Major Errors by a Business Analyst

Major Errors by a Business Analyst

A great business analyst helps provide various benefits and advantages to an organization by delivering quality information and methods that lead to success and growth. However, a bad BA can complicate matters and provide poor solutions that hinder business growth and even result in closure.

Let’s understand the major errors committed by business analysts that can lead to losses and fatal consequences for the business.

  1. Creating Requirements Gathering at a very early stage:
    Many business analyst projects fail right from the beginning. For a project to be successful, the requirements of an enterprise or organization must be defined by the most senior executives within the company. However, this is often handled ineffectively, leading to a waste of time.
    The main reasons for improper requirements gathering include junior analysts who don’t know how to do it, experienced analysts who think they don’t need to do it, and senior executives handing over their tasks to juniors. Due to these silos in thinking and a lack of proper project handling and workflows, there can be issues with the requirements understanding of the whole team.
  2. Improper Modeling:
    Improper modeling is another issue faced by BAs during analysis, due to the first error. It means that the current workflows of an organization will be the same in the future, with no improvised solutions provided. Furthermore, due to low requirements gathering, no one bothers to find out what the business is lacking and provide a proper path through analysis.
    For example, junior analysts, being fresher, mistakenly believe that talking to people in the enterprise who operate the current systems on a day-to-day basis is the ideal place to learn what the enterprise requires. Mid-level/senior analysts, who know exactly what the enterprise needs, will want to cover their backs by producing some sort of documentation or business model prior to building or modifying a system, so they will start documenting, or get a junior analyst to document what already happens in the enterprise.
  3. Only Using Process Modeling:
    Another error by a BA is to use only process modeling as the primary business modeling technique. Process modeling was introduced when business process management was used. Although everything is not based on the business process, there are other areas that also need to be worked out within each and every process. Process modeling can be a waste of time and money.
    Also, when users attempt to decompose processes, it introduces logically flawed structures because processes are structurally networks, not hierarchies. The best modeling technique that is ideally suited for modeling all activities across all or part of an enterprise is Function Modeling, which consists of three levels: everything that happens in an enterprise is a business function; business functions are hierarchical in structure, and no redundant models are produced.
  4. Modeling ‘How’ as Opposed to ‘What’:
    When it comes to understanding complex systems or phenomena, there are generally two main approaches: modeling ‘what’ and modeling ‘how’. Modeling ‘what’ involves creating a representation of the system that captures its structure and components and can be used to simulate its behavior under different conditions. Modeling ‘how’, on the other hand, focuses on understanding the underlying mechanisms and processes that drive the system’s behavior.
    After having made all of the errors above, analysts then compound them by modeling mechanisms as opposed to functions and procedures as opposed to processes. In other words, they model the “how” as opposed to the “what”.
  5. Modeling Data Separately from Function:
    By separating data and function, the system becomes more modular and easier to maintain. Changes to the data or functions can be made independently, without affecting other parts of the system. However, it can prevent the maximum benefit from being delivered to the enterprise, such as when an organization hires “business analysts” who cannot perform data analysis tasks. Those hired as data analysts start looking for data elements using entirely

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