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By Jean Mauris
Co-founder and Head of Product at Avokaado
Every single organization requires some sort of document management. Whether you run a small family business or manage a large 10,000+ employee organization, you have to deal with documents one way or another. Document management itself started even before computers were widely adopted and was designed around the ability to “create” a document when necessary, get it to another party (for example, a contract or an agreement), negotiate and sign it (with ink), and then keep it for records.
And for decades, that was good enough. Then computers came along, and we started creating, exchanging, and storing documents in digital formats. This was a relief at the time, and everybody called it “digitalization.”
I recently recorded a short video explaining the differences between digitalization and digital transformation (they are quite impressive), so feel free to watch the LinkedIn video or continue reading.
A simple explanation of the difference between the two terms is this: digitalization affects one particular item (in our case, a document) inside your organization, with the main goal of improving it. Digital transformation, on the other hand, is a holistic approach that impacts entire organizations. Instead of creating incremental improvements, it can expand the organization into completely different business models, opportunities, and markets.
Many years ago, we approached documents with the “digitalization” technique, where we simply replaced our pieces of paper with PDFs, DOCs, and other document formats common to the business world.
And as you probably know, it was still focused on the medium instead of the content—and it still is. Open Microsoft Word, Google Docs, or any other popular text/document processing app, and you see a blank page. Essentially, we took a physical page and made it digital. It was a great accomplishment at the time, but it’s not enough anymore.
Constantly expanding and changing compliance and regulatory requirements put a lot of pressure on document management. It’s no longer enough just to have a document; you need to be able to answer questions about its content. An organization needs to analyze (often ad hoc) every single document to see if it’s compliant with GDPR, HIPAA, or any other relevant regulation.
It also extends well beyond the content: you have to know how long each document should be kept, who should have access to it, when to destroy it, and so on. Essentially, we are talking about document governance, which every organization should have.
Remember, digital transformation is far more complex than digitalization. It requires a holistic approach within an organization. So how do we digitally transform document management?
Stop thinking about pages and paragraphs and switch to a data-centric mindset. This is the key change needed to tackle the problem. Every single document in a company is a set of data points. Some of these data points are relevant to one team (e.g., People Operations), while others are relevant to different functions (e.g., Legal Operations). Let’s take an example.
Everyone is familiar with an employment contract. It can be several pages long (depending on the organization) and include multiple annexes. If a dispute arises, you need every single letter of those documents. But disputes are rare, and in the vast majority of cases, you only need certain data points from the contract. For example:
Basically, every single employment contract is just a set of data points extracted from a long (and frankly, quite boring) contract. These data points drive daily operational decisions and are needed to monitor organizational risks and compliance with various regulations.
We already understand that document management is hampered by pages and paragraphs, where all the data points are hidden. So how do we start thinking (and acting) about documents from a data-centric perspective? How do we kick off digital transformation in any organization in regard to document management?
The first step is to stop creating “plain” documents and truly commit to a data-first approach. This means focusing on the critical data points you need before generating the full text. Essentially, you’ll need to ditch Microsoft Word (for this specific purpose) and adopt data-first solutions, where paragraphs and styles are secondary to the data.
Once you’ve changed your mindset, the next step is to create a list of document types—the documents that are relevant and required for your organization’s operations. Examples could include:
This is by no means a complete list—just an example to illustrate how to think about document types.
When you have your list, I suggest tagging all of them with one of three “origin source” types:
You’ll now have a clear overview (a handy table) of all document types your organization needs and where each one originates.
The next step is obvious but crucial: identify data points for each document type. For simplicity, I suggest two layers:
Feel free to create as many data points as needed, but don’t go overboard. Start with the most business-critical data and then move on to less-critical (but still relevant) data you want to manage.
Keep in mind that for contracts and agreements, there should always be a data set for counterparties—i.e., everyone you do business with, whether they’re businesses or private individuals.
This is a very basic (zero-to-one) approach. I won’t go too deep here, but if you’re more advanced, consider additional dimensions for each data point, such as:
I always suggest starting small; even a basic structure for your document data points will create a completely different level of clarity in your organization. You’ll now have a foundation to shift your focus from document management to data management.
When we talk about documents and contracts your organization owns, it’s all about document automation. Many solutions on the market can help you automate the drafting process (including all data points) for your documents. You do, however, need to be prepared to move beyond your comfort zone and stop using Microsoft Word or similar software for this particular purpose.
With automated documents and contracts, you don’t have to worry about versions, wording, or compliance, because all your documents of a given type (e.g., an employment agreement) will be automatically created from a pre-approved template in the system.
Once you’ve implemented document automation, all your data points will start getting filled in each time you create a new document from the template. Here are some reasons to automate any outgoing document:
So, don’t hesitate—automate. Avokaado, for example, can help your organization get started. Just book a demo or sign up for a free trial.
We’ve figured out how to deal with outgoing (new, owned by you) documents. Now, let’s look at existing and incoming documents. With these, you don’t have control over the content. They come (or exist) “as is,” but you still need to have visibility into the data points.
This is where Generative AI and Large Language Models (LLMs) come into play. The main idea is to take the document type and data points you identified earlier and prompt an AI model with the document and the data points you want extracted. In non-technical terms, it goes something like this:
*“Here is a service agreement [uploaded PDF or DOC]. I need to extract the following data points:
Counterparty name
Counterparty registration number
Contract value
Contract execution date
Present the result as a table.”*
You can include as many data points as you want for every document you process. However, going through them one by one can be time-consuming, so I suggest using a solution (like Avokaado) that lets you batch-process. This means you can upload all your vendor, NDA, or employment agreements, apply a specific document type, and extract all relevant data points from all documents at once.
I’ve described the approach we use at Avokaado AI, but you can apply the same concept with other solutions (like ChatGPT, Gemini, Claude, or any other LLM) as well.
Once your documents and contract data are available (either via automation for outgoing documents or data extraction for incoming and legacy ones), you can switch primarily to data management. Instead of needing every document at your fingertips all the time, you can focus on the data tables built from the contracts’ data.
At Avokaado, we distinguish between two main data registries:
Let’s take a closer look at both.
To clarify, a parties registry is not a CRM. A CRM typically contains information about your customers (including potential ones) but not your employees. The parties registry doesn’t replace your CRM or your HRIS.
Its main purpose is to have one source of truth about everyone you do business with (including employees), keeping their information in one place and updated. If it’s PII (personally identifiable information), you can follow GDPR requirements (e.g., how you keep, retain, and destroy personal data).
A parties registry also gives you a clear overview of all documents and contracts ever signed with a particular counterparty, their statuses, data points, and more—all in one centralized registry that’s constantly updated.
Now that we’ve clarified what the parties registry contains, let’s move on to the data registry. The main goal of the data registry is to keep track of all data points inside every document and contract. Think of it as a central database containing all relevant information from every contract, linked to both parties and the documents themselves.
Having all data points organized in a single, easy-to-read table view lets you stop searching through entire documents just to find something specific. It’s like a bird’s-eye view of all the documents in your system.
A data registry also enables you to create reports, analyze data under various conditions or criteria, and review compliance clauses without opening a single document. If you do need the full details, every record is linked to the corresponding document, which you can open anytime.
And of course, because you have all the data points, you can quickly reuse them the next time you create a document for the same party.
The final step in data management is configuring access to that data. Considering modern data regulations (GDPR, DORA, NIS2, etc.), it’s clear that every organization should have complete and transparent control over who has access to which information. The parties and data registries make this possible.
When data points are separated from the original documents and grouped, any organization can configure and control access on a very granular level. You can grant access to specific data points for certain groups of people.
Here is a comprehensive list of benefits when you maintain parties and data registries:
Below is a concise roadmap for switching from document management to data management in any organization:
We at Avokaado offer a no-code platform that empowers any organization to strengthen its document management by focusing on data rather than pages and paragraphs. Our three main pillars are:
Interested to learn more? Book a demo with one of our experts to see how Avokaado can help you manage data, workflows, and documents on a single platform.
See how Avokaado replaces chaos with clarity by automating manual work, cutting delays, and giving you full visibility across every document.
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