The role of Big Data Analytics in business process optimisation & automation

The optimisation and automation of business processes are essential nowadays if fintech companies are to remain profitable, enhance the quality of their services and stay competitive.

There’s a close interlinkage and interdependence between the optimisation and automation of business processes. In the current landscape, the automation of processes is the best way to optimise them.

This is where Big Data analytics, AI and ML take the stage. Read to find out how these technologies can help solve most problems that exist in business process optimisation and make it more efficient.

Business process optimisation explained

Business process optimisation is a component of the business process management mechanisms of an organisation. It is a set of practices that fintech companies or other organisations can use to make optimum use of the available resources.

It includes the creation of streamlined platforms for human resources so that they can complete their tasks individually and collectively. They are also required, at times, to create large scale changes in different processes.

Business process optimisation aims to enhance organisational efficiency by focusing on individual processes and improving their standards.

Creating seamlessness in workflows, forecasting and adapting to probable changes along with accurate communication, are some of the vital facets of business process optimisation.

Fintech companies can optimise their business processes by identifying and analysing problems and devising solutions. This should be followed by the implementation and monitoring of the solutions that have been deployed.

However, optimal handling all of these tasks is quite a challenge. And this is where automation with the help of Big Data Analytics, AI and ML steps in.

The significance of automation in business process optimisation

By using automation, fintech companies can make better decisions, which are driven by the accurate analysis of data.

For example, the marketing processes of fintech companies receive a considerable boost by the use of automated processes powered with Artificial Intelligence, Machine Learning and Big Data analytics. Similarly, fintech companies involved in equity and currency trading can use high-quality algorithms created after the analysis and processing of voluminous datasets to improve their operational efficiency.

What are the challenges in business process optimisation & automation?

The various steps in optimising business processes are well-known but implementing them properly to leverage optimum solutions can be difficult. Optimising processes for different organisations mandates specific plans to counter the existing redundancies and problems. However, there are some challenges which are prevalent in the fintech industry and make the most significant overall impact. Some of them are listed below:

• Inability to identify problems – The identification of issues leading to decreased productivity in different processes is the first step in optimising processes and making them more effective. Many financial institutions and fintech companies are not able to achieve this, leading to continued inefficiency in operations. At times, major issues might be present in multiple processes making it difficult for them recover before considerable resources are wasted.

• Wastage of resources – Numerous financial institutions and fintech companies fail to use their existing resources in the most profitable manner, which leads to substantial wastage. Creating optimised plans for using resources has always been a challenging task for financial institutions.

• Issues in the management of human resources – When optimising business processes within a fintech company, substantial emphasis needs to be put on human resource management. Assessing and tracking the performance of employees using well-defined and relevant metrics is a crucial task, but many companies aren’t up to the mark in this area.

• Improper handling of data – Optimising business processes requires fintech companies to make data-driven decisions at all times. Inaccurate analysis of datasets and the absence of substantial data can create chaotic situations. This is the case in many fintech companies.

• Not using the most effective automation software – When companies begin automating their business processes, they need to make use of high-quality software solutions with capabilities suitable to their requirements. Failure to select the right automation software can be one of the biggest obstacles in optimising individual business processes.

How can Big Data help in business process optimisation & automation?

Fintech companies can reap numerous benefits by using Big Data analytics, Machine Learning tools and Artificial Intelligence when optimising their business processes. Well-planned and accurate usage of these technologies can solve most problems that exist in business process optimisation.

Identifying issues faster

All fintech companies need to focus on monitoring business processes to identify problems at the earliest opportunity. By using insights formulated after the processing of accurate datasets, fintech companies can be confident in their ability to detect issues and take measures to solve them.

Managing resources more effectively

Big Data analytics can provide fintech companies detailed insights for the allocation and use of resources. The processing and analysis of data will allow them to ascertain the areas where resource allocation can generate maximum profitability.

As a result, wastage of resources will be prevented, leading to increase in revenues and more effective business processes.

Increasing productivity

The recruitment, as well as management of human resources, is one of the key areas of business process optimisation where Big Data analytics can play a vital role.

Using data sciences for employee recruitment and management can help you identify problematic areas in productivity. It enables you to hire talent in accordance with the needs of the business and predictive data models can be used to assess the performance of employees.

Improving data security

Fintech companies should use data management to create a centralised database facilitated by cloud-based platforms. Using role-based access methodology will ensure the security of data by preventing unauthorised access. All of this can be achieved by using relevant AI and ML tools.

Supercharging automation software

It is vital that fintech companies use automation software with Big Data analytics capabilities. Automation software must guarantee real-time tracking of processes to facilitate the resolution of bottlenecks before they get out of control.

The quality of automation that is incorporated in business processes greatly affects their efficiency. So, unless you have selected optimum software solutions, the results will not be as expected and the optimisation of your business processes will not be possible.

What’s the Spyrosoft’s approach to business process optimisation?

Empowering our clients by helping them attain their Business Process Optimisation and Automation goals are one of the core specialisms of Spyrosoft.

We have a team of experts well-versed in all aspects of Big Data analytics, Artificial Intelligence & Machine Learning that can revamp the business processes.

At Spyrosoft, we place equal emphasis and importance on using state-of-the-art automation solutions and incorporating suitable methods of business process optimisation.

Read more about our AI and ML services >>