Seven steps: Developing a successful data strategy roadmap
Let’s walk through the 7-steps to developing a successful data strategy roadmap, along with a roadmap that aligns with your business goals. If you've been looking to revise your current data strategy or compare data strategy frameworks, we hope this helps.
#1 Start with a Data Strategy Consultant
Cutting out false starts makes getting external expert guidance a very valuable exercise. Notitia's data strategy consultants are Melbourne and Adelaide-based (with services Australia-wide) and bring a jaw-dropping wealth of experience and industry insights to the table.
They can help you assess your current data landscape, identify pain points, and chart a successful path toward a value-driven and robust data strategy.
#2 Develop a Data Strategy Framework
A solid data strategy requires a clear, but simple framework. Your Data Strategy Framework will outline your organisation's:
- data-related goals
- objectives, and
- key performance indicators (KPIs).
This is the backbone, ensuring that your tactical implementation is aligned with your overarching business vision.
#3 Plan how to address business challenges (before they become problems)
Before diving into implementation, understanding how your business will overcome data challenges plays a big part in the success.
- Identify the specific challenges your organisation faces, such as data silos, quality issues, or lack of data governance.
- Outline the steps and resources required to address these challenges effectively.
#4 Create a Data Strategy Roadmap
Here, we pull together work from your data strategy framework and challenge analysis to create your data strategy roadmap.
A data strategy roadmap acts as a visual guide, detailing the timeline for implementing various components of your strategy. It helps you track progress, allocate resources, and stay on course, ensuring that your strategy remains dynamic and adaptive.
Goal 1
Assess Current Data Landscape: Conduct a thorough assessment of your current data infrastructure, processes, and capabilities. This lays the groundwork for identifying gaps and opportunities.
Example: Notitia often begins with a detailed data assessment, as seen in their work with Gippsland Health Alliance (GHA), where they identified critical gaps and opportunities to expand data services to regional health sites.
Goal 2
Initiate Vendor Selection:
Identify and select key vendors and technology partners. This ensures that all subsequent tools, infrastructure, and external expertise align with your business goals and data strategy.
Example: Early vendor selection has helped our clients streamline the integration of customised solutions, such as in Notitia's collaboration with Fyna Foods, where vendor evaluation and selection were critical to modernising their technology stack.
Goal 3
Establish Data Ianfrastructure:
Set up or migrate your data infrastructure, including cloud solutions if necessary. This is critical to support the new data strategy.
Example: Notitia's work with GHA involved a cloud migration that was pivotal for enabling advanced data analytics and expanding data services across regional health sites.
Goal 4
Team Training and Data Literacy: Begin training your team on the new data tools and processes, with a strong focus on data literacy. Ensuring your staff are equipped to handle and interpret data is crucial for successful implementation. Conduct Data Literacy Workshops: Enhance your team’s ability to work with data by holding data literacy workshops. These sessions help bridge any gaps in understanding and ensure that the entire organisation can leverage the new systems effectively.
Example: At West Gippsland Healthcare Group (WGHG), Notitia provided data literacy training alongside their deployment of automated reporting and dashboards, ensuring stakeholders could effectively use and interpret data. Data literacy workshops were a significant part of Notitia’s engagement with WGHG, empowering teams to make more informed decisions using the newly implemented data systems.
Goal 5
Deploy Data Management Systems: Implement data management systems across key departments, ensuring they integrate seamlessly with existing workflows. This is crucial for consistency and efficiency.
Example: In their project with WGHG, Notitia deployed integrated data systems that streamlined data access and reporting, significantly improving operational efficiency.
Goal 6
Automate Key Data Processes:
Start automating data processing tasks to enhance efficiency, reduce manual errors, and free up resources for more strategic activities. Automation is often a game-changer in data strategy implementation.
Example: Notitia automated several data processes for Fyna Foods, reducing manual effort and improving data-driven decision-making. Ensure that all automated processes are fully integrated into the business operations, with all data flows running smoothly and efficiently. Full integration was crucial in Notitia’s work with Fyna Foods, where automation led to significant operational improvements and cost savings.
Goal 7
Implement Customised Dashboards: Develop and deploy customised dashboards that provide real-time data insights tailored to the specific needs of your business. This step is essential for turning raw data into actionable insights.
Example: Notitia’s work with WGHG involved creating multi-layered dashboards tailored to different departments, providing valuable real-time insights for decision-making.
Goal 8
Evaluate System Performance: Conduct a series of evaluations to assess the performance of your new systems, gathering feedback from users to identify any areas for improvement. Adjust KPIs and processes as needed.
Example: Continuous performance evaluation was a key factor in Notitia’s partnership with Outcome Health, ensuring that the data systems remained aligned with the evolving needs of the healthcare provider.
Goal 9
Internal Audit for Data Governance:
Perform an internal audit to ensure that all data governance standards and security protocols are being met. This step is vital for maintaining data integrity and compliance.
Example: In their project with GHA, Notitia ensured strict data governance and privacy standards were met, critical for the successful deployment of shared data services across regional health sites.
Goal 10
Compliance and Adjustments:
Review and finalise all compliance measures, making any last adjustments based on audit results and ongoing evaluations. This step ensures that the data strategy is robust, secure, and adaptable.
Example: Notitia’s approach with GHA included finalising data governance and compliance measures, ensuring the long-term success and security of the data strategy.
Goal 11
Continuous Improvement Plan:
Implement a continuous improvement plan that includes regular updates to the data strategy, ongoing support, and periodic reviews to keep the strategy dynamic and responsive to new challenges.
Example: Notitia’s long-term partnership approach with clients like Outcome Health includes continuous refinement of their data strategies to adapt to evolving healthcare needs.
#5 Setting up your business to successfully implement your data strategy
Implementation involves setting up the necessary infrastructure, tools, and processes to execute your data strategy.
It's crucial here to ensure that your team is well-equipped and trained to handle data effectively.
Consider leveraging external data strategy services to complement your in-house capabilities.
Notitia works closely with our clients to help with data strategy implementation, which includes many of the puzzle pieces including vendor selection, data integration, analytics, technical training and data governance solutions to streamline data strategy execution.
#6 Data literacy is a "whole-of-business" thing
To ensure that your objectives are met and understood by your organisation, remember that data literacy is crucial for your people across your whole business.
Data integration and analytics platform Qlik recently commissioned Omdia to compile their report Driving Data in the APAC Public Sector: Balancing Governance and Innovation.
Qlik 's report found that while 90% of respondents had a data strategy in place for their organisation, around half believed that their goals and objectives were not understood by the business.
#7 Again, don’t forget about data quality + data governance
Successful data strategies are built on a foundation of best practices. These include data quality management and data governance frameworks to ensure that your data remains reliable, compliant, and secure.
Excellence Data Governance = Excellent Data Quality. Data Governance is the overall management of the data in your business. It considers the availability, usability, integrity + security of data.
If you'd like to see how our team can help, check our data quality + data governance services.
About Alex Avery, Notitia Managing Director + Founder
>Questions about how we can help? Book a meeting.
Alex Avery, Notitia Founder and Managing Director, heads our operations in Melbourne to provide data analytics and digital transformation services to more than 60 clients across Australia.
He is highly regarded for his ability to quickly analyse complex operational scenarios and provide workable solutions to achieve business objectives. This, along with considerable experience in the management of technical and business teams across both project environments and "business as usual" is the reason why most clients have come via word of mouth.
Having spent close to a decade working across Australian and global startups, Big 4 consulting and academia, Alex launched Notitia in 2019, which has since skyrocketed in growth.
Today, Alex leads his expanding team across data + analytics, design + development + strategy to help Australian clients solve their data challenges.
He sees technology as an enabler and partners with the biggest vendors to utilise best of breed software.
With the right technology and expertise, Alex says that problems of any size can be solved through valuable insights from accurate data.
Book a chat with Alex to find out how he can solve your data challenge.
