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Tag: Skills

BATimes_Aug30_2023

Don’t Deliver a Donkey instead of a Horse

All of us at some point in our life have heard of the children’s game called Telephone Game or Broken Telephone. In this game, Players form a line or circle, and the first player comes up with a message and whispers it to the ear of the second person in the line. The second player repeats the message to the third player, and so on. When the last player is reached, they announce the message they just heard, to the entire group. Very often, the message that comes out at the end is quite different from what the first player had whispered, and this creates a lot of amusement.

Now imagine that same game being played when a project is initiated. In this case, the project sponsor or sponsors may request for a given deliverables at the onset of the project based on business needs. However, after the message gets filtered through many teams, the outcome may not match what was asked for in this first place resulting in a number of unhappy customers or stakeholders. This can be considered as delivering a Donkey when asked for a Horse. The moral of this story is that if there was proper end to end communication, the result would have been much closer to what the sponsor asked for in the first place. Effective Communication is considered as one of the most important aspects of both personal and work life.

 

Business analysts need to effectively gather and convey information between stakeholders, team members, and other parties involved in a project. Clear and concise communication ensures that requirements are accurately understood, objectives are aligned, and expectations are managed. Effective communication fosters collaboration helps in resolving conflicts and ensures that the project stays on track. Some of the key techniques or aspects of communication within the business analysis domain are discussed below. All of them are equally important and need to be considered during any engagement and can be improved through training and constant practise.

 

  1. Active Listening.

Active listening plays a crucial role in business analysis. It involves fully engaging with stakeholders, understanding their needs, concerns, and requirements. This helps the BA to gather accurate and detailed requirement related information, which is essential for making informed decisions and developing effective solutions. Active listening improves collaboration, builds rapport, and ensures that project goals align with stakeholders’ expectations.

 

  1. Interpersonal Communication

Interpersonal communication skills are vital in business analysis because they involve interactions with various stakeholders, each with their own perspectives and needs. Along with the Active Listening mentioned above, building rapport, and empathising with the viewpoint of the stakeholders are crucial for establishing trust and understanding. These skills help business analysts navigate conversations, gather requirements, and address concerns effectively. Related techniques such as Collaborative problem-solving, negotiation, and conflict resolution also rely heavily on strong interpersonal communication. By fostering positive relationships and adapting their communication style, business analysts can facilitate smoother interactions and achieve better outcomes throughout the project lifecycle.

 

  1. Stakeholder Management

Stakeholder management is a critical aspect of business analysis that involves identifying, engaging, and effectively communicating with all parties impacted by a project. Business analysts need to understand stakeholders’ interests, expectations, and concerns. By building relationships and maintaining a clearly defined two-way lines of communication, the Business Analyst can ensure that stakeholder needs are considered throughout the project lifecycle. Effective stakeholder management involves involving the right people, keeping them informed, addressing their feedback, and managing conflicts when they arise. Successful stakeholder management contributes to project success by aligning goals, managing expectations, and fostering collaboration

 

Within stakeholder management, a crucial element to consider is Communication strategy. This has a number of components of its own including  identifying the audience for each message,  understanding the environment or business situation  under which the given project has been initiated, getting a clear understanding of the sponsor vision or objectives , being able to define  what needs to be said to whom and when,  and knowing what are the various ways in which the message can be delivered and feedback received.

 

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  1. Facilitation

Facilitation is an important technique in business analysis that involves guiding discussions and workshops to achieve productive outcomes. By facilitating meetings, workshops, and brainstorming sessions as per the needs of the project, business analysts can encourage participation, manage conflicts, and ensure viewpoints from all the stakeholders or impacted parties are heard. Facilitation helps in eliciting requirements, prioritizing features and functionality, and fostering collaboration among stakeholders. It also aids in reaching a collective understanding and agreement of the objectives and making informed decisions, leading to more successful project outcomes

 

  1. Business Writing

Strong writing skills are crucial for business analysts as they are responsible for documenting and communicating various aspects of their work. Clear and concise writing is essential for creating requirements documents, project plans, reports, and other forms of documentation. Effective writing ensures that complex deliverables or impacts are accurately and clearly represented to stakeholders, team members, and decision-makers. It also helps in avoiding misunderstandings and serves as a reference for project progress and decisions. Well-written documentation contributes to effective communication, reduces ambiguity, and supports the overall success of business analysis efforts.

 

  1. Presentation Skills

Visual and presentation skills are essential for effective communication in business analysis. They help convey complex ideas, data, and information to stakeholders in a clear and understandable manner. Business analysts often use visual aids like diagrams, charts, and models to represent processes, workflows, and requirements visually. Strong presentation skills enable them to deliver findings, recommendations, and project updates to diverse audiences, ensuring engagement and comprehension. These skills enhance collaboration, facilitate decision-making, and contribute to the overall success of projects.

 

  1. Nonverbal communication

It is often mentioned that over 70 percent of face-to-face communication is Non-Verbal. Nonverbal behavior, such as body language, facial expressions, and gestures, plays a significant role in business analysis. It helps convey emotions, attitudes, and intentions that words alone might not capture. Observing nonverbal cues during meetings and interactions with stakeholders can provide valuable insights into their reactions, level of engagement, and concerns. Being attuned to nonverbal behavior allows business analysts to adapt their communication style, build rapport, and ensure effective collaboration. It also helps in detecting potential misunderstandings and addressing them promptly.

By considering and effectively executing all the above techniques, the Business Analyst is certain to have a much higher success rate in delivering and meeting the needs of the stakeholders

 

  1. Communication Strategy

This can be considered as the overarching technique or approach that is used and includes elements or all the above techniques.

BATimes_Aug24_2023

Best of BATimes: What Problem Are You Trying To Solve?

One of the most important lessons I’ve learned to ask during my BA career is “What problem are you trying to solve?” It’s not as straightforward as it might appear.

 

Often, business partners come with all sorts of preconceptions, which they present as the actual problem. Sometimes they try to be helpful. It’s the BAs job to ask more questions to determine if that’s the real problem.

For example, I had a business partner who told me that the data in an email we were sending to one of our customers was “encrypted”. It would have been easy to waste hours trying to chase that down. I started down that road, until I caught myself and asked “What’s the problem I’m trying to solve?” I asked the business partner to see a copy of the email. It was then that I realized that what she was referring to as being encrypted was actually just raw XML being presented straight to the page. The problem wasn’t that the email was encrypted, it was that it wasn’t easily readable by a human. One parameter change later, and the problem was fixed.

Donald Gause and Gerald Weinberg wrote a seminal work on discovering the real problem called “Are Your Lights On?” I reread it at least once a year, to remind myself how to ask the questions needed to determine the real problem, because sometimes what appears to be the problem at first glance isn’t the real cause.

 

A recent real-life example was encountered by the Dutch bike manufacturer Van Moof, who found that over 25% of their bicycles were being damaged en route to the customer, especially when being shipped to the US. The company could have invested money in improving their packaging or looking for a new shipping company. Instead, they spent time identifying what the real problem was: the people doing the shipping weren’t being careful with the product, perhaps because they perceived a bicycle as being sturdy enough to withstand rough handling. Or perhaps they didn’t perceive bicycles as being as valuable, so they didn’t feel the need to take extra care when handling them. What was the solution?

In the end, the bicycle company put a picture of a large screen TV behind the picture of the bike. They didn’t indicate that there was a TV in the box. The shippers, who apparently don’t have time to read carefully, treated the updated boxes like there was an actual big screen TV inside them. As a result, damages in transit dropped by 80%.

 

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1. Asking the business or customer what the problem is that they are trying to solve isn’t the end of the process, it’s only the beginning. Here are some ways you can get to the real problem:
Ask what things would look like if the problem was solved. Often, this will let you identify the real problem based on what the business sees as the desirable result. An example given in the book was a building whose tenants complained about the elevator being too slow. The desired solution wasn’t that the elevators be made faster, it was that the tenant’s stopped complaining. In the end, a mirror placed on each side of the elevator offered enough distraction that the perception of the elevator’s speed was no longer an issue.

 

2. Don’t accept a solution as the problem. Often in my career, the customer brings a solution that they want rather than a problem to be solved. Asking what the problem is that’s trying to be solved often allows for simpler resolutions. For example, one department is complaining that another department’s data entry isn’t accurate. The solution they presented was to add a high number of edits and validity check to the system where the data was entered. This would have required a large quantity of analysis and development time to ensure that the validations were correct and didn’t create additional follow on effects. Instead, time was spent bringing the two departments together to discuss the issues and looking for ways to improve accuracy at the front end. In the end, development wasn’t required, and the problem was solved via process improvement.

 

3. Spend time on root cause analysis. Sometimes the perceived problem is a symptom, not the actual malady. When I wrote software, a bug would frequently be caused by a change to a variable much removed in the stack from the code I was looking at. Doing root cause analysis will often help you identify what element is actually causing pain. This can also be a matter of overlooking something because “We’ve always done it that way.” The root cause may be the result of some process before or after the pain point that is creating the issue.

 

In the end, finding the real problem that needs to be solved, can be simple, complicated or somewhere in between. Taking the time to do the right level of investigation is an important part of the BA’s value in the development process.

 

Published: 2020/06/04
BATimes_Aug9_2023

Transformative Impact of AI in Business Analysis

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.

 

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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.

 

BATimes_July26_2023

Embracing AI in Business Analysis: A Guide for BAs

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. Engineering 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.

 

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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]

 

BATimes_July06_2023

Information Science, Knowledge Management and the Business Analyst

In today’s fast changing world, information, and technology are changing the way organizations and nations operate. The quality of information available to an organization, its ease of use and systems of dissemination can make the difference between organizations that thrive and those that get left behind in the archives of history. To understand this better, let’s look at the science of information.

Information science is the discipline that deals with managing information, from creation to final archiving or destruction. It is concerned with the generation of data, the associated technologies, and the transformation of data into information and knowledge. What is information? Let’s begin by defining data.

 

Data

Data can be described as independent entities, , numbers, letters etc. that on their own do not convey any useful meaning. Consider the following data set:  ‘A’, ‘John’, ‘boy’ ‘good’ ‘is’ ‘1’, ‘class’ ‘and’ ‘in’  ‘number’ ‘his’ . Each entity on its own does not really convey any useful meaning. However, when this data is put through a transformation process, with a pattern or structure, it conveys a meaning ‘John is a good boy and number 1 in his class – these entities which has been structured or patterned becomes information within the system.

 

Information

Information can therefore be described as data with a meaningful pattern to the system receiving it, such that it can change the state of the system. In other words when information is received by an individual, an organization or a system, it must be meaningful to that system: they have been transformed by this information. In some cases, the information received enables them to take an action or make a decision. This change in state might be from a current (as-is) state to a future (to-be) state, or just a change in position from point a to b, or from a less informed state to a more informed state.

 

Knowledge

Knowledge: When information has been fully understood, digested, and internalized by a system such that the system can reproduce it in various forms and disseminate it easily to others, it has become knowledge to that system. For example, an employee may build up their knowledge of a domain through multiple channels: training, conferences, water cooler conversations etc.  and become an expert with a full understanding of the subject area. They can simplify it into various forms and train others: the information they have absorbed has become their knowledge.

This relationship between data, information and knowledge can be represented as shown below in a knowledge circle.

 

 

The importance of knowledge to an organization can never be overemphasized. Organizations can thrive or fail depending on the quality of knowledge that exists within them. Knowledge in organizations exists in two forms: explicit and tacit knowledge.

Explicit knowledge is the knowledge that exists in the public domain of an organization. It is in their culture, in their SharePoint systems, books, journals… It is documented and widely available to all.

Tacit knowledge is the knowledge that exists within individuals and SMEs, it is unwritten, can be heuristic, is veritable and often lost when such individuals are no longer with the organization.

Seeing the value of knowledge to the continued existence of organizations, how can businesses best elicit the knowledge within their domain? How can they ensure the quality of their information, and extract valuable tacit knowledge from SMEs? Answers to these questions lies in the domain of business analysis.

 

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Business Analysts

Business Analysts are change agents who often sit between the business and technology arms of an organization. They help the communication between the business and technology, ensuring data from both sides is translated into meaningful information which both parties understand, ultimately causing a change in the state of the organization. Business Analysts help organizations move forward from a current state to a future state.

Business Analysts by nature of their training can elicit tacit knowledge from SMEs, document the knowledge and ensure organizations do not increase their technical debt when valuable employees leave. They are also well placed to investigate and scrutinize the volume of information accessible to an organization by verifying and validating it with SMEs before such information is used in business decisions, thus improving the quality of an organization’s information and knowledge.

 

Some of the Business Analysts’ skills include the following:

 

 

Concluding Remarks

The knowledge circle will continue to be at the heart of an organization’s growth. Organizations which harness their knowledge correctly will continue to outperform their counterparts, and Business Analysts who understand their role in this circle will continue to be great assets and instrumental to the success of their organizations.