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Data Analytics: Key To Business Growth, Improved Industry Efficiency

The data analytics is very essential in promoting business expansion and enhancing sector efficiency.

Effective data management has become increasingly important in the digital and globally evolved environment in which we live to provide worthwhile and advantageous results.
The Pension Fund Operators Association of Nigeria (PenOp) organised a seminar for experts in the pension business with this in mind.

The seminar’s main objective was to inform the attendees of the value of using data analytics to create long-lasting changes in the sector.

The online seminar, titled “Enhancing Operational Efficiency in the Pension Industry through Data Analytics,” had as its goal highlighting the importance of data as a resource. It placed emphasis on the necessity of managing unstructured data for business needs and gaining knowledge of potential patterns based on past data.

In-depth discussion on these and other subjects took place at a recent knowledge-sharing session hosted by PenOp. Professionals from all tiers of Nigeria’s pension industry took part in the event.

The Chief Executive Officer of PenOp, Oguche Agudah, gave an overview of his expertise and the successful applications of data in various industries. He talked about how data has changed over time, highlighting how it may improve office productivity.

Adeiza Suleman and Efemena Ikpro, co-founders of 10Alytics, led the session. Both are experts in data analytics, have assisted sectors like financial services, ed-tech, energy, and automobiles, and have more than ten years of management and consulting experience.

Over 8,500 people have profited from their combined knowledge.
The session started out with an introduction to a great operating model for firms employing performance reporting and customer analytics to enhance the customer experience.

The realisation that Data Analytics and Science comply to the CRISP DM – Cross Industry Standard Process for Data Mining – was the seminar’s key takeaway.

This process is targeted at producing insights, automating business procedures, producing data products, making product recommendations, and improving already-existing products.

The “Scientific Method” in analytics, which includes business understanding, data comprehension, data preparation, modelling, evaluation, and implementation, was also covered in the seminar.

Customer data, investment data, marketing data, customer service data, compliance data, and actuarial data collected on a regular basis, however, can turn into a knowledge deficit and a liability without sufficient analytics. Risk management, customer feedback analytics, recommendation systems, portfolio optimisation, customer lifetime value analytics, and investment portfolio optimisation are just a few applications for data analytics.

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