Data storytelling in Financial Services: Turn insights into action

Numbers have always been crucial for measuring success. From revenue figures to profit margins and customer acquisition expenses, these numbers guide critical decisions. Yet, today, the challenge remains in creating stories that can shift these numerical dials.

It's about taking complex datasets and turning them into narratives that drive real change.

Here are some strategies for identifying key metrics and crafting narratives:

Understand your data 🗺️

Before diving into data storytelling, it's essential to grasp the full scope of your available data. This groundwork typically involves two critical phases: a comprehensive data audit and robust data governance practices.

Step 1: Data audit

A data audit is the foundation of effective data management and storytelling. It involves:

1. Cataloguing 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.

2. Gauging 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.

3. Identifying 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 governance safeguards the consistency, accuracy, and security of your data. Consider these key aspects:

1. Ensuring data consistency and accuracy: Implement validation processes at every stage—ingestion, processing, and output.

2. Implementing data security and compliance: 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.

3. Maintaining comprehensive 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.

4. Facilitating 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.)

To sum up: 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. The first step is to make sure you understand the objectives—what are the goals you're aiming to address, and from this work backwards to key measures.

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:

1. Set the context: Provide background information that helps your audience understand why this data matters.

2. Present the problem or opportunity: Use your data to highlight a challenge or potential area for improvement.

3. Reveal key insights: This is where your data analysis shines. Present your findings clearly, using visualisations where appropriate.

4. 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 can elevate your data narratives, making complex information more digestible and highlighting key trends. When designing data visualisations, prioritise simplicity and clarity. Use descriptive labels and titles, minimise clutter, and employ colour strategically to emphasise crucial points.

Consider incorporating interactive elements when appropriate. This empowers your audience to explore the data firsthand, allowing executives to grasp key insights whilst enabling operational teams to delve deeper into the details.

Whilst the specific tool is secondary to how you utilise it, the right software can streamline the creation of effective visualisations. But remember, it's the analyst's expertise that truly brings the narrative to life in the chart.

Connecting data to business objectives🔗

Here are 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.

Tackling data storytelling hurdles📐

Even with thorough preparation, challenges arise. Here are some common data storytelling obstacles 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.

Crafting stories that drive real action

Data storytelling in financial services isn't just about presenting numbers—it's about weaving insights into a compelling narrative that guides strategic decisions. By understanding your data, choosing the right metrics, and aligning your stories with business goals, you can turn raw data into impactful actions.

The crux lies in striking a balance between precision and clarity, ensuring each insight you share connects directly to tangible results. When done effectively, data storytelling can shape the future of your business.