Faberwork’s Notes and Trends series offers new approaches and tools for companies to proactively address uncertainty and risk. Here we look at the reinvention of an old tool – technical documentation.
Business planning discussions often begin with the enormous opportunities created by changes in our technology and economy. But, before long, the discussion focuses on uncertainty and risk. Uncertainty and risk loom large in our business and professional lives. Tools to control or at least manage them are critical to reducing our stress and unlocking the profit potential of all the change around us.
Documenting the failure of documentation
The greatest symbol of the failure in traditional documentation has to be the U.S. Tax code. It funds the machinery of the U.S. Government which needs a mere six Trillion dollars a year to run. The Standard Federal Tax Reporter has at least 70,000 pages and the Code is generally incomprehensible to all but a narrow set of experts who often work on only a few sections.
It is a model we all want to avoid but should remember. The number and size of business technical manuals from hardware to software has ballooned. And the reasons are easy to see.
Basically, right now the old-school approach to technical documentation in many companies involves a big user manual that attempts to embed everything in one place and is generally text. The user is expected to search dictionary fashion until they are satisfied that they have in fact obtained the required information.
And what about the user?
From the user’s perspective, they are often left wondering why they have to read or search an entire voluminous manual if they’re only interested in a small piece of information.
It’s a logical question that needs answering, especially because the search can often take more time than is anticipated or allocated. This leaves the user with less time to devote to technical research even as its volume has surged. The term information overload is really inadequate to describe the environment most employees face when needing to find information in a technical document.
And did we mention that many of them are working from home? The user interface experience with emails, notices and huge data manuals is often a bit of a fog. So, as the technical manuals have grown, the attention span of the user has become ever more squeezed.
The current documentation structure can be summed as:
- Placing the burden of inquiry description entirely on the user, who must determine the relevant features
- Lacking a seamless sequential arrangement that can vary with the user type. One size does not fit all.
- Providing a single explanation for one type of user and not a generalized educational instruction.
- Missing a modern UI with diagrams, screenshots, or visual aids.
AI comes to UI
There is a solution—Synthesis AI.
Most users of technical manuals need a quick education on a narrow topic. And the operative word here is education. Efforts to employ AI to improve education have some of their roots in the formidable work of DARPA and its AI Next initiative in 1987. And Faberwork is bringing it to technical documentation, which is often narrow but an extremely complex bit of education.
With technical support the type of user really matters. They can vary and each has its own reasons for a technical inquiry. Each type of user can, however, benefit from an enhanced process. That educational process can be based on scenario and/or include videos, searchable videos, role-specific and content-specific searches. The current system of tedious, time-consuming and manual searching offers little overall compared to the enhancements which are possible.
How does this new technical support work?
Suppose you are a technician trying to understand an aspect of an energy management system. These systems are complex, but you only want to decipher a little piece of this puzzle. Instead of having to read the entire documentation or searching it, AI synthesis can give what is needed concisely and quickly.
People prefer videos and Faberwork can make the UI for most inquiries into small videos and put a voice over them in a consistent and pleasant tone. Search is still available but now, Synthesis AI makes it possible to search either the text or the video for the needed information. Using Synthesis AI, the technician under pressure could bypass watching a 3-minute video and get exactly what is required in 30 seconds.
To facilitate this, there should be a readily accessible link to a brief video showcasing the specific feature set. The document should include accurate and relevant screenshots, as well as video sequences. The use of a consistent professional voice and speech modulation as well as the use of signal processing and speech synthesis AI tools ease the communication with the researcher. Searchable help is a key element.
Quick video links for each feature set enhance visual accessibility and provide a dynamic understanding of functionalities. Visual aids complement the text, catering to diverse learning preferences for a comprehensive learning experience. Proper screenshots in documentation add clarity, allowing users to visually connect with described features.
The Faberwork Model
Faberwork has embedded the new UI capabilities in search techniques, creating a unique and proprietary model. Faberwork recognizes that there is a better way than sending users to the technical dictionaries that waste time and can easily confuse the reader with an overflow of technical jargon.
Faberwork seeks to shift the current dictionary-like presentation—which lacks a seamless sequential arrangement suitable for all user types, exhibits a process flow that is not appropriately structured for user guidance and does not include diagrams, to a scenario-based, more detailed, video-based role-specific approach.
Scenario Based
The user can skip guessing the right keywords to search for in the documentation and worry the search is incomplete. Instead, the search can be based on a scenario of events and letting the model identify the technical terms available.
More detailed
The output of a search utilizing synthesis AI is as narrow or as extensive as the scenario demands. Quick questions get quick results, but complex questions are enumerated in full.
Video-based
UI for the modern user relies on video technology. Think of a “how-to” inquiry and a technologic-specific video. This can include individualized flow diagrams.
Role-Specific
Because the context of the problem can be related by user type and scenario, the tech support provided can be AI intuited into Role-Specific output into an easy to digest UI. This tailor-made Documentation delivers no superfluous Information, only relevant Help, and Module Help content, which is assembled to deliver the final Role Specific Documentation. The benefits include increased user efficiency and better UX.
With the new approach of sequential flow, the features are presented in the order of how the application is configured and utilized by the user. Specific functionalities are systematically listed along with corresponding screenshots.
The two main benefits of sequential flow are sequentially presenting specific functionalities in the documentation, complemented by pertinent screenshots. This enhances clarity and fosters an intuitive grasp of the features and their capabilities. This organized approach also facilitates effective navigation and comprehension of features, improving the overall user experience.
Help Section Integration
Our model incorporates a help functionality as other documentation does. But ours is a Context-Specific Help. The model dynamically creates a vHelp. This is ‘help’ with Help that goes beyond what current documentation offers. It is ‘help’ that dynamically appears on the user interface and gives a dynamically determined role-specific display. The user gains new benefits from our help. It is seamless, and provides instant access to detailed information in a new and digestible interface.
A final note
Don’t expect the IRS to implement anything like this by April 15th.
