Future of Business Analysis in RPA, AI / ML, & Big Data Analytics

4 mn read

Introduction

The field of business analysis is changing fast. New technology is rolling out at an exponential rate, creating new pressures & demands on every business organization. It’s very important for the Business Analyst (BA) to understand where the field is going so that they can proactively prepare for the drastic changes ahead.

Some of these changes are already happening right now.

Robotic Process Automation (RPA)

RPA is the automation of repetitive processes so that they require minimal or no human intervention. An example of RPA might be a chatbot you interact with online, like the ones on technical support sites. The bot is programmed to respond to the most questions people have, which it may identify through keywords.

“DoNotPay” is the world’s first robotic lawyer created by Joshua Browder, a British – American entrepreneur. It helps people fight parking tickets in several major cities by automating the ticket appeals process. It asks you a series of questions & then creates an appeal letter based on your responses. You then send the letter to the ticketing authority. It has helped citizens overturn over 200,000 parking tickets worth millions of dollars in revenue. It has a 60 % appeal success rate. The chatbot was originally built to contest parking tickets but has expanded to include other services as well. The power of RPA quickly scales into huge value when its efficiency gains apply to a large number of customers.

RPA techniques can apply to any data-driven process that allows the software to automatically capture, react & respond to a situation. That response could be output back to a user, or communicate with other systems, or input into a successive process.

RPA & BA

The Business Analyst will be essential to RPA in various ways. First, the BA will identify which business processes are sufficiently data-driven to lend themselves are prime RPA contenders. Second, the BA will help shape RPA by analyzing business processes & creating the business rules that the RPA software will process. Third, the BA will create the requirements necessary to implement RPA & adapt interfacing systems to accommodate it. Fourth, the BA will find ways to measure the value that RPA brings to the organization.

Artificial Intelligence (AI) / Machine Learning (ML)

RPA has a limitation in that it can’t learn. If one answers questions or responds in unexpected ways, RPA will not know what to do next. That’s where AI comes in. AI is becoming self-learning because of rapid advancement in the field of machine learning. It can figure out or be told an answer & then use that answer in the future to solve another problem. It keeps improving. Its self-learning ability increasingly means that AI will completely understand & respond to natural language.

AI self-learn by being taught how to react when it encounters a problem it doesn’t know the answer for. An example could be – an AI that answers call for a company’s customer contact centre. The company may program AI to answer the most common questions that come into the centre. When someone asks a question that AI doesn’t know, the AI may know how to search an internal knowledge base, the Internet, or Wikipedia. And the question can also get routed to a human agent, who then programs the AI with the response. From that point forward, anytime someone asks that question, the AI will have a ready answer. The process continues, & the AI keeps improving until it can handle almost any question.

Machine learning is also increasing understanding of context. AI can search surrounding words to understand what you are talking about if you ask, “How do I pay off my car loan?” AI can understand that you are asking about the loan, & not about your car or how to write a check, & that you want to know how to get free of it by paying it in full.

BA & AI

The Business Analyst will support AI the same way it will support RPA. The Business Analyst will also create the business processes & requirements necessary to enable AI to self-learn & understand the context. That might be supporting the business’s knowledge base or helping to implement sound Knowledge Management processes in the organization. If data is dispersed throughout the organization, the BA may identify the right data priorities & interfaces the AI will need. Or the BA might “train” the AI directly.

BIG DATA

Data is everywhere. The number of connected devices is increasing exponentially. Once the Internet of Things (IoT) gets going full-throttle there will be billions of sensors, smart appliances, & other devices connecting to the Internet & generating data.

Business organizations are increasingly drowning in data but may lack the means to make sense of it all. Yet there is a burning desire to make informed business decisions by using the available data.

Getting a handle on the fire channel of data coming in is a huge task. Consider:

  • ·       A business must define the data it wants & the means/interfaces for obtaining it;
  • ·       The data has to be of good quality, not junk;
  • ·       The data has to be meaningfully structured so that it’s useful;
  • ·       Large amounts of data must get stored or archived in a way that allows the business to access it when needed;
  • ·       One may need to tag some data with metadata so that one can readily find what one’s looking for;
  • ·       One must ensure data security & privacy; &
  • ·       One must have a way of pulling data to create meaningful & insightful analytics that the business can use.

BA & BIG DATA

The Business Analyst will have some role to play in all aspects of collecting, organizing, & presenting data. Some of the tasks listed above will usually be done by technical experts, analysts, & architects. But the BA is still responsible for creating the requirements around all of these functions. For example, she may define the metadata that is important for the business to use when searching for data or she may provide requirements that define how long the IT department must store data & the security standards the organization must apply. If an application requires particular data to function, the BA will be at the forefront of providing the necessary requirements.

But the most visible & important task the Business Analyst will have – is to help the business make sense of available data. The BA will learn to use tools (Ex – Tableau) to pull data & create meaningful, insightful analyses that the organization can use to make good business decisions. The BA can also help define relevant metrics to use for measuring business performance. Using analytics, the BA can show the business how well it has done in the past & predict future trends based on current performance.

The BA will be essential in creating a fully data-driven organization.

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