Collaborative Document Generation
Below is an article that appeared in Contracting Excellence, the International Association of Contracting and Commercial Management (IACCM) online magazine about Document Agility's solution.
Organizations face a host of challenges when creating contract documents because the creation process itself is often inefficient, lengthy and expensive. The resulting documentation does not always reflect the business intent of the contract and there is often little access to the data required for an organization to manage the contract obligations.
At the heart of these issues is the challenge of collaboration – coordinating the many groups that must come together to gather and work on the required information. Coordination is especially challenging considering today's highly distributed and mobile workplace. As a result, generating documentation is essentially crowd-sourced.
In this distributed work environment, data is most often contributed in a variety of unstructured ways - by email, spreadsheets and even paper checklists. These methods are problematic. This is what can happen:
Data contributions by email and spreadsheets are susceptible to error. Studies show that the basic human keystroke error rate is approximately 1%, and additional studies revealed that 1.7% of cells in the average spreadsheet contain an error.
The recipient must re-key that data into a file, checklist or system that will be used to create the contract document.
This re-keying process significantly increases the risk of data entry errors.
Fixing errors created by flawed data is a costly proposition. The Harvard Business Review estimates that the cost of performance is increased tenfold when flaws exist in the document data versus when flaws do not exist.
In addition to the data collection problem, another issue that affects the quality of the data used in the generation of contracts is the process that involves the legal or contracts staff interpreting the data. The interpretation process, by its very nature, opens the possibility for error. Even legal experts can misinterpret the data and make mistakes in drafting the appropriate contract language or selecting language based on their interpretation. This also places the most time-intensive and difficult part of the contract creation process with the legal department – the group that likely has the highest cost, fewest members (compared to the number of data contributors), and sometimes the least direct knowledge of the client.
Technology offers a new cloud-based approach - Collaborative Document Generation
Highly suited to cloud-based working, collaborative document generation consists of two technological approaches that help reduce errors and address the distributed and collaborative nature of data collection: 1) Distributed Data Assembly and 2) Rules-Based Document Creation.
The Distributed Data Assembly method operates in much the same way that a manufacturer assembles a physical product. Each team, business system, or stakeholder sequentially adds its unique information to an accumulating set of data that is efficiently moved among teams. As this data capture “engine” moves throughout the organization, it assembles data held in the cloud and accessible by all stakeholders into an accurate, cumulative representation of a given transaction.
This approach collects data through online interviews using questions grouped and tailored to a particular team's role in the collection process. Interviews use conditional logic to control the order and type of questions presented to ensure that all required data is collected.
For example a commercial loan transaction might begin with an account manager in the field who answers questions in an online interview about the client and the basic loan provisions they want. When the account manager completes the questions, workflow rules move the interview engine to a compliance group. There a team member would see an interview with more complex questions that he/she is qualified to answer. Once all data is captured, workflow rules move the transaction to a legal group that generates the required documents.
This process efficiently and effectively collects data more accurately and completely. Data can then be used to create the contract document.
The Rules-Based Document Creation approach can accommodate non-standardized contract provisions resulting from negotiation between parties. In this situation, an organization identifies areas of the contract most often negotiated by other parties and modifies standardized interviews to let users add customized language. This approach accommodates most situations. However, in cases where greater customization is needed, the rules-based approach at least provides an accurate “base” contract from which parties can negotiate.
This method eliminates errors of interpretation and ensures that documents are uniform and accurate. This approach uses business rules, for example government regulations and stakeholder business requirements and best practices, to generate documents directly from the data itself. Rules are created in advance and maintained by an organization's legal and contract staff to ensure compliance.
Rules are stored in template files that contain the possible variations of contract language and the logic that controls which language is used, based on how online interview questions are answered. Legal and contracts staff create these templates using an add-in to traditional word processing software, which also allows them to create and order the questions used in online interviews.
When documents are generated directly from data using the established rules, much of the creation can be done during the data capture process by the contributing teams. This enables legal resources to concentrate on higher-margin activities, rather than struggling to wordsmith the large number of contractual documents originated within their companies.
Wrapping it up
Taken together, the two processes (Distributed Data Assembly and Rules-Based Document Creation) form an overall approach referred to as Collaborative Document Generation. See Figure 3.
In addition to improving the document creation process, this cloud-based approach also improves the accuracy and accessibility data organizations need to develop their contracts, and saves on time and costly errors caused by flawed data.