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5 Reasons Why Data Isn’t Working in Your Organisation

5 Reasons Why Data Isn’t Working in Your Organisation

5 Reasons Why Data Isn’t Working in Your Organisation


The power of data cannot be overstated. We love data and you should too!  

Organisations in every industry, everywhere are relying on data to make informed decisions, drive innovation, and gain a competitive edge. And if you’re not… WTF are you doing? 

However, despite the potential that data holds, many organizations struggle to harness it effectively. 

In this blog post, we’ll explore what data is and how it can be used. After this, highlighting the 5 common reasons why data initiatives may not be working in your organisation and how to overcome these challenges. 

Data: What is it? How is it used? 

Okay, so what is data? If you didn’t know already (if you already know, skip this bit) 

Data refers to raw facts, figures, and statistics that are collected, recorded, or stored in various forms.  

It can take the form of numbers, text, images, audio, or any other structured or unstructured information.  

Data is the fundamental building block of information and knowledge. It can be categorised into two primary types: 

  • Structured Data: This type of data is organised into a predefined format and is easy to analyse. It’s often found in databases and spreadsheets, and each data point has a specific meaning. Examples include numerical values in an Excel spreadsheet or customer details in a relational database. 
  • Unstructured Data: Unstructured data is not organized in a predefined manner. It can be in the form of text, images, audio, or video and doesn’t fit neatly into rows and columns. Examples include social media posts, emails, images, and videos. 

Data is a valuable resource that can be harnessed for various purposes in different sectors. Here are some common ways data can be used: 

  • Decision Making: Data is crucial for informed decision-making. Organizations use data to analyse trends, identify opportunities, and make strategic choices. For example, a retail company may use sales data to decide which products to stock. 
  • Performance Analysis: Data can be used to assess the performance of processes, products, or individuals. In sports, for instance, performance data is used to evaluate athlete performance and make improvements. 
  • Predictive Analytics: By analysing historical data, organizations can make predictions about future events. For example, financial institutions use historical transaction data to detect fraudulent activities. 
  • Personalization: Data is used to tailor experiences for individuals. Online retailers, for instance, use data to suggest products based on a customer’s browsing and purchase history. 
  • Marketing: Marketers use data to target specific demographics, track campaign performance, and optimize their strategies. 
  • Customer Insights: Customer data helps businesses understand their customer’s preferences, behaviours, and needs, enabling them to provide better products and services. 
  • Financial Analysis: Financial institutions rely on data for risk assessment, investment decisions, and fraud detection. 

Data can be a powerful tool when collected, processed, and analysed effectively.  

However, you might be using data in your organisation. Yet, it is failing or not being used to its fullest potential!  

Here are 5 common reasons why may not be working in your organisation and how to overcome these challenges. 

Reason 1: Lack of Data Strategy

A clear data strategy is the foundation upon which successful data initiatives are built. Without it, organizations are essentially navigating uncharted waters.  

A data strategy encompasses a structured plan for collecting, storing, analysing, and using data to achieve specific business goals. It defines the what, why, and how of data management. 

It is basically a business strategy using data.  

The consequences of not having a clear data strategy are numerous. It often leads to confusion, redundancy, and a lack of direction. Without a strategy, you may find yourself collecting and storing data that is irrelevant to your business objectives. 

To overcome this challenge, look to organisations like Amazon and Google, which have well-defined data strategies. They use data to optimise their operations, enhance customer experiences, and drive growth.  

Create a data strategy that aligns with your business goals and ensure it is communicated and followed throughout your organisation. 

Understand more about data strategy here.  

Reason 2: Data Silos

Data silos occur when different departments or teams in an organisation store data independently, without sharing or integrating it.

This can hinder effective data utilisation, decision-making, and collaboration.  

Imagine marketing and sales teams using different data sources, leading to conflicting information and missed opportunities. 

To break down data silos, implement systems that allow for easy data sharing and integration. Encourage cross-functional collaboration and ensure that data is accessible to all who need it.  

Tools like data warehouses and collaboration platforms can be instrumental in this process. 

Understand more about Data Silos and how to eliminate them here.  

Reason 3: Inadequate Data Quality

Poor data quality can be a major roadblock to effective data utilisation. Have you heard the term s#!t in = s#!t out?? 

Inaccurate, incomplete, or outdated data can lead to misguided decisions and analysis. To mitigate these risks, organisations must prioritise data quality. 

Start by implementing data validation and cleansing processes. Regularly audit your data for accuracy and completeness. Establish data quality standards and make sure they are consistently upheld across the organization. 

Reason 4: Resistance to Change

Implementing data-driven practices often encounters resistance from employees or teams comfortable with existing methods. 

It’s essential to recognize that data-driven decision-making may necessitate changes in established workflows and practices. 

To address resistance, consider offering training and education to your employees. Show them the benefits of data-driven decision-making through success stories from other organisations. 

Create a supportive culture where employees are encouraged to embrace data and innovation. 

Also, with data automation your team’s output will increase and reduce costs – it is obviously the way forward. Make your team efficient and happy!  

Reason 5: Insufficient Data Governance

Data governance is the framework that ensures data is managed, utilised, and protected effectively within an organisation.  

Without robust data governance, data-related issues can easily spiral out of control. 

To establish effective data governance, define roles and responsibilities for data management, set data access controls, and enforce data policies and standards.  

This will ensure that data is protected and used ethically and responsibly. 


In conclusion, data is an invaluable asset for any organisation, but to unlock its full potential, it’s crucial to address common bottlenecks that may hinder its effectiveness.  

By implementing a clear data strategy, breaking down data silos, ensuring data quality, addressing resistance to change, and establishing strong data governance, you can transform your organization into a data-driven powerhouse. 

Obviously, these aren’t the ONLY reasons why working with data isn’t working within your organisation. But these are the most common reasons why!  

Stick around though, we may go more in-depth into your specific reasons soon as to why data isn’t working in your organisation!

Take a moment to assess your organisation’s data practices.  

Are any of the challenges mentioned in this blog post affecting your data initiatives? If so, consider taking steps to address them and unlock the full potential of data in your organisation.  

Fill out the form below to reach out if you have questions or need further guidance on any of these topics!

Let’s make data WORK! You need it to have a thriving business in 2024! 

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Harnessing Data in 2024: A Must for Medium-Sized Financial Services Organisations 

Harnessing Data in 2024: A Must for Medium-Sized Financial Services Organisations 

Harnessing Data in 2024: A Must for Medium-Sized Financial Services Organisations 


The financial services industry is no stranger to change, and as we’re soon to enter 2024, it’s apparent that data is becoming the driving force behind success.  

Medium-sized financial services organisations find themselves at a pivotal juncture.  

Financial services have come a long way from traditional banking to a tech-driven industry. Fintech innovation, regulatory shifts, and changing customer expectations have redefined the sector. Data has become the new currency in finance. It fuels decision-making, drives innovation, and is integral to every aspect of financial operations. 

In this blog post, we will explore the imperative for these organisations to harness data in 2024 to stay competitive, address challenges, and seize opportunities in the ever-evolving financial landscape.

The Imperative for Medium-Sized Financial Services Organisations:

Medium-sized financial organisations occupy a unique space. They are neither large enough to have the vast resources of giants nor small enough to be agile startups.  

As a result, they must adopt data strategies that suit their specific needs and capabilities. 

2024 is going to present both challenges and opportunities.  

Increased competition, evolving customer preferences, and regulatory changes are challenges, while data-driven insights, innovation, and customer-centricity offer opportunities for growth. 

Data isn’t just a tool; it’s the key to competitiveness.  

It empowers medium-sized financial organisations to level the playing field with larger institutions and carve out niches in the market. 

Data Utilisation in Core Operation

Customer Acquisition and Retention 

  • Personalisation through Data Analysis: Medium-sized firms can use customer data to offer personalized services and experiences, fostering stronger customer relationships. 
  • Data-Driven Marketing Strategies: Targeted marketing campaigns based on data insights can lead to higher conversion rates and improved customer retention. 

Risk Assessment and Management 

  • Real-time Data for Better Risk Evaluation: Real-time data analytics enables organizations to assess risk promptly and make informed decisions. 
  • Predictive Analytics for Proactive Risk Mitigation: Predictive models can help identify potential risks before they materialize, reducing the likelihood of financial losses. 

Cost Optimisation and Efficiency 

  • Streamlining Operations Through Data Automation: Automation of routine tasks and processes can lead to cost savings and increased operational efficiency. 
  • Data-Driven Decision-Making for Resource Allocation: Data insights guide resource allocation, ensuring that medium-sized organisations make informed choices. 

Data Utilisation in Core Operation

Evolving Regulatory Landscape 

The regulatory environment is constantly evolving. Medium-sized financial organisations need to adapt to changes in regulations, reporting requirements, and compliance standards. 

Data-Driven Compliance Solutions 

Data can streamline compliance efforts by automating data collection, ensuring accurate reporting, and providing transparency to regulators. 

Benefits of Proactive Compliance 

Proactively addressing compliance through data utilisation not only reduces the risk of regulatory fines but also enhances the organisation’s reputation and trustworthiness. 

Data Security and Privacy

Data Security Risks 

Medium-sized financial organisations must be vigilant against data breaches and cyberattacks, which can have devastating consequences. 

Data Privacy Concerns 

Data privacy regulations require organizations to protect customer data rigorously and ensure that it is used ethically. 

Strategies for Ensuring Data Security and Privacy 

Robust cybersecurity measures, encryption, employee training, and strict data access controls are essential components of a comprehensive data security strategy.

Building a Data-Driven Culture

Nurturing Data-Driven Mindsets 

Leadership must foster a culture where data is valued, and decisions are informed by data-driven insights. 

Training and Upskilling Employees 

Investing in employee training and development is crucial to ensure that staff can effectively leverage data tools and technologies. 

Fostering a Culture of Data Ethics 

Data ethics should be a cornerstone of the organisation’s culture, ensuring that data is used responsibly and in alignment with regulatory and ethical standards. 

Leveraging Technology and Tools

Data Analytics and Visualisation Tools 

Medium-sized firms can leverage data analytics and visualisation tools to extract meaningful insights from their data. 

Artificial Intelligence and Machine Learning 

AI and machine learning can help automate processes, improve decision-making, and predict customer behaviours. 

Blockchain Technology for Security and Transparency 

Blockchain can enhance security, transparency, and trust, making it a valuable technology for medium-sized financial organizations.

Future-Proofing with Data

Anticipating Trends Beyond 2024 

Medium-sized financial organisations should not only adapt to the current data landscape but also anticipate future trends to remain competitive. 

Continuous Adaptation and Innovation 

The data landscape is constantly evolving. Organisations must stay agile and continue innovating to leverage new data sources and technologies effectively. 

The Long-Term Value of Data Investments 

Data utilisation is an investment in the future. Over time, the benefits compound, and medium-sized financial organizations can achieve sustainable growth and competitiveness. 

In conclusion, using data is no longer optional for medium-sized financial services organisations; it is a must for staying competitive in 2024 and beyond.  

By harnessing the power of data, these organisations can navigate challenges, seize opportunities, and provide superior services to their clients. 

You must embrace data in 2024 and set your medium-sized financial organisation on a path to success in the data-driven financial landscape.

Want to delve deeper into the world of data utilisation for medium-sized financial services organisations?

Download our Guide on how to Overcome 2024’s Financial Services Problems with Data-Driven Solutions. 

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The Hidden Costs of Small IT and Data Teams

The Hidden Costs of Small IT and Data Teams

The Hidden Costs of Small IT and Data Teams:

How to Make Your Business Thrive Again 


From powering day-to-day operations to driving strategic decision-making, technology plays a pivotal role – and with this so does your IT and Data Management. 

However, not all businesses are equipped with the resources and expertise needed to manage their Data and IT effectively. 

Let’s explore the challenges faced by businesses with small IT and Data Teams and how you can help your business thrive again, with some small tweaks and a different approach.

The Downside of Small IT and Data Teams:

Inefficient Operations 

Small IT and Data teams often struggle to keep up with the demands of daily operations.  

Overloaded employees may find it challenging to respond promptly to issues, resulting in downtime and customer dissatisfaction. Productivity can take a hit, impacting the bottom line. 

Limited Expertise 

With small teams, it’s challenging to maintain expertise in every area of technology. This can lead to suboptimal technology decisions, outdated systems, and inadequate security measures. The risks associated with these gaps can be significant, including data breaches and compliance issues. 

Incomplete Data Management 

Effective data management is essential for business growth. Small teams may find it difficult to harness the full potential of their data. This not only hinders decision-making but also puts businesses at risk of losing valuable insights and opportunities. 


The Cost of Not Changing Your Ways:

Lost Opportunities 

Businesses with small IT and Data teams often miss out on valuable opportunities for growth and innovation. They may struggle to adopt new technologies or adapt to changing market conditions. This can result in stagnation and lost market share. 

Increased Costs 

Paradoxically, efforts to cut costs by maintaining small teams can lead to higher expenses in the long run. Inefficient processes, downtime, and costly emergency fixes can erode profitability. What initially seemed like a cost-saving measure can end up being a financial burden. 


How We Can Help You:

Expertise and Resources 

By partnering with the crew at Engaging Data, your business will gain access to a wealth of expertise and resources. Our team is equipped with specialised knowledge, cutting-edge technologies, and a deep understanding of industry best practices. 

Improved Efficiency 

Our services are designed to streamline operations and boost productivity. With responsive support and proactive maintenance, we ensure that your technology infrastructure runs smoothly.  

Say goodbye to frustrating downtime and hello to enhanced efficiency. 

Comprehensive Data Management 

We take data management seriously. Our approach includes robust security measures and compliance protocols to safeguard your data. We also help you unlock the potential of your data, turning it into a valuable asset for making informed decisions. 


To conclude, small IT and Data teams can unintentionally hamper business growth and incur hidden costs – this is not great!  

However, there is a way out.  

By partnering with the Data Nerds at Engaging Data, you can unlock the full potential of your technology infrastructure and data assets.  

Don’t let limitations hold your business back.

Let’s book in a call and help your business thrive in the digital age. 

Fill out the form below, let’s have a chat to discuss your limitations, problems and how we can overcome them together!

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Engaging Data Bites: VaultSpeed

Engaging Data Bites: VaultSpeed

Engaging Data Bites: VaultSpeed


Feast on Knowledge about VaultSpeed: Join this Engaging Data Bites Lunch and Learn!️ 

Are you hungry for the latest in data acceleration technology?  

Engaging Data is thrilled to invite you to an appetizing Lunch and Learn Webinar where you can dive into the world of VaultSpeed. 

About VaultSpeed –

VaultSpeed provides the fastest Data Warehouse Automation tool on the market. 

It is the only tool that provides a code-free approach to integrate and model different data from a multitude of sources and technologies, covering 2220 combinations. 

VaultSpeed combines the best automation, Data Vault modelling and cloud-native performance, and is the smart choice for companies that move their analytics infrastructure to the cloud. 

Why Should you Attend? 

  • Unlock VaultSpeed’s Secrets: Discover the magic behind VaultSpeed  
  • For Data Enthusiasts and Business Leaders: Whether you’re a data pro or a business decision-maker, this event is tailored to your needs. 
  • Optimize Data Operations: Learn how VaultSpeed can supercharge your data workflows, saving you time and resources. 
  • Interactive Q&A: Engage with our experts in a live Q&A session. Get answers to your most burning questions. 

Engaging Data Bites –  

Come and join us for this Engaging Data Bites Session with VaultSpeed! 

  • Date: 22nd November
  • Time: 12:30pm – 13:30pm GMT
  • Location: Online Webinar, hosted on Microsoft Teams

Data-Driven Finance: Leveraging Analytics in the Era of Digital Transformation 

Data-Driven Finance: Leveraging Analytics in the Era of Digital Transformation 

Data Driven Finance:

Leveraging Analytics in the Era of Digital Transformation


In the fast-evolving landscape of the financial services industry, a new era has dawned—one that revolves around data.  

Data-driven finance is no longer a mere concept; it’s a fundamental shift that is reshaping the way financial institutions operate and make strategic decisions.  

In this era of digital transformation, data has emerged as a potent currency, enabling financial organizations to gain insights that were previously unimaginable.  

In this blog post, we delve into the world of data-driven finance, exploring its significance, benefits, challenges, and the promising future it holds. 

The Role of Data in Financial Services  

Traditionally, financial services have always relied on data and information to drive their operations. From analysing market trends to assessing customer creditworthiness, data has been the backbone of decision-making.  

However, with the advent of digital transformation, the importance of data has surged to new heights.  

Digital transformation is the process of adoption and implementation of digital technology by an organisation to create new or modify existing products, services and operations. The goal for its implementation is to increase value through innovation, invention, improved customer experience and efficiency. 

As financial services become increasingly complex and competitive, the need for accurate, timely, and relevant data has intensified. In this data-centric era, financial institutions are not just making decisions; they are uncovering insights that can redefine the entire industry.

Key Benefits of Data-Driven Finance 

By harnessing the power of data analytics, financial institutions can: 

  • Gain deeper insights into customer behaviour 
  • Enhance data collection 
  • Market dynamics 
  • Internal processes 
  • Encourages data-driven culture (with improved collaboration 
  • Increased profits 
  • Increased agility 

This newfound understanding enables: 

  •  more informed decision-making 
  • leading to improved risk management  
  • better customer experiences 
  • enhanced operational efficiency 

Consider companies like Monzo and Starling, which utilized data-driven approaches to tailor personalized financial solutions, ultimately setting them apart from their competitors. 

Data Sources and Collection Methods

The array of data sources available to financial institutions today is astounding.  

Customer transactions, market data, social media interactions, and even sensor data from Internet of Things (IoT) devices.  

All of which contribute to the wealth of information at their disposal.  

Modern data collection methods have expanded to include mobile apps, online platforms, and interconnected devices.  

This data influx not only broadens the scope of analysis but also presents new challenges in terms of data quality, integration, and privacy. 

Analytics Techniques in Financial Services 

Data analytics techniques have evolved hand in hand with the digital transformation of finance.  

Descriptive analytics offers insights into historical trends, while predictive analytics helps anticipate future outcomes.  

Prescriptive analytics goes a step further, recommending optimal actions based on data insights.  

Machine learning and artificial intelligence are driving breakthroughs in analysing vast datasets and uncovering patterns that were previously hidden.  

These techniques enable financial institutions to make more accurate predictions, streamline processes, and discover untapped opportunities. 

Use Cases of Data-Driven Finance 

The impact of data-driven analytics is felt across various sectors within finance.  

In banking, institutions leverage data to personalize services, detect fraud, and enhance risk assessment. Investment firms use data-driven insights to inform portfolio management and optimize investment strategies.  

Insurance companies employ data to assess claims and tailor coverage plans. Lending institutions rely on data analytics to evaluate creditworthiness and streamline loan processing.  

Each of these use cases showcases how data-driven finance is transforming traditional practices and opening new avenues for innovation. 

Challenges and Considerations 

While the benefits of data-driven finance are clear, challenges must also be acknowledged.  

Data privacy concerns, security risks, and regulatory compliance are critical issues that financial institutions must navigate.  

The ethical use of data is paramount, as biased algorithms can perpetuate inequalities. Addressing these challenges requires a balanced approach that prioritizes transparency, accountability, and adherence to regulatory standards. 

Building a Data-Driven Culture  

Embracing data-driven finance entails more than just adopting advanced technologies – it requires a cultural shift within financial institutions.  

Leadership support, training programs, and cross-departmental collaboration are essential elements of building a data-driven mindset.  

Organizations need to foster an environment where data is valued, and analytics is integrated into decision-making processes at all levels. 

The Future of Data-Driven Finance   

The journey of data-driven finance is an ongoing one, marked by continuous innovation and exploration.  

As technology advances, new opportunities emerge and hold the potential to revolutionize data processing and analysis, while advanced analytics techniques like deep learning promise even deeper insights.  

Data marketplaces may reshape how financial institutions access and exchange data, fostering collaboration and accelerating industry progress.  

The rise of AI-generated financial insights and predictions could further amplify the capabilities of data-driven finance. 

In conclusion, data-driven finance stands as a cornerstone of the digital transformation sweeping through the financial services industry.  

By leveraging data analytics, institutions are navigating complexities, uncovering opportunities, and forging pathways toward greater efficiency and customer-centricity.  

As this era continues to unfold, staying informed about evolving data trends and embracing data-driven strategies will be pivotal for both financial organizations and individuals seeking to thrive in this dynamic landscape. 

Start your digital transformation before it’s too late and you lose out in the competitive marketplace and are left behind. 

Fill out the form below and get in touch.

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