Over the years technology has bridged many gaps. These gaps existed between processes, skills and resources. However, an interesting turn of events happened with the era of Business analysis. This brought a time where data became the real asset and insights, disruptions and innovations followed. Not only this, data analysis helped solving recurrent business problems, something quite unimaginable in the times of manual file-based processes.
How did it all start?
Back in the days when everything was manually recorded on paper within hard bound files, technology gave the world a better way to manage processes with IT systems. Once these systems were in place, everyone started creating a lot of data. Only after a few years of accumulation of this data did organisations thought about using this data for generating value. This is where business analysis took precedence. There was an obvious market need for innovation and organisations realised that they need to be able to analyse this data and draw insights.
What does the present look like?
Today business analysis courses has evolved as an amalgamation of domains and analytical skills. Domain is one of the key ingredients for identifying patterns because without an understanding of the business it is simply not quite possible to draw any kind of conclusions or even understand the data. Several analytical techniques have become common. Some include MOST (Mission, Objectives, Strategies and Tactics), PESTLE (Political, Economic, Sociological, Technological, Legal and Environmental), SWOT (Strengths, Weaknesses, Opportunities and Threats), MOSCOW (Must or Should, Could or Would) and Six Thinking Hats.
Today, data talks well with folks with a keen understanding of domain and a good grasp of implementing analytical techniques. Their key challenges are ensuring that data is relevant and integrated. Once solved, organisations can harness the data and release innovative solutions in the market. Over the past few years, the market has witnessed ideas ranging from digitised health platforms to big data stylist services – all born from data analysis. And this is just the tip of the iceberg!
What does the future hold?
With automation and agile becoming a norm, there is an obvious push towards complexity. This means a major chunk of business analysis tasks that require human intervention today will be automated. While this is great news from a business perspective because it will bring reduced errors, lower cost of maintenance and less time to insights. The other end of the impact would be on utilisation of the insights resulted from data analysis. This would most likely be the next sweet spot where a keen understanding of business strategy would come into play to make real business decisions.
Business analysis that we know as of today is a much-advanced version of what it initially was scoped to deliver. Today, business analysis attempts to solve the data challenge by identifying the right data and analysing it to solve business problems. While the future looks complex, we can expect some real innovation and market disruptions from business analysis.