How to Build BA Processes - Part 1: Understanding the Foundation

Practical lessons from real projects, without turning analysis into bureaucracy

Introduction

Business Analysts often find themselves in situations where they are expected not only to perform analysis but also to define how analysis should be conducted in the first place.

This usually happens for two reasons:

·       There may have been no BA on the project before, so requirements were handled informally by product owners, project managers, developers, or business stakeholders.

·       Some form of BA process may already exist, but it no longer works: it is too vague, too heavy, too fragmented, or simply disconnected from the real way the team delivers.

In both situations, the symptoms are usually similar: unclear tickets, repeated misunderstandings, hidden dependencies, delayed decisions, scope drift, and a lot of wasted time in clarification. Teams often try to solve this by adding more documentation, but documentation alone rarely fixes the underlying problem. If the process around communication, validation, prioritization, and change handling is weak, even the most beautifully written requirements will not save the delivery.

I have had to build or rebuild BA processes from scratch in several different environments: multi-vendor setups, cross-platform product teams, and projects where analysis existed only at the discovery stage and then disappeared at the moment when the team needed it most. The contexts were different, but one lesson repeated itself every time:

A good BA process should make work easier for the team, not just more formal

This article is about how to build BA processes in a practical way: what should be included, what common patterns exist, how to adapt them to different delivery models, and what lessons are worth remembering if you want the process to be useful rather than theoretical.

📖 Article structure: 

This is Part 1 of a two-part series. Part 1 covers the foundations - what BA processes mean, why they need to be built from scratch, common patterns, and what should be included. 

Part 2 focuses on how to actually build them, how to tailor an existing process, practical advice, and common mistakes.

What BA Processes Actually Mean

When people talk about BA processes, they often reduce them to documentation standards. In reality, BA processes are much broader. They define how a business need is understood, clarified, transformed into delivery-ready scope, and supported throughout implementation.

In practice, BA processes usually include:

● understanding the business problem or opportunity; 

● identifying stakeholders;

● eliciting requirements;

● analyzing and structuring information;

● documenting requirements in the right format;

● validating understanding; 

● supporting prioritization;

● helping the team during implementation;

● managing requirement changes;

● maintaining visibility of decisions and dependencies.

This distinction matters because on many projects, the issue is not that there are "no requirements." The issue is that there is no consistent path from request to implementation.

For example, on one project in the utilities domain, the team included mobile, web, backend, and integration streams. From the outside, it looked like requirements existed because tickets were being created. In reality, the Product Owner on the client side often created tickets with very limited detail, frontend work depended on backend endpoints that were not prepared in advance, and another external design team produced designs without checking technical feasibility with the development team. So the problem was not a lack of activity. The problem was the absence of an analysis process that could connect all these moving parts early enough.

That is an important point:

BA process is not just about writing things down. It is about creating a system that allows the team to understand, align, and deliver.

Why BA Processes Often Need to Be Built from Scratch

There are several common situations where building BA processes from scratch becomes necessary.

One is when there was no dedicated BA role before. In such cases, analysis work is usually distributed across several people. Product Owners create tickets, PMs track scope, developers clarify business rules directly, and stakeholders share expectations in meetings. This may work for a while, especially in small or fast-moving teams, but once dependencies increase, hidden gaps begin to show.

Another common situation is when BA processes exist, but they are ineffective. They may look structured on paper, but in reality teams bypass them because they are too heavy, too slow, or simply not useful.

A process that people avoid is already telling you something important.

A third trigger is growth in complexity. More systems, more teams, more vendors, more dependencies, more stakeholders - all of that increases the cost of ambiguity.

I saw this very clearly in a large multi-vendor environment in the travel and rentals domain. Several dedicated teams worked on interconnected parts of the platform, and multiple BAs were involved, but there was no clear leadership or shared ownership of the analysis landscape. One of the core problems was that there was not even a common understanding of the current state across the teams. It is very difficult to improve a process or define future changes when different people have different pictures of how things work today. In that situation, building a BA process meant first restoring visibility: splitting BA responsibilities by subsystem, setting up regular knowledge-sharing between analysts, and working with business stakeholders to map the current-state business processes. Only after that did future-state discussions become productive.

This is why BA processes often need to be rebuilt, not just built. As projects evolve, the original way of working may stop matching the current reality.

Basic BA Process Patterns

There is no single universal BA process, but most projects follow one of three patterns: linear, iterative, or hybrid:

• A linear pattern moves from request to analysis to documentation to validation to delivery in a relatively sequential way. This is useful where control, approvals, or fixed-scope coordination are important.

• An iterative pattern is more common in agile and product teams, where requirements are progressively elaborated and refined through recurring cycles of discussion, detailing, validation, and delivery.

• A hybrid pattern combines both. In my experience, this is the most realistic approach for many teams, especially when there are multiple parties involved. You may need structured up-front alignment for scope, dependencies, and responsibilities, but still keep detailed implementation requirements lightweight and adaptive.

The utilities project I mentioned earlier is a good example. The team could not rely on a purely informal agile flow because there were too many cross-stream dependencies: mobile, web, backend, API integration, and external design. At the same time, a heavy documentation model would have slowed the team down even more. What worked there was a hybrid setup: structured requirements documentation in Confluence, short Jira tasks linked to detailed requirement pages, and several types of refinements with different purposes. Internal refinements were used to identify dependencies and technical blockers early. Co-refinements helped align expectations around integration points. Sessions with the design team helped ensure that proposed designs were realistic from a technical point of view before implementation discussions went too far.

The lesson was simple:

Process structure should reflect the actual risks of the project. Where dependencies are complex, communication checkpoints matter more than perfect templates.

What a BA Process Should Include

If you are building a BA process, it helps to think not in terms of "documents to create," but in terms of "problems to solve." In most cases, a workable BA process should cover at least the following areas.

1. Intake or request initiation

The team needs to understand how new requests appear and what minimum information is needed before analysis starts. If requests enter the flow chaotically, the rest of the process will stay chaotic too.  

In some teams, even a simple request template can already improve quality significantly:

• what is needed;

• why it is needed;

• who requested it;

• what problem it solves;

• what systems or teams may be affected.

• 
  

This does not need to be bureaucratic. It just needs to be enough to start meaningful analysis.

2. Stakeholder identification

One of the fastest ways to create rework is to validate requirements with the wrong people - or with only one type of stakeholder.

This becomes especially important in multi-team or multi-vendor environments. In the travel domain project, clarifying responsibilities by subsystem was not just an organizational decision. It was necessary to make stakeholder engagement manageable. Without clear ownership, analysts can easily duplicate work, miss dependencies, or make assumptions based on incomplete local knowledge.

3. Elicitation and clarification

The exact elicitation methods depend on context: interviews, workshops, observations, document analysis, ticket reviews, data reviews, or process walkthroughs. But the point is always the same - gather enough information to reduce ambiguity before the team starts implementing assumptions.

On the sports retail project I joined at a late stage, one of the biggest issues was that BA activity had effectively stopped after discovery. The PM was left trying to manage scope and requests, but he was overloaded, and some requests were simply not transformed into tasks at all. Even when tickets existed, they lacked sufficient detail, so the team spent too much time on ongoing clarification. By the time I was involved, the client was already dissatisfied and the release timeline had been affected.

In that situation, rebuilding the BA process did not require something innovative. Quite the opposite - it required restoring basic but essential practices that had been skipped: proper refinements, scope prioritization, estimation discipline, and structured bug assessment.

Sometimes, process recovery is not about inventing something new. It is about reintroducing practices that should have been there all along. 

4. Analysis and structuring

Raw stakeholder input is rarely complete or consistent. Good BA process should define how information is structured, challenged, decomposed, and validated.

This can include:

• clarifying business rules;

• identifying missing information;

• exposing contradictions;

• mapping dependencies;

• modeling current and future processes;

• decomposing scope into manageable parts.

On the travel platform project, mapping current-state business processes with business stakeholders was one of the most valuable steps. It gave the team a shared understanding of how things worked now, where the pain points were, and where the proposed improvements actually belonged. Without that current-state view, improvement discussions would have remained abstract.

5. Documentation

Documentation should be sufficient, usable, and adapted to the team's delivery model.

The utilities project taught me again that the problem is often not that documentation is missing, but that it is fragmented or disconnected from execution. What worked there was a simple but disciplined structure:

• detailed requirements in Confluence;

• concise task descriptions in Jira;

• clear linking between Jira items and the related requirement pages.

This kept implementation tasks lightweight while preserving context in a central place. It also reduced the need to repeat the same explanation in every ticket.

The exact artifact set can vary, but common elements include:

• business need summary;

• requirement pages;

• user stories;

• acceptance criteria;

• process diagrams;

• decision logs;

• dependency notes.

6. Validation and prioritization

A BA process should define how understanding is confirmed and how priorities are agreed. Otherwise, scope tends to become a mix of assumptions, urgency claims, and unofficial promises.

On the delayed retail project, scope prioritization became one of the recovery tools. Once everything is already late, it becomes painfully clear that not every request is equally important. Formalizing prioritization helped focus the team on what truly mattered for release.

7. Delivery support and change handling

Analysis should not disappear once implementation starts. The team still needs ongoing clarification, support during refinement, and structured handling of scope changes.

This is particularly important where dependencies exist between streams. On the utilities project, internal refinements were valuable not only for clarifying requirements, but also for identifying where frontend could be unblocked through mocking backend endpoints when backend was not ready yet. That is a good reminder that BA process is not only about documenting expected functionality. It is also about creating the communication flow that helps the team keep moving.

🔗 Continue to Part 2

You now understand what BA processes are, why they often need to be rebuilt, which patterns to consider, and what elements they should include.

In Part 2, we move from theory to practice:

• How to actually build a BA process from scratch

• How to update or tailor an existing BA process

• Practical advice that makes the process work

• Common mistakes to avoid

• Final takeaways and a comparison of weak vs. healthy BA processes

  
  

👉 Continue reading: "How to Build BA Processes from Scratch - Part 2: Building, Tailoring, and Sustaining the Process"

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