Your maturity result:
BeginnerIntermediateAdvanced

Low Maturity

Your score means your digital document maturity is only at the beginning stage.

Low-maturity companies can start with a clean slate.

Firstly, recognize that you are not alone. One-third of respondents note that their companies are in this position. To begin growing your digital document maturity, start taking advantage of recent advances in document technologies. For example:

• Use e-signature platforms to improve customer flexibility. APIs make integration with document generation and authentication processes easier and more flexible. Leverage these capabilities in your customer interactions.
• Take advantage of dynamic forms for better user experiences.  Static form solutions of the past can be replaced with dynamic forms that repopulate from business systems and adapt to any display type. This allows you to present the right amount of data to users when collecting information. Forms can change their layout according to the data entered.
• Utilize intelligent document extraction platform (IDEP) solutions for better extraction accuracy. Years of struggle with template administration are gone with newer solutions that use natural language processing and machine learning to adjust to form changes. With newer solutions, accurate extraction is assumed, and attention can be spent on gaining insight and taking action post-extraction.

Medium Maturity

Your score means your digital document maturity has advanced to the intermediate stage.

Medium-maturity companies can expand on early success.

Medium maturity means you are halfway through the digital transformation journey. The good news is that you’re comfortable with the areas that are succeeding and where organizational, compliance, and skill shortages have slowed progress. In order to advance to the next level:

• Double down on your early success. You have a mix of partially automated and fully automated processes. Examine what’s worked for the mature digital processes. How did the project start, and how were obstacles overcome? What providers and partners were key to that success?
• Create a SWAT team of digital experts. You are not a document automation rookie; your early success created some valuable insights. Medium-maturity companies often silo and protect digital skills. Start viewing these resources as digital vitamins by organizing and sending them out as subject matter experts to kick-start document automation around the enterprise.
• Put document process improvement on you’re the agenda of you automation center of excellence (COE). Document-focused process improvement is often not a strong focus of automation COEs, and this is an oversight. Automation COEs develop a pipeline of document automation projects with formal processes to retrieve ideas from the business and revive them.

High Maturity

Congratulations! Your score means that your digital document processes and technology are advanced!

At this level, your organization has a solid digital infrastructure that you can continue building on. Take advantage of recent advances in automation to see even greater benefits. Mature companies should:

• Expand on early success with AI for document analytics and text mining. Build on initial point solutions to create a shared service to support use cases across the enterprise.
• Extend expertise and skillsets for document automation to business end points. Develop guidance for use of automation tools such as RPA, document creation, dynamic forms, workflows, and document technologies. Guidelines should help your employees more effectively extract data for business developers.
• Experiment with emerging document and related technologies. The potential is vast for AI to transform many business processes. Think of building a digital workforce of intelligent assistants that support employees to proactively complete document-related tasks. For example, self-service automation can autonomously support customers and employees who need documents created at the point of service. Exceptions can be handled with machine learning and predictive analytics.