Tag: Learning

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.

Mentoring For Success

Written by Victor Medugu on February 21, 2024. Posted in Articles.

The year 2023 brought about significant achievements in my mentoring journey as four of my mentees successfully secured Business Analyst roles in the UK.

My passion for mentoring was ignited during my transition to the Learning and Development department at the International Committee of the Red Cross several years ago. This transformative experience marked the beginning of my dedication to fostering growth and professional development in others.

Mentoring aligns with the 70-20-10 model, specifically falling within the 20% designated for social learning. In this context, learners engage in collaborative knowledge exchange with peers and mentors, creating an environment conducive to skill development and personal growth. The 70% is designated to pivotal role of practical experience in shaping competence on the role, continuous learning by doing. The 10% is accredited to formal learning conducted in in either in online sessions or in workshops or classrooms.

A mutually beneficial relationship between the mentor and the mentee characterises successful mentoring. The mentee receives individualised counsel and access to a wealth of knowledge, and the mentor finds joy in helping someone progress. This stimulating exchange fosters self-assurance, leadership skills, and a greater comprehension of one’s area of expertise. Consequently, mentoring emerges as a keystone for achievement, bridging the knowledge gap between theory and practice and enabling people to travel with direction and clarity.

Essentially, mentorship spreads like wildfire, encouraging a culture of never-ending growth and success. A mentor facilitates the growth and learning of the mentee by offering insightful counsel, encouragement, and support. The mentor’s experience and skill set serve as a beacon, providing guidance and insight along the way to success. This connection extends beyond traditional schooling, providing insights from the actual world and strengthening abilities that are frequently absent from textbooks.

Business analysis is a profession with a T-shaped skill set, it places strong emphasis on personal qualities. These qualities are not only crucial for success in the field but also form the foundation for effective mentorship. Key among these qualities is relationship building, as mentoring thrives in an environment of openness, trust, active listening, and the ability to provide and receive constructive feedback.

Dr. Linda Philips-Jones, in her enlightening article “Skills for Successful Mentoring,” outlines essential qualities for a good mentor, including the ability to inspire, offer corrective feedback, and, notably, open doors. I resonate with the concept of “opening doors” in mentoring, as it encapsulates the mentor’s role in guiding a mentee toward new opportunities. I prefer to frame it as showing the mentee the door, emphasizing the mentor’s responsibility to guide and support the mentee in achieving new skills and heights.

A mentor’s effectiveness hinges on maintaining a friendly and approachable disposition. Accessibility and availability are paramount, even in today’s fast-paced world filled with numerous commitments. Mentoring in the professional realm of business analysis involves not only imparting technical skills but also guiding protégés to succeed as consultants within the dynamic field of business analysis.

According to Memon J et al. (2015), mentorship can evolve through various life stages, including initiation, cultivation, and separation. Moreover, there may be a definition stage that facilitates the establishment of a meaningful friendship between the mentor and mentee. Each stage introduces distinct challenges and opportunities, contributing to the comprehensive development of the mentoring relationship.

In the context of actively seeking a role, a mentee should possess the crucial skill of effective networking, a great place to start is LinkedIn. This goes beyond using the platform solely for job searches; it includes joining industry-specific groups to acquire valuable information, knowledge, and opportunities. LinkedIn functions as a tool for recruiters to directly approach individuals for interviews. However, before initiating contact with recruiters, thorough preparation is essential. This preparation involves gaining a solid understanding of fundamental Business Analysis concepts, including requirement gathering/elicitation, analysis, and management.

A comprehensive approach to processes is essential, involving the ability to assess and enhance them by understanding the current state and making improvements for a better customer experience. Effective communication with a diverse range of stakeholders, both internal and external, is key, utilizing various requirement gathering methods. Identifying the right individuals to meet with and providing relevant responses often requires creating a stakeholder matrix to map those involved in the project.

Documentation plays a vital role, involving the use of process models to create organizational templates such as requirement catalogues, functional specifications, or Jira boards. Finally, extensive collaboration, active participation in meetings, and volunteering beyond one’s immediate task and job description are important aspects to contribute effectively in a professional setting.

The most gratifying moment in mentoring comes when a mentee reaches out with the news of securing a job, expressing gratitude for the support provided. While not every mentee may secure a position immediately, the success of even one mentee is deeply rewarding, showcasing the tangible results of effective mentorship.

Mentoring goes beyond simply obtaining a business analyst role; it encompasses on-the-job coaching as well. It aims to ensure that the mentee grasps the crucial knowledge needed to seamlessly integrate into the role. Nevertheless, many mentees appear to prefer a coach within their organization, as it accelerates their acclimatization, helps them comprehend the tacit knowledge of the workplace, and enables alignment with colleagues who can facilitate a smoother transition into the role.

As I reflect on the successes of 2023, I look forward to continuing my mentoring support to colleagues in 2024.

What’s The Point of Peer Review?

Written by Christina Lovelock on February 15, 2024. Posted in Articles.

When time is tight and the pressure is on, it feels like ‘peer’ review is a luxury we cannot afford, but what’s the cost of this decision?

What Is Peer Review?

Sharing our analysis outputs (whether this is documents, models, presentation slides or feature tickets) with other business analysts before they are shared with any other stakeholders is the essence of peer review. BA peer reviewers should be able to share useful observations and insights about the output, whether or not they have specific business domain knowledge. If something is not clear to a fellow BA, there is a good chance it will not be understood by customers, suppliers, stakeholders and other recipients.

Why is Peer Review Valuable?

Many business analysts have a tendency towards perfectionism, and the longer we work on something without feedback, the more disappointing it is to receive any feedback, however constructive. It is much harder to accept and incorporate feedback on a polished final draft than an early rough draft. We need to share our work early in the process to be able to influence our own thinking and approach, and prevent us making significant errors or omissions.

Why is Peer Review Valuable?

Peer review is valuable from multiple perspectives.

#1 The producer

The person who created the output. We all bring assumptions to our work, whether this is a single piece of acceptance criteria, complex model or large document. The producer gets the benefits of a fresh perspective and the opportunity to catch errors and drive out assumptions. A peer review should be a way to improve quality without any worry of reputational or relationship risk. It also provides the opportunity for increased consistency across BA products and to learn lessons from other business areas.

#2 The peer reviewer

There is always something to gain from seeing how someone else works, whether they have more or less experience than us, and wherever they sit in the organisational hierarchy. So as well as making a valuable contribution to our colleague’s work we are likely to learn something through peer reviewing.

#3 Stakeholders

Any business, dev team or project stakeholders that will also be asked to review/validate/approve the deliverable will benefit greatly if a peer review has already taken place. Some errors and ambiguities will have been addressed, saving them time and increasing their confidence in the quality of the output.

The Review Triangle

This model reminds us that the highest number of errors should be spotted and rectified by the person creating the output, as part of a specific review phase.

Self-Review

The model emphasises the need for self-review, which is a separate activity to creating the analysis output, and involves:

Standards check (adherences to templates, branding and guidelines)
Assumptions check (provide key, glossary etc.)
Accessibility check (e.g. readability, compatibility with assistive tech, alt text for pictures)
Sense check
Error check
Spelling and grammar check.

Moving from a ‘creating’ to ‘reviewing’ mindset can be achieved by taking a break, and switching to reviewing when we return, or moving to a different device as this often forces us to look at something differently.

Peer Review

Peer review is also about adherence to standards, and is valuable even when the reviewer does not have relevant subject matter knowledge. They should be able to identify and challenge assumptions made, spot logic knots and highlight the use of acronyms and jargon. They can also share insights and observations from their own experience, such as level of detail and formats preferred by different internal audiences.

Stakeholder Review

Stakeholders should not be faced with errors that we could have easily caught through self or peer review. This does not mean we should only share perfect and complete outputs, but that we give stakeholders the best chance of spotting significant gaps and fundamental errors by removing low level distractions.

Many stakeholders find it difficult to simply ‘ignore’ spelling and other small errors. This level of error can undermine their confidence in our analysis.

Depending on the number of stakeholders and the complexity of the output, it is often better to do a group review exercise (synchronous) rather than a comments based (asynchronous) review. This is for several reasons:

Confidence everyone has actually seen what is being reviewed/validated/agreed
Prevents multiple stakeholders making the same (or conflicting) observations
Changes can be discussed and agreed.

Conclusion

The benefits of peer review, to individual BAs, the internal BA community and to our stakeholders and customers is significant. Attempting to ‘save time’ by avoiding this activity is a false economy. Organisations that aspire to be a truly ‘learning organisation’ encourage and enable effective peer reviews. Where organisations don’t place emphasis on this, BAs can choose to role model this commitment to quality and learning, and lead by example.

Further reading

Delivering Business Analysis: The BA Service Handbook, D Paul & C Lovelock, 2019

Editing for Success: Applying Hollywood Wisdom to Projects

Written by Adrian Reed on January 10, 2024. Posted in Articles.

I’ve long been a believer that a good movie is 90 – 120 minutes long. Sure, there’s the occasional storyline that can keep my attention for longer than that, but generally speaking after a couple of hours I’m getting pretty restless. One of the reasons I rarely go to the movie theater these days is that films seem to be getting longer and longer, and unlike watching at home I can’t press ‘pause’ in the theater!

It turns out that I’m not alone. Celebrated film director Sir Ridley Scott, who directed films including Alien, Gladiator and Blade Runner recently spoke about the ‘bum ache’ (‘butt ache’) factor of films. Too long sitting down and apparently movie-goers will get uncomfortable, and this is something that he takes account of in his editing. A classic case of “less is more”, and a director being empathetic to his audience.

Less Is More

I know virtually nothing about movie production, but I’m guessing that it is probably technically easier to produce and distribute a long film than it was, say, 40 years ago. I gather that in the past films came on multiple spools, all of which had to be physically duplicated and distributed. Apparently since the early 2000s, films have been distributed digitally to theaters. With fewer constraints, you could have a ten hour film if you really wanted it.

Yet being unconstrained isn’t a good thing. I’m guessing few people are lining up to watch the ten hour film “Paint Drying” (which is a real film, but was a protest against the cost of censorship). The fact that it’s possible to do something because a constraint is removed doesn’t mean that it’s actually a good thing to do. Sometimes constraints can foster creativity.

From Hollywood To Projects: Time As A Constraint

I’m guessing that you probably don’t work on Hollywood movies, but there’s a direct parallel with projects here. After all, a Hollywood movie brings together a collection of specialists for a period of time to create a deliverable that will generate benefits for its sponsor… which sounds strongly analogous to a project!

One constraint that you and I probably come up against frequently is time. There never seems to be enough, and time is always the thing being squeezed. It is easy to become somewhat jaded to this, and either just accept the deadline (but implicitly know that it’ll never be met) or rally against it.

Certainly, calling out unrealistic deadlines is an important thing to do. Yet, in some circumstances an alternative approach is to test the constraint and see how it balances against others.

Let’s imagine that a sponsor has set a deadline of 1st January for the launch of a product or project deliverable. We feel there’s a risk that this is an arbitrary deadline, so we start to tactfully ask “if it was two weeks later, but 10% cheaper, would that be beneficial?”. If the sponsor says “Absolutely, yes!” then we know that they probably value the budget over a fixed deadline. Or we might ask “How about we delivered it on that date, but the quality was lower?”. They might answer “No! Absolutely not”, at which point we know quality is paramount. We might ask these types of questions about all sorts of things, including scope, timeframe, deliverables, style of delivery and so on.

What we’re doing here is understanding which are hard constraints that genuinely can’t change (or, there would be a significantly negative impact of breaching) and those that can potentially bend. Not achieving regulatory compliance by a mandated date, where the regulator is strict and there’s a significant fine, might be an example of a hard deadline. It’s better to pay more now, and dedicate more resources to ensure compliance. Other things which appear to be constraints might be more malleable.

Product Management and Business Analysis as Film Editing

Once the hard constraints are identified, it’s tempting to be deflated. Rarely are we dealing with a situation where there’s too much time, resources and budget. Yet another way of looking at this is to think about the movie theater experience… sometimes less is more. Much as an ambitious scriptwriter might have a scene cut because it’s not essential to the story (or the location is too expensive to hire), we can ‘edit’ elements of a project or product in or out.

This probably sounds obvious, I mean scoping and prioritization is crucial. Yet, too often scoping and prioritization are carried out somewhat in isolation. It’s easy to end up with an incoherent set of features, or (worse) to find that only the person who shouts the loudest gets what they want…

If we reframe this as a process of ‘editing’, then we are keeping in mind the coherence and desirability of the product as a whole. Imagine asking twenty people for their favorite ever scenes in movies. Perhaps one mentions a scene from Wargames, another from the Barbie movie, another from Love Actually and so on. Now imagine making a film out of these ‘best’ scenes… it wouldn’t make any sense. The same can be true of a product too. If the features aren’t coherent it can become somewhat of a Frankenstein’s monster that is difficult to use and doesn’t really serve any single purpose well.

Another thing about editing is that it involves compromises and making difficult decisions. I’d guess actors probably hate having their biggest scene cut. And script writers probably hate being told they can’t have that on-location scene in Barbados due to budgetary cuts. But, it is the editing that means that the film makes money (achieves its financial outcomes) while also providing an experience that the consumer wants (achieving another of its core purposes).

I suspect this is a balance that we all tread on our projects and products, and bringing it to the fore and making tradeoffs transparently and purposefully can only be a good thing!

Beyond the Finish Line: Understanding the Art of Value Enablement

Written by Adrian Reed on December 27, 2023. Posted in Articles.

We recently needed some repair work done to the roof of our house, so called some local roofing firms. Understandably, roofers don’t always answer their phones immediately (I guess they are often out on site working), so we left voicemails for three different roofers.

Out of the voicemails we left, only two of the roofers replied. Both came round, inspected the roof, and explained what needed to be done. They both said they had availability and would send over a quote showing how much the work would cost. However, only one of the roofers actually sent a quote. We accepted the quote and I’m pleased to say that the work is now complete. But this got me thinking about business, business analysis, and value-enablement more generally.

Close, But Stopped Short

Let’s examine the approaches that the different roofers took. The first one didn’t reply. We might argue that this is bad customer service, but if they knew they were busy and had no shortage of business, then not replying might be an acceptable thing to do. It might not be a good long-term approach, but it doesn’t waste any of my time or their time. So while I might have preferred them to drop over a quick reply, I can understand why they didn’t.

The roofer who I really don’t understand is the one who came out, inspected the roof, but didn’t follow up with an estimate. They were so close to actually getting the work, but they failed because they didn’t carry out the final task. They’d spent time (and gas) driving out to see the roof, only to implicitly ‘give up’ by not following up. I found this really puzzling!

When Is Value Enabled?

This led me to think about value in a broader context, and I think it has some interesting parallels with business analysis. The roofer did all the work to potentially enable some value for him (payment) and for me (a fixed roof), but stopped just before a crucial moment.

In a project or product context, usually we are building (or changing) something with the purpose of enabling value for a range of stakeholders. The value that is enabled may vary for each stakeholder group. A retail bank releasing an app might provide convenience for its customers, while also saving money (and increasing profit) for its shareholders. For the app to be a success, it needs to balance the different perspectives on value. If it’s inconvenient, or hard to use, it’ll backfire—it might actually increase the number of times people call the call center, meaning operational costs increase. Knowing what different groups value is important so that this balance can be struck.

Yet as well as knowing what value can be enabled, it’s important to know when that happens and what the precursors are. Imagine a bank released a self-service banking app but didn’t advertise it to its customers. Sure, some early adopters might find it in the app store, but there would be a range of people who would use it if they knew about it that probably aren’t actively looking for it. Delivering the app without a communications and engagement plan alongside might end up being similar to the roofer who didn’t send a quote… it stops just short of the line for value enablement.

Finding The Finish Line

It is worth fostering discussions over what needs to happen not just for a product or project to be delivered, but what needs to happen for value to be enabled. It is too easy to stop just short of the finish line and declare success prematurely. “On time” and “on budget” are important aspects, but “on strategy” and “on benefit” are things that make a long-term difference. In the fog of urgency, it’s important that we don’t lose sight of these.

As James Clear comments in his book Atomic Habits, there’s an old saying that “the last mile is the least crowded”. Perhaps that’s just as true in a project and product context, and by focusing on the last mile and cultivating conversations about value we can help achieve better results for our stakeholders and communities. And surely that’s worthwhile?