Data Services

Data Foundations

Overview

In the modern world, data is the lifeblood of decision-making. It is the foundation upon which organisations build their strategies, make their decisions and measure their success. At Methods Analytics, we understand the critical importance of data strategy, and we offer a comprehensive data foundations service to help public sector organisations transform their processes to become more data-driven.

We offer a comprehensive suite of services to help you master data management within your organisation, and empower everyone within your teams to make better decisions, laying the groundwork for a data-centric culture. For data to enable effective decision-making, it must be readily available, well-understood and trusted - and this is what we'll help you to deliver.

Whether you’re looking to embark on your first data strategy, kick off a focused project to improve data quality, or design a programme to build your organisation’s data culture, we help you lay the strongest possible data foundations. We work with you to build the data foundations you need to support the change you want.

To learn more about how we can assist your data management strategy, get in touch with us today. We will advise you on how to unlock the full power of data within your organisation.

Our Data Foundations services

We help organisations to drive data quality improvements by establishing a solid foundation for providing meaningful data-enabled services. This is a holistic process, and we'll work with you to implement changes across your organisation to ensure you're able to rely on trustworthy data at all times.

Here are the key data foundation services we can deliver for you:

Data Strategy & Transformation: We work with you to develop a data strategy that aligns with your organisational goals and objectives, enabling you to leverage the power of data across your business, increase productivity and efficiency, and create new opportunities.
A robust data strategy is the cornerstone of any data-driven organisation. We can help you create a strategy that will give your organisation a strong foundation to make better decisions that drive progress and change, better serve your service users and teams, and deliver on your policy objectives.
Data Governance & Information Management: We help you design a practical data governance strategy to improve the accuracy, reliability and availability of your data, enabling increasingly insightful interactions. We provide processes, frameworks and an implementation plan that ensures clarity over roles and responsibilities.
To manage data effectively, you’ll need to have the right people, processes and data governance tools in place. We will help with this by designing an effective data governance framework designed to offer continuous improvements in the accuracy, reliability and availability of your data, enabling increasingly insightful interactions. We’ll provide processes, systems and an implementation plan that ensures accountable officers, practitioners and everyday users of data have clarity over their roles and responsibilities
Data Skills Development: Data literacy is a critical skill in a data-driven organisation. We help you understand your current levels of data literacy, identify gaps and develop comprehensive training plans to fill those gaps. By taking advantage of the learning materials offered through our Data Academy service, you will be able to access expert training and established partnerships with training providers. This will help you to improve data literacy across your entire organisation and nurture an inclusive data culture. In doing so, we empower people at every level of your team to become data stewards, giving them the knowledge they need to use their data most effectively.

Tools of specialty

Microsoft Purview

Microsoft Purview is a unified data governance solution that helps you manage and govern your data. We’ll help you create a holistic, up-to-date map of your data landscape with automated data discovery, sensitive data classification, and end-to-end data lineage.

Informatica

Informatica’s Intelligent Data Management Cloud is the first and most comprehensive AI-powered data management solution. We’ll enable every cloud-native service you will ever need for next-gen data management, all in one platform.

How to build a data foundation

Building an intelligent data foundation is a critical step in becoming a truly modern data-driven organisation. It involves creating a structured environment where data is readily available, well-understood and trusted, and any poor-quality data can be filtered out and addressed. Here's how we will guide you through this process:

Data maturity assessment: the first step in building a data foundation is understanding your current data capabilities. This involves conducting a data maturity assessment to evaluate how well your organisation is currently using data, and where there are opportunities for improvement. We assess your data infrastructure, data processing practices, data literacy levels, and the overall data culture within your organisation. This assessment provides a baseline from which we can measure progress and identify key areas of focus.
Data discovery: once we understand your current data capabilities, the next step is data discovery. This involves creating a holistic, up-to-date map of your data landscape. We use automated data discovery tools, such as Microsoft Purview, to identify where data resides within your organisation, what type of data you have, and how it's being used. This process also involves sensitive data classification and end-to-end data lineage, ensuring you have a complete understanding of your current data assets.
Data strategy development: with a clear understanding of your data landscape, we then work with you to develop a data strategy. This strategy outlines how your organisation will manage and use data to achieve its objectives. It includes plans for improving data quality, integrating data sources, implementing data governance, and developing data literacy within your organisation. The data transformation strategy also outlines how data will be used to drive decision-making and create new opportunities for your organisation.
Implementation: with a data strategy for digital transformation now firmly in place, the next step is implementation. This involves putting the people, processes and tools in place to manage and use data effectively. We work with you to design and implement data governance frameworks, improve data quality, and offer data literacy training to those who require it within your organisation. We also help you select and implement the right data management tools, such as Informatica’s Intelligent Data Management Cloud, to support your data strategy.
Continuous improvement: Building a data foundation is not a one-time project, but an ongoing process of continuous improvement. We help you establish processes for monitoring and improving data security and quality, managing data governance, and developing data skills within your organisation. We also help you stay up-to-date with the latest data analytics tools and practices, ensuring your data foundation remains strong and effective over time.

By following these steps, you can build a strong data foundation that enables your organisation to become truly data-driven. This foundation, paired with an effective data governance strategy, will empower everyone in your organisation to make better decisions, drive progress and change, and deliver on your policy objectives.

The benefits of a strong data foundation

A robust data foundation is the bedrock upon which data-driven organisations are built. It provides the infrastructure, oversight and culture necessary to leverage data effectively and responsibly, and ensure that you are meeting the necessary data security standards.

Here are some of the key benefits of establishing a strong data foundation:

Improved decision-making: a strong data foundation and unified data governance enables better decision-making across your organisation. When data is readily available, well-understood and trusted, it can be used to inform strategic decisions, drive operational efficiency and improve the delivery of high-quality data-enabled services. This leads to more effective and efficient decision-making processes, with outcomes that better align with your organisation's objectives.
Enhanced data quality: a robust data foundation includes processes for improving and maintaining data quality. High-quality data is accurate, complete, consistent, timely and relevant. With high-quality data, your organisation can generate more reliable insights, make more informed decisions, and reduce the risk of errors and inaccuracies.
Greater data literacy, maturity and culture: building a strong data foundation involves developing data literacy within your organisation. Data literacy is the ability to read, understand, create and communicate data as information. By increasing data literacy, you empower everyone in your organisation to use data effectively, fostering a culture of data-driven decision-making. This also delivers better data maturity, making it easier to assess the “as is” and “to be” positions of your organisation. With a strong data culture in place, change management becomes easier, helping your organisation to adopt and maintain new practices and ways of working around data.
Increased operational efficiency: a robust data foundation can greatly improve the efficiency of your data systems across the entire data lifecycle. By integrating sources, automating processes and improving the quality of your enterprise data, you can reduce the time and effort required to manage and use data. This can free up resources for more strategic tasks, leading to greater efficiency and productivity.
Data protection, privacy, security and risk management: a strong data foundation facilitates robust data governance, which is essential for data security compliance and risk management. Data governance involves the people, processes and technologies needed to manage and protect your organisation's internal and external data. With effective data governance, you can ensure compliance with data protection regulations, avoid potential data quality issues, and build trust with stakeholders. Because the control of appropriate access to data depends on how it was obtained, we will work with clients, partners and owners within the enterprise to ensure that the needs of all stakeholders are met.
Greater control and ownership: effective data stewardship and ownership makes it easier to maintain the proper use and quality of the data assets of your organisation. How we control domains of data is key to making sure they are fit for purpose and ready to utilise. Making sure that those in charge of data are properly invested in making a difference ensures that no areas are left underserved and lacking. The strong mechanisms we put in place for escalation, remediation and feedback are critical to the data governance model of operation.
Greater data classification and management: we help you create an efficient data management approach within your business glossary and taxonomy, which is of paramount importance to how your data is managed across your organisation. This will incorporate collecting, organising, protecting and storing your data so it can be analysed for business decisions.
Innovation and growth: lastly, a robust data foundation can drive innovation and growth. By leveraging data effectively, your organisation can identify new opportunities, develop innovative services, and make more informed strategic decisions. This can lead to new growth opportunities and a competitive advantage in your sector.

In summary, a strong data foundation is not just about managing and using data effectively. We can help you to implement a foundation to transform your organisation into a data-driven entity, capable of leveraging data to drive decision-making, improve performance, manage risks, and foster new ideas to help you move forwards.

What needs to be considered for a data transformation strategy?

Embarking on a data transformation journey is a significant undertaking that requires careful planning and consideration. Here are some key questions that you should be asking when developing a strategy that will help you master data management:

What are our goals and objectives? The first step in any data transformation strategy is to clearly define your targets. What do you hope to achieve through data transformation? This could range from improving decision-making processes, enhancing customer service, increasing operational efficiency, or driving innovation. Your goals and objectives will guide your data transformation strategy and help you measure its success.
How will this fit into the current data landscape? Understanding the current context of the data landscape is crucial. This involves assessing your existing data sources, metadata management and data accuracy, as well as how this data is currently used, and any existing data-related challenges. This will help you identify areas for improvement and determine what needs to be done to achieve your data transformation goals.
What kind of data governance policies do we want? You will need to establish the policies, procedures and standards for data management and use. Effective data governance ensures data quality, protects sensitive data, and ensures compliance with relevant regulations.
What kind of data culture are we trying to create? For a data transformation to be successful, it needs to be supported by a strong data culture. This involves fostering an environment where data is valued, understood and used effectively across the organisation. Building a data culture requires training and education to improve data literacy, as well as leadership support to drive data-driven decision-making.
What technology and infrastructure are right for us? Choosing the right technology and infrastructure is essential for data transformation. This could involve implementing new data management systems, adopting cloud-based solutions, or leveraging advanced analytics and AI technologies. The choice of technology should align with your organisation's needs, capabilities and budget.
What skills and capabilities do we need to develop? Data transformation may require you to add new skillsets to your team's capabilities. This could involve hiring new data scientists, training existing employees or partnering with external experts. It's important to assess your organisation's current skills and capabilities and identify any gaps that need to be addressed.
How will we measure success? Finally, it's important to measure and evaluate the success of your data transformation strategy. This involves establishing key performance indicators (KPIs) and regularly reviewing progress against these metrics. This will help you identify any issues or challenges early on and make necessary adjustments to your strategy.

When working with us to create your new data transformation strategy, we will help you to develop comprehensive answers to all of these questions, ensuring that your strategy is properly equipped to drive meaningful and sustainable change in your organisation.

What is needed for strong data governance and information management?

Implementing a robust data governance strategy and information management protocols will help ensure your organisation's data is accurate, reliable, secure and accessible. A comprehensive data governance strategy should incorporate the following:

Data governance framework: this provides the structure for data management across an organisation. It outlines the roles, responsibilities and processes for data governance, ensuring that everyone knows who is responsible for what when it comes to data.
Designated data stewards: these are individuals or teams responsible for managing and maintaining data within an organisation. They ensure that data is accurate, complete and reliable, and they are responsible for resolving any issues with data quality.
Data quality management processes: this incorporates all processes and technologies used to ensure the accuracy and consistency of data. This includes data cleansing, data integration and data validation.
Data security and privacy: with the increasing importance of data, it's critical to ensure that data is secure and that privacy is maintained. This involves implementing security measures such as encryption and access controls, as well as complying with data privacy regulations.
Data architecture plans: this refers to the way data is structured and organised within an organisation. A well-designed data architecture makes it easier to manage and use data effectively.
Data literacy training: for data governance and information management to be effective, everyone in the organisation needs to understand the importance of data and how to use it. This involves training and education to improve data literacy across the organisation.
Data governance tools: there are many tools available that can help with data governance and information management. These include data catalogues, data quality tools and data governance platforms.
Continuous monitoring and improvement: data governance and information management are not one-time activities. They require continuous monitoring and improvement to ensure that they remain effective as the organisation and its data needs evolve.

Our data governance services will help you put all of these elements in place and establish the strongest possible data governance and information management standards, enabling you to make the most of your data and drive better decision-making.

How to employ strong data literacy training

Much like literacy as a general concept, data literacy focuses on the competencies involved in working with data, and refers to the ability to read, understand, create and communicate data as information. It's not just about understanding data, but also about how to use data effectively to make decisions.

Here are the key factors that must be considered when organising strong data literacy training for your team:

Assess current data literacy levels: before you start with any training programme, it's important to assess the current data literacy levels within your organisation. This will help you understand where the gaps are and where training is needed most. You can do this through surveys, interviews, or by observing how your team currently works with data.
Define your data literacy goals: what do you want your employees to achieve with their new data skills? Whether it's making better decisions, understanding customer needs or improving service delivery, having clear goals will help shape your data literacy training programme.
Develop a comprehensive training scheme: based on your assessment and goals, develop a training programme that covers all aspects of data literacy. This could include understanding data concepts, using data tools, interpreting data analytics visualisations and applying data in decision-making. The training should be tailored to the needs of your organisation and the skill levels of your employees.
Use real-world examples: one of the best ways to teach data literacy is through real-world examples. Use data that your team works with on a daily basis in your training. This will make the training more relevant and easier to understand.
Provide continuous learning opportunities: data literacy should be seen as a continuous learning process. Provide opportunities for your team to continuously improve their data skills through regular training sessions, online courses, or resources for self-learning.
Foster a data-driven culture: data literacy training should be part of a wider effort to foster a data-driven culture within your organisation. Encourage your team to use data in their decision-making, recognise and reward data-driven achievements, and make data accessible and understandable for everyone.
Evaluate the effectiveness of the training: finally, it's important to evaluate the effectiveness of your data literacy training. Are your employees more comfortable working with data? Are they using data more in their decision-making? Use surveys, interviews and observation to evaluate the impact of the training and make improvements as needed.

We'll work with you to deliver data literacy training that delivers on all of these objectives, empowering your team to make better, data-driven decisions, and ultimately leading to improved performance and success for your organisation.

Our approach

Discover: We believe delivering enduring change starts with engaging with your users, understanding their needs and the context of the organisation you work within. During our research phase we will agree a shared vision and objectives and develop and implement a stakeholder engagement plan. We will assess the data maturity level of your organisation to baseline your current capabilities and understand the levels of data literacy across your teams. Our user researchers will help you curate a backlog of use cases that underpin your case for change and compose a roadmap that stakeholders can buy into.
Design: Effective programme design is crucial for transforming your data foundations over the long-term. We’ll take the outputs of our research and work with your executives, management, and users to design your data strategy. We’ll collaborate on a to-be organisational design that will empower your organisation to get from A to B, embedding user research and putting user needs at the heart of your change. You’ll work with us to develop a practical implementation plan that is scoped to reflect both the challenges, and your organisational capacity and appetite for change. We will ensure the approach delivers that change in a sustainable way, with governance and reporting that ensures we can evidence the value-add to your board.
Execute: We are with you all the way through this transformation. Our team of multidisciplinary data experts will work alongside your team, to augment and develop their capabilities. Together we’ll begin the transition to your to-be organisational design, implementing agile ways of working and user centred design. We’ll kick-off new ceremonies as one team, taking part in Stand-ups, Sprint Planning and Retrospectives. You’ll use these to deliver prioritised use cases from the backlog, learning new skills through doing and proving the value of iterative development to your users and stakeholders.
Embed: Now it’s time for your team to stretch their wings and use their new data foundations to deliver sustained value to the business. We’ll increasingly take a back-seat but still be there when you need us. Our partnership approach ensures knowledge is transferred effectively throughout the entirety of our engagements, rather than relying on rushed handover meetings and lengthy documents at the end. During this final phase we will focus on ensuring active feedback from users and stakeholders is used to perfect your tools and processes, and carry out any final training needed to make sure your teams are fully equipped to deliver the sustained improvements needed to make an organisation truly data-driven.

Case Studies

Positioning Data at the heart of Innovation - Swindon Borough Council (SBC)

The council employs over 2000 staff who work to prioritise improving infrastructure and housing to support a growing, low-carbon economy; offer education opportunities that lead to the right skills and the right jobs in the right places; ensure clean and safe streets; improve public spaces and local culture; and helps people to help themselves, while always protecting the most vulnerable children and adult. As part of its pledge to compete at the forefront of digital innovation with a commitment to using
technology for positive change, the council wanted to improve organisational data management enabling it to more effectively use its data, lower costs and support new services.

Stethoscope - The CCG

The CCG was overloaded with datasets, spending a lot of time collating data from various sources for analysis. They required assistance in navigating the vast flows of data that the NHS generates and had a requirement to access this data through an online platform and automated reports, which could visualise benchmarked and predictive data for interpretation in a clearer way than their current and complex spreadsheets.