I am assuming that you are here because your business has data to help it grow? Or, you know that operating without a data strategy introduces risk and are wondering, how do we get started with one? Or perhaps you have some cool ideas for data products but don't have time to wait around for decisions from the top? Please read on!
I will cover; do you need a data strategy? What makes them successful and why do they fail? How to get started with buy-in for that data product you so passionately want to build and need!
What is a Data Strategy and Do You Need One?
You probably already know this, but just in case I have the introduction completely wrong, let's just quickly cover what a data strategy is and highlight why you might feel the need to have one.
As someone passionate about strategy, I can't emphasise enough how crucial a robust data strategy is for business growth. Without one, the potential of your business remains untapped.
However, you cannot have a data strategy without a business strategy. A business strategy focuses on the business’ future and its culture. A data strategy should focus on the people, process and technology required to manage a business’ information assets. There are many articles about what a data strategy is and why they are important yet they tend to focus on the what and how rather than the who and why. This report from Accenture is an example of how investing in the right people as part of a business strategy can help make a data strategy a success.
If your leaders do not see the value of data or your business does not embrace a data driven culture, you need a plan to influence that change first of all. Your business must focus on what brings in the most value through return on investment in line with its strategy and sometimes that is not data. To start a data strategy, you must convince the right people that data is an asset and there is a need amongst its people..
So why do I feel I need a data strategy right now?
Probably because you can see how valuable data is! There have been lots of buzz words in the data world : Big Data, Machine Learning, Hire a Data Scientist!, Data Mesh and most recently AI. Yet, none of them matter if you don’t understand why you need all these shiny things AND if your data and business is not ready.
Or maybe your business is ready and you know that data can help your business in many ways i..e improve workflows and operations, identify threats and opportunities, generate income through a data product.
You could have all these benefits but first, you must assess the business’ data readiness/maturity and the best way to start is with a good data audit to feed your data strategy.
Starting a Successful Data Strategy
Now, let's get to the heart of the matter – how to kick off a successful data strategy:
1. Conduct a Data Audit:
Assess current data maturity and align goals with business objectives. Identify gaps and areas where data can add value. A thorough audit involves reviewing data quality, sources, governance practices, and technology infrastructure. It helps in setting a baseline to measure progress.
Identify high-value changes and prioritise them. Focus on areas that will deliver the highest ROI and align with strategic business goals. This might include addressing data quality issues, consolidating data sources, or enhancing data accessibility.
2. Define Value and ROI
Establish clear priorities and expectations for return on investment. This involves setting measurable goals, such as improved decision-making capabilities, enhanced operational efficiency, or increased revenue. Clearly defining the expected outcomes helps in gaining stakeholder buy-in and justifying the investments in data initiatives.
3. Iterate and Adapt
Continuously evolve your strategy to adapt to changing internal and external environments. Regular reviews and updates based on feedback, performance metrics, and emerging trends are crucial. An agile approach allows organisations to pivot quickly and take advantage of new opportunities or address challenges as they arise.
4. Embrace Design Thinking
Foster a culture that supports data-driven decision-making. Design thinking encourages organisations to focus on user needs, prototype solutions, and iterate based on feedback. Applying this mindset to data strategy helps in creating solutions that are user-centric, innovative, and practical.
5. Assign Ownership
Designate responsibility for monitoring and measuring the strategy's effectiveness. Assigning clear ownership ensures accountability and ongoing oversight. This might involve creating a dedicated data governance team or appointing data stewards within each department who are responsible for maintaining data quality and compliance.
The Essential Role of Data Audits in Building a Data Strategy
Alright, so you’re on board with building a data strategy. But what’s the secret sauce? Regular data audits! Here are some of the key benefits:
1. Identify Problems
Pinpoint inefficiencies and areas for improvement in people, processes and technology. A comprehensive audit reveals where data practices are falling short and what needs to be addressed to enhance overall data management and utilization.
2. Eliminate Data Silos
Achieve a comprehensive view of data to enhance management and decision-making. Breaking down data silos allows for more integrated and holistic insights, facilitating better strategic decisions and operational efficiencies.
3. Manage Risks and Performance
Monitor performance and identify risks in alignment with business objectives. Regular data audits help in proactively identifying and mitigating risks related to data security, compliance and quality. This ensures that data practices remain robust and aligned with regulatory requirements.
4. Discover Opportunities
Uncover potential for new products and services. By thoroughly examining data assets, businesses can identify untapped opportunities for innovation, product development and market expansion. Data audits can highlight trends and patterns that might not be evident through day-to-day operations.
5. Drive Improvement & Growth
Guide strategic decision-making by highlighting areas for improvement and growth. Data audits provide actionable insights that can inform strategic initiatives, helping businesses to optimise processes, enhance customer experiences, and drive growth.
How to conduct a Data Audit?
A data audit helps answer critical questions and normally opens a can of worms! It's easy to overthink or get sidetracked. This is why it's important to keep revisiting the business goals and priorities. It's also OK to start small. For example, you have data products already and want to improve them. Which one creates the most problems for its users and which ones actually return the most value and why?
Below are some steps to help structure a data audition more detail :
1. Current State and Future Needs
Where are you now, and where do you need to be? Assessing the current data landscape and defining future goals helps in creating a clear roadmap for data strategy implementation.
2. Challenges and Priorities
Identify critical and valuable challenges. Prioritising issues based on their impact and alignment with business goals ensures that efforts are focused on the most significant areas first.
3. Identify key stakeholders and actions
Determine who is required and when to act on objectives. A detailed action plan outlines the roles and responsibilities of team members, timelines, and milestones to ensure coordinated and efficient execution.
4. Tools and Technologies
Assess if current tools and technologies align with data goals. Evaluating the existing technology stack helps in identifying gaps and opportunities for improvement, ensuring that the organisation is equipped with the right tools to support its data strategy.
Consequences of Skipping Data Audits
Without regular audits, businesses risk misaligned strategies, inefficiencies, outdated technology, data silos, and missed opportunities. Regular audits ensure strategies remain relevant and effective.
How to gain buy-in for a data audit?
Securing buy-in for a data audit can be challenging as they take time and don’t actually build the tangible product you really want to build. Yet, If this blog hasn't done so already, here’s how to convince leadership (or yourself) how a data audit is an essential place to start, if you want to develop a high value product and/or culture :
1. Highlight Benefits*
Risk reduction, improved efficiency, and better decision-making. Clearly communicate how a data audit can directly benefit the organisation by enhancing data practices and supporting strategic goals.
2. Communicate Costs of Inaction
Compliance risks, operational inefficiencies, and competitive disadvantages. Emphasise the potential negative consequences of not conducting regular audits, such as falling behind competitors or facing regulatory penalties.
3. Align with Business Goals
Link audit outcomes to strategic objectives. Demonstrate how the results of a data audit will contribute to achieving key business goals, such as market expansion, innovation, or customer satisfaction.
4. Start Small
Propose a pilot project to demonstrate value. Starting with a smaller-scale audit can provide tangible evidence of the benefits, making it easier to secure broader support for larger initiatives.
5. Leverage Internal Champions
Engage stakeholders who benefit most from improved data practices. Identify and involve key stakeholders who can advocate for the audit and help build momentum within the organisation.
6. Use Real Examples and Case Studies
Share success stories to illustrate benefits. Providing examples of how other organisations have successfully implemented data audits and the resulting positive outcomes can make a compelling case.
7. Prepare a Clear Plan
Present a detailed plan for the audit. A well-structured plan outlining the scope, timeline, resources, and expected outcomes helps in addressing concerns and demonstrating the feasibility of the audit.
8. Educate and Inform
Hold workshops or training sessions to raise awareness. Increasing understanding and awareness of data quality and governance across the organization helps in building a supportive culture for data audits.
9. Leverage Data Visualization Tools
Use visuals to show data quality issues and potential improvements. Visual representations of data issues and improvements can effectively communicate the value of a data audit to stakeholders.
Why a data strategy might fail
A data strategy is important to ensure data is an asset to your business and help it grow, both internally and externally.
Good communication and a high level of buy-in are key to a data strategy’s success. Buy-in must start from the top. If you can’t make a case for data being an asset to the business, a strategy is likely to fail or not start at all.
Leaders must also champion the idea of a data culture in order to inspire change across the organisation. At the same time, if you don’t have a business strategy that supports growth through data, you are unlikely to get a budget and see value.
Some common examples of why a data strategy might fail are :
1. Lack of Communication:
Poor communication leads to misaligned goals and fragmented efforts. Clear, consistent communication across all levels of the organisation is vital. Regular meetings, updates, and transparent reporting can help mitigate this issue. Think of it as steering a ship; everyone needs to know the course.
2. Lack of Process Management:
Siloed departments and unsynchronized processes impede cohesive data strategies. Effective process management involves integrating data across departments, standardising processes, and ensuring that data flows seamlessly. This includes implementing enterprise-wide data governance frameworks and tools that facilitate better data integration and accessibility. Every cog in the machine must work in harmony.
3. Lack of Specialised Skills:
Inadequate expertise prevents effective implementation. A successful data strategy requires skills in data analysis, data engineering, and data science. Organisations should invest in training their staff, hiring specialists, and fostering a culture of continuous learning. You wouldn’t send a novice into a chess tournament, so why skimp on your data strategy team?
4. Overly Ambitious Plans:
Many data strategies fail because they are too ambitious, undefined, or simply unorganised. Businesses often don't know where to start or don't have the right people in the right place at the right time.
5. Siloed Data and Teams:
In larger organisations, data and teams are often siloed by department. Each department has a different way of working. It's important to sync all to truly become a data culture that works together to action your data strategy. Therefore, it's crucial to have people in place to facilitate communication across the business environment, understand needs and pain points, understand the goals and people, and ensure that sub-processes align with the overall project goals.
Of course data strategies can fail for many reasons, like people, it's impossible to predict everything that may impact them. The key is to review and adapt depending on the pace of your industry and business culture. They are comprehensive plans that must be managed and reviewed systematically
Conclusion
A successful data strategy requires a good understanding of business objectives and goals, clear communication, process synchronisation, skilled personnel, and continuous iteration.
Regular data audits are essential for maintaining an effective data strategy. They ensure alignment with business goals, identify inefficiencies, and uncover opportunities for growth. Begin your data strategy journey with a thorough audit to build a solid foundation for future success, save money, time and minimise risk for your organisation.
