Your business knowledge gives an AI project direction.
A category or spreadsheet formula often holds decisions refined over years of work. Making them understandable helps shape a tool that respects how your business operates.
Business knowledge gives meaning to the information and decisions in a project.
Why are two similar amounts classified differently? Why does a calculation use this value rather than another? A file can show the result of a decision without explaining the reason behind it. For people who have done the work for years, the answer can seem obvious.
In a project using AI, that experience provides valuable direction. It helps identify useful information, explain rules and assess the results of an early workflow. We want to give it an explicit place in the design.
Start with someone who knows the work.
When a process needs to evolve, we propose meeting an experienced user to understand the actual work. What are they trying to accomplish? Which situations do they distinguish? When do they know information is correct or an exception needs attention?
Those questions reveal knowledge that goes beyond a description of the screens. A category may direct the next stage of a record. A grouping may support a decision. We look for the reason behind these choices so that the people who understand the work can help judge the next tool’s usefulness.
Look at files as a record of decisions.
We also ask for sample Excel files, the objectives behind them and existing calculations. A formula or classification can hold rules refined over years. The file becomes a concrete way to explain the business.
We can follow an example together: where does the value come from, why does it belong to this category and what changes as a result? That process helps identify the information to preserve, the calculations to clarify and the decisions that need to remain visible in the new tool.
Understand the existing tool’s particular mechanisms.
The user understands the task. The person who developed the existing tool can explain particular mechanisms: why a rule sits in a certain place, how a calculation works or which constraints shaped a decision.
Those perspectives complement each other. We propose bringing them together when available and identifying the questions that need answers. The goal is to connect a rule to its purpose and know who can confirm it when the next design is examined.
Make business decisions usable in the project.
AI can help produce an interface quickly. The reasons specific to your company also need to enter the discussion: what a category means, which decision a calculation supports and when a rule changes.
We turn that knowledge into material people can examine: representative examples, clearly expressed rules and questions to resolve. These reference points can guide the design and the help provided by AI. They also let the people who know the business discuss whether a result is useful.
Let users respond to a concrete workflow.
One approach we propose is to prepare a prototype and let the client and a few users try it. The examples they provide give substance to the workflow: find a record, understand a grouping or check a calculation.
Feedback can then address the meaning of the work. Is a category precise enough? Does the result support the right decision? Is a known case missing? These observations help clarify the requirements before preparing data connections. A test database may be considered depending on the project.
From business knowledge to a workflow people can try
01UnderstandUsers explain the objectives, examples and rules.
02PrototypeAn early workflow makes design choices concrete.
03Try it togetherThe client and a few users assess whether the results make sense.
04Prepare connectionsThe data and exchanges needed for the next stage are defined.
A proposed approach. Trials can change the workflow and the questions to address before connecting the data.
Keep business users in the conversation.
A rule explained once can raise new questions as the workflow takes shape. We propose keeping the people concerned involved in the discussion throughout design.
Your contribution can start simply: someone who knows the work, a few representative files and an objective to explain. The experience accumulated in your company becomes a set of reference points for the project. The design team can use them to build, propose and assess the result with you.
Knowledge to bring to a first conversation
✓ An experienced user who can explain a real task.
✓ The objectives that give meaning to classifications and calculations.
✓ Representative examples containing the necessary information.
✓ Particular mechanisms the existing tool’s developer can explain.
✓ People who can try the prototype and discuss the results.
