Business proposals are rarely written from scratch, they usually comes from the culmination of similar documents from the knowledge base of the company. With this in mind, wouldn’t it be super useful to gather relevant information in a few easy steps instead of having to trawl through archives of files? Using key information from old documents to place into new proposals or simply to use for guidance and insights? Of course it would, that’s why we at Headshift | DachisGroup put ourselves to work on an automatic tool for document generation. We focused on proposals, but as the output document depends entirely on the library’s content, this system could be applied to many other mediums.
We knew it needed to be simple and fast. More efficient than just manually browsing folders and searching through masses of content.
First we set out requirements. Users should be able to:
* Create tables of content
* Add, remove & edit content
* Search with a selection of filters
(i.e. business sector, proposal type)
* Export output
If you want to try this week’s example, do your design now (no more than 10 minutes, remember) and then go on reading.
Our first consideration was the relevance of results. A filter based search system needs to be built in a way that gives balance between the volume and accuracy of results. This implies that the labelling system should both include an exhaustive categorisation for the single item and an accurate differentiation among each tag, so that the result list appears to be complete, precise and effective in relation to the search terms. In other words, the filter system has to manage the complexities of searching while respecting the relevance of the results. In this way, the system would help users to narrow their search step-by-step, decreasing the number of operations needed to reach their targeted result.
Image may be NSFW.
Clik here to view.
The second issue was regarding content editing tools. They were revealed to be a primary feature, not only allowing users to modify the content but by enabling them to source it from the library and create original content. With this feature, the system would be a tool to support the exploration and elaboration of the knowledge base.
Image may be NSFW.
Clik here to view.
The user’s control is also an aspect we raised, especially in relation to the different approaches the system can be based on. We identified two distinct paths: one, creating a starting point to retrieve targeted contents. The other, building a one-stop-shop to facilitate content creation. In the latter, the interaction flow is strongly focused on users’ actions, allowing several iterations along the user journey. In this approach the user’s control over the process needs to constantly show actions taken and options within the interface.
The solutions had interesting parallels:
Keeping the process in one page.
It helps shorten the journey and allows users to easily change options and filters though the sections. It is also gives an effective overview of the whole document architecture, helping to give a full understanding of the output. Two different layouts were used for this purpose. The first, a 2 or 3 column wizard, where filter options are shown progressively on narrowing layers. This solutions results would be particularly useful as the filter options give the output. The other idea places filter options on an overlay, this is the opposite layout to the previous: while the wizard put filters on a higher IA level, the overlay trick can be used for a document-based tool, so that the content is the starting point to explore the library and add information.
Helping the users understand the process.
In a consequential process, it’s very important to avoid disorientation. Users should always understand the action they’re required to take, those they have taken and those they are about to take. Most of all, they should be aware of the locations of sections and be able to identify them if they need to make changes. Both a progress bar and hints are helpful solutions. The progress bar, or a similar kind of process description, let the user identify the context of the action and get an overview of the full journey. On a complementary side, hints explain features in detail; they provide suggestions on how best to use the tools and, guide the users through actions, helping make decisions.
Using filters VS bookmarking.
This is mostly referring to library management and implies some technical considerations we couldn’t fully approach during our short exercise. However, on an initial reflection, filtering and bookmarking are clearly two different ways of conceiving the system, one centralising the source for categorisation and the other one expanding it. Filtering implies a strong control on content categorisation and labelling, it requires an administrator maintaining a coherent taxonomy inside the system, making the system a self-sufficient environment. Bookmarking however, allows a multiple selection of sources, so that it configures the system as an open platform for extended knowledge management.
Independently from the solution implemented, the design should take into account the system needs to be adaptive to different sources and outputs, whether they are exportable documents, wiki pages or lists of feeds.