(Illustrated above) A financial trader often needs to find previously completed transactions in his trading application. He can identify individual trades by their unique trade numbers or a combination factors such as the security traded, the quantity traded, and which trader in his group completed the deal.

An architect names and saves a selected structural element as a reusable template within her building modeling application. She applies a variety of searchable attributes to the new template, including the building element’s function and material composition.

A scientist identifies a new clinical sample in her laboratory information management application using a code for the tissue’s donor and the experimental treatment that it will undergo.

How do targeted individuals currently identify specific instances of their workplace artifacts — especially those items that are involved in the tasks and larger activities that your team is striving to mediate?

Are existing methods based on free form names? Do they contain categorical identification attributes?

What important variations in identification approaches can your team find within and across targeted organizations?

How might your team translate existing identification methods into your application concepts? How could existing methods be extended?

What object identification information will satisfy the majority of cases? How much identification might be too much?

What customizations might your team envision to support uncommon object identification needs within targeted organizations? Will this functionality provide enough value to offset its added complexity?

How will workers enter object identification data in your sketched functionality concepts? What innovative methods might your team envision to valuably decrease these efforts?

As volumes of data build up over time, what secondary information could also serve as identification for different types of interaction objects? What implicit attributes could become elements of larger identification schemes?

How might your team’s ideas about such schemes relate to your other design responses for supporting work in the context of volumes of information?

Do you have enough information to usefully answer these and other envisioning questions? What additional research, problem space models, and design concepting could valuably inform your team’s application envisioning efforts?