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Tag: Methodologies

Mapping Success Together: Tips for Inclusive Process Maps

There are numerous things that we can do to make process maps more inclusive; however, while they tend to go against established practices, they offer a range of benefits to making maps more inclusive for all.


A process map should be standardized within a business to map out the steps to achieve a business goal and show sequential steps, tasks, and gateways. There are a few established standards (UML, BPMN, etc.). My aim is not to advocate methods but to encourage inclusive standardization. Consistency is key, as it enables comparison and evaluation and can also assist colleagues with neurodiversities.

Typically, there are two sight-loss personas: low vision and no vision. Low vision is when a colleague has a combination of: fields—the amount of sight you have (half-close your eyes to see top and bottom field loss). The other is acuity, which is how sharp it can be seen (almost fully closing your eyes until the words go fuzzy can demonstrate acuity loss). The huge amount of variation between fields and acuity loss means that it is very hard to get a one-size-fits-all solution to sight loss.

The second persona has no vision. This is typically what you think of when you think of the word “blind.” No vision means no useful vision—you may be able to see something, but you cannot understand it without third-party intervention. Only a small percentage of vision-impaired people have no vision, but it is crucial to ensure inclusivity for them.

Process maps are inherently visual, so the following tips are mostly based on low vision. Low-vision users, with some tweaks, can read process maps if care is taken by the business analysts to make them as inclusive as possible.


Firstly, some whole-map tips. Use a clear font, classified as “sans serif.” These are simple, non-fancy stroke fonts that are easy to read, e.g., Arial and Calibri. Bad examples are brush script, harlow solid, and monotype cursive. Another consideration is the font size. Typically, it is best to produce it in large print, size 14, or giant print, size 18. This is not just helpful for those with low vision but will also reduce eye strain for fully sighted users. San-serif fonts are also dyslexia-friendly.

Secondly, make the connectors, or the lines between process steps, consistent in both thickness and color. The thicker the better, as there is more chance of seeing them, but they must also be in proportion to the other objects, or else it will look so odd that few people will engage seriously with the map. This is the balance between usability and accessibility.




Thirdly, low-vision users will zoom in a lot more than they are used to, sometimes only having a few letters on screen. With this in mind, there are two things that must be considered: Navigation: ID codes. By coding every step, data object, or note, you allow a low-vision user to navigate quicker using metadata instead of engaging with the full object. Each object class should be different; typically, I use process steps as numbers, notes as N1, N2, etc., and data objects as D1, D2, etc. Depending on which software you use to map your process, this can also assist any user in searching quickly and efficiently.

Screen real estate is also an important consideration. The more you zoom in, the less you can see the bigger picture. So, if objects are spaced far apart, it’s harder to understand the map. I recommend placing objects close together. Where you have multiple connectors coming out of an object, line them up so they overlap, looking like one connector, and have them branch off with the connector text as close to the break as possible, allowing someone who is zoomed in to be able to follow with ease.


Fourthly, color is important. There are several vision-impaired color schemes, such as yellow on black, white on black, etc. These are all highly subjective but share one common feature: they are high-contrast colors. My advice then is not to use similar colors, such as black and grey, white and silver, or white and yellow, as these types of pairings are very hard to see and can be easily missed or unreadable. Neon colors are highly effective, as most accessible technology offers color inversion, and when you invert a neon color, it stays the exact same shade, meaning there can be no misunderstanding in color coding like RAG systems. I advise only using one color scheme, or at most, in the case of impact assessing a process, a RAG for change size and blue for new—all in neon colors.

Finally, for all users, but specifically No Vision users, think about object semantics. By this, I specifically mean connector lines. Accepted practice means that we have no arrow heads on lines, and a double arrow head is assumed. This is presumably to make it look nice. A screen reader, though, has no context for this as there is no semantic instruction to relay to the user. Therefore, adding doule arrow heads will allow the semantic meaning to go through the connector. This is because a screen reader will consider the connector itself, not the thing it is connected to, which is what a person with sight will do. All a screen reader will visualize is a line, and a sighted user will see the line and the objects connected.


To summarize, process maps are visual. We can make them inclusive of low- and no-vision users by adapting our frameworks and standards. Specifically, by looking at font type and size, object layout and identification, color schemes, and the semantic meanings of diagram objects, we can minimize the risk of low- or no-vision users not understanding, thus making the business more inclusive and effective.

These tips are by no means exhaustive nor gospel, so please feel free to use them as a starter for ten, and hopefully they will help you kickstart your own inclusive process map designs!

Business Analysis: How and Why Do I Need To Evolve?

Without a doubt, artificial intelligence (AI) is here to stay and is not going anywhere. Still, it would and has even started disrupting the status quo of many industries and organizations. Well, this is an undisputable, crucial innovation. Still, I would gladly refute Elon Musk’s’ claim that “We will have for the first time something smarter than the smartest human. It’s hard to say exactly what that moment is, but there will come a point where no job is needed” (Marr,2023).

The human factor must be considered in every career path or industry; however, professionals in every space and sphere must evolve with the dynamic and changing environment.

Why do we need to evolve?

Regarding my specialization as a Business Analyst, how and why do I need to evolve?

Recently, there has been a surge in the search for business analysts. This is not because this is a new field; instead, it has existed since the Middle of the Old Stone Age, when the ancestors were able to effectively adapt to the changing natural environment, identify their needs, problems, and opportunities, and develop solutions to make their abode livable and habitable.


What is Business Analysis?

According to the BABOK Guide V3, Business analysis enables change in an enterprise by defining needs and recommending solutions that deliver value to stakeholders. Business analysis enables an enterprise to articulate needs and the rationale for change and design and describe solutions that deliver value.

The business analysis field has undergone several nomenclature changes and could be referred to by different names in different industries. Some famous names include Business systems analysis, business process analysis, functional analysis, product ownership, systems architecture, project management, usability analysis, user experience consulting, operations assessment, and technical writing.


Business Analysis Requirements

The BABOK Guide v3 views requirements as a usable representation of a need and a design as the usable requirement of a solution. Still, both concepts can be used interchangeably and primarily depend on the context of being used or adopted. Requirements need to be identified, collected, modeled, analyzed, validated, verified, traced, prioritized, managed, and maintained in the lifecycle of a project (Pre and post-project stages). Still, they are all related to a business problem that requires a solution. It could be in the form of an organizational objective that must be met, a business process that needs to be optimized, and an existing solution that needs to be improved or even retired. The BABOK guide v3 defines a Context as the circumstances that influence or are influenced and provide an understanding of a required change. This explains that requirements are broad and depend on the context, such as industry, regulation, project, weather, attitudes, behaviors, etc.




Unpacking BA requirements for Artificial Intelligence

Business analysts should not view themselves as AI experts but understand that they exist to drive change while still understanding the capabilities that AI provides and its complexities. Business analysts must see themselves as a bridge between business needs and AI capabilities.

Understanding the complexities of AI algorithms may and may not be a hard nut to crack; however, with a fundamental understanding of Natural language processing/ machine learning and knowing that most AI tools have been embedded with the critical technology to understand human language, as well as the ability to sieve through large data sets and establish a pattern or relationships, could serve as helpful information. Business Analysis could also establish broader knowledge of AI capabilities.

Also, the core of business analysis is need identification and solution generation. Both are valuable, but the most critical is correctly and efficiently identifying existing needs or problems, thus providing room for developing requirements and generating solutions.

This brings us to the question: can AI help in need identification or problem assessment? Realistically, with established data and available documentation, AI could help identify a need, but Hey, that need would be missing users’ humanity. Whatever solution is generated should provide or enhance satisfaction. However, can AI understand the complexity of the human emotion? With AI, we could develop the goals, desired outcomes, and key performance indicators (KPIs) and define roles and responsibilities, but how can usability be assessed?

With AI in business analysis requirements comes data quality, security, and privacy requirements. Every requirement generated for BA activities must answer these 3 data prongs. How reliable is the requirement gathered? If a requirement is trustworthy, it could speak to its quality. Was the requirement confirmed, verified by necessary stakeholders, and validated to align with identified needs?

To achieve these three tasks, the requirements must be specified and modeled to fit the organization’s environment with due consideration of the stakeholders involved. The modeling can be in the form of matrices or even diagrams, for which AI could be beneficial. Still, the prompts must be correct, which reflects the data quality and reliability. Using AI to generate, specify, or even model requirements (inexhaustive) would lead to data security and privacy prongs.

Privacy and security are critical issues in the professional world, not just business analysis. Before every BA task, how AI should be adopted and what data should be provided as AI prompts need to be addressed. There is a need to protect user privacy and define adequate security measures, as IT systems are susceptible to attacks. Privately owned AI tools can still be attacked; strict security and privacy rules must be strictly followed.

This is also very important as some requirements can serve as Unique selling points for a specific business or even a trade secret. In this situation, the use of AI might be optional.



Knowing that the Business analysis role will continue to evolve as a context evolves or dictates or even as a business dictates while putting Artificial intelligence as an addition in a context, it is recommended that the requirements generated in previous contexts be adequately managed and maintained for reuse. When done correctly, this would enhance knowledge sharing as AI could help create a central repository for past project requirements, thus making it easier for business analysts to learn from past experiences and build on existing knowledge, which could lead to overall project success.


Beyond The Happy Path: One Size Does Not Fit All

Up until a few years ago, I used to spend a lot of time working ‘on the road’. I’d spend time traveling between different client-sites, and this would inevitably mean spending far too much time in airports. Business travel is one of those things that sounds really glamorous until you do it, but believe me it soon gets really boring.


When you are a regular traveler, you tend to become very familiar with certain airports and you know exactly how to transition through them quickly. If you’re ever at an airport, you can usually spot regular travelers as they tend to know exactly where they are going, and tend to move at pace.  This is completely different to the family who are checking in with three kids, who are having to refer to the signs, and might have even initially arrived at the wrong terminal. Quite understandably, they often need a little bit more help.

I used to joke that it would be good to have an entrance especially for regular travelers, as their needs are so different (I certainly wouldn’t be buying anything from the duty free store, not even one of those giant airport Toblerones that seem ubiquitous in Europe, but a family may well do). This wouldn’t be practical in airports, but it does highlight a point that has direct relevance for business and business analysis: sometimes you need two (metaphorical) entrances…


Understanding Different Usage Patterns

When defining a process, journey or set of features for an IT system, it’s common to think about one path or scenario through which users will navigate.  This main success scenario or ‘happy path’ is then often supplemented by exceptions and alternative paths which are essentially ‘branches’ from the main scenario.

Yet it is worth considering that different types of stakeholders might have different needs as they navigate through. There might even be benefit in having two entry points. Building on the airport analogy, an experienced traveler probably doesn’t need to be told about the security rules (unless they have changed recently). A new or less frequent traveler may well need to be informed in detail.

This translates to wider contexts too. An experienced user of an IT system probably won’t want lots of dialogue boxes popping up with hints and tips. A new user might need virtual hand-holding as they learn how the application works.  Someone who calls a call center once might need to hear that three minute Interactive Voice Response (IVR) message explaining all about the services they can access via phone, and letting them know which number to press.  Someone who calls every day as part of their job probably doesn’t need to listen to the whole three minute spiel every time they call… Understanding these usage patterns is key.




One Size Rarely Fits All

There is often a desire to standardize processes, journeys and customer experiences. There is benefit in doing this, but the benefit really surfaces when the different users and stakeholders are understood. Understanding whether users will be casual/occasional or regular is important, as is understanding what they are ultimately trying to achieve.

This relies on elicitation and customer research. This is an area where business analysts can add value by advocating for the customer’s perspective. Too often definition and design decisions are made by people in comfortable conference rooms who are detached from what the experience will actually be like. Sometimes those decisions are made by people who haven’t spoken to a real customer in a decade (or ever!).

In these situations we can ask important but difficult questions such as “what evidence do we have that customers want that?”,  “which types of customers does that appeal to most?” or “how do we know this will be a priority for our customers?”.  Using a technique such as personas, when coupled with proper insight and research, can make a real difference here.


As in so many cases, asking these questions can sometimes be uncomfortable. But if we don’t ask them, who will?

Don’t Let Your Software Requirements Die

In the realm of software development, the clarity and accuracy of software requirements are pivotal for project success. Traditionally viewed as static documents to be archived post-project, this perspective neglects their ongoing potential. 


Living software requirements is a paradigm where these documents evolve continually with the software, serving as an enduring source of truth. This approach not only maintains relevance but also actively shapes the software’s lifecycle, promoting adaptability and precision in development processes. 

They ensure that as software grows and changes, the documentation is not left behind, thus avoiding the pitfalls of outdated or irrelevant information – because often zero documentation is worse than out of date documentation!


How requirements slowly die.

Picture this: a new software project kicks off with energy and optimism. The business analyst dives deep, engaging with stakeholders to gather an amazing set of requirements. They craft an impressive functional specification that serves as the project’s North Star, and as the project kicks off, hundreds of tasks get populated into a project management tool like Jira, mapping out the journey ahead.

The software delivery team starts strong. 


As expected, questions and clarifications emerge, evolving the requirements a little. Some tasks need tweaks; others have missing components, and there are even some sew requirements that surface. This is fine (we are agile after all!) – and these changes and additions are all added into the project management tool, as that’s now the source of truth keeping the project on track. 

As the tasks are ticked off, a sense of accomplishment fills the air. Finally, the project crosses the finish line, the board clears, and it’s a wrap. Success!

Or is it? Software, particularly the large, mission-critical kind, is never truly ‘done.’ 

The project may have ended, but the software lives on, continuous adaptation and enhancement are normal these days. But scoping new tasks becomes a little harder, as the detailed system knowledge from that original functional specification, has now changed. The source of truth is now fragmented across completed Jira tasks and buried in comment threads. 

In this scenario, the requirements didn’t just become obsolete; they died a slow death, leaving the team navigating a labyrinth of past decisions and discussions to grasp the full scope of their own software. 




How to keep my requirements alive?

Keeping software requirements alive is pivotal for the long-term health and adaptability of your system. Rather than relegating these crucial insights to a static document, consider embedding them within a collaborative platform accessible to the entire organization. This living, breathing approach ensures that requirements can evolve alongside your software, reflecting real-time changes and decisions. Here’s how you can make it happen:


1. Centralize requirements and allow collaboration: Choose a platform where stakeholders across the business can access, review, and iterate on the requirements. This system should be the go-to source for everything related to what your software does and why, and platforms such as Userdoc are specifically tailored to this task.


2. Project management integration: While the main body of requirements should live outside, ensure there’s a seamless flow of information into your project management tools like Jira. This helps in translating the high-level requirements into actionable tasks and ensures day-to-day activities align with the broader goals.


3. Continuous updates and iterations: Encourage a culture where updating the requirements is part of the process, not an afterthought. This keeps the requirements current and relevant throughout the software lifecycle.


4. Embrace AI – AI can be an amazing tool for helping determine what changes could affect other parts of your system, and understanding that when writing requirements for New Feature X, you will also need to update Existing Feature Y’s requirements.


5. Requirements versioning: Just like with code, software requirements need versions and branches. Ensure you clearly denote what features are live, what features are in development, and what features are still being scoped.


6. Living reference for all teams: From development to QA, from business analysts to project managers, ensure that everyone references and contributes to the same set of requirements. This alignment prevents information silos and fosters a unified understanding of the system.


7. Long-term business asset: Beyond project completion, maintain these requirements as a living record of what’s in place. This becomes invaluable for training, onboarding, and new developers understanding the system’s capabilities and limitations. It also ensures the source code isn’t the only source of truth for the system’s functionality.


Transforming your software requirements into living documentation is a strategic move that pays dividends throughout the lifecycle of your software. 

And the thing is, it’s not actually doing any extra work – it’s just simply unifying the place where that work is done, and fostering a culture of continuous collaboration and documentation.

Embrace the concept of living software requirements and watch your software, and team, move faster with more confidence.

Unveiling the Unsaid: The Power of Subtle Stakeholder Cues

When eliciting information from stakeholders, often what isn’t said can be as significant as what is said. Of course, the information that a stakeholder explicitly mentions is of crucial importance, but often there are subtle and nuanced details that aren’t obvious unless you look for them. Perhaps a stakeholder subtly pauses and looks uncomfortable and avoids answering a specific part of a question. Or perhaps they use a qualifying word like “usually” or “sometimes”. Either way, it is crucial to probe further and find out more.


Hearing What You Expect To Hear

Looking out for these clues is important, but is easier said than done, particularly when time is tight. When there are a number of stakeholders to speak to, it is easy to get drawn into a pattern of hearing what you expect to hear. We’ve probably all experienced this: after three people from different departments outline a process consistently, speaking to the fourth and fifth person seems like ticking a box. After all, they are going to just confirm what the first three people have described, surely?

That might be the case, but equally they might have additional insights that the original three did not. There is presumably a reason that they have been selected to participate in the elicitation activities, perhaps because they have a different perspective on things. Yet, it would be easy to let those discussions be swayed by the conversations that have happened before. To almost go on ‘autopilot’ and lead the stakeholder in a particular direction. It is worth being especially aware of those subtle cues and nuances in situations like this.

An Example

Imagine interviewing a stakeholder in a finance team about the invoice payment process. You’ve spoken to other stakeholders previously and you’re pretty sure you know the process:

“So, you get an invoice in, and as long as there’s a purchase order number on there, and as long as it’s approved, it gets scheduled for payment, is that right?”

“So, yes, mainly…. Yeah, mostly that’s it.”


It’d be easy to move on from this. It would be easy to assume that they are confirming some of the key decision rules (if an invoice has a purchase order number and has been approved, it gets scheduled).  But the stakeholder has added qualifying words: mainly and mostly.  These are easy to miss, but definitely require probing.


Probing might go like this:

“I noticed you said that this is mainly how the process works, are there other circumstances?”

“Yes, only very occasionally though. Sometimes, we get ‘proforma’ invoices that have to be paid immediately. We have a different process for those. Also, there are some cases where we pay up front by credit card. For example, booking training and conference places. That has a slightly different process too.”


Suddenly, a whole new set of facts becomes available. If this were a real situation, this would lead to further probing (e.g. “Are there any other times when the process operates differently?”, “Is there just one corporate credit card, and if so who is responsible for it” etc, etc).




Make Sure They Feel Heard

Of course, probing this way is important to ensure that nothing crucial is missed. However, genuinely listening is important for another reason too: to ensure that people actually feel heard.

If you’ve ever had the experience of speaking to someone who appears to be preoccupied, and is perhaps presuming what your responses are, you’ll know that this rarely feels great. As analysts, it’s important that we empathize with and genuinely hear what people are saying.

Listening in this way will help uncover important information. It is a crucial and often taken for granted skill, but one that we can probably all hone and improve upon!