Companies across industries collect a rapidly increasing stream of user, event and product data, but are not always using it optimally to meet their goals or – in the worst case – are not using it at all. HBR estimates indicate that less than half of an organization’s structured data is used in making decisions, and less than 1% of its unstructured data is used at all. What good is data if you do not have a data strategy to guide its use?
Part of the lack-of-use problem can be attributed to the sheer overwhelming amount of data: how best should you be managing this volume overload? Another important aspect of this problem focuses on data strategy principles. Building a data strategy, or improving an underperforming data strategy, is essential both to managing your data successfully and, ultimately, to achieving your business goals.
What Is Data Strategy?
A data strategy underpins data management and sets up guiding principles, goals and actions for your data. That is, how will it be integrated and used to deliver short-term and long-term business priorities? Diving a bit deeper into specifics, a data strategy also aims to ensure that data does what it is supposed to – deliver valuable insight both now, in the short term, and in the future as trends and needs change.
More fundamentally, a data strategy is a plan to manage how you collect, store, manage, share and use data.
Many companies, as evidenced by the statistics highlighted above, tend to plan for the short term, looking at ways to use data to cope with pressing and immediate issues, but this is neither strategic nor long term in focus. A data strategy requires both the short and long-term goals for organizing, managing, analyzing and deploying data and a reliable, replicable method and structure.
Planning Your Data Strategy: A Data Strategy Roadmap
A data strategy is first and foremost a guide to keep you from being overwhelmed and to help you become as data-driven in your decision-making as you can be. Whether it’s data-driven marketing or improving operational efficiency, a data strategy fosters your ability to derive value from your data assets.
At a basic level, your data strategy needs to meet four criteria, according to consultancy firm PWC:
- Actionable
- Relevant to the organization and its goals
- Evolutionary
- Integrated/connected
These key criteria will govern your choices, about the data, its governance and the people who work with data in your organization. That is, what do you need the data to do for you? This should lead to a set of questions that come from your overall business strategy, such as:
- What problems do I need to solve?
- What kind of data could give me answers?
- How can I collect and analyze this data?
- How can I operationalize the data and make sure it gets to the right people in the organization?
- Who will take care of these actions and responsibilities?
Most data strategy consultants will urge you to focus on clarity and what you need to get from your data rather than the volume of data you can collect.
Answering these questions leads to more technical, hands-on data considerations.
What the Data Needs to Do
Data can inform day-to-day activities, such as giving marketing and sales teams insight into their customers. But the data can also be a foundation for longer-term forecasts, monetization or performance metrics. Your strategy will need to define these objectives and start to think about where and how this data can be obtained.
Data Collection: Master Data Management
Taking a step back after deciding what data is needed, data collection – both what kinds of data can be captured and what technologies and data infrastructure are required – is the next logical step in your data strategy creation. The technology decisions should include your previous thinking on what data you need to undertake the activities you plan because this will determine a great deal about the nitty-gritty of data collection and management, such as:
- Data collection
- Data storage
- Data analytics and processing tools
- Data accessibility and portability
- Data visualization
- Data format (structured, unstructured) and quality
By no means an exhaustive account of what you will need to consider, these are important parts of generating value. It is worth asking the tough questions upfront about what kind of data you have, and what you want to get from it now and over time.
People
Predictions indicate that there will be nowhere near enough data analytics talent to go around, despite the fact that the number of people with advanced analytics skills will continue to increase exponentially.
Technical experts, data analysts, chief data officers and data strategy consultants will become more necessary than ever – and are a key part of planning, implementing and ensuring the success of a data strategy.
This becomes particularly crucial as data privacy, security and stewardship measures become higher stakes (e.g., GDPR violations are very expensive, and data breaches are becoming increasingly common). On the other side of the coin, your data-driven organization needs to create a data-literate workforce more generally, to ensure that everyone in the company understands the importance of data, has basic data literacy and can access and deploy the data they need to do their jobs and meet company goals.
Why You Need a Data Strategy
Data has a key role to play in the success of your business and in achieving your overall business strategy. A cohesive and clear data strategy will ensure that you gain maximum value from the data you have and power your data-driven future.
A data strategy consultant can help answer more questions about data strategy, collection, clarity of data, and what information you need to get from your data. You don’t have to do this alone, our team can speak data intelligence with expert fluency.
