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10 reasons why it’s important to understand the value of your data.

April 9, 2024

10 reasons why it’s important to understand the value of your data.

Imagine for a minute the bits of data within your organisation were puzzle pieces. Hundreds of disconnected pieces of all shapes, sizes and colours, each piece distinctly unique yet, with dedicated time and effort, they harmoniously fit with one another, and a cohesive masterpiece emerges.

Could yours fit together nicely and create one whole image? We’re guessing your answer is “no.” There is too much knowledge available to justify making any decision that is not data-driven and businesses today from all industries have one key challenge in common: data.

Going with your gut, taking uneducated guesses and making assumptions are a thing of the past. To quote the great, W. Edwards Deming, “Without data, you’re just another person with an opinion”.

Ask yourself:

  • If you had to make decisions based on your data today, would you know where to find the right data fields to answer your questions?
  • Do you trust your data source(s) to be up-to-date and accurate, ready to include in your analysis?
  • Are you able to describe the purpose, calculations involved and contents of each data field you are using?

Despite our extensive experience in data and AI initiatives, it’s astonishing that businesses in 2024 still struggle to realise and demonstrate the true business value of their data investments. There seems to be unanimous agreement on the importance of investing in data, yet it remains both costly and problematic for many.

One fundamental issue lies in the predominant focus of data projects on data, analytics, and reports, often neglecting the crucial aspect of achieving tangible business outcomes and the necessary insights to support their measurement and achievement.

The reality is that data, analytics, machine learning models, or reports alone do not inherently deliver any business value. It is only when people utilise these tools to inform their decisions and actions that real value is achieved (can you see the picture on the box you’re looking to create?) Therefore, when designing and delivering data solutions, we must dedicate as much time and effort to focusing on outcomes, actions, and decisions as we do on data and analytics.

Compounding this issue is often the lack of sufficient senior business sponsorship and direction for data and AI initiatives. These endeavours are often led and executed by technology, information or data teams that may lack alignment with the business strategy or engagement from key stakeholders whose decisions drive business performance. These teams, while exceptional in technology delivery, data engineering, and model training, often confine their conversations with the business to databases, models, and reports, rarely straying outside of their comfort zones.

However, there is a growing recognition that organisations must cultivate a mature data culture at their core, often through executive sponsorship, such as a Chief Data Officer or partnering with a Data and AI specialist agency. This increases the likelihood that teams and departments will take more ownership of their data and its utilisation.

For data teams entering this landscape, particularly those more adept at discussing data and reports rather than business outcomes and benefits, convincing business stakeholders of the value of defining business value-driven requirements can be a challenge.

Here are 10 reasons to help make that case:

  1. Increase the likelihood of delivering measurable value and aligning with business objectives: When we clearly understand what the business needs and aims to achieve, we’re more likely to deliver outcomes that matter. This alignment ensures our efforts directly contribute to the organisation’s goals, making it easier to measure and showcase the value we bring.
  2. Support decision-making, alerting on important business events for timely resolution: Imagine having insights that help us make quick and informed decisions when critical events occur. By understanding the business context, we can set up alerts and notifications to stay ahead of potential issues, enabling us to act swiftly and effectively.
  3. Determine problem existence or ensure focus on the right issues: By diving into what truly matters to the business, we can pinpoint the challenges that need our attention. This ensures we’re focusing our efforts on the right areas, helping us solve the real problems that impact the organisation.
  4. Measure progress and provide evidence of expected benefits: It’s like having a roadmap with clear milestones to track our progress. Defining specific goals and metrics allows us to measure how well we’re doing and provides concrete evidence of the benefits we’re delivering along the way.
  5. Understand reasons for success or failure: When we connect our data efforts to business outcomes, we gain valuable insights into what works and what doesn’t. Understanding these reasons helps us learn and adapt, paving the way for future success.
  6. Develop data fluency skills for a mature data culture: Imagine everyone in the organisation speaking the same data language. Engaging in discussions about business value helps us all become more fluent in data, encouraging a culture where data-driven decisions are the norm.
  7. Unlock creativity and value within teams: When we know the business context behind our data initiatives, it sparks creativity within our teams. This collaboration allows us to come up with innovative solutions that truly maximise the value of our data.
  8. Provide a basis for scoping, prioritising, and budgeting decisions: Having a clear understanding of the business value helps us make smart decisions on where to focus our efforts. It guides us in prioritising tasks based on their impact, ensuring we’re making the most of our resources and budget.
  9. Improve solution design and quality of delivery: Imagine delivering solutions that perfectly fit the business needs, right from the start. By starting with a deep understanding of business requirements, we’re more likely to design solutions that hit the mark, resulting in higher-quality outcomes.
  10. Enable focus and basis for business readiness planning: Knowing the business value upfront (remember that picture on the box) allows us to plan for the changes and preparations needed. This includes training, process adjustments, and ensuring the organisation is ready for the new data solution, making the transition smoother and more successful.

By engaging in discussions around business value, data teams can enhance their solution design and quality, improve their business readiness planning, and build trust and more productive working relationships with the business.

It’s crucial to engage in conversations on benefits planning and business value analysis. Sharing experiences and insights can lead to invaluable learnings and improvements in your approach to data projects.

But let’s not forget if businesses want to truly create a data-driven culture, the journey starts from the top. Companies with strong data-driven cultures tend to have top managers who set an expectation that decisions be anchored in data — which is normal, not novel.

Simply put aspiring to be data-driven is not enough. To be driven by data, companies need to develop cultures in which this mindset can flourish, and the pieces of the puzzle can be put together seamlessly to form a super clear picture promoting proactive decision-making and ultimately success.

Learn how to unlock investment and put data at the heart of your organisation’s future through a business-led data strategy. Contact us for more information.


At ELLA, we know a thing or two about creating successful data strategies. Drawing on our years of expertise, we’ve honed a practical and successful approach to creating and implementing a data strategy that puts data at the heart of your organisation’s future.

Your data strategy should set the vision, detailed strategy, and roadmap to explain how your organisation will use its data and analytics to realise your business objectives.

Done properly a data strategy will unite data-driven activity behind a clear set of business-aligned goals with a compelling vision and case for change to drive engagement and adoption.