Tag: Communication

How Generative-AI Can Help Modernize Your Legacy Software

Written by Jacelyn Sia on May 1, 2024. Posted in Articles.

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

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

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

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

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

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 Security Vulnerabilities: Outdated coding practices and unpatched vulnerabilities can leave your legacy software exposed to cyberattacks.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

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

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

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

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

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

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

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

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

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

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

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

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

Step 1: Identify Target Applications:

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

Step 2: Inventory and Analyze Existing Systems:

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

Step 3: Code Refactoring and Optimization:

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

Step 4: Modern UI/UX Design:

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

Step 5: Incremental Modernization:

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

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

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

Step 7: Monitoring and Performance Analysis:

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

4 Tips for Managing Ambiguity as a Business Analyst

Written by Giorgos Sioutzos on April 17, 2024. Posted in Articles.

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

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

#1- Approve Ambiguity

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

#2- Mindset Shift

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

#3- Utilizing Effective Risk Response Strategies

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

#4 – Have a Compass

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

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

Web 3.0: The Future of Process Catalogue Management?

Written by Adam Pearson on March 27, 2024. Posted in Articles.

Web 3.0 technology, in my view, can be used for new innovations and has the ability to deliver positive change quicker. Specifically, Blockchain technology could allow for a transparent, automatic and secure way to manage a business’ process catalogue.

Traditionally, when analysing processes things like Upper/Lower Specified Limits, Service Level Agreements, and Defects Per Million Opportunities are used to understand whether a process is performing satisfactorily. This requires a BA to take measurements, validate them and then work with the business to pivot the process back to delivering the agreed standard. The typical business trigger event for this is either automatic or internal– it requires a BA to pick up during routine quality testing, or an actor to notice and raise through an agreed mechanism. This is because the process infrastructure is basically storage; it could be coined as “static management”. This means things can be missed, as humans make mistakes and the data does not work for the business, rather the business works for the data.

There have been recent advancements in technology, namely Web 3.0, which can reduce or potentially eliminate the human error element and turn the process catalogue into a dynamic storage, in which the data works for the business. In particular, Blockchain technology offers several features that could transform the way we work.

A Blockchain has several features, such as: Nodes, Ledger, and Wallets. Nodes are users/devices that hold the ledger, in full or in part. The Ledger is the record of transactions that happen across the blockchain and wallets are areas, in crypto blockchains, where the cryptocurrencies are stored.

At a first glance, this ecosystem seems locked to currencies, I believe it can be adapted to handle processes. Each process would need to be broken down into its steps and identified by its inputs/outputs and business actors. This dataset is then integrated into a blockchain – with each block containing the data from a single process step. In terms of a traditional process map, the block is the process step and the transaction is the connector lines between two process steps. In process terms it would be Step, Connector, Step; in blockchain terms it would be Block, Transaction, Block.

When the process is run, new unique blocks are added to the chain with the details of that unique process step run, which are then linked to further blocks/steps via transactions, providing a completely transparent and auditable record.

This setup has an infrastructure advantage because a blockchain validates transactions through decentralisation, using other blocks already in the chain. It means process rules are embedded in a chain from existing blocks and are then used to validate new blocks, resulting in a guaranteed uniformed process run, as the blockchain would only validate the transactions in accordance with the blocks already there.

The blockchain allows for easy performance monitoring, as each block is recorded with management information as well as process information and this is all in one place, it is easy for an analyst to calculate run times, business actor performance on individual or multiple transactions and process efficiencies.

Once an improvement is identified, the process is updated and released onto the blockchain, then becoming the single-source-of-truth for transaction validation, therefore only allowing the most up-to-date process to be followed by business actors. In this sense, the blockchain is both the governing authority as well as storage for processes.

The problem with this is that it is still reliant on humans picking up on the fact that a process is not performing, so whilst we have an enforceable process level to six sigma, we do not have the benefit of removing the human error or time lag associated with a drop in process performance.

This can be resolved using a feature of a blockchain called a smart contract. Smart contracts are automated digital contracts which trigger when the terms and conditions of that contract are met. There is an equivalent document in the business world, which sets out an agreement between two parties to perform in a particular way or to a particular standard under particular terms – a Service Level Agreement (SLA).

The smart contract is the Web 3.0 equivalent to the SLA. However, a smart contract offers much more than just an agreement, it self-executes which means as soon as the terms are met, action is taken with virtually no time lag.

The smart contract is created using an if/when then statement. An example smart contract can be if a customer makes an enquiry and no one contacts the customer in 3 working days, then an escalation notice is sent to the assigned persons manager. As this is automated, as soon as the condition is met, the contract is acted upon – meaning management do not have to spend time reviewing whether the conditions within SLAs, making both service and personal performance management easier.

There are, however, some issues with blockchains which need further consideration to overcome: a large number of transactions can cause lag on the chain, due to the required effort to process them all, meaning slower transaction times. It may mean that this model is best suited to small startups/businesses. Blockchain technology is still new, and therefore is not thoroughly regulated yet, meaning it can be difficult to fit in with current governance structures. This can be tackled by robust risk management and future legislation or policies, meaning this model may be suited to an innovator type business.

In summary, Web 3.0 Blockchains can offer improvements to the operation, governance and management of processes. By leveraging features of blockchains, it’s possible to move from a static process catalogue to a dynamic, automatic and smart infrastructure which reacts quicker to changes in business environments, freeing up staff to find other efficiencies or grow the business in other ways. While there are concerns and issues around things like scalability and regulations, it is clear that Web 3.0 technologies can offer new and exciting opportunities.

The Mind as the Canvas

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Ego Check: The Secret Sauce of Successful Business Analysis

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

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

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

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

Don’t let this be you!

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

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

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

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

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

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

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

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

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

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