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Shifting Realities and the “New Normal”

As the world adjusts to the ‘new normal’, the entire pattern of work and life has shifted. One thing has especially become clear – everything we thought we knew about customers has changed, from their movements to their purchasing habits, to the products they buy.

Trusted data is now more important than ever and extracting value from the data is a critical source of competitive advantage. Businesses must reconsider their data strategy to ensure they can keep up in a world where the future is uncertain, and the only real constant is that everything keeps changing.

Table of Contents

• Data is the heart of insight
• The four data foundations for extracting value
• The relationship between the pillars
• The role of data strategy

Data is the heart of insight

The major benefit of a digital world is the plethora of data available for analysis. However, if businesses are not extracting value from the data, it is useless to them, and they will likely fall behind their competitors who are doing so. Extracting value from data delivers better insight, competitive analysis, improved products and the ability to understand how to adapt to change, which is the key to becoming more successful.

Forget “garbage in, garbage out” – the true impact of quality data on analytics engines lies beyond mere cleanliness. Dive with me into the hidden depths of data, where under-discussed stats reveal the transformative power of good data:

1. The Cost of Bad Data Bites:

• Stat: Poor data quality costs US businesses an average of $3.1 trillion annually, with wasted resources, operational inefficiencies, and reputational damage being major culprits. (Source: IBM)
• Breakdown: Clean data isn’t just a nicety – it’s a bottom-line booster. Investing in data quality can significantly reduce these hidden costs and unlock substantial ROI.

2. The Untapped Potential of Predictive Power:

• Stat: More than 50% of respondents agree that models trained on high-quality data achieve higher accuracy in predictive analytics, leading to more precise forecasting and proactive decision-making. (Source: Appen, 2022 State of AI Report)
• Breakdown: Clean data isn’t just about avoiding errors – it unlocks the true potential of AI and machine learning. Accurate models powered by good data can predict customer churn, market trends, and future scenarios with unparalleled precision.

3. The Innovation Accelerator:

• Stat: Organizations with strong data quality practices are more likely to successfully implement new AI and analytics initiatives with 82% having to rework analytics projects. (Source: Snaplogic, The State of Data Management)
• Breakdown: Good data lays the foundation for innovation. When your data is clean and trustworthy, you can confidently explore cutting-edge analytics solutions and unlock new business opportunities without fear of skewed results.

4. The Trust Catalyst:

• Stat: 95% of respondents believe that bad data is negatively affecting customer experience. (Source: Experian, Global Data Management report)
• Breakdown: In today’s data-driven world, trust is paramount. High-quality data fuels transparent and ethical analytics, fostering stronger customer relationships and building brand loyalty.

5. The Human Advantage:

• Stat: While AI automates data cleaning tasks, human expertise remains critical for interpreting complex data anomalies and making strategic data quality decisions. (Source: Deloitte)
• Breakdown: Don’t let automation fool you – human judgment is still essential. Experienced data scientists and analysts are invaluable in ensuring data quality aligns with business goals and drives meaningful insights.

These hidden stats paint a clear picture: quality data isn’t just a technical checkbox, it’s a strategic imperative. To achieve quality, data needs to be accessible to everyone who needs it to do their job. This may seem like a simple task, but with the way digital transformation has occurred, data siloes are a real barrier. There is also the challenge of providing the right data to the right people while still ensuring it is protected from both a security and a data privacy perspective. Adding to the challenge, data needs to flow seamlessly between networks and external devices.

The four data foundations for extracting value

Working with data has become increasingly complex in the new paradigm. These four foundations ensure value can be extracted to drive insight for competitive advantage and enhanced success rates:

• Data transparency – this is the ability to easily find, understand and access the data you need, no matter where it is located or what application was used to create it. Part of this is the assurance that data is accurate and originates from an official source, in other words, that it can be trusted. Governance plays a significant role in this element, and capabilities such as data lineage and metadata management are important components.
• Data integrity – this flows from data transparency and is the ability to deliver trusted data for both operations and analytics. Businesses need to know that their data is accurate for the purpose it needs to be used, and that it can be accessed and located whenever and wherever it is required.
• Data privacy – protecting the fundamental rights of your staff, customers and suppliers has never been more important, with the growth of digitalisation and the increase in data privacy legislation such as the Protection of Personal Information Act (PoPIA). Organisations need to know what sensitive information they have, where it is being stored and for what purpose it is used. Data privacy is not about blocking access to data, because this will prevent it from being used at all, but about creating the necessary nuances around levels of control, to make data accessible based on role and requirements.
• Data literacy – the need to understand how to use and manage data. If people do not have this knowledge, they will not be able to use data to extract value. Data Management Training is essential to ensure that everyone in the organisation, from senior management down, understands the importance of data and data integrity, how to analyse and assess data, and importantly, how to leverage data better.

Intrinsically linked

Together, these four foundations—data transparency, integrity, privacy, and literacy—play a pivotal role in fostering trusted data and sound decision-making within organizations.

Firstly, data transparency ensures that information is readily accessible, understandable, and traceable. This transparency instills confidence in the accuracy and origin of data, facilitating informed decision-making by providing a clear view of data sources and lineage.

Secondly, data integrity reinforces the reliability and consistency of data across its lifecycle. When data is trustworthy and consistent, decision-makers can rely on its accuracy and relevance, leading to more confident and accurate conclusions.

Thirdly, data privacy safeguards sensitive information, ensuring that personal and critical data is appropriately protected. By adhering to privacy regulations and implementing robust control mechanisms, organizations build trust with stakeholders and mitigate the risks associated with data breaches, fostering a conducive environment for confident decision-making.

Finally, data literacy ensures that individuals across the organization possess the necessary skills to interpret and utilize data effectively. When employees are equipped with data literacy skills, they can derive meaningful insights, interpret data accurately, and make informed decisions aligned with organizational objectives.

None of these pillars can be easily delivered in isolation. They are all intrinsically interlinked and form part of an ongoing process to continually extract and leverage the value of data, so making the appropriate investment at the appropriate time is crucial. This is a complex challenge that requires a systematic approach with a long-term view, beginning with a specific use case or problem. Getting the foundations in place and investing in technology, services and partnerships will empower organisations to begin their journey on the right foot. Data is always changing, so business requirements around it must continually evolve, and the right partner is key in helping organisations leverage their data investment in the long term.

The role of the data strategy

Collectively, these four foundations establish a framework that cultivates trust in data accuracy, accessibility, security, and comprehension. This trust forms the bedrock for sound decision-making, empowering organizations to leverage data as a strategic asset, drive innovation, and stay agile in an ever-evolving landscape.

In the pursuit of establishing the four foundations for data value extraction, the data strategy stands as the guiding force. It serves as the architect, orchestrating the alignment and implementation of these pillars within an organization.

An actionable data strategy not only outlines the roadmap for achieving data transparency, integrity, privacy, and literacy but also delineates the methodologies and frameworks essential for their integration into the organizational fabric. It’s the blueprint that ensures these foundational elements synchronize seamlessly, enabling businesses to harness the true potential of their data assets.

To truly harness the power of data, it’s imperative to avoid common mistakes in your data strategy By prioritizing a comprehensive understanding of your organization’s data needs, leveraging the right tools, and fostering a culture of data-driven decision-making, you can steer clear of these pitfalls and pave the way for a resilient and impactful data strategy that will deliver trusted data and valued insights.

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So, are you ready to unleash the hidden gems of your data and empower your analytics engines to shine? The choice is yours – invest in quality, and watch your data-driven decisions light up the path to success.

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