Data serves as the foundation for informed decision-making, providing a single source of truth that empowers valuable insights to be gained about industry trends, market behaviour and changing visitor preferences. By harnessing the power of data analytics, organisations can identify emerging opportunities, optimise their operations and make data-driven decisions that maximise performance and productivity. A robust data infrastructure ensures that information is accurate, accessible and reliable, enabling informed choices that drive the achievement of strategic objectives and boost industry-wide collaboration.

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This data audit is designed to give a structured overview of how every department within your organisation currently uses data and their ambitions for becoming more adept at leveraging the insights obtained. By examining the data practices of each department, you will identify opportunities for improvement and uncover hidden potential. This audit will help you understand the current state of data usage, identify knowledge gaps and assess your organisation's readiness to leverage data more effectively. By completing this process, you will be well-positioned to develop a roadmap for enhancing data literacy, improving data quality and maximising the value of data-driven insights.

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Preparation

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• Update the data audit template with the name of every department within your organisation.
• Establish an internal data working group to provide support and guidance during the process.
• Ask each Head of Department to nominate one person to coordinate their team's contribution to the data audit.

Conducting the Audit

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The data audit is separated into four sections:

1. Data Sources
2. Indicators
3. Skills Matrix
4. Data Wish List

Data Sources

Complete a row for each set of data held, maintained or used by your department as follows:

1. Name of the dataset.
2. Availability of data (e.g. Internal Data, User Data, Open Data, Industry Data or Licensed Data).
3. Type of data (Audience Data, Behavioural Data, Business Intelligence Data, Inbound Travel Demand Data, Brand Impact & Competitor Data, Consumer & Sentiment Research Data, Transactional Data, Sustainability Data, Movement & Spatial Data, Media Insights Data, Marketing Performance Data or CRM Data).
4. Format raw data is shared (No Access to Raw Data, Spreadsheet, Database, Cloud Storage, Flat Files, Application Data, API or Other).
5. The presence of a dedicated client dashboard for viewing and analysing the data.
6. Frequency of data updates (Real Time, Hourly, Daily, Weekly, Monthly, Quarterly, Annually, Bi-Annually, Ad-Hoc / Infrequent).
7. Cost of the annual license (Free, £1 - 1,000, £1,001 - 5,000, £5,001 - 15,000, £15,001 - £50,000, £50,001+).
8. Add any relevant notes associated with how the data is used.

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Indicators

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Outline an exhaustive list of indicators that are used by your department to measure success as follows:

1. Indicator description.
2. Frequency of monitoring / reporting (Real Time, Hourly, Daily, Weekly, Monthly, Quarterly, Annually, Bi-Annually, Ad-Hoc / Infrequent).
3. Assess the quality and reliability of the data (Not Available, Poor, Sufficient, Good, Excellent).
4. Rationale as to the strategic goals this indicator supports.
5. Add any additional comments regarding the strengths or weaknesses associated with using this indicator to make decisions.

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Skills Matrix

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Give a general view of how data is playing a role in your department as follows:

1. Describe the importance and role of data within your department.
2. Rank the following skills of your department's team on a scale of 0 - 5:
3. Data Cleaning / Preparation Skills
4. Data Analytics Skills
5. Data Visualisation Skills
6. Data Development Skills
7. Data Storytelling Skills

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Data Wishlist

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Complete a row for identifying missing data and why each set of data is desired by your department as follows:

1. Name of the dataset.
2. Type of data (Audience Data, Behavioural Data, Business Intelligence Data, Inbound Travel Demand Data, Brand Impact & Competitor Data, Consumer & Sentiment Research Data, Transactional Data, Sustainability Data, Movement & Spatial Data, Media Insights Data, Marketing Performance Data or CRM Data).
3. Primary motivations for acquiring this data.
4. The barriers to obtaining this data and why this data doesn’t exist or isn’t accessible today.

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