Tag: Career

Beyond Frameworks: Agile Insights from a BA’s Odyssey

Written by Afaq Qazi on April 18, 2024. Posted in Articles.

Reflecting on my journey from a Junior Business Analyst to a seasoned Business Analyst and eventually evolving into a role where Business Analysis and Product Management intersect, I’ve had the privilege to contribute to organizations as diverse as Boeing, Rolls-Royce, and EPAM, alongside navigating the unique challenges of smaller entities.

This path, spanning over 13 years and multiple domains, has equipped me with a deep understanding of Business Analysis from the grassroots, teaching me the crucial balance between adhering to frameworks and embracing the agility necessary for today’s dynamic business environment. This narrative is an exploration of that journey, emphasizing the transition from rigid methodologies to agile adaptability, and the critical importance of customer focus and stakeholder management.

In the early stages of my career, the allure of frameworks was undeniable. They presented a structured way of understanding Business Analysis and Product Management, offering a semblance of control and predictability in the chaotic realm of project management.

However, as I progressed, the limitations of these frameworks became increasingly apparent. The real-world application of Business Analysis goes beyond the confines of any framework. It demands an acute awareness of the shifting business landscape and the ability to think on one’s feet—a blend of deep analytical thinking and pragmatic street smarts.

This evolution in perspective was mirrored in my approach to project management. Initially, my focus was on mastering the technical aspects: understanding the ‘what’ and ‘why’ to navigate towards solutions and create value for users. Yet, I quickly learned that the essence of effective Business Analysis lies in the ability to communicate, adapt, and understand the broader business context—skills that are foundational yet flourish only with experience and deliberate practice.

Communication emerged as the cornerstone of my professional development. The capacity to engage with a diverse set of stakeholders—customers, engineers, designers, and executives—and synthesize their insights is paramount. It’s a skill that goes beyond mere articulation; it’s about understanding the audience, choosing the right words, and effectively conveying complex ideas in a manner that resonates.

This skill set has been instrumental in navigating the complexities of projects, ensuring alignment across teams, and driving towards common goals with clarity and purpose.

As I embraced the agile methodology, the importance of flexibility became glaringly evident. Agile is not just a buzzword; it’s a mindset that values adaptability, customer-centricity, and continuous improvement.

It challenged me to think differently about project management, to be more iterative in my approach, and to prioritize direct feedback loops with stakeholders and customers. This agility has been crucial in climbing the project ladder, allowing for rapid pivots and adjustments in response to new insights or changing market dynamics.

Customer focus and stakeholder management have been the bedrock of my growth as a Business Analyst. Recognizing the criticality of these aspects, I’ve dedicated myself to becoming adept at navigating the complex web of stakeholder relationships and ensuring that the voice of the customer is always at the forefront of decision-making. This has involved honing my ability to manage expectations, articulate value propositions clearly, and foster an environment of trust and collaboration.

In retrospect, the journey from adhering strictly to frameworks to adopting a more flexible, agile approach has been transformative. It has taught me that while frameworks provide valuable guidance, the essence of Business Analysis and Product Management lies in the ability to adapt, communicate effectively, and maintain a relentless focus on the customer and business objectives.

As I continue to navigate this ever-evolving landscape, these insights will remain central to my approach, guiding my decisions and actions in the pursuit of creating meaningful, impactful solutions.

Don’t Let Your Software Requirements Die

Written by Chris Rickard on April 11, 2024. Posted in Articles.

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.

How AI will Affect Business Analysis in 2024

Written by Shaz Shafiq on April 4, 2024. Posted in Articles.

Artificial intelligence (AI) has been making waves in the field of technology, and experts firmly believe that it will continue to grow in 2024. AI has become an integral part of our daily lives, manifesting through voice assistants for customer service, chatbots, market trend prediction, proactive identification of potential health issues, and other such things. In recent times, businesses have increasingly embraced AI to enhance their efficiency and secure a competitive advantage. That is why the importance of artificial intelligence is being taught in business analyst courses.

AI is transforming the business landscape, playing a pivotal role in boosting growth and operational efficiency. It has evolved into a formidable ally, assisting businesses to get data-driven insights, optimize processes, and enhance decision-making capabilities. Once a blurry science fiction vision, AI has become a necessity for modern businesses. Its journey from just a theoretical groundwork in the mid-20th century to corporate boardrooms in 2024 has been astonishing. But how will it affect business analysis and the jobs of professionals in the future?

Well it is reported by Goldman Sachs that Ai could potentially replace 300 million full time jobs world wide.

The good news is Business Analysis as a job cannot be replaced with Ai, but the job can be supplemented with Ai.

The reason for this is, business analysts help organizations effectively implement change initiatives, the biggest change since the emergence of the internet has been the use of Ai, which is set to disrupt many markets. In order for organisations to stay competitive, organisations will have to implement the changes to their processes and embed the wave of Ai, and which role in particular helps organisations implement change? Business Analysts!

Let’s now delve into AI’s role in business analysis and how things will unfold.

Enhanced Data Analysis

AI is capable of processing complex data in large volumes and at a high speed. This will lead to more accurate business insights in less time. AI-powered text analytics tools can quickly analyze unstructured data like social media comments or customer reviews, which will provide valuable insights into customer preferences and sentiment. This allows businesses to make more informed decisions, increasing productivity.

Predictive Analytics

The adoption of AI for predictive analytics is now widespread in the realm of business intelligence. Companies, both large and small, are leveraging AI models to swiftly analyze various data sets, such as sales, customer information, and marketing data. This utilization of AI empowers businesses to proactively anticipate market trends, understand customer behaviors, and identify potential risks.

While predictive analytics has been a part of business strategies for as long as data has been collected, the integration of AI has revolutionized the process. This foresight becomes instrumental in guiding strategic decisions and enhancing the overall efficiency of business analysis procedures.

Automation of Routine Tasks

AI is poised to automate routine and repetitive tasks in business analysis, thereby reducing errors, enhancing efficiency, and liberating human resources. This, in turn, enables business analysts to concentrate on more intricate and strategic facets of their work. The automated tasks encompass processes like data collection and report generation, which, when handled by AI, release valuable time for value-added analysis.

Natural Language Processing (NLP)

AI-powered NLP will allow business analysts to interact with data using natural language. It means that users with business analyst certification as well as non-technical users will find it easier to understand and access complex datasets. This will lead to collaboration between different departments within an organization.

Personalized Business Insights

AI will allow the customization of business insights based on individual user needs. Analysts can receive tailored recommendations and reports, improving the relevance and applicability of the information provided. AI facilitates a highly personalized customer experience by sifting through customer data in large volumes, including purchase history, browsing patterns, and social media behavior. This capacity for thorough analysis helps businesses recognize individual customer preferences, thus tailoring their interactions and recommendations to cater to these specific tastes and requirements.

Improved Decision Support Systems

AI-driven decision support systems are likely to have a great impact and become integral to business analysis. These systems can process large volumes of data, assess various scenarios, and recommend optimal decisions. This will provide valuable guidance to business analysts and decision-makers.

Real-time Analytics

AI will enhance business analysis through real-time analytics capabilities. By leveraging AI technologies, businesses can access the most up-to-date information, empowering them to make informed decisions promptly. The significance of this real-time capability cannot be overstated, especially in the dynamic landscape of market changes. With AI-driven real-time analytics, businesses can respond swiftly to emerging trends, evolving customer behaviors, and market fluctuations, thereby staying competitive in today’s fast-paced business environment. This proactive approach to data analysis ensures that businesses are not only informed but also well-positioned to adapt and thrive in the face of constant change.

Advanced Pattern Recognition

AI’s advanced pattern recognition capabilities will enhance the detection of subtle trends and anomalies in data. This can be especially valuable in identifying emerging opportunities or potential risks that might go unnoticed with traditional analysis methods. Whether you have completed your business analyst training or not, the AI can make your task a lot easier and accurate.

Improve Risk Management & Fraud Detection

AI algorithms are designed in such a way that they can autonomously interpret and analyze even the most complex financial data. This allows them to uncover hidden patterns and irregularities that might indicate fraudulent activity. By leveraging natural language processing, data analytics, and machine learning techniques, AI systems can process large volumes of structured and unstructured data, find outliers, and generate actionable insights quickly. This approach empowers businesses, and financial institutions in particular, to detect fraudulent activities early and implement appropriate strategies to minimize the risk.

AI for Business Analyst in 2024: A Great Tool, Not a Replacement

The notion of AI making business analysts obsolete looks unlikely when considering the unique value that these professionals bring to organizations, a dimension that artificial intelligence struggles to replicate. Business analysts play a pivotal role in eliciting, prioritizing, and refining requirements in collaboration with stakeholders—a task that involves nuanced understanding and interpersonal skills that AI currently lacks.

Furthermore, business analysts serve as a crucial bridge between the business and its IT team, ensuring seamless communication and alignment of objectives. Their ability to communicate effectively with stakeholders is not only about conveying information but also about fostering relationships and steering projects towards their goals. This human touch is indispensable in complex organizational dynamics.

The proficiency of business analysts in understanding the end-to-end processes that they learn during business analyst programs, is a multifaceted skill that AI has yet to master. This involves a deep comprehension of organizational intricacies and the ability to navigate the complexities of both the business and technology realms.

Equally significant is the creative problem-solving approach that business analysts bring to the table. While AI excels in data-driven tasks and pattern recognition, the intuitive and creative thinking required for innovative problem-solving is a distinctively human trait that currently eludes artificial intelligence.

In short, the multifaceted roles and responsibilities of business analysts, encompassing collaboration, communication, understanding of business processes, and creative problem-solving, collectively form a skill set that AI, in its current state, cannot replicate. The symbiotic relationship between AI and human professionals, where each leverages its unique strengths, is likely to persist, ensuring the continued relevance and indispensability of business analysts in the foreseeable future.

Take Away

The profound impact of AI on business analysis is evident. The integration of AI technologies is revolutionizing the industry by automating routine tasks, enabling real-time analytics, and providing customized insights. This transformative shift not only enhances efficiency but also empowers business analysts to delve into more strategic aspects of their work.

The ability of AI to adapt to market changes swiftly ensures businesses remain competitive in the ever-evolving market. The use of AI in business analysis promises not just data-driven decision-making but a major change in how organizations leverage information for growth and innovation. The journey into the future of business analysis is undeniably shaped by the capabilities AI brings to the table.

The Mind as the Canvas

Written by Adam Pearson on March 20, 2024. Posted in Articles.

In the ever-evolving world of business analysis, the ability to convey complex data insights and concepts is paramount. For many, Visualization is a fundamental tool, often associated with software applications such as Power BI, Tableau, or Excel. In these tools an image containing all data points is generated for visual consumption and interpretation.

However, for Business Analysts who are certified with Sight Loss, this traditional approach of transcribing an externally generated image visualization into the mind can present a barrier to conducting their duties. In order to overcome these barriers it is essential to embrace non-visual representation, not only to ensure the Business Analyst with Sight Loss can complete their job, but by doing so it also develops and encourages many other benefits for the entire business.

Using a traditional Visualisation method, namely consuming and transcribing an external image into the consumers mind for analysis and interpretation, presents significant challenges for those who cannot access the external image in the first instance. Visualisation is an internal process and we use external stimuli to reconstruct this in our minds. These mental images can be real or imaginary, for example if I ask you to think of a pink elephant, you can do so, despite it not existing. The objective of having a pre-generated image to transcribe is one of time saving through consistency. By having technology that converts non-visual data into a visual image saves the user from having to do this themselves. Further, it also ensures that every consumer of the image has the same input and is therefore the internal process goes from reconstruction to transcription.

Think back to the pink elephant, if two people had to imagine it and compare, there would be differences in the size of the elephant, the ears, the hue of pink, and many other variables. Any question raised by the variability can be removed when transcribing, because you do not have to think about the construction of the image just the result of the image.

It is therefore logical to conclude that the essence of visualisation lies in cognitive processing and data communication methods. The communication method traditionally gives a visual representation before entering the mind, which is usually accepted by the brain as fact. There can be no more clearer way to draw out the problems of this than the recent phenomenon of the Changing Dress, which appears either Blue and Black or White and Gold to different people. Both versions are subjectively true. We accept pre-generated images to be true because of various reasons from the size of the dataset the image has been generated from, to the relationship between stakeholders, to the attitude and aptitude of the Analyst.

The concept of non-visual data representation is a crucial avenue for enabling not only Analysts with Sight Loss to excel in their roles, but to ensure that the risk of incorrect data insight is minimised.

There are several benefits to not relying solely on a pre-generated image. Firstly, enhanced data comprehension, namely non-visual data consumption that relies on auditory, tactile, and textual methods to convey the knowledge of data as data points, not visual graphics. Utilizing alternative communication methods can allow access and interpretation of complex datasets in a new and engaging way. This approach allows for a deeper understanding of the data, in the same way that reading a book cover-to-cover (i.e. the dataset), instead of just the blurb (i.e. a pre-generated external image) gives a fuller understanding of the content.

Secondly, when presenting findings to stakeholders, it can be beneficial for them to understand it not in a mental-visual aspect but as data points, facts, and relationships. This includes verbal descriptions, accessible documents, audio tracks and storytelling (as opposed to story boarding). By doing so, analysts can articulate their insights clearly and persuasively without traditional visual aids or statistical jargon. It can also enable the stakeholders to engage more effectively with the data and can apply their own domain knowledge, further helping the project being undertaken.

Thirdly, for those BAs with sight loss, the advancement in technology means that they can process data more effectively with Screen Reader software and tactile graphics, building a graph in the mind. Much in the same way that following instructions on Google Maps and actually walking the route, are two very different experiences. These tools can provide real-time feedback and enable analysts to explore data, scenarios, and outliers effectively, all while maintaining the focus on the data itself, instead of interpretations of data.

Fourthly, a further benefit of non-visual communication is increased collaboration and teamwork. Non-visual communication allows analysts to work seamlessly with both sighted and colleagues with sight loss, to share their findings, develop requirements, and craft compelling data narratives, centred on the concept or data’s intrinsic qualities.

Further to these benefits, non-visual communication can encourages innovative problem-solving techniques, because it does not funnel people into thinking visually, it does not bias them towards any particulars, by predisposing them to the stimuli of a pre-generated image. Analysts with Sight loss can apply their unique perspectives to explore different approaches and scenarios, contributing valuable insights to the analysis process without relying on visual cues.

In conclusion, within the realm of business analysis, non-visual processing is crucial for individuals who have sight loss to equally participate, but it can also present business-wide benefits. Embracing non-visual approaches empowers all staff members of an organisation to excel in their roles, offering enhanced data comprehension, alternative communication, and adaptive problem-solving techniques that focus on the data itself, not a pre-defined notion. As we strive for inclusivity and diversity in the workforce, it is essential that the business analysis field acknowledges the value of non-visual processing and provides the necessary support and resources for Analysts with Sight Loss to thrive.

In doing so, we ensure that all individuals, regardless of their Sight capability, have an equal opportunity to contribute their skills and insights to this dynamic field, with the primary focus on processing as the valuable core of their analysis.

Ego Check: The Secret Sauce of Successful Business Analysis

Written by Steve Jones on March 14, 2024. Posted in Articles.

You’ve spent days or even weeks working through your discovery and analysis details to craft wire frames for a new application or capability. You know what your stakeholders might ask for in terms of alternatives, so you create those versions as well. The day arrives when you’re finally ready to share with business and IT, the work you’ve labored over.

The big meeting happens and your stakeholder destroys everything you’d worked so diligently over, ripping your heart out.

Sound familiar? Some people take this as a crushing defeat and question their choice of profession.

Don’t let this be you!

You need to have a thick skin in this game. As a business analyst, your role resides at the crossroads of business operations and IT solutions. Navigating the complexities and personalities of both requires not only some technical knowledge and business acumen but also a crucial personality trait — the ability to leave your ego at the door. While this notion may seem daunting at first, it stands as one of the most invaluable skills a business analyst can possess.

Bringing your ego along in conversations tends to add chaos, disrupting free-flowing communication in an environment that might already have some chaos. Setting aside your ego entails acknowledging you don’t have all the answers; that meticulously crafted strategies may necessitate revisions; and that your perspective, no matter how comprehensive, may not encapsulate the entirety of a problem or its solution.

Within the dynamics of a business environment, ego can often act as a hindrance, impeding effective communication. A business analyst who can restrain their ego is more amenable to guidance for research and receptive to feedback, fostering continuous learning and growth.

While criticism is frequently viewed unfavorably, it carries substantial value within a business context, serving as an indispensable tool for development when harnessed constructively. As BAs, our mission revolves around streamlining processes, enhancing capability & value, and facilitating change — tasks that demand perpetual scrutiny and re-evaluation. Feedback, including criticism, serves as a critical lense through which we refine our insights and strategies.

You need to be strong enough to withstand the critique to investigate what the underlying cause or comments are about. When the feedback seems overly harsh and does not feel like it is constructive, exercise what you have available to you – use your tools to continue the conversation. Start by expressing appreciation for the input. Depending on the harshness of the initial comments, this can be disarming, so utilize the connection to ask questions for feedback that could be actionable areas for your improvement.

In addition to seeking constructive feedback, you can also practice the agile principle of Simplicity. If you don’t quite understand what “the art of maximizing the amount of work not done” really means for a BA… it’s this; don’t spend so much time trying to produce a pristine wireframe or perfectly crafted requirement. Do enough to identify value during conversations.

While on a project or during a product increment, the initial requirements documentation is really intended to be just enough to draw out the valuable conversation to confirm understanding while narrowing in on the solution and it’s constraints to facilitate realization of the business value.

Internalizing feedback can obstruct the broader perspective and overall objective of the task at hand. Conversely, leveraging feedback as a means of self-improvement can significantly elevate your standing within the team, while enhancing the quality of output and fostering stronger work relationships.

Keeping your ego in check does not mean a dismissal of your ideas, opinions, or self-assurance entirely. Rather, it involves striking a balance — knowing when to advocate persistently for your ideas and when to step back, listen, and glean insights from others. For seasoned analysts, this should be second nature but it’s worth a reminder from time to time.

In conclusion, the absence of ego can quell the chaos, amplify your capacity to discover and comprehend the real issues, and embrace diverse perspectives to construct robust and effective solutions. Thus, resisting the urge to take criticism personally and ensuring that our egos do not overshadow the primary goal of problem-solving constitutes an trait every successful business analyst must master.