Tag: Tools

Transformative Impact of AI in Business Analysis

Written by Lalita Lalwani on August 9, 2023. Posted in Articles.

Integration of AI’s transformative potential into our analysis processes can unleash human potential, drive innovation, and foster a culture of continuous improvement. The future belongs to those who embrace AI in business analysis, and the time to seize this unparalleled opportunity is now. So, let’s take the leap together and unlock new horizons of success with AI as our ally.

The Fourth Industrial Revolution has ushered in a new era of technological innovation, and at the forefront of this revolution is Artificial Intelligence (AI). In the world of business analysis, AI has transcended its role as a buzzword and has become a game-changer in driving business growth and efficiency. AI has emerged as a powerful ally, empowering organizations to harness data-driven insights, streamline operations, and make more informed decisions.

Embracing AI in business analysis is no longer a choice but a strategic imperative for companies looking to gain a competitive edge and thrive in today’s dynamic marketplace. Let’s delve into the transformative impact of AI in business analysis and understand how organizations can leverage this cutting-edge technology to unlock new horizons of success.

The Power of Data-Driven Insights

At the heart of business analysis lies data, and the ability to extract meaningful insights from vast datasets can make or break an organization’s success. AI-driven analytics tools have revolutionized this process by processing large volumes of data at unparalleled speeds and advanced algorithms to provide real-time, data-driven insights. By employing machine learning algorithms, AI can identify patterns, trends, and correlations that may remain hidden from traditional analysis methods.

With AI-powered data analysis, businesses gain a deeper understanding of their customers, markets, and industry dynamics. This data-driven approach empowers decision-makers to make well-informed decisions promptly, minimizing risks and optimizing opportunities. Organizations can harness a more comprehensive understanding of their markets, customers, and competitors, optimizing their marketing strategies, fine-tuning product offerings, identify emerging market trends, driving innovation, growth, competitiveness, and profitability.

Automation: Unleashing Human Potential

Business analysts are often burdened with repetitive and time-consuming tasks, leaving little room for strategic thinking. AI automation can alleviate this burden, liberating analysts from mundane activities and allowing them to focus on higher-value initiatives that require creativity, critical thinking, and strategic planning.

AI-powered automation can handle data collection, data cleaning, report generation, and even predictive modeling. As a result, business analysts can dedicate more time to interpreting results, formulating strategic plans, and collaborating cross-functionally. This not only enhances productivity but also fosters a culture of innovation within the organization.

Personalizing Customer Experiences

In an era where customer experience reigns supreme, personalization has become a key differentiator for businesses. AI plays a pivotal role in this domain by enabling businesses to personalize interactions with customers. Leveraging AI-driven analysis, organizations can understand individual customer preferences, behaviours, needs, and engagement patterns to segment customers. This enables businesses to hyper-personalized product recommendations and tailored marketing campaigns to individual customers.

By delivering personalized experiences, businesses can foster increased customer loyalty, satisfaction, ultimately leading to increased revenue and brand advocacy.

Predictive Analytics: Anticipating the Future

Traditional business analysis often focuses on historical data, providing a retrospective view of performance. However, in today’s fast-paced business environment, organizations must be forward-thinking and anticipate future trends and challenges. AI-driven predictive analytics enables just that. By analysing historical data, market trends, and external factors through sophisticated predictive models, AI can forecast future trends, demand patterns, identify potential risks, and anticipate changing customer preferences empowering organizations to make proactive decisions.

Armed with these insights, businesses can proactively adapt their strategies, pre-emptively address challenges, seize new opportunities as they arise and can stay ahead of the curve and gaining a competitive edge.

Improving Fraud Detection and Risk Management

In an increasingly interconnected world and increasing digitization of business processes, cybersecurity threats and fraudulent activities have become major concerns for organizations. AI excels in detecting anomalies and patterns indicative of fraudulent activities. AI-driven fraud detection models can learn from historical data to identify suspicious patterns and flag potential fraudulent transactions promptly.

Additionally, AI-powered risk management tools can assess and mitigate risks, helping businesses safeguard their assets and maintain trust with customers and stakeholders.

Conclusion: Unlocking New Horizons of Success

Embracing AI in business analysis is no longer an option; it’s a necessity for organizations that aspire to thrive in today’s dynamic market. From data-driven decision-making and process automation to personalized customer experiences and predictive analytics, AI’s impact on business analysis is undeniable.

As business analysts and leaders, embracing AI unlocks new horizons of success, driving growth, innovation, and efficiency. It’s time to seize the transformative power of AI and shape the future of our businesses with confidence and enthusiasm. So, let us embark on this exciting journey of AI-driven business analysis and embark on a path of unrivalled success.

Embracing AI in Business Analysis: A Guide for BAs

Written by Arunabh Satpathy on July 26, 2023. Posted in Articles.

Artificial Intelligence in business analysis is fast becoming the next big evolution of the BA practice. It acts as a superpower to enhance decision-making, automate repetitive tasks, free up time for strategic work.

BAs add value to organizations that AI cannot replace, like problem-solving, critical thinking, communication, and collaboration. But with increasing competition in companies, BAs can use an assistant like artificial intelligence to do more with less. This article covers the growing influence of AI in business analysis and how you can thrive as a business analyst in the age of generative AI.

AI in Business Analysis: A Growing Field

Business analytics powered by AI can detect patterns, anomalies, and deviations and raises them for review by business analysts.

Business analysts are embracing AI/ML tools to make more informed decisions and improve their competitive advantage. Tools like Tableau, Power BI, and others increasingly have a significant AI component

BA coaches have also begun thinking and producing content on how to use AI tools like ChatGPT for business analysis.

The growth of AI tools has also led to an increasing push for human oversight over AI. For instance, the European Commission has proposed a regulation the stipulates how high-risk AI systems like facial recognition algorithms should be created with human oversight in the loop.

Developing regulations like these will affect downstream industries like business analysis in due time.

AI-enhanced Business Analysts

The most beneficial way to deal with the rise of AI is to enhance your existing skill set using it. Generative AI tools can also lead to happier and more productive workers.

Here are some ways you can adapt to the changing reality:

Know your Core BA Skills

As recently as May 2023, Forbes recognized six core business analysis skills:

Analysis: Parsing large amounts of complex data and recommending solutions.
Communication: Active listening and clear delivery of data in verbal and written form.
Interpersonal: Working effectively with stakeholders and teams within client organizations.
Problem-solving: Creative solving of unique client issues.
Time Management: Prioritizing tasks and getting the job done quickly.

AI can do parts of these tasks for you, but none fully. For instance, an AI-based requirements management tool can help you analyze and write requirements based on raw data, but only with your approval. But it fails at active listening, stakeholder engagement, or creative problem solving.

Without human oversight, AI can be ineffective or even counterproductive. Business analysts can excel through expert management of AI tools and ensure that AIs output aligns with the goals of the organization.

Another core skill that AIs cannot compete is an up-to-date understanding of the industry. BAs with domain knowledge can spot problems and suggest fixes before a project reaches the development team. They have the knowledge and connections to understand market conditions and protocols beyond what is available on AI databases.

Strategies for developing industry domain expertise include:

Researching the history, current situation, and prospects of the industry.
Learning market-specific protocols. For example, ASPICE is a key automotive regulation.
Competitive analysis.
Asking questions to other domain experts.

Enhance Your Data Management and Analysis Skills

According to Peter Sondergaard, the SVP and Global Head of Research at Gartner, “Information is the oil of the 21st century, and analytics is the combustion engine.” Analytical skills help BAs generate high quality outcomes that meet business needs.

In practical terms, you need to have a combination of the following data analytics skills to position you as a high-value and competitive BA candidate:

Data Literacy: Familiarity with data language, types, sources, and analytical tools.
Data Collection: Knowing how to collect unbiased and reliable data through various methods.
Statistical Analysis: Knowing statistical terms and techniques like hypothesis testing, linear regression, and p-values to extract insights.
Data Visualization: Presenting data honestly to communicate insights.

Learn to Work with AI Tools

A recent survey by Gartner showed that 70 percent of U.S. workers want to use AI to reduce some common tiresome and repetitive tasks.

The top task that workers hoped AI would automate is data processing. The demands of a business analyst already include many of these tasks and will do so in the future. Here’s how BAs can leverage AI tools for data processing:

Integration: Building “master lists” of data, like merging lists while retaining their integrity.
Classification: collecting, extracting, and structuring data from documents, photos, audio, video, and other media.
Cataloging: Organizing, cleaning, and retrieving data. SQL is already a key skill for data retrieval and OpenRefine helps with basic data cleaning.
Quality: Reducing errors, contradictions, or low quality in databases or requirements authoring.
Security: Keeping data safe from bad actors.
Compliance: Adhering to relevant industry-based or national compliance standards. E.g. ASPICE for automotive.

BAs should also learn how to interact with AI tools. Some tools have button-based interfaces, but others like ChatGPT use prompts. Engineer ing prompts will itself become a skill not dissimilar to making SQL queries. The right query may be the difference between an important insight and a dead end.

This collaborative approach to AI in business analysis will help increase the efficiency and effectiveness of the entire organization. The MIT Sloan Management Review and Boston Consulting Group’s global executive survey found that companies combining AI and human abilities are best positioned to succeed.

These days, many tools help boost the productivity of BAs. Some staples like Tableau and Power BI have into their legacy offerings. Others have leveraged the to analyze, write, rewrite, and suggest requirements.

Adapt to Changing Roles and Responsibilities

Beyond working with AI tools, BAs will have to adapt and expand their skill sets to market realities. BAs can stay on top of things by:

Keeping up with cutting-edge technologies like blockchain, digital trust, and artificial intelligence.
Asking better questions about business needs, technology needs, and stakeholder satisfaction.
Considering hybrid roles that combine BA skills with related fields like statistics, data analysis, project management, and UX.
Enhancing soft skills. BAs who communication, critical thinking, negotiation, and collaboration skills can adapt and thrive in any environment.

The Future of Business Analysis is Bright

The fundamental role of the business analyst will be no less relevant in the near future. Somebody has to perform crucial tasks like business processes evaluation, problem identification, and more. Embracing the paradigm of new AI tools will only increase the productivity of BAs. Combined with their core BA toolkit, domain expertise, fluency in data management, and soft skills, business analysts can thrive and drive the success of their companies in the 2020s and beyond.

Source: AI in Employee Engagement: 7 Applications to Try Yourself | Zavvy [AS1] [AS1]

https://www.statista.com/chart/27127/tasks-us-workers-want-ai-to-take-over/ [AS2]

Deconstructing the Stress Factors in the Business Analyst Role

Written by Shanekia (Shay) Thomas on July 13, 2023. Posted in Articles.

Over my years as a professional, I have come to realize that the title of Business Analyst (BA) is a heavy one. How each organization defines the role can be completely different. A BA in Company C may be a requirements scribe, whereas a BA in Company D wears many hats: process analyst, project manager proxy, test validator, etc. Whichever way the role is defined, I think stress has plagued many of us who call Business Analysis our profession. If you have found yourself feeling anxious or overwhelmed at any point during your career in business analysis, you are not alone. There are many factors that can play into that feeling. I want to deconstruct a few of the typical stressors here and offer some potential solutions.

1. Not understanding the area of study:

BAs are often on the fringes of the business. It is analogous to being a window cleaner. As each pane gets cleaned, we can see a little more into the room in front of us, but we are still only seeing a portion. Each pane reveals a bit more about the room, but the entire picture may still elude us. We are on the outside looking in. Not having the full picture of the business, its processes, or its business drivers can leave a Business Analyst feeling inadequate and uninformed.

As a BA, questions are your friend (like your squeegee on the dirty window). I have been guilty of feeling like I was asking too many questions. What I realized is that if I don’t ask my second follow-up question, which may lead to a third follow-up question, I risk not gaining the knowledge that I need to understand the business to write better requirements.

Feeling anxious because we don’t know the business is stressful, but not asking enough questions to get the understanding we need will cause more stress later. If you have 100 questions, don’t stop at number 99. Ask all 100. If you find that the participants are getting a little impatient with your questions, gently remind them that you are trying to understand them as an outsider looking in. Once you gain a better understanding, your perspective changes, and you are no longer looking through smudged windowpanes.

2. Large complex projects:

If you have been on projects with multiple stakeholders, then you may feel pressure before you even type the ‘r’ in requirements. It can be daunting to start a new project. You may be working in a new department with all new faces. Unfamiliarity coupled with complexity can be intimidating. In instances like this, it is important to build alliances.

Find project team members that you can trust. Relationship building is so important to your success as a BA and will also go a long way in helping alleviate some of your stress. It can be nice to have a friend when you are on the fringes.

3. Requirement Elicitation is not one size fits all:

For those who do not practice Business analysis, gathering requirements may seem like a simple task. You find out the need, and you write it down. It is not at all that simple. Different stakeholders require different elicitation methods. Some stakeholders are very forthcoming with information. Others can be more guarded or may simply not know how to express the need. Interviewing may work for some. Passing e-mails back and forth may be more appropriate for others.

The key here is to really take the pulse of your stakeholder population (a personality assessment of sorts). Understand their optimal mode of communication and how you can best work within the confines of that. Also, do not neglect your best mode of working as well. Finding the proper balance between stakeholder and BA methods of working will be key to helping alleviate stress.

Do not feel pressured to use an elicitation technique that is not a good fit. We do not want to simply check boxes on the list of deliverables; we want to add true value.

4. Feeling pressured by deadlines:

Every project comes with a start and end date. BAs often occupy a few task lines on that project schedule, and the pressure to meet those deadlines can feel immense. We don’t want to be the ripple that causes the project timeline to shift.

As BAs, we often take the deadlines given to us and work to fit within them. If we do not understand the business, the project is complex, and we don’t know what elicitation method to use when starting a project, then how can we be tied to a deadline?

Speak up when you feel that timelines are not realistic. Open and honest conversations can be uncomfortable but can also be wholly necessary when the quality of work is on the line. The timeline may not shift because you raised a concern, but I guarantee you will feel a little less pressure when you have been open and honest and raised your hand.

This is not an exhaustive list; it is just some of the key things I noticed in my career as a previously stressed and anxious BA. In the end, it is important to remember that your success as a Business Analyst rests in part on your ability to perform the job well. Different stress factors can become obstacles to your performance. Understanding those factors is the first step in tackling them. Apply different techniques to alleviate the stress. You will thank yourself.

Complexity Science Terminology Applied to Business Requirements

Written by Ligia Groza on June 28, 2023. Posted in Articles.

Borrowing from the terminology used in the complexity science field, in which systems are classified as Simple, Complicated or Complex, this article provides a short description of these characteristics, and suggests using the same terms, in a different interpretation, in the context of documenting Business Requirements.

In the book “Getting to Maybe: How the World Is Changed: Westley, Frances, Zimmerman, Brenda, Patton, Michael” the following meaning is given to the three types of systems:

<<Simple>> systems are based on a small set of rules or steps to function. They are robust, in the sense that the same input will generate the same output, with little variance. An example would be baking a cake by following a recipe.

<<Complicated>> system have a high number of rules and laws, even thousands, like the project to launch a spaceship to reach the Space Station. These systems can be managed by computers, are considered predictable, but they are not necessarily robust: an error in an input parameter can lead to a different outcome than desired (the spaceship ending up on another place instead of the Space Station).

<<Complex>> systems are those in which the component agents interact amongst themselves and adapt to the new conditions. For example, raising a teenager is complex because teenagers change their moods, they interact with their peers and the environment, and they adapt to the new context. Such systems are emergent, and other examples include languages, a pandemic spread, or the car traffic.

We can adapt this complexity systems terminology to the situation of a Business Analyst who is part of an on-going project to enhance an ERP application (Enterprise Resource Planning) in a specific organization.

In this framework the starting point are the business users who face the real world and have <<Complex>> problems. The role of the Business Analyst is to translate that complexity into a form that is <<Complicated>> but fully described. The final form of this translation is the Business Requirements Document, aligning the understanding of the requirements among the team members, with sections detailing <<Simple>> logical components.

From this perspective regarding the Business Analysts’ work, the categories are:

<<Complex>> problems known by the business users. These problems may touch several areas of the ERP, have unclear or vague rules, or the granularity of the logic and desired actions is not fully explained.

<<Complicated>> requirements with a high number of rules, parameters, procedures, algorithms. With the huge computing power available nowadays, ERP applications are able to handle such complicated systems, and they routinely process huge number of transactions run very fast on large databases.

Using the complexity lens to look at requirements provides benefits such as:

First, this perspective can reduce the frustration within the project team around requirements, by emphasizing the complex and changing nature of the business user’s problems.

Second, it increases the appreciation for the Business Analysts’ role in the team, since their talent and ability to translate <<Complex>> problems into <<Complicated>> requirements are key in this framework.

Lastly, untangling complex problems requires judgment, intuition, and context sensing – all characteristics that are unique to the human mind. In the current environment dominated by Artificial Intelligence applications, a Business Analyst with this view in mind would have less to worry about a being replaced by a robot and losing their job, if they see themselves from the position of contributing to the translation of complex problems into complicated requirements.

Equipped with the tools and techniques recommended by the BABOK, Business Analysts are in a unique position in the process of documenting the business requirements.

The following components of a Business Analyst’s toolkit are particularly useful in the requirements elicitation and documentation described in this framework:

Offering mock-ups and diagrams: Visual representations of the requirements can be highly effective in helping stakeholders understand the proposed solution.
Setting up test cases in the ERP application, to assess how well the information currently provided by the ERP system can support the proposed changes.
Performing a gap analysis between current and future state. This technique helps ensure that the requirements align with the overall business objectives and can serve as a basis for defining the scope and priorities of the project.
Organizing walkthrough sessions to gather feedback and ensure that the requirements are accurately captured. Business Analysts can generate and present iterations of the BRD with revision points, and address follow-up questions from stakeholders.
Asking open-ended questions to encourage stakeholders to share their insights, perspectives, and concerns, which can help uncover hidden requirements and potential issues that may not be captured through closed-ended questions.
Nudging the discussion towards “what” is the ultimate need, instead of the “how” to meet that need. This approach encourages stakeholders to articulate their true requirements and avoid premature solutioning. This approach allows for more creativity and flexibility in exploring different options and arriving at the most appropriate solution.
Being flexible in case the requirements change in time as the project progresses. and appreciate that the scenarios might be unchartered territory for the users themselves.

The Dilemma of Test Scripts

Written by Kimberly Yoss on May 31, 2023. Posted in Articles.

Mention software testing to 10 people in IT and you will get several different responses.

“That’s what QA is for.”

“Unit testing covers what we need.”

“What do we need to test for? The application works fine!”

“We’re Agile. We don’t need to test.”

“The client’s not banging down my door – so all is good.”

“No, we can’t release to UAT yet. I’m only halfway through writing the test scripts.”

“I don’t have time to test.”

“I don’t know how to test this. I’ll need some guidelines.”

“That’s not in the budget.”

If you work as a BA in an IT department, you have likely heard all of these retorts – sometimes even from those who should know better.

It is also a trigger that can lead down a deep rabbit hole of shortcuts and excuses, with the ultimate result being sloppy code, error-prone software, and possibly tons of rework post-release. Not only impacting you and your team, but also potentially leaving your company with very unhappy customers.

Software testing has several variations, all meant to ensure that the customer is happy in the end and that fewer issues, or bugs come back to haunt the product development team. Unit testing and smoke-testing are two of the most common types of testing. Unit testing is ordinarily done by the engineer as a part of coding and is meant to test the individual functions of the various components of the specific software. Smoke-testing is done after the release of the code into production. It serves as a means to make sure that nothing has been broken by the new code. Another critical form of testing is called regression testing, which focuses on how the new code works with the existing code. Regression testing requires additional planning and visibility of enhancements between releases.

At a bare minimum, unit testing and smoke-testing are essential. They are cheap and easy and require a minimal amount of effort.

The real testing, however, comes in the form of functional tests and acceptance tests. This is how you connect the code that is created by the engineers with the business needs of the customers and the real-life use of the application.

Functional tests validate that the newly designed process aligns with the requirements that were provided to the development team. Functional testing is best performed by either the business analyst or the QA analyst. A distinct benefit is gained here when functional tests are designed and completed by someone who is familiar with both the application and the enhancement requirements. Here is a tip: well written requirements and an experienced QA analyst are your best friend for stellar results!

Acceptance tests (also known as User Acceptance Testing or UAT) validate that the finished product aligns with the needs of the business user. This type of testing allows the end user to touch-and-feel the new process to make sure that it will correctly address the defined business need. An end user is also looking to make sure that the workflow is not made worse. At the end of the day, the user still has a job to do!

A well-designed set of test scripts is the most efficient way to track results, and to facilitate tracing the functionality back to the requirements. A plethora of applications exist that do this for you! Many of these applications can also run the test scripts in an automated fashion, which works great for regression testing. If I have access to an experienced QA analyst, I leave the decision up to that person. I simply provide rock-solid requirements and expectations and make myself available for questions.

That said, I am a big advocate of DIY.

If I am running functional tests myself, I create test scripts the old-fashioned way: Excel spreadsheets. The perception is that this takes too much time. Yes. It can be tedious. However, if you consider that good test scripts can also be used for system and user documentation – a bonus for start-ups – it is an essential task, regardless of the effort. They can be maintained and re-used.

Put your user hat on and give it a try!

Begin with a few basic columns:

Who is the user? What role is the user filling while performing this task?

What is being tested? Describe the function in simple terms.

What are the exact steps to get the desired result?

What is supposed to happen when the steps are completed?

What actually happened when the steps were completed? Ideally, you would want this to be the same as what was supposed to happen. Many times, it is not.

Did the test Pass or Fail?

Add more context for tracking and tracing back to the requirements, like test IDs for each test and date tracking to facilitate repeat testing. Add a column for additional comments so that the person who is running through the tests can add additional observations about what was experienced during the test.

In short, product quality drives customer satisfaction. Complete and consistent testing and retesting is one of the best ways to drive customer satisfaction with new products and product enhancements. It’s well worth your time and effort.

Happy testing!