A business systems analyst (BSA) can be described as someone who undertakes business analysis tasks as stated in the BABOK Guide. A BSA is responsible for finding, extracting and interpreting information from a range of business sources including tools, procedures, documents and stakeholders. A BSA ensures that the requirements of the stakeholders are well elicited. This involves examining and articulating their stated needs to establish the problems in a system and its causes.
The role of a BSA is to align the planned and implemented strategies with stakeholder needs. The tasks that analysts perform include: understanding enterprise problems and goals; analysing needs and solutions; devising strategies; driving change; facilitating stakeholder collaboration (BABOK v 3.0, 2015).
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When trying to deliver a project, business analysts’ employee the use of multiple methodologies. Organisations have historically used waterfall model to deliver these projects. But with advancement in technology and the need to deliver systems faster, companies have moved towards using agile as a preferred framework. But to align to a new methodology is not an easy task. It comes with its own set of challenges. At the centre of this integration are the various roles and commitments that key project team stakeholders need to serve. BSAs are a key part of these members that were required to change their way of working and embracing agile methodology. The have adopted new roles and are now responsible for different goals and achievable (Shah, 2017).
With growing use of technology in each aspect of the market, the data being generated daily is huge. Companies try to use this data for important decision making process and perform multiple operations on millions of lines of data each day. Compiling all this data together in a single place and then segregating it into chunks with similar attributes is a task that was initially carried out by engineers. But making sense out of this data and delivering useful information to the top level management is the job of someone who can understand the business well. This is where Systems Analysts come in. Nowadays, business analysts not only have to perform their regular tasks, but dive deep into the world of big data and data analytics to generate information that can be put to use to make important business decisions.
Agile
According to Kumar (2019), Agile Methodology believes that the procedures needed in today's market to produce high value software are not predictable. Needs change, technology evolves, and efficiency of individual team member is highly unpredictable. When activities are not stable, and effects cannot be anticipated within reasonable range, we cannot use predictability-based planning techniques. We need to change the methods instead and direct them to produce our intended results. Agile project management achieves so by having development readily visible, monitoring project results regularly, and retaining the capacity to respond to changing situations when required.
Today, agile methodologies — which include new ideals, concepts, procedures and advantages and are a revolutionary alternative to traditional style management — are expanding through a wide variety of sectors and roles, and even into the C-suite. National Public Radio uses agile approaches to develop innovative content. These are used by John Deere to build new machinery, and by Saab to manufacture modern fighter jets. Intronis, a major provider of cloud storage services, uses these to market their products effectively and innovatively. C.H. Robinson, a multinational logistics supplier to third parties, extends the use of agile to human resources. Mission Bell Winery uses it for everything from wine making to storing to managing its senior management department. And GE relies on these methodologies to drive itself from being a 20th century conglomerate to a 'digital industrial enterprise' of the 21st century. By taking people out of their organisational silos and positioning them in multidisciplinary groups that are self-managed and client-focused, the agile model not only accelerates economic growth but also helps to develop a new breed of professional team managers (Rigby, Sutherland, & Takeuchi, 2016).
A 'mindset' is the set of behaviours that we put into one aspect of our life. In this case, we are thinking about getting an agile mentality on how we perform business analysis and how it relates to profitability in the real world. The agile approach is focused on a shared framework of human values that includes loyalty, confidence, teamwork, ongoing training, emphasis on customers and increasing value (Shane & Ananta, 2019).
In traditional software development practices, a business analyst had to gather requirements in the beginning of the project and then went ahead with planning designing and production. This created problems with longer projects in which the requirements would get changed a lot. This resulted in unnecessary delays or problems. Kumar (2019) stated that, agile focuses on moving towards clarity, instead of building complexity-managing processes. What Agile also does is compel specifications to be broken down much sooner in the life cycle, just so that their reach can be identified and converted to a User Story in the backlog to be prioritised. We have an expected autonomy among the functions because of the design of the agile specifications. Development is embedded within the user story, and each story can be individually checked, removing the need for complicated management software for specifications. Agile teams will also use advanced monitoring tools to track demands and handle them through the entire life cycle of growth.
So, while traditional software development methodologies like the waterfall model relied on complex methods to solve their problems, Agile uses simple and effective techniques to work its way around problems. Also, Agile is a faster and more efficient way to develop software in this fast paced and ever-changing market. With its whole premise being based around expecting changes, Agile works closely with changing requirements and changing stakeholder demands to ensure the end product is as market fit as possible.
As Shane & Ananta (2019) mentioned, agile practitioners concentrate on creating something, presenting it to customers, and prompt input to assess whether they are on course to fulfil the need. Agile practitioners in market research include stakeholders in discussions to create and sustain mutual understanding. Documentation does offer meaning, but only if it is written in accordance with its planned intent. Agile business analysis experts generate the required documents when they incorporate a transition and use it to promote and sustain stakeholder conversations.
Closely working with stakeholders on a project enables business analysts to ensure that any requirement changes in the project are always accounted for. In a market that is extremely volatile, the needs of an organisation changes every day and this needs to reflect on the end product. Stakeholders get regular updates so that they can guide the team whether they are on the right track or not. This makes agile a highly effective tools in a business analyst’s arsenal as he is the one who will always be in contact with the stakeholders on the inside and out. He is the one making sure that everything runs smoothly.
Big Data & Data Science
With the growing use of technology, data is also growing. Big data means not only large and complex data collection but also revolutionary thinking, smart technology and an ambitious technical revolution. Using big data, data analysts can process additional data and then have the capacity to manage many characteristics on a vast number of records. Big data is hugely critical and has to be analysed in order to gain valuable information and make the best business decisions (Liu, 2020).
According to Steinberg & Aronovich (2020), the use of data analytics in the industry and businesses has a variety of features that stick out. One of the most significant is that the issues are given priority, not because of the technical obstacle they present, but because of the additional value they bring the organisation. In this climate, a successful data science specialist has to recognize what powers the business of the client and recognise the influence of their assesses and resources on the end. This perception is also important for deciding which issues to include in line with the empirical engineering paradigm to set priorities.
As Murthy and Raghunath have stated in their whitepaper (n.d.), business analysis requires assessing business workflows or structures, and reviewing the business strategy and its application with innovations such as data science. Nonetheless, several companies concentrate more on the need for data scientists to believe that it will be enough to improve metrics and neglect the role of BA specialists who can actually play a critical role in this transformation process. BA experts can serve as a bridge between the analytics team and realistic solutions to business matters. Having BA professionals on deck will have an impact on whether the investment made by an organisation pays off and develops into usable information.
An organisation might feel that it can get by with only data analysts in the team but having knowledge of both business processes and accessing the right data is critical. Business analysts can provide the perfect combination with a little upskilling and can help an organisation find the right data to base its results on. As Khanna & Singh (n.d.) explain, the BA specialist can use his or her industry expertise to determine the correct set of data needed to test the prioritised concept, verify the usability of the data and confirm the legal rights to use the details, given that some of these data could come from interfaces used by consumers. The next stage, once the staff has access to the right data, is to search for lost, insufficient, inaccurate and distorted data. The BA expert can then pick the data which yields the best business impact for the client based on his or her industry experience. It can also prove useful to do a cost benefit analysis or a business case on the dataset chosen for the analysis.
Requirement gathering can thus be improved by ensuring a close-knit workplace with data analysts and business analysts where the data analysts work on the technical side of the data and the business analyst ensures that the data is always relevant and presents value to the business.
The use of data and data science in the healthcare sector is particularly promising. In the last five years, healthcare providers have committed billions of dollars in technology to maximise patient engagement, increase the quality of patient care and reduce the overall care costs. And investors in healthcare are highly curious about investing in Healthcare IT. Electronic medical records or EMRs have evolved rapidly due to innovation in technology. (Roth, 2019)
Big data continues to affect healthcare firms. “Few dispute that organizations have more data than ever at their disposal”, said McKinsey and Company (2016). “But actually deriving meaningful insights from that data—and converting knowledge into action—is easier said than done”.
Roth (2019) tells us that, business analysts are a valuable tool for healthcare companies as they are wading through a large volume of data and putting it to effective use. Data science is a valuable asset for healthcare institutions but it is useless if left unused. Business analysts help corporate leaders draw on the importance of big data for enhancing the health of patients. Apart from this, BAs help the top level formulate and execute strategies that help the companies with their cost and growth.
But data science is not all sunshine. It brings its own set of problems for companies implementing it. All stakeholders do not have the technical understanding to comprehend the information derived from the operations performed by the data scientists. It falls on the business analysts, to analyse that information and form structure and meaning so that all level of stakeholders can understand and make informed decisions.
Conclusion
Business analysis is on the cusp of transformation and technologies like agile and data science are leading the charge. From gathering requirements in an organisation to managing stakeholders, everything is changing. Along with this change, it is time for business analysts to change their skillset as well. The boundary between business analysts and data analysts is slowly diminishing as they cross over each others functions and responsibilities. But the knowledge of business and industry expertise with a BA is still a valuable weapon in his set of arsenal.
Agile is improving the way BAs deliver software projects by expecting change all along the way of the project while the extraordinary amount of data produced nowadays helps them to generate important information which is extremely beneficial to the corporate leaders in a company.
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