Organizations, no matter how big or small, have processes and procedures. Some are smaller and more specific; others are more encompassing, but all of them are vital to how a business runs.
Despite their importance, many management teams still rely on basic documents, both paper-based and in basic spreadsheets and document files, and while this works, it keeps processes static and can be tough to adapt to changing business needs.
But turning these documents into practical tools has traditionally required technical development, as well as coding knowledge and software teams. Recently, however, AI is allowing businesses to use platforms like Pave to move from written processes to working applications.
Before beginning to turn all documents into apps, it’s important to understand the benefits of doing so.
Why Do It?
Process documents tell your staff how work needs to be done, a key part of their training and ongoing performance within a company. Employees must read, interpret, and manually follow the steps within the documents.
With this information existing in written format, processes can be passive and don’t encourage active participation. Also, completion visibility requires manual checking and logging from management, and consistency largely depends on the person who created the document.
Turning them into apps tries to avoid these by creating an interactive, self-tracking, and consistent workflow. Processes become more visible and accessible throughout the company.
Rather than just recreating documents digitally, the aim is to create something employees can actively use based on the expertise and processes the company already possesses.
However, the process isn’t as simple as just typing out a document into the platform. Here are some key steps to help you translate your process documents into functional apps.
Every App Starts with a Process
Before starting to develop an app, it’s important to first understand the process you want to create. Although process documents describe how work should happen, AI provides a way to turn this into the basis for an application.
This requires an organization to understand and be able to declare success states for the app they want to create. Without taking this step, companies run the risk of creating software bloat that doesn’t serve a clear purpose.
Once the process is understood, AI can begin turning that information into an app.
Turn Requirements Into Draft
Once the process that is being used is fully understood, the creation can begin. AI can translate the mapped process into an initial structure.
From here, the AI can help build the core workflow for each process and allow the designer to test the app using realistic scenarios. At this stage, it’s important to compare what happens in the app against what was expected during the real process.
At this stage, avoid trying to generate the entire finished application in a single prompt; this can be both frustrating for the user and difficult to deliver. It is also important to avoid assuming that because something works technically, it will work operationally; it’s important to test fully.
Once the basic framework is in place and the core process can be replicated, then it can be built upon.
Onboard and Integrate
After the creation and testing, the app will be ready for integration. AI can help with connecting and establishing points that the new app can fit in with the existing technology environment.
This should be done in smaller batches within the AI framework to allow more stress-testing and bug finding before complete launch. This will also allow natural-language changes, making it easier to adapt. It will also allow feedback from early users to be quickly translated into refinements.
For this step, don’t forget that AI-generated changes will need validation themselves. It is also important to monitor how the new app is connecting to everything to avoid creating new points of friction.
Steady and purposeful integration helps establish the new app firmly and securely.
Maintain and Improve
Once the app is up and running, the work is not finished, and leaving it might cause it to become outdated and unusable quickly, costing the business money. AI platforms help keep the app evolving as the process does.
Whilst the app is active, keep gathering feedback and usage information to help keep modifications useful and relevant. Test modifications before deployment, and make sure to regularly compare the new app against the current real-world process to ensure progress is being made.
It’s easy to forget that repeated AI-generated changes can have a cumulative effect, so make sure to keep track of what changes are being made. At this stage, it’s also important to be aware of how many users are able to make modifications.
Losing track is one of the biggest dangers now facing the new app.
The aim of making an app is to take a process document and turn it into something that your employees can use. The ability to do this takes understanding and flexibility. Although AI reduces the technical barrier required to make the change, it still requires active management and participation.
If done correctly, a process document doesn’t just describe how work gets done; it gives the staff a starting point.
