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Will business analysis survive the onslaught of data analysis?

Image of LN Mishra
LN Mishra

Will business analysis survive the onslaught of data analysis? This is really running in most business analysts’ minds. Data analysis has developed a new religion of its own. Presidents and Prime Ministers of countries are talking about the role of data in improving the living standards of citizens across the globe.

Will data analysis make business analysis redundant? Consequently, will business analysis as a profession cease to exist? Technology has and can disrupt various jobs and professions over many centuries. I personally have seen the practical death of IT project managers in the last 2 decades. Will we business analysts also become an extinct species?

Before we make any predictions, let’s understand at a high level the pre-requisites and utilities of data analysis and associated technologies such as machine learning, deep learning, and artificial intelligence.

Simpler forms of data analysis and business analysis co-existed for centuries and thus, there is no reason to believe that simpler forms of data analysis pose any sort of existential challenge to business analysis.

Now coming to machine learning and deep learning, these programs do have the capability to derive business rules which are not intuitive to business analysts and stakeholders. For rules which are known to stakeholders, we can use business analysis to capture them. At the same time, data analysis can provide insights that were not known to stakeholders and BAs.

Rule discovery quadrant

Rule discovery quadrant

As we look at the above 2 by 2 quadrant, 3 quadrants are discoverable by business analysis whereas one quadrant remains discoverable by data analysis.

Now, which are the areas business analysts and data analysts can collaborate on? Let’s look at the diagram below.

Skills for Business Analyst vs. Data Analyst

Business Analyst vs. Data Analyst

Any initiative including data analysis initiative will involve a certain amount of cost. As BAs, we need to ascertain if the value received from the initiative will be more than the cost incurred.

Data analysis also requires stakeholder management, planning, communication, elicitation, solution verification, and solution validation – All these areas are something business analysts are acutely aware of and can contribute significantly.

As technology progresses, a number of data analysis algorithms will be available at a level which non-data analysts can also leverage. Again, organizations can leverage their BAs to do low complexity data analysis projects and use expensive data analysis experts for more complex problems.

The patterns and rules identified during data analysis need to be incorporated into business processes and applications. This is again an area of high familiarity for business analysts.

It is imperative that business analysts be aware of capabilities available through data analysis and help stakeholders achieve their goals. In the future, many business analysts will acquire data analysis skills and may prefer to work purely in data analysis projects.

Ultimately, business analysts and data analysts will continue to support each other for better business outcomes. 

I will be very happy to get input from all my fellow business analysts if they have added some more information on business analysis vs. data analysis.

Suggested Reading-

https://www.adaptiveus.com/business-analyst-vs-data-analyst/

https://www.adaptiveus.com/should-business-analysts-learn-data-analytics/

 


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