Being “data-driven” doesn’t help create project success; being evidence-based does. Evidence-based problem solving reduces the risk of blind spots and confirmation bias and increases the chances of achieving the desired outcomes. In high-stakes projects, risks can be dramatically reduced when a business analyst is willing to apply first principles thinking, hypothesis testing, and information value analysis to integrate the best evidence into the decision-making process.
Collaboration is not about resolving conflict. It is about surfacing team members’ alternate opinions or their concerns with the overall groups’ decisions. And it also does not mean that everybody must be happy with the final decision. Everyone should understand what the decision is, why the choice was made, and have a very good feeling that all aspects of the issue, both pro and con, were given adequate discussion. In other words, once a decision is made everyone should be in agreement that they are behind the decision and will work to make the decision successful. Collaboration is achieved and group think is avoided when every person voices their view of the issue and is allowed to retain their personal view even when the final decision or conclusion varies from that view.
Business Analysts solve problems, but ultimately these solutions are meant to serve people, and it takes people to create the definition for these solutions. With that said, no matter how great an analyst is at discovery, analysis and solutioning, key soft skills are essential to being a best-in-class business analyst.
Soft skills are the people-side of business and really any type of engagement. There is a large variety of skills included in the soft skills category depending on which resource you read. But there are two that always seem to land in the top five..
Sometimes the best solutions are right in front of us, hidden in plain sight. Get in the habit of working from first principles and you’ll find it easier to cut through preconceptions to change the business question and quickly see alternatives that you may have missed.
The objective of this article is to help business analysts capture functional requirements for an information system as User Stories. It discusses four levels of story. The first two levels represent business context. Levels three and four involve functional detail needed by developers and testers to deliver stories at those levels.
Where an organization opts to move into agile methodologies that help to provide quick and customized solutions, it is imperative to use a technology that supports agile workflow and application development.
There are several Frameworks and Programming Languages in the market that help in building Agile Solutions but as compared to all the available Stacks, PHP is the one that Comes up with a collection of Potential Frameworks that are actually contributing well in developing effective Application Development.
The PHP frameworks are a set of process conventions and technologies that simplify and accelerate application development and maintenance. A framework provides certain functionalities to an application through ready-made features and practices.
It is more than important the modern business analyst to focus on the end to end customer experience. A BA shall act as a consultant that listen to the pains of the end users and is dedicated in solving them through providing solutions that will alleviate those pains. How do you define a customer-centric mindset you can actually execute? Below are some elements of the customer – centricity mindset...
In the eyes of process analysts, quality improvement professionals, and business analysts, who still rely on the more than 100 years-old, strictly procedural notions of a process and on flowcharting notations that were also invented in the last century, IT IS IMPOSSIBLE to perceive and model something like playing soccer as a sequential process.
The most effective business processes are not only structurally sound and efficient but also highly dynamic and agile. A high-quality business process structure today is one that has been conceived, structured, and can be readily configured as a network of specialized, collaborating, event-driven, and outcome-oriented services, not just as a sequential procedure.
Being successful as a business analyst is not a feat - reserved for a select few. Neither is it rocket science. It is achievable and within your grasp, if you apply a well-rounded approach to how you manage your career. While these tips are centered around the business analysis career, they can be applied to any career.
We hear the buzzword “business transformation” everywhere. It has become almost expected of any organization to announce they are on their digital transformation journey. What does it mean?
There are many definitions of digital transformation. This abundance points to a broad interpretation of the term. The ambiguity of these statements reflects vague expectations of many organizations embarking on their “digital transformation journeys”.
What is Use Case?
Use case represents requirement in the form of user interactions with the system. Use case is always written with a specific user goal in mind. Each use case must contain an actor and verb. For example, ‘online buyer’ is an actor and ‘add item to cart’ is a verb.
A use case diagram represents the scope of all the features of the solution. It follows Unified Modelling Language™ notation. Use case diagram comprises of several use cases that make the system altogether.
What is User Story?
User story is a business analysis artifact that is also user or persona driven. It describes the business need in the form of an ability user (or system) wants in the solution. It also must state why the ability is required and what the benefits of that ability are. It does not have any mandatory format though
User story is part of the (product/project) backlog. The backlog in turn contains user stories/tasks (requirements) in a linear fashion. Backlog is usually prioritized from high to low, additionally with a ranking when priorities are the same. When it is prioritized by business value of the tasks/stories in it, it is called managed backlog. In many projects, user stories are also represented visually as a user story map, which is a structured visualization of a backlog. User story map is a map of user stories that are transposed from a linear backlog, onto a visual working board.
Each of this concept is a detailed topic in itself. For the context of this article, I will limit it only at the introductory level. Let's now look into differences and similarities between user stories and use cases.
When engaging on projects we need to lead our clients to get the outcomes we need for analysis. If we act passively and don’t take charge then they’ll take things all over the place and create chaos. In this article we’ll explore how a problem statement acts as a powerful tool to keep control of our engagement and analysis right through the project lifecycle.
Taking a product from an abstract idea to an item that’s widely available in the marketplace demands a hands-on approach to prevent things from falling through the cracks. A technique that goes back nearly a century, product lifecycle management (PLM) has for decades been used to improve the efficiency of product development and design.
In recent years, however, a growing number of organizations are realizing the capability of cloud-based PLM software to drive fulfillment benefits. There is a recognition that you can strengthen your supply chain management by deploying PLM from product conception to multi-faceted fulfillment. As your product approaches maturity, it necessitates changes to workflow, supply chain, and fulfillment processes as a means of attaining sales objectives and driving overall business strategy.
But before we get into that and how PLM affects fulfillment, first a definition of PLM.
Does it make sense to merge Agile philosophies with data science? The short answer is yes, as long as the organization recognizes and accommodates the ambiguous, non-linear nature of the data science process rather than expecting data scientists to fit into the same mold they’ve adopted for “Agile software development”. The problem, in my experience, is that this rarely happens. Probably because the data science field is still new, many organizations are still trying to shoehorn data science into Agile software engineering practices that compromise the natural data science lifecycle.
I’ve written this article to provide an overview of AWS (Amazon Web Services) for Business Analysts.
The cloud (in particular AWS) is now a part of many projects. If you’ve been in meetings where people have mentioned: ‘EC2’, ‘ELB’, ‘AZs’ and thought ‘WTF’ then this article should help you.
This article will provide:
brought to you by enabling practitioners & organizations to achieve their goals using:
enabling practitioners & organizations to achieve their goals using: