Introduction

In a world that is becoming heavily reliant on information, statistics and trends, data analytics helps individuals and organisations use various tools and techniques to gain informative insights that drive decision-making and thoughtful management to optimise processes and increase the overall efficiency of a business or system. According to Gartner, data analytics is the critical accelerant of an organisation's digitisation and transformation efforts (Source 1) thus, giving rise to the Data-Driven Era.

Types of Data Analytics

There are four basic types of data analytics (Source 2);

1. Descriptive Data Analytics: This describes what has happened over a specified period

2. Diagnostic Data Analytics: Analyses the reasoning behind a particular outcome

3. Predictive Data Analytics: Predicts what is likely to happen in the near future

4. Prescriptive Data Analytics: Suggests a specific course of action based on the analysis of past data

Process of Data Analysis

Step 1: Define the data requirement

What do you need from the data? What type of insights are you looking for? For example, if you want to analyse how your customers perceive your brand, you may group the data into age, income and gender.

Step 2: Data Collection

Collecting both structured and unstructured data from various internal and external source

Step 3: Data Cleaning

This process involves removing any duplication and inaccuracies from the collected data and organising the data in a way that makes it easy to analyse

Step 4: Data Analytics

Involves using data visualisation tools to identify and analyse patterns and trends to gain valuable insights

Step 5: Decision Making

Using these insights to make well-informed strategic decisions to achieve objectives

Importance of Data Analytics in business analysis

90% of enterprise analytics and business professionals say that data and analytics are critical to their organisation's digital transformation initiatives (Source 3). Data analytics can support BAs in many activities ranging from processing simple routine tasks to complex behavioural analysis and predictive modelling. The benefits of data analytics are explored in more detail below.

1. Proactivity and anticipating customer needs

In compliance with McKinsey Global Institute, data-driven organisations are 23 times more likely to acquire customers, 6 times as likely to retain customers and 19 times more likely to be profitable. Data analytics allows BAs to identify and analyse consumer trends to understand clients' needs better. The surge in online interactions since the onset of the pandemic in 2019 has seen 71% of consumers expect companies to deliver personalised interactions mentioned below (Source 4).

Companies that strive to foster high levels of customer intimacy have seen a 40% rise in revenues from personalisation alone (Source 4). Thus, it is clear that data analysts can support the discovery of hidden patterns, correlations, market trends, and customer preferences that can help organisations make smarter business decisions and develop a unique selling point and competitive advantage.

1. Improved efficiency

Business analysts can leverage data analytics to identify and gain a more holistic understanding of inefficiencies within an organisation. This knowledge can then be used to deploy resources more efficiently, streamline processes and improve strategic decisions, improving overall efficiency and reducing costs. Further, a survey conducted by BARC saw that organisations that use big data experienced an 8% rise in profit and a 10% fall in costs (Source 5).

2. Fraud and Risk

Using statistical, network, path, and extensive data methodologies in predictive fraud propensity models can generate real-time threat detection alerts, predict the future fraudulent activity and identify and track perpetrators. Such risk-reducing data analytics allow business analysts to identify and mitigate potential risks/ threats and deliver optimum fraud prevention and overall organisational security.

How CBI uses data analytics

1. Project Management

As mentioned, data analytics provides opportunities to optimise your project management process. Data-based decision-making improves planning, forecasting, and business modelling resource management, enhances project risk management, learning from the past and applying intelligence to future needs- improves project outcomes and the ability of an organisation to learn and improve.

It will enable our team at CBI to gain a more thorough understanding of our client's needs and a deeper understanding of our ability and performance. This underpins our ability to make well-informed decisions which ensure the goals of projects closely align with the business's strategic objectives, turning your plan into successful delivery.

2. Process review/ improvement

Drawing on data analytics fortifies our ability to collaborate with your organisation to identify opportunities for improvement and support you in your journey towards standardisation across your organisation. Our As Is / To Be visuals employ a combination of descriptive, diagnostic and prescriptive analytics to illustrate the starting point for change and highlight areas that require improvement.

3. Stakeholder Management

Engagement and cooperation between stakeholders are integral for the success of a project. Utilising data analytics allows our BAs to identify different stakeholders needs and priorities which are incorporated into the formulation of strategies. Data analytics also allows out team to understand, evaluate and manage stakeholder expectations, ensuring all stakeholders of your business are taken care of well.

Conclusion

The stark reality is that data analytics is crucial for modern businesses' success. The statistics above show that data helps companies grow and expand faster than ever. In addition, the increased accessibility of data analytics technologies and solutions means that the barrier of entry to insights is eroding every day. Simply put, if your business is not looking to reap the benefits of good data analytics, it could result in an adverse competitive disadvantage. But, on the other hand, if your business takes advantage of the opportunities data analytics has to offer, your business could be the one to gain a first-mover advantage.

With that being said, analytics is not a one-size-fits-all solution. A company must have a clear use case in mind before implementation. High-quality data analytics and proper implementation are crucial to generate the best results and reap the rewards.

Contact us now to see how CBI can help with your digital transformation and help you stay ahead of the competition.

Sources:

1. Gartner (2019): Why Data and Analytics Are Key to Digital Transformation

2. Investopedia (2023): Data Analytics: What It Is, How It's Used, and 4 Basic Techniques

3. Keebola (2022): 5 Stats That Show How Data-Driven Organizations Outperform Their Competition

4. McKinsey and Company (2021): The value of getting personalization right—or wrong—is multiplying

5. BARC: Benefits of Big Data Analytics: Increased Revenues and Reduced Costs