Document Management is Dead. Long Live Data Management.
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.”
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.
Digitizing Documents, and What Went Wrong
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.
Digital Transformation for Document Management
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.
An Employment Contract 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:
Accounting needs the compensation amount and information about bonuses.
The Legal team needs the NDA clause, no-solicitation clause, or other compliance requirements to be there and acknowledged by the employee.
The HR team needs the probation period, annual review dates, and other relevant information.
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.
From Document Management to Data Management
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?
Intelligent Documents
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.
Document Types
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:
Employment Agreement
Non-Compete Agreement
Non-Disclosure Agreement (NDA)
Service Agreement
Scope of Work
Sales Agreement
Purchase Order
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:
Outgoing – Documents you own and create, which you can amend and change as needed (e.g., employment-related documents, NDAs, DPAs, service agreements, or other core business documents).
Incoming – Documents you don’t own or control but need to keep and track data from (e.g., vendor agreements, third-party agreements, sometimes NDAs).
Legacy – Documents you already have and need to keep and manage. These can be both owned by you or by a third party.
You’ll now have a clear overview (a handy table) of all document types your organization needs and where each one originates.
Data Points Design
The next step is obvious but crucial: identify data points for each document type. For simplicity, I suggest two layers:
Data points (smart fields) – A single data point you need to track. It can be contract value, execution date, first name, company name, email, conflict of interest, etc.
Data sets – A group of data points that helps you organize them for better visibility and clarity. This also helps determine who should have access to which data points for each document type.
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:
Does this data point contain personally identifiable information (PII)?
Data point retention period (GDPR-related).
Visibility/access within the organization (security control).
Data point origin (manually added, added by a third party, added via integration).
Any organization-specific tags for data points or data sets.
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.
But How Do We Get This Data for Every Document?
For Outgoing Documents – Automation
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:
Time Savings – Automation replaces manual, repetitive tasks (e.g., data entry, template creation), letting employees focus on higher-value work.
Error Reduction – By pulling data from reliable sources and using predefined templates, automation significantly lowers the risk of manual mistakes.
Increased Productivity – Streamlined processes speed up document creation, approval, and distribution, enabling teams to handle more work in less time.
Cost Efficiency – Fewer manual steps and less labor lead to lower operating costs, including printing, postage, and storage.
Consistency & Compliance – Standardized templates ensure correct fields, language, and formatting, supporting regulatory and policy adherence.
Scalability & Flexibility – Automated systems handle higher volumes of documents and adapt to growing business needs without proportional staffing costs.
Better Collaboration – Centralized platforms and automated workflows improve team visibility, reduce back-and-forth communication, and keep everyone updated in real time.
Improved Customer Experience – Faster turnaround times and accurate, professional documents make a positive impression on clients or partners.
Enhanced Security & Audit Trails – Automated solutions typically include versioning, permission controls, and audit logs, boosting data security and traceability.
Data-Driven Insights – Tracking and reporting features in automation tools identify process bottlenecks and inform strategic decisions to further optimize operations.
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.
For Incoming and Legacy Documents – Data Extraction
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.
Data Management
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:
Parties Registry – Essentially a database of every party with whom you’ve ever signed an agreement (this can include both businesses and individuals).
Data Registry – A database of all data points collected across all processed documents and contracts.
Let’s take a closer look at both.
Parties Registry – Not a CRM
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.
Data Registry
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.
Access Control
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.
Contract & Document Data Management Benefits
Here is a comprehensive list of benefits when you maintain parties and data registries:
Legal & Regulatory Compliance – Having a complete list of contractual relationships helps demonstrate compliance with laws, regulations, and industry standards.
Risk Management – Centralized records help spot and handle potential risks (e.g., overlapping terms, conflicting clauses, or non-compliant vendors).
Financial Control & Forecasting – Visibility into contract obligations allows for accurate budgeting and forecasting (e.g., recurring fees, subscription renewals).
Contract Compliance & Obligation Tracking – Clear responsibilities and timelines lower the risk of missing key deliverables, SLAs, or milestones.
Renewal & Termination Management – Detailed records simplify renewal processes and help avoid unintended auto-renewals.
Improved Collaboration & Transparency – Centralizing contract data makes information readily accessible to relevant teams (legal, finance, procurement, etc.).
Relationship Management – Knowing all existing relationships helps maintain stronger partnerships through proactive dispute resolution and performance monitoring.
Historical Data & Analytics – Past contract data can provide insights into supplier performance, payment terms, and negotiation outcomes.
Step-by-Step Instructions (Short Version)
Below is a concise roadmap for switching from document management to data management in any organization:
Identify the most important documents your organization needs.
Define data points for each document type, and organize them into data sets for clarity and visibility.
Automate outgoing (documents you own) so that at least 90% of your daily outgoing documents are automated.
Use AI to extract data points from existing and incoming documents. Focus on what’s most important and relevant.
Organize data into parties and data registries.
Grant access to relevant people for the relevant parts of the data registry.
Ensure data remains current whenever contracts are amended or changed.
Avokaado Operational Intelligence Platform – A Data-First Document Management
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:
Complete transparency into documents, data, and workflows.
Document and workflow automation to achieve operational excellence.
Compliance on autopilot through a data-first approach to document management.
Interested to learn more? Book a demo with one of our experts or request access to a free trial workspace to see how Avokaado can help you manage data, workflows, and documents on a single platform.
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