Although we think of it as a product of the digital age, data analysis isn’t new. It’s been around for decades.
In his 1962 book, The Future of Data Analysis, John W. Tukey predicted that evolving statistical mathematical models would give rise to something more complex: data science. It’s even possible to trace the origins of predictive analytics, something we would usually associate with advanced artificial intelligence and machine learning algorithms, all the way back to the 1940s.
Despite the long and storied history of data analytics, many businesses have only scratched the surface when it comes to unlocking its full potential. For them, the journey towards true data maturity has only just begun.
What is data maturity?
Data maturity is the measure of your data management and analytical capabilities relative to others. Less mature companies typically rely on manual approaches and basic tools like Excel to manage and process data. There’s little consistency or internal expertise, outside of one or two specialists who everyone else in the team relies on.
At the other end of the spectrum, you have data mature companies. They combine in-house expertise and advanced technologies – including automation, machine learning, and predictive analytics – to deliver business intelligence quickly and at scale. Data underpins their core systems and processes; it’s woven into their DNA.
Data maturity breeds business success
It takes dedication, not to mention a considerable investment of time, money, and effort to become data mature. But the evidence shows data maturity and business success go hand-in-hand.
Increasing your data maturity can help you:
- Make better decisions
- Identify opportunities and risks
- Streamline internal processes
- Achieve greater ROI
Make better decisions
Data mature companies base their decisions on research and careful analysis, not hunches or assumptions. It’s simple: a data-driven approach allows you to make faster, more accurate decisions that align with your wider business goals.
Take this example from McKinsey:
A European home-appliance manufacturer used advanced analytics to scan more than 12 million invoices across 5,000 suppliers, identifying opportunities to reduce total costs by 7.8%.
It’s no surprise that 49% of respondents in a Deloitte survey said that better decision-making was the main benefit of data analytics.
Identify opportunities and issues
When you have access to a regular stream of objective business insights, you can spot opportunities much earlier than your competitors. Predictive analytics, for example, allows you to monitor market trends and create new products or services to satisfy demand.
In addition, data mature businesses can quickly spot potential issues. That could be a legacy product that no longer provides value to your customer base or growing dissatisfaction among your employees.
Streamline internal processes
Using data analytics to understand consumer behaviour is nothing new in B2C contexts. Personalisation is a prime example of the way retailers use customer information to provide more accurate product recommendations and a better level of service. You can apply the same methodology to improve your internal processes.
Your data warehouses are likely full of invaluable insights that could help you spot bottlenecks, inefficient processes, and wasted spend. Careful analysis can also reveal solutions to these problems, and, with predictive analytics, the impact remediation might have on your operations.
Achieve greater ROI
To make the case for any new business initiative, you must prove that it can deliver a decent return on investment. And research suggests few investments are as profitable as data analytics.
Analytics and business intelligence solutions deliver an average ROI of 1301%. A wide range of factors contribute to this incredible statistic, including:
- Increased sales
- New business opportunities
- Reduced operational costs
- Enhanced risk management
- Better understanding of financial drivers
As AI and machine learning become mainstream, advanced data analysis will unlock even more opportunities.
Turn your data into a strategic asset
Data maturity is a journey with multiple stages, not a short-term project. Before you take the first step, you must know where you are now and where you want to be. After all, how can you plot your course if you don’t know the destination?
This requires more than technology. You need a data maturity model and the right combination of data visualisation and analytics tools, knowledge, and experience to navigate the pitfalls that stand between you and your goal. It might seem like an overwhelming task if you’re starting from scratch. But the longer you wait, the further you’ll fall behind your competitors.
