You've invested in a data project – great! But now what? How do you actually use all that data to improve your business? The answer is effective data messaging. It's about taking complex data and turning it into a clear story that everyone can understand and act on. It's not just a "nice-to-have"; it's the essential ingredient for getting real value from your data investment.
Business data leaders are responsible for not only accurate data collection but also effective data presentation (data messaging). This article explores the critical importance of data messaging and how it elevates business intelligence (BI) beyond standard management information (MI) reporting. We'll guide you through the transition from reactive reporting to proactive, data-driven insights, demonstrating how BI can transform your organisation.
So, where does the circle start from? For a deeper understanding of the earlier stages of data projects, explore our related articles on data strategy, data quality, and data visualisation.
Data messaging
What is it?
Data messaging is the art of presenting business process outcomes using data-driven evidence. It involves the ability to appropriately simplify and summarize data for the intended audience.
Why and how is it done?
We all understand the nuances of data within operational systems. However, to make effective data-driven decisions, we must embrace these operational challenges and infer the true representation of business process outcomes from the captured data.
This is typically achieved through data engineering, applying business rules that evolve over time.
Data messaging is not about identifying operator errors in the operational system. That is the responsibility of operational or data quality monitoring systems (see our 5-minute refresher on Data Quality essentials).
Unless the intended audience is in operator training, where the quality of data entry itself is a data point used to monitor training effectiveness.
Data messaging should focus on representing the value the operation delivers to the business.
Value can be measured.
Value can be inferred.
Value can be compared.
Data messaging should not simply be an extract of operational data in a central location. Data centralisation should enable organisation-wide data analysis and establish a single source of truth for business intelligence.
Audience: Tailoring Data Messaging for Impact
When presenting information, it's crucial that the style, content, and message are easily understood by the recipient and enable further analysis if needed. The amount of information and the message conveyed must align with the recipient's needs—the message portrayed must meet the audience's expectations.
The same information can be presented in different ways depending on the intended message for the target audience. Effective data messaging is all about keeping the audience at the center.
Several artifacts are used in effective data messaging; some familiar terms include:
Dashboard
Report
Visual
Other common aspects of effective messaging that increase message acceptance include:
Styling
Layout
Compliance
Visual Artifacts for Effective Data Messaging
When introducing a data-driven culture within an organisation, it's essential to familiarise everyone with the common terminology used in the data delivery process. The basic terms we use are Data Point, Visual, Report, and Dashboard. While each organisation can adapt and agree upon its own definitions, establishing a consistent framework is a crucial starting point.
Data Point (Datum)
A data point (or datum) is a single piece of information that is generated and relevant to a business outcome. While there are many variations of this definition, a simple way to understand it is to consider whether it is:
(a) Relevant: Is it discussed within the business?
(b) Useful: Does something depend on it?
(c) Not a General Calculation: Is it distinct from a metric (e.g., an average)?
Data points are the foundation of all data-driven insights. For example, the "number of employees" can be considered both a data point and a metric, depending on its usage. Its classification depends on whether it can be reconciled with actual values and tracked events within the business. The "number of visitors," on the other hand, is more likely a metric because it's often considered a pure calculation (quantitative measurement).
Visual
A visual is a chart that represents a single or tightly correlated data point to the audience.
Figure 1: Single data point
report
A report combines charts representing single or potentially correlated data points. The purpose of a report is to present the impact of these data points in an easily understandable way for the audience. The most effective reports are those that require no interaction from the user to find the information they need—the insights are immediately apparent.
Figure 2: multiple related data points.
Dashboard
A dashboard is a concise summary of charts designed to provide an immediate overview for a targeted audience. It acts as a landing page, summarising the most useful data points and typically linking back to the underlying, more detailed reports.
A dashboard should focus on the specific needs of its audience. Within an organisation, dashboards are often designed according to the business role of the intended users. For example, you might have a Human Resources dashboard, a Finance dashboard, or an Exam Results dashboard.
Figure 3: Targeted data points.
User interface (UI)
Any presentation of information is best perceived when it adheres to a standard. While this principle might not apply to artistic endeavors, in the data world, the user's focus should be on the message and the resulting insights, rather than being overwhelmed by excessive data presented in numerous formats and themes. Therefore, an organisation must establish and adhere to standardised user interface (UI) practices that encompass at least:
Styling: (Consistent use of colors, fonts, and branding.)
Layout: (The organisation and arrangement of information.)
Delivery: (How the information is distributed and accessed.)
Data Presentation: (The specific methods used to display data, such as charts and tables.)
Our tip: Modern Business Intelligence platforms offer a wealth of default features. It's generally best to leverage these standard features and avoid extensive customisation. The more you deviate from standard platform features, the less time you'll spend extracting value from your data, as customisation can introduce complexity and maintenance overhead.
styling
Emphasise the message over unnecessary visual embellishments. Use familiar themes to enhance understanding, but avoid directly mimicking website designs. Ensure high contrast for optimal readability.
Figure 4: focus on the data
Figure 5: High contrast
Layout
Organise content to follow a left-to-right, then top-to-bottom reading pattern. Lead with a concise summary of key findings. Present data from concise overviews to broader, more detailed charts. Provide clear options to drill down for additional details as needed.
Figure 6: Example layout
Want help designing effective data visualisations and dashboards? Ei Square specialises in creating clear, impactful data solutions. Contact us today for a consultation!
Delivery
Reporting Platform: Embrace a reporting platform that your audience can access directly. This aligns with the "single source of truth" philosophy, enhances data security, and prevents data from becoming stale.
PDF Email: One-off data extracts should be distributed in a non-editable format (like PDF) and clearly dated to avoid confusion with outdated information. However, email distribution is generally less ideal as overall distribution control is limited.
Website/SharePoint: Corporate websites or SharePoint platforms can be used to host reports, providing your audience with a familiar and centralized access point.
Apps: Many reporting platforms offer dedicated apps for report distribution. These apps are often tightly integrated with your organization’s security framework.
Considerations for Data Delivery:Stale Information: Prioritise providing access to information from a single, online source. Offline information can quickly become outdated, leading to incorrect inferences.
Sensitive Information: Ensure sensitive information is secured based on user access permissions. This data should not be easily exportable.
ComplianceIBCS (International Business Communication Standards):
The IBCS Version 1.2 provides practical guidelines for the consistent design of reports, presentations, dashboards, and the charts and tables they contain. The IBCS Association, a non-profit organization, manages the ongoing development of these standards.
Figure 7: IBCS sample
Internal Standards:
Every organisation has its own audience with unique preferences. Pie charts, bar charts, and line graphs all have strengths and appropriate uses. However, the key is to avoid cluttering or overwhelming your audience with excessive information or variety in a single visualisation.
Three Fundamental Principles for Data Messaging:
Announce Your Outcome: Clearly state the key takeaway or message upfront.
Summarise Your Findings: Provide a concise summary of the data points supporting your outcome.
Show Your Evidence: Use appropriate visualisations to showcase your data, adhering to best practices for clarity and readability.
Ei Square Recommends: Crafting Clear and Concise Data Visualisations
While we recommend considering industry standards like IBCS, we also emphasise the importance of user-centric design. User testing and audience feedback are crucial for crafting data visualisations that are not only compliant but also clear and impactful.
A proposed layout
Keep to the reading left to right then top to bottom reading approach.
The Importance of Effective Data Messaging: From Data to Action
Effective data messaging is the bridge between raw data and actionable insights that drive a return on your data investment. It empowers organisations to make data-informed decisions by clearly communicating key trends and influencing factors. Without effective messaging, valuable time is spent searching for insights rather than acting on them.
To maximise the impact of your data messaging efforts:
Gather feedback from middle management, but be aware of positive bias.
Prioritise anonymous surveys to encourage honest feedback, including constructive criticism.
Focus on identifying and promoting factors that contribute to improved business outcomes and positive change.
Effective data messaging is not a luxury – it's a necessity. Without it, valuable time is wasted deciphering data and drawing conclusions. You may turn your data into an efficient instrument that supports informed choices and successful business outcomes by placing a high priority on transparent communication, user-centric design, and proactive reporting.
Ready to unlock the power of your data and transform it into actionable insights? Let Ei Square be your guide.
We offer a comprehensive suite of data consulting services designed to help you:
Craft clear and concise data visualisations that resonate with your audience.
Develop a data messaging strategy that aligns with your business goals.
Implement proactive reporting practices that deliver immediate value.
Contact Ei Square today for a free consultation! Let's discuss your data challenges and explore how we can help you turn them into opportunities for success.