Numbers have always been crucial for measuring success. Revenue, profit margins, and customer acquisition costs form the foundation of decision-making. However, in our data-rich environment, the challenge lies in creating stories that can shift these numerical dials.
It's about taking complex datasets and turning them into narratives that drive real change.
In this post, we discuss the art of data storytelling. We'll look at how to choose the right metrics and create narratives that align with business objectives so that you can take meaningful action.
Understand your data landscape🗺️
But first. Before you can tell compelling stories with your data, you need to have a full understanding of the data you have to play with. This usually involves two main steps: a thorough data audit and data governance.
Step 1: Data audit
A data audit is the foundation of effective data management and storytelling. It involves:
- Identify diverse data sources: Map out all the places where your organisation collects and stores data. This usually includes customer databases, sales records, website analytics, social media metrics, risk data, and more.
- Assess data quality and reliability: Evaluate the accuracy, completeness, and consistency of your data. Think of the old adage; "Garbage in, garbage out.” Effective storytelling relies on accurate data, otherwise, it's misleading and possibly damaging.
- Understand data gaps: Identify areas where you lack crucial information. This helps in prioritising future data collection efforts.
Step 2: Data governance
Data governance ensures that your data remains consistent, accurate, and secure. For this, you will need to consider:
- Data consistency and accuracy: Ensure you have processes to validate data at every step—loading, processing, and output. For instance, at Jaywing we check that new data coming in makes sense and is within expected tolerance. We also check that loaded data has the expected data—so we haven't missed a day unexpectedly, for example.
- Data security and compliance measures: With increasing regulations around data protection, it's crucial to have strong security measures in place. This not only protects your organisation but also builds trust with your stakeholders.
- Documentation: Data must be documented. This makes sure all users have the same understanding of the data—the calculations made, the sensitivity of the data, and who can use it. Great documentation, if shared, prevents information silos and helps support data democratisation.
- Accessibility: Make sure your data is easily accessible to those who need it. (You don't want your key metrics hidden in a spreadsheet somewhere.)
Bottom line: By investing time in understanding your data landscape, you'll be able to trust your data, know its limitations, and use it confidently to drive your narrative and decision-making processes. After all, the goal is to have quality, reliable data that can fuel insights and drive action.
Creating your data story🪄
Once you have a solid understanding of your data, it's time to create your data story. This involves several key steps:
#1. Start with a deeper understanding of your data and goals
Before diving into the narrative, it's important to understand both your data and your objectives. At Jaywing, the first step is to make sure we understand the objectives—what are the goals we're aiming to address, and from this work backwards to what are the key measures that will help address these.
Consider:
- What business questions are you trying to answer?
- What decisions need to be made based on this data?
- Who is your audience, and what matters most to them?
#2. Choose the right numbers to focus on
Not all data points are created equal. The KPIs need to directly relate to what we're trying to understand, not some vanity measure that's slightly in the same field.
When selecting metrics:
- Ensure they're actionable: Don't pick a KPI that you can't impact, but also steer clear of vanity metrics that aren't related to the outcome.
- Consider both backward and forward-looking metrics: Revenue and debt tell you how things have been, leads and applications indicate how things might go in the future.
- Tailor to your audience: Different stakeholders have very different needs, and so different metrics will be relevant.
#3. Create a narrative arc
A compelling data story follows a narrative structure, which might look a little something like this:
- Set the context: Provide background information that helps your audience understand why this data matters.
- Present the problem or opportunity: Use your data to highlight a challenge or potential area for improvement.
- Reveal key insights: This is where your data analysis shines. Present your findings clearly, using visualisations where appropriate.
- Propose actionable solutions: Based on your insights, what actions should be taken? Be specific and tie these recommendations back to your original objectives.
The key here is to use layers of storytelling... Start high-level then ensure you provide the ability to drill down. Produce your key takeaways headlines, and core actions for your exec stakeholders. But then, if feasible, enable the ability/option to drill down further to satisfy your detail-driven audiences.
#4. Balance accuracy and clarity
While it's important to be thorough, you also need to keep your story clear and engaging. To ensure simplicity, focusing on the key metrics as outlined earlier is crucial. Be selective on detail but take care not to distort the message—ask yourself if the detail adds more insight to support the main point.
Remember, a great data story isn't just about the numbers—it's about the narrative you build around them; A human touch. A clear objective from the outset. A compelling structure that leads us on a journey and keeps us engaged.
Visualisation techniques for effective storytelling📊
Visual representations of data can enhance your data storytelling, making complex information more accessible and highlighting key trends. When creating data visualisations, keep it simple and clear. Use clear labels and titles, avoid clutter, and use colour strategically to highlight key points.
Consider making your visualisations interactive when appropriate. This allows your audience to explore the data themselves, enabling executives to see key takeaways while operational teams can drill down for more detail.
While the specific tool isn't as important as how you use it, having the right software can make creating effective visualisations easier. At Jaywing, we often use PowerBI for its ability to handle large datasets and integrate with other tools. Other popular options include Tableau, Looker Studio, and even Excel. Remember, it's the analyst behind the tool that brings the narrative to the chart.
Connecting data to business objectives🔗
Effective data storytelling means tying the right numbers to your goals and strategies. Here's a few quick tips to ensure your data stories drive action:
- Align insights with strategic goals: Start by understanding your organisation's key objectives. The first step is to make sure we understand the objectives—what are the goals we're aiming to address, and from this work backwards to what are the key measures that will help address these. This approach ensures that every insight you present is directly relevant to your company's direction.
- Demonstrate potential ROI: Decision-makers often want to see the bottom line. When possible, translate your insights into potential financial impacts. This could involve projecting cost savings, revenue increases, or efficiency gains based on your data analysis.
- Address stakeholder concerns and priorities: Different stakeholders have very different needs, and so different metrics will be relevant. Tailor your story to your audience, focusing on the insights that matter most to them.
- Show actionable metrics: Metrics must be actionable. Don't pick a KPI that you can't impact, but also steer clear of vanity metrics that aren't related to the outcome. Focus on data points that can drive decision-making and lead to concrete actions.
- Balance short-term and long-term perspectives: Consider metrics that look both backwards and forwards. Revenue and debt tell you how things have been, leads and applications indicate how things might go in the future. This balanced approach helps paint a comprehensive picture of your business situation.
By connecting your data directly to business objectives, your data story drives organisational strategy and decision-making.
Overcoming data storytelling challenges📐
Even with the best preparation, we all face hurdles. Here are some common data storytelling challenges and strategies to overcome them:
Dealing with complex or technical data
Technical jargon can be an issue in specialised areas, such as risk, but you have to be careful not to oversimplify and lose accuracy and the key themes. Strike a balance by using clear, jargon-free language without sacrificing the essence of your insights. Consider using analogies or real-world examples to make it more relatable.
Addressing data gaps or uncertainties
Sometimes, you'll have incomplete data or face uncertainties in your analysis. Be transparent about these limitations. It's really easy to build a dashboard with a load of metrics, but what's the hook? There is sometimes a disconnect between the figures and action. How can we drive recommendations from the findings? Focus on the insights you can confidently draw from the available data, and be clear about areas that require further investigation.
Maintaining objectivity
It's important to present data accurately without letting personal biases skew the story. Opinions can be added, but clearly marked. Stick to the facts. If you're presenting interpretations or recommendations, clearly label them as such.
Dealing with data overload
With the vast amount of data available, it's easy to get overwhelmed. With so much data flying around, what's useful? Where are the nuggets of insight hiding? Focus on the most relevant metrics that align with your business objectives. As previously mentioned, "Don't pick a KPI that you can't impact, but also steer clear of vanity metrics that aren't related to the outcome."
Engaging diverse audiences
Different stakeholders may have varying levels of data literacy. Likewise, the language of the boardroom is not the language spoken by the operational teams. Tailor your presentation style and level of detail to your audience, providing additional context or explanations where necessary.
Case example: successful data storytelling in action🎬
This case study shows how data storytelling can challenge long-held assumptions and reveal surprising insights about a business's customer base.
The client: An e-commerce retailer offering credit options to customers.
The assumption: The retailer had a more mature customer base and the senior leadership team firmly believed that the oldest customers were their key audience for interest-bearing accounts.
The analysis:
Our team conducted an in-depth analysis of the retailer's customer data, focusing on:
- Profiling key credit users
- Analysing where profit was generated, specifically comparing Interest Bearing vs. 0% rate accounts
The revelation: The data told a story that was at complete odds with the leadership team’s belief. The oldest customers were not, in fact, the primary users of interest-bearing accounts as assumed.
The impact: This insight challenged a fundamental assumption about the business's customer base and credit offering strategy. It highlighted how myths can proliferate within an organisation when data isn't being tracked and analysed effectively.
The lesson: Without proper data tracking and analysis, companies can miss important trends or changes in customer behaviour. This can leave them unprepared and slow to react to market shifts. It also illustrates the importance of creating a culture where long-held beliefs can be questioned and tested against data.
The value of data storytelling
By presenting this data in a clear, compelling way, we were able to:
- Challenge an entrenched assumption
- Provide the client with a more accurate understanding of their customer base
- Offer an opportunity to realign their credit offering strategy based on actual customer behaviour rather than assumptions
This case study demonstrates how effective data storytelling can reveal unexpected insights and drive significant changes in business strategy.
The Jaywing advantage: where numbers meet narrative
At Jaywing, we understand that effective data storytelling is about creating compelling narratives that drive action and deliver results. Here's how we approach this challenge:
- Deep understanding of data and objectives: We start by ensuring we fully grasp both your data and your business objectives.
- Comprehensive data management: Our approach involves gathering, connecting, storing, and analysing data from various sources. We ensure data consistency, accuracy, and accessibility, providing a solid foundation for insightful analysis.
- Focus on actionable insights: We don't just present data; we focus on extracting actionable insights.
- Tailored storytelling: We understand that different stakeholders have different needs. We tailor our data stories to resonate with your specific audience, whether it's executives, operational teams, or external stakeholders.
- Cutting-edge technology: While we're tool-agnostic, we leverage advanced technologies like PowerBI, AI, and machine learning to uncover deeper insights and create compelling visualisations.
- Experienced team: Our flexible teams of analytics and consulting experts bring years of experience across various industries, ensuring you get insights that are both data-driven and contextually relevant.
The power of our work lies in our ability to transform complex data into clear, compelling stories that drive business decisions. We help you see beyond the numbers to understand what they mean for your business and how you can act on them.
By combining robust data management, advanced analytics, and effective storytelling, we help you leverage your data as a strategic asset, giving you the confidence that your risk is under control and the inspiration to use it to your advantage.
Take the first step towards data-driven excellence. Get in touch with our team today, and let's explore how we can make your data work harder for you.