How to build a better business with data analytics

In what ways can a business be improved through the use of data analysis? The possibilities are seemingly endless, but this article will give a top-level overview of the benefits of data analytics to any organisation – then deep dive into some specific analytics use cases to explain how this modern business intelligence (BI) solution can lead to improvements across a variety of business areas and departments.

The first modern data analysts, as we would understand the term today, used hand-typed spreadsheets. It was a slow and manual process. But the rapid acceleration of computer technology in recent decades has transformed data analytics into what we know today. Modern business intelligence means that countless data points can be collected in the Cloud, in real time.

There are many competitive advantages data analytics can offer to businesses. Here are just some of the top-level ways organisations can benefit from a data-driven approach.

Improved customer acquisition and retention 

Because data analysis can track patterns of consumer behaviour, companies can use it to understand exactly what their customers are looking for. This helps to build a solid customer base, and find ways to keep customers happy and build brand loyalty.

A business that has made a huge success of this approach is Amazon. The retail giant uses the purchase history of users, as well as the browsing behaviour of other customers, to deliver a highly personalised online shopping experience.

Powered by increasingly sophisticated algorithms and predictive analytics models, 35% of Amazon’s total sales are a direct result of this personalisation.

Better targeting

Data analysis – for example, the monitoring of online purchases and behaviour – gives companies consumer insights that allow them to deliver tightly focused campaigns tailored to their target audience.

By closely analysing customer trends, brands can create experiences that are far more effective than expensive blanket advertising campaigns.

Risk identification

In high-risk business environments, a robust risk management process is essential. Big data can be used to help your business to identify and forecast risks that can cause  harm and impact profits. 

Product innovation

Through the collection of vast amounts of consumer data, companies are able to identify a better fit between their products and their customers. This helps them tailor their existing products as well as developing new ones.

Product innovation, which for many years relied on the instincts of businesses, is now a smarter, data-driven process – able to track customer feedback and competitor activity to stay ahead.

Enhanced supply chains 

Today’s companies can offer their supplier networks more precision and insights than ever before. Through the use of big data, suppliers can gain more contextual intelligence to overcome the problems they typically face.

For instance, a data-driven approach allows suppliers to implement high-level collaboration, so networks can take new knowledge and apply it to solve existing problems.

How could data analytics improve your business? 

When it comes to transforming specific business areas and departments, there are many ways companies can use data analytics to improve.

Agility 

Agility has long been a core term in software development, describing a method of project management with loose or evolving requirements.

In wider business, agility relies on collaboration and iteration – both are critical skills in data analytics. Companies can use data analytics to optimise existing processes, or disrupt them through the development of completely new ways of working.

Real-time data analytics means teams are able to collaborate instantly, meaning faster decision-making and increased business agility. It allows for faster, smarter and more informed responses in a rapidly changing business environment.

Strategy 

The sheer amount of data available for analysis has the potential to transform traditional business practices, including strategy and planning.

Making data a core part of the business means companies can approach business problems from an analytical perspective. Data analytics can positively disrupt the entire company culture – developing data literacy and incentivising innovation.

Data-driven organisations that learn how to incorporate data collection and analysis into their strategic business plan enable more effective marketing, new opportunities, improved customer service and better efficiency.

Transformation

Crucial components of business transformation are high operational efficiency and customer centricity. Adoption of real-time data analytics will help improve operational efficiency and drive faster, smarter decision making – as well as help businesses better understand consumer behaviour and needs.

By allowing organisations to keep pace with rapidly changing market dynamics and technological landscape, data analytics strategies enable true business transformation.

Risk 

Many businesses are using data analytics to help develop and enhance their risk management solutions. Modern data analytics tools enable organisations to quantify and model the everyday risks they face.

Using the power of big data and Cloud-based analytics means businesses are able to formulate smarter risk mitigation strategies.

In the US, National Basketball Association (NBA) teams use game data analytics to inform almost every team decision – from designing game-winning strategies to anticipating injury risk. Data shows that players are less likely to suffer injury if they’re rested for 30 days after playing 30 games.

Prediction 

Predictive analytics is a branch of data analytics that helps businesses understand what is likely to happen next. Sometimes known as ‘advanced analytics’, it models historical data in order to make predictions.

For many businesses, predictive analytics is used to predict the most probable answer to a specific question – for instance, ‘what are customers likely to do in a given situation?’ This enables organisations to tailor their decision-making accordingly.

By analysing and predicting consumer behaviour, predictive analytics can reduce churn, improve customer service and increase conversion rates.

Supercharging a super-brand 

There are many examples of data analytics use cases. One of the biggest brands to take advantage of data analytics is Coca-Cola. They regularly collect consumer data in innovative ways to give them valuable insights into their customers’ needs and behaviours – using this data to inform product development and business strategy.

Back in 2009, Coca-Cola released its ‘Freestyle’ vending machine, which enabled customers to mix over 100 flavours using touchscreen controls. Installed across the USA in movie theatres, shopping malls, and fast food restaurants, these vending machines allowed Coca-Cola to collect and analyse huge quantities of valuable data and insight into the flavour preferences of their customers.

The superbrand’s clever data strategy further expanded in 2015, with the building of a digital-led loyalty programme. The programme delighted loyal customers with rewards, which required social authentication to claim. This allowed Coca-Cola to collect more valuable consumer data. This data allowed the company to understand its customers better, connecting more personality with them to increase consumption of existing products, and upsell new ones.

Why choose data analytics? 

Data analytics can add value to every team, up-skilling employees through data literacy. With the skills to read, write, analyse and think with data, employees can uncover the right insights to improve productivity and generate more business value.

As explained above, data analytics not only helps companies understand more about where their business is right now, it also helps prepare them for the future. By using data-led predictive analytics, organisations can shape smarter strategies in real time.

We’ve also seen strong data analytics use cases across many areas of business – from business strategy and risk management to agility and transformation. And, from a whole-business perspective, adopting a data-driven culture can help your whole organisation harness the power of collaborative analytics. Empowering employees through data literacy to innovate and make smarter, informed decisions.

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