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Tag: Skills

Learning to Love Compliance

OK, I’m going to let you into a secret here. I genuinely like compliance projects. You know the ones, those projects that people think are really boring because they relate to a change in regulation or legislation? The ones that it’s really hard to get people excited about? The ones that few BAs volunteer for? Yep, those ones!

 

Framed differently, there’s often a real opportunity to shape and scope things in a way that isn’t always the case with other (seemingly more exciting) projects. These projects can be career-enhancing, provide more autonomy and really don’t have to be boring. Or, at the very least, they don’t have to be as boring as they first appear! Let me explain…

 

Pain Reliever or Vitamin

I remember reading somewhere that one question that some Silicon Valley venture capitalists will ask startups when they are pitching for funding is:

“Is your product a pain reliever or a vitamin?”

 

You might think it is better to be a vitamin. Yet, apparently, the answer that investors are looking for is ‘pain killer’. Sure, we might take vitamins some days, but it’s easy to forget. But if you’re in pain, you will soon remember to reach for the pain reliever. So, solving a pain point will likely get people to reach into their wallet.

Think about a change in regulation or legislation. Most people who are part of the core business know they need to comply, but if we’re brutally honest, they probably aren’t that interested. A change in (say) data protection legislation is just a distraction to them. They probably don’t care how it’s solved, as long as it doesn’t disrupt them too much, and as long as it doesn’t cost too much.  In fact, they might even be worried that the legal & compliance team are going to be ‘heavy handed’ and create all sorts of bureaucracy for them.

 

This is an area where BAs can act as a real pain reliever. By working with the relevant business areas and the legal and compliance team, by working with stakeholders to understand enough about the business operations, the solution landscape and the legislation or regulation we can co-create innovative solutions. We can find a balance that works for the different stakeholders, and rather than just achieving compliance, might actually improve things for them too. Imagine that, a compliance project actually leading to improvements!  It is totally possible.

Crucially, we take away a distraction for them. We get far more autonomy and leeway to shape things precisely because they just want the pain to go away.

 

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Understanding The Problem

One of the things I love about compliance problems is the fact that business people usually haven’t pre-determined a solution. Other projects often come with an assumed solution attached (e.g. “Oh, we’re going to implement XYZ system, so we need you to write a couple of user stories”, leading to us having to work backwards to understand the problem).  Usually the brief is really broad (e.g. “Comply with the new Data Protection Act).

This leaves the BA with a significant amount of autonomy and latitude. There will be many ways of solving that problem, and defining the problem space is usually really fun and makes a huge difference to the success. The biggest challenge is people will often think that the impact is small, when actually it is actually far wider ranging. It’s therefore necessary to bring stakeholders along on the journey.

Although every compliance project is different, I typically find starting by identifying and having an understanding of the legislation or regulation is key. Of course, the BA does not need to be a legal expert, but we need to know enough to ask sensible questions and challenge. In many jurisdictions, legislation is written in (fairly) plain language, and you can even start to imagine some of the business rules/impacts that might be implied by it as you read it.

 

However, an important next step is to work with the relevant business and compliance stakeholders to determine the company’s interpretation of the legislation or regulation.  Rarely are these things completely prescriptive. You’ll find words like “appropriate” and “from time to time” and other phrases that show the intent without prescribing solutions. Particularly with new regulations this can be tricky, as there’s no existing convention or regulator judgements to base things on. Ultimately this is often a balancing act, and an area where good facilitation is key.

Ultimately, all of this leads us to a position where we can judge the impact on existing processes, applications, data and more. This is where the requirements or stories get written, but they will trace neatly back to an interpretation of a piece of the legislation or regulation. In many ways scoping can be easier on regulatory projects… a requirement either maps to a piece of the regulation or it doesn’t! (OK, it’s never quite that binary, but it is close).

 

Fringe Benefits

There’s still the challenge of selling regulatory projects to stakeholders. If we can’t get them excited about them, then there’s a chance their attention will wane and they won’t give us the input we need.

This is where our pain reliever/vitamin analogy comes in useful again. In fact, a good compliance project can be both.  A (hypothetical) project to comply with new data protection legislation might ensure we avoid million dollar fines (pain killer) while also providing us the opportunity to cleanse our existing data, so reports are more accurate (pain killer) and we have more flexibility on how we capture future data (vitamin).  This is just an example, but I am sure you get the gist.

So, have I changed your view of compliance projects? Either way, connect with me on LinkedIn and let me know. I’d love to hear your views!

 

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.

 

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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.

 

Conclusion

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.

 

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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?

How Generative-AI Can Help Modernize Your Legacy Software

Legacy applications, those trusty workhorses that have powered your business for years, can start to resemble a classic car.  They might be reliable, but they lack the sleek design and efficiency of newer models.  Maintaining them can be expensive, and they often struggle to keep pace with evolving security threats and changing business needs.  A study found that 70% of enterprises still grapple with legacy applications, hindering their ability to innovate and adapt. But unlike a car you can trade in, replacing these applications entirely can be a costly and disruptive endeavor.

Here’s where Generative AI swoops in, offering a revolutionary approach to legacy system modernization. Imagine a tool that can analyze your aging codebase, understand its functionality, and then generate modern, efficient code that replicates its core functionality. That’s the magic of Generative AI!

 

7 Warning Signs Your Legacy Software Needs Modernization (and How Generative AI Can Help)

1. Frequent System Crashes and Performance Issues: Legacy software, built with older technologies, might struggle with increased data volumes and user traffic. This can lead to frequent crashes, slow loading times, and a frustrating user experience.

Role of Generative AI: It can analyze code bottlenecks and suggest optimizations to improve performance. It can also help identify areas for code modernization to handle larger datasets efficiently.

 

2. Security Vulnerabilities: Outdated coding practices and unpatched vulnerabilities can leave your legacy software exposed to cyberattacks. This puts your company data and customer information at risk.

Role of Generative AI: It can analyze code for known vulnerabilities and suggest potential fixes. It can also help developers stay up-to-date on security best practices by generating code that adheres to secure coding standards.

 

3. Incompatibility with Modern Systems and Devices: Legacy applications might not integrate well with newer software and hardware, creating data silos and hindering operational efficiency.

Role of Generative AI: It can analyze APIs and suggest code modifications or generation for seamless integration with modern software development. This allows your legacy application to communicate and exchange data effectively.\

 

4. High Maintenance Costs: Maintaining legacy software can be a significant drain on resources.  Bug fixes, code updates, and compatibility issues can require a dedicated team of developers with specialized knowledge of the aging codebase.

Role of Generative AI: It can automate tasks like code documentation and code refactoring. This reduces the need for manual maintenance and frees up developers to focus on more strategic initiatives.

 

5. Lack of Features and Functionality:  Legacy applications might lack the features and functionalities of modern software, hindering your ability to compete and meet evolving customer needs.

Role of Generative AI: It can analyze user interactions and suggest improvements to the UI/UX. It can also generate code snippets for modern UI frameworks, allowing developers to create a fresh and user-friendly experience.

 

6. Difficulty in Finding Developers with Legacy Expertise: As technology advances, developers with expertise in older programming languages and frameworks become scarce. This can make it challenging to find qualified personnel to maintain and update your legacy application.

Role of Generative AI: It can bridge the knowledge gap by automatically generating code that replicates the core functionality of the legacy application. This allows developers with modern skill sets to contribute to the modernization process.

 

7. Limited Scalability: Legacy applications might not be able to scale to accommodate future growth or increased demand. This can stifle your business potential and hinder your ability to expand.

Role of Generative AI: It can analyze code for scalability bottlenecks and suggest optimizations. It can also generate code for integrating with cloud platforms that offer greater flexibility and scalability.

 

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Step-by-Step Process to Modernize Legacy Software with Generative AI

Step 1: Identify Target Applications:

Begin by prioritizing which legacy applications require modernization the most. Focus on systems critical to business operations or those causing significant pain points.

Step 2: Inventory and Analyze Existing Systems:

Document your current technology stack, including programming languages, frameworks, and databases used by the legacy application. Analyze the codebase to understand its functionality and identify areas for improvement.

Step 3: Code Refactoring and Optimization:

Utilize GenAI tools to analyze the codebase and suggest automated refactoring options. This can involve removing redundant code, improving code readability, and optimizing for performance.

Step 4: Modern UI/UX Design:

Use GenAI to analyze user interactions and data to identify opportunities for improving the user interface and user experience. Generate code snippets or mockups for a modern and intuitive design.

Step 5: Incremental Modernization:

Modernize the legacy application in phases to minimize disruption and risk. Start with smaller, less critical functionalities and gradually work your way towards core components.

Step 6: Continuous Integration and Delivery (CI/CD):

Implement a CI/CD pipeline to automate code testing and deployment. This ensures rapid integration of GenAI-generated code with minimal errors.

Step 7: Monitoring and Performance Analysis:

Continuously monitor the performance of the modernized application and address any potential issues promptly. Utilize AI-powered monitoring tools for proactive problem identification.

4 Tips for Managing Ambiguity as a Business Analyst

As a business analyst, it is common to face ambiguity in many different forms and aspects. It may be the ambiguity of the business analysis approach you have chosen, the requirements, or the design decisions that you have to contribute to.

Ambiguity and constant changes are something that is expected. It’s up to you to respond constructively. The following tips may help:

 

#1- Approve Ambiguity

Although you may want to have full control over the circumstances, it will not happen. It may take time and changes in order to establish a business analysis approach to customers’ needs or understand the full aspects of the system to be developed. It is fine not to have the full picture from the beginning of the analysis journey, but it is your job to progressively clear out the context and the scope. Approve the ambiguity of the intrinsic part of the analysis.

 

#2- Mindset Shift

Ambiguity can cause plenty of negative thoughts and worries. Instead of entering into a negative, endless dialogue, try to view ambiguity as an opportunity for new approaches, for innovation, and for gaining experience. Ambiguity can cause team members frustration and challenges, as the situations triggering it are mostly out of our control. It is important to reframe biassed thinking patterns concerning ambiguity into positive ones.

 

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#3- Utilizing Effective Risk Response Strategies

As a business analyst, you should cooperate with the project manager to recognize factors and assumptions that can affect the business analysis objectives. You have to understand the sources of the risk and craft alternatives you can use if those risks actually occur. Whether you are a lead business analyst or other team member, your ability to identify and respond to risks effectively will affect the team’s ability to successfully complete project tasks.

#4 – Have a Compass

Having a specific compass for ambiguous situations is essential to guiding your decisions and actions. Orienting yourself and leading your team through a period of ambiguity can be supported by a stable and valuable foundation of personal and organizational vision, mission goals, and objectives. Knowing at any time why you are doing something and what you want to achieve and being true to yourself and your team can guide you as the North Stare in unpredictable and chaotic situations.

 

By viewing ambiguity as an opportunity, you can reduce the stress imposed by an ambiguous situation, experiment with new processes and ideas, and develop your team members. Identifying a goal or value that can be used as a “compass” can contribute to avoiding actions and behaviours you will regret later.