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Types of Contract Process Data and How They Help Your Business

Three colleagues smiling across a work table at a person not in the shot | Types of Contract Process Data and How They Help Your Business

Contract data contained within legal documents has the potential to help your organization grow at exponential rates. Drawing up innovative strategies using various types of process data and applying them to advance your business is a great way to start. 

Contracts are at the forefront of every business because they offer protection and data analysis. Tracking legal data via contract management aids in making better business-related decisions. 

This article will cover:

  • Types of process data
  • ‌How to strategize process data for business growth
  • ‌Challenges faced during data processing and their solutions

Test Your Own Contract Processes

Process data and its types

It’s important to understand the difference between contract metadata and process data. Process data is essentially the information drawn up to organize and strategize contract metadata. Process data recording uses manual or automated tools. It involves collecting data, structuring and managing it properly, storing it carefully for easier accessibility, and altering it wherever required. 

There are several ways to carry out data processing. It consists of steps and tools that can convert raw data into usable forms. The types of data processing depend on the input—the raw data that you want to convert into machine-detectable information like images, charts, figures, and graphs.

Commercial data processing is used in marketing for customer relationship management (CRM) and transactions. Data optimization uses standard methods, so the chances of errors are minimal. Since the input data is massive, organizations opt for simple automated processing that’s foolproof. Batch processing combined with commerce is often used in commercial process data.

Academics and research studies depend on scientific data processing. This involves a low amount of input and output data since there’s very little room for error. However, the computational processing that goes into scientific process data is quite complex. Thus, it takes more time than other data processing types because data-based conclusions have to be as accurate as possible.

Computing methods also determine the types of process data. This includes batch data processing, online data processing, and real-time processing.

Batch data processing involves computing several documents at the same time. It’s a somewhat older technique mainly used for financial applications. The process data is generally of the same type and present in large amounts. Simplified commands process a large amount of data simultaneously. Batch data processing is helpful for banks or other organizations that require additional security measures. It requires minimal human intervention.

The opposite of batch data processing is online data processing, which is the act of recording process data via automated means. The mechanism is continuous, which means that as soon as the optimization of one set of process data finishes, the software will move on to the next one.

Online data processing is beneficial for large retail outlets, like Target and Walmart, where inventory systems require frequent updates. Companies with massive amounts of contractual and business data should opt for online data processing as well.

Lastly, when data needs computing right on the spot, companies use real-time data processing. An example of this is the tracking of stock markets and cryptocurrency. Quick actions are required here because the timeframe for data processing is mere seconds.

In this method, stream processing records the data. It means that the information collected comes directly from the source. Conclusions become possible without data transfer. Another technique for real-time data processing is data virtualization, which only extracts valuable data from the source, thereby reducing the chances of error.

Data types to track

Here are some basic process data types that companies track for optimization:

  • ‌Total contracts completed: This metric calculates the contract completion rate by comparing the contracts that have been executed successfully to the ones that are still in the approval phase. By knowing the total number of contracts completed, your company can optimize your vendors’ performance.
  • ‌Average contract value (ACV): This is the average monetary value that a customer contributes to your company during a specific period. It’s useful for determining the company’s health. Companies that depend on subscriptions to sell their products depend on ACV the most.
  • ‌Average days to completion: This indicates the average amount of time taken for completing contract workflows. If the value is too high, the company needs to strategize and provide teams with additional resources for a faster completion rate.
  • ‌Average days spent per step: This metric is similar to the average days of completion. It determines the number of days spent in each process or stage of the contract. The steps that are taking more time for completion are optimized individually for better overall performance.
  • ‌Steps that take the most time: Here, you can gain insight into the hurdles or sticking points in your contract lifecycle. Your company can efficiently judge where optimization is needed the most.
  • ‌Number of redlines: The number of redlines indicates where editing has taken place in the contract. It will tell you how long your negotiations are taking. A high number of redlines means that the negotiation process is being dragged out. They should be eliminated accordingly.

Business growth via process data strategies

Process data provides an overview of how teams are performing within an organization. The effectiveness and workload extracted from this data help companies hire new people. Process metrics reports show the average time spent on contract dealing. The contract data lifecycle will tell you what agreements and transactions to prioritize. Companies can make timely decisions to speed up their work and get the job done sooner.

You can gain insight into the average contract value via process data optimization. It’s an important metric that helps track your company’s health. The ACV will confirm how much a customer contributes to the company in terms of monetary gains.

This leads to forecasting the average recurring revenue (ARR), therefore enabling the measurement of the company’s growth. Making future predictions regarding the advancement of the company is also possible.

By using process data, you can judge which steps in the contract lifecycle are taking up the most time. Some teams within the organization may be generating and completing workflows faster than others. You can optimize contract workflows accordingly and ensure that the teams having trouble receive ample resources to complete their tasks. 

Data processing will also enable you to study the number of redlines within a contract. If a contract has too many redlines, it becomes difficult to track. It’s best to avoid too many of them by gathering all details for crucial terms and reviewing them carefully among all teams, primarily Legal. It can help with formatting and tracking changes within your contracts if done correctly. 

Your company can use process data metrics to determine how much business you’re doing and the revenue it’s bringing in. All the completed contracts and the efficiency of individual teams are tracked. Everyone can gain access to team operations and determine which workflows are blocking further progress. Strategies drawn up based on these metrics will help businesses prioritize value-added work and make progress. 

Challenges during data processing and their solutions

Tracking process data and strategizing it helps in business growth. However, the process comes with its challenges. 

The overflow of contract data in organizations is challenging to store adequately. If it’s stored among various platforms, restrictions will spring up concerning access and visibility. A viable solution for these issues is opting for digital contract management. Multiple software tools can make your life easier by automating contract workflows. This way, tracking process data is easier and faster.

Tools like the Dynamic Repository enable you to store and organize all your process data in one place. You won’t need to spend extra on security and multiple cloud storage platforms. Accessing your documents will be quick and efficient, too.

Some organizations still use manual methods for data processing. This takes time and distracts you from the essential matters at hand, like strategizing process data for business growth. Luckily, contract workflow designers make the job easier by enabling simpler contract generation. Instead of spending months gathering process data and getting contracts approved, you can do it in minutes.

You can also choose which workflow metrics you want to track. For example, a multinational cosmetics company like L’Oreal focuses on tracking its return on investment and gaining ambassadors. A sports team like the Texas Rangers may choose workflows to track how many seats it sells.

Editing contract process data is a cumbersome task. It’s tricky to keep yourself updated about all the changes made, and human error is unavoidable. Having a tool that does the editing will prevent the unnecessary stress that goes into this process. 

The Ironclad Editor helps customers with contract redlining, negotiations, and revisions. Previously, such changes took place manually. Parties had to go back and forth editing several documents. With the online editor, you can make changes to your contracts without involving the opposite party at all. 

Process data needs adequate contract lifecycle management (CLM) so that it can help a business grow. Even though automation can’t replace contract data management completely, it can minimize everyday contracting tasks. Innovative artificial intelligence (AI) technology will enable you to get your contracts reviewed in record time. Getting signatures will become easier, and negotiations will feel like a piece of cake. 

Deriving a game plan for business growth from process data means being able to execute contracts remotely. Sending documents back and forth via emails causes them to pile up. The Clickwrap allows one-click acceptance for low-negotiation contracts. Generating and approving legal contracts with you and your customers on the same platform is quick and simple. The management of all the terms and conditions becomes possible in a single place as well.

Tools for success

Legal work has the opportunity to contribute to business growth by tracking both metadata and process data. Since every business is unique, you need to build up process data strategies for progress and advancement. This is possible only when you focus on strategic data collection and use modern tools to stay ahead of your competitors. Click here to request a demo of Ironclad to help with your process data collection. 

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