for data-driven decision-making. With a powerful combination of technology, legal expertise, and business acumen, Exigent creates expert solutions that drive better legal and business outcomes for law firms and corporations. Whether it is leveraging AI for contract management and due diligence or providing expert witnesses and medical legal support or serving as an outsourcing partner, Exigent delivers scale, expertise and insights that generate bigger returns for our clients.

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