The Struggle is Real: Why Businesses are Grappling with Becoming Data-Driven

An overly dramatised depiction of the journey to data-driven success. Generated by DALLE

In the fast-paced world of business, data has emerged as the new gold. It's no secret that companies that effectively leverage data to guide their decisions and strategies often outperform their competitors. In fact, according to a study by McKinsey Global Institute, data-driven organisations are 23 times more likely to acquire customers, six times as likely to retain them, and 19 times more likely to be profitable. However, despite the clear benefits, many businesses find themselves struggling to become truly data-driven.

The Importance of Being Data-Driven

Before we delve into the challenges, let's take a moment to understand why being data-driven is so crucial. In today's digital landscape, businesses generate vast amounts of data from various sources, including customer interactions, operational processes, and market trends. This data holds valuable insights that can help organisations:

• Make informed decisions
• Optimise their strategies
• Drive innovation

By harnessing the power of data, businesses can gain a competitive edge, improve efficiency, and ultimately, boost their bottom line. According to BARC research, businesses using their data saw an 8 percent increase in profit and a 10 percent reduction in cost.

The Hurdles on the Path to Data-Driven Success

The difference between good and bad quality data. Generated by DALLE

So, why do businesses struggle to become data-driven? Let's explore some of the common obstacles:

Data Quality

Firstly, data quality is a major hurdle. Poor data quality, characterised by inaccuracies, inconsistencies, and incompleteness, can lead to flawed insights and decision-making. It's like trying to build a house on a shaky foundation - no matter how beautiful the design, it's bound to crumble. Studies from Gartner show that poor data quality costs businesses an average of $15 million per year. It's a silent killer that undermines the very essence of being data-driven.

In my own experience conducting research, I encountered this challenge firsthand. While researching generalisation across datasets, I found that the data often came in different formats, and the quality of many datasets was subpar, rendering them unusable for my analysis and experimentation. This issue is not limited to academic research; I've noticed the same problem in industrial projects. The data collected is not always suitable for AI and analysis, forcing teams to get creative in finding solutions.

Data Structure

Secondly, businesses often grapple with unstructured or poorly structured data. Oracle claims that around 80% of business data is unstructured. When data is scattered across different systems and formats, it becomes a nightmare to integrate and analyse effectively. It's like trying to solve a puzzle with pieces from different boxes - it's frustrating and time-consuming. This lack of a unified data structure hinders the ability to extract meaningful insights and derive value from the data.

In one particular project, our team faced a situation where the client had data stored in various formats across multiple databases. Some data was in CSV files, others in SQL databases, and some even in plain text documents. We had to invest significant time and effort in data preprocessing and transformation before we could even begin the analysis and AI pipeline designs. This experience highlighted the importance of having a well-structured and consistent data architecture.

Data Strategy

Thirdly, many organisations lack a clear and comprehensive data strategy. Without a roadmap for collecting, managing, and utilising data, businesses find themselves drowning in a sea of information. A well-defined data strategy is the compass that guides businesses towards data-driven success.

To add to this, data siloing can also be a significant barrier to becoming data-driven, if not done right. When data is isolated within different departments or systems unnecessarily, it prevents a holistic view of the business. Siloed data leads to inefficiencies, duplication of efforts, and missed opportunities for collaboration and innovation.

Overcoming the Obstacles: Strategies for Becoming Data-Driven

Now that we've identified the challenges, let's explore some strategies to overcome them:

Data Governance

Implement a robust data governance framework to ensure data quality and consistency. This involves setting data standards, implementing validation processes, and assigning clear roles and responsibilities. Regular data audits and cleansing exercises can help maintain the integrity of your data.

Speaking from personal experience, at the start of our journey as a company, we actually neglected data auditing. Surprising, considering we are all data professionals, right? When we did start needing this data as we began growing, we realised that we had to do it anyway. Not only that, but we also had to spend time converting the data we already collected to adhere to the structure we had formulated. It was a valuable lesson in the importance of proactive data governance.

Data Strategy and Integrations

• Invest in data integration solutions to break down data silos and enable seamless analysis. By connecting disparate data sources and creating a unified view, businesses can unlock the full potential of their data. It's like assembling the pieces of the puzzle to reveal the complete picture.

• Develop a comprehensive data strategy that aligns with your business objectives. This roadmap should encompass data collection, storage, security, and utilisation guidelines. It should also define clear metrics to measure the success of your data-driven initiatives.

Several data integration solutions exist, including ETL (Extract, Transform, Load) tools that automate the process of extracting data from various sources, transforming it into a consistent format, and loading it into a central repository.

This is one area where we at Numvio actually excelled from the start. Two key aspects contributed to our success: effective communication within our team about what we needed to store and for what purpose, and our technical expertise in designing an infrastructure that was scalable for our needs, manageable for our small team, secure, and unified for easy analysis across datasets. Getting the data strategy right from the outset can save a lot of headaches down the line.

Culture and Education

Foster a data-driven culture that encourages data literacy and data-informed decision-making. This is a key point that most companies neglect, but is actually the key barrier to being truly effective with your data. What's the point of setting up systems and processes if your employees don’t understand how to use them, and why they need them? Provide training and resources to empower your employees with the skills to leverage data effectively. Celebrate successes and showcase the impact of data-driven decisions to reinforce the importance of this approach.

Creating a data-driven culture is not just about tools and processes; it's about people. At Numvio, we made a conscious effort to promote data literacy at all levels. We conducted regular training sessions, shared success stories, and encouraged cross-functional collaboration around data initiatives. By empowering our employees with the skills and mindset to leverage data effectively, we were able to create a culture that truly embraced data-driven decision-making.

These strategies, when implemented effectively, can help businesses overcome the obstacles on their path to becoming data-driven. It's not always an easy journey, but the rewards are well worth the effort. By prioritising data governance, investing in the right solutions, developing a comprehensive data strategy, and fostering a data-driven culture, businesses can unlock the full potential of their data and gain a competitive edge in today's digital landscape.

Conclusion

Becoming data-driven is not a destination; it's a journey. It requires overcoming challenges related to data quality, structure, strategy, and siloing. But the rewards are well worth the effort. By implementing the right strategies and fostering a data-driven culture, businesses can unlock the full potential of their data and stay ahead in today's competitive landscape.

Even we at Numvio, as an AI company, didn't have a perfect journey. It's a common challenge that businesses face, regardless of their industry or size.

In larger organisations, collaboration is key. When teams operate in isolation, chances are that data will also be isolated. Breaking down these silos and fostering cross-functional collaboration is essential to achieving a truly data-driven approach.

Remember, Rome wasn't built in a day, and neither is a data-driven organisation. It takes time, persistence, and continuous improvement. But with the right mindset and approach, you can transform your business into a data-powered engine of growth and success. So, embrace the power of data and let it guide you towards a brighter future. The struggle may be real, but so are the opportunities that await.

Now, that’s me done. I want to hear from you now: Have you faced this struggle in your own business? How did you tackle it? Did you have any failures or mind-blowing successes along the way? Share your stories, tips, and battle scars in the comments below.