Gartners 2022 research omnibus survey revealed that 58% of Data and Analytics (D&A) leaders see D&A alignment with business strategy as a top three driver of success. Data Strategy is integral to all organisations to manage and use data more effectively. Having the right data strategy in place is key to achieving both business and technology objectives. However, according to a 2021 MIT Tech Review and Databricks study, only 13% of organisations are delivering on their data strategy.
So what is a data strategy and what are the key components required to successfully implement a data strategy?
What is data strategy?
“A set of choices and decisions that together, chart a high-level course of action to achieve high-level goals. A data strategy should include business plans to use the information to competitive advantage.”
Data Management Body of Knowledge (DAMA)
Data strategy shouldn’t be approached with a siloed mindset. Businesses often view data strategy as a separate entity, dealing with specific business cases and problems the organisation has, when in fact it needs to be closely linked to the overall business objectives and strategy. It needs to be a dynamic process, which closely supports the organisation’s objectives, and is continually adapted and reviewed to reflect changing priorities and economical realities.
Data strategy is having a clear vision of what we can do with the data we generate or collect. It's a set of procedures and principles that define the 3Ws (and 1 H) of data management. Firstly, Why you require data within the organisation? Understanding Who your stakeholders are. What business drivers are we supporting, derived from clearly defined and measurable KPIs? Finally, How are we as an organisation going to achieve this and how are the roles and responsibilities defined across the team or department to ensure they work efficiently across different data domains?
“A highly dynamic process employed to support the acquisition, organization, analysis, and delivery of data in support of business objectives.”
3 W's (and 1 H)
The Why - building a vision statement
Understanding and communicating the vision of what you hope to achieve is key to ensuring that there is a shared goal. The strategy should be aligned with and support broader organisational objectives. It should be short and concise, limited to approximately 20-40 words. All stakeholders should be addressed and it needs to mention your overall goal, and also give a brief sentence on how you hope to achieve this. Try summarising the Who, What and How into a sentence or two.
The Who - identifying your stakeholders
A successful data strategy depends on the engagement and support of stakeholders, so it's important to identify all stakeholders, both internal and external, who have some form of interest in the data solution at the beginning of the process. It’s important to identify your key stakeholders as some may have more of a vested interest than others. Stakeholder mapping can be a great way to categorise different stakeholders by ascertaining their interests and influence. Start by listing all of the stakeholders, and categorise them into the following; High interest and high influence; High interest and low influence; Low interest and high influence; Low interest and low influence.
The category a stakeholder sits in will determine how much engagement and communication each stakeholder requires
The What - defining your KPIs
Identifying how a project can be deemed successful is important but so often forgotten, with Gartner estimating 75% of data strategies as having limited KPIs to measure against.
Clearly defined and measurable key performance indicators (KPIs) will help assess the impact and significance of your data strategy. Impactful KPIs should be written SMART (specific, measurable, achievable, relevant, and time-bound).
When defining KPIs, they should be aligned with overall business goals or objectives, a natural evolution of the overall business objectives.
The How - the right people and organisation
Relevant stakeholders will want to know how you're going to deliver your strategy. Having a visual representation of an operating model will achieve this as it provides best practices for an organisation's team for enabling successful data management practices.
The roles should be clearly defined, whilst also explaining the business data stewards and the technical data management professionals.
How do we assess the data strategy of an organisation?
As part of the Rittman Mead Data Governance Assessment Framework, we focus on three key areas of a company's Data Strategy in order to assess their maturity level.
- Business Case and Program Funding (who)
- Organisation and People (how)
- Principles and Process (why and what)
Business Case and Program Funding
Successful data strategy initiatives require buy-in from leadership and stakeholders. Part of the assessment will focus on the business’ commitment to the strategy, focusing on the business case which was utilised to achieve the buy-in, whether or not a compelling long-term vision has been set and will ensure that the business case addresses all of the fundamental topics.
Organisation and People
This part of the assessment focuses on the operating model. The roles and responsibilities will need to be clearly defined, by clearly illustrating how different people interact with one another. The operating model must be suitable for your organisation and aligned with business goals.
Principles and Process
The assessment questions in this area focus on guiding values, principles and management perspectives of your data strategy to ensure that the correct processes are put in place to manage this. Ask yourself ‘Do these principles try to identify proposed measures of success for your Data Strategy'.
A comprehensive data strategy is vital
You wouldn’t start a business venture without a strategy, so why treat data any differently
Data management strategy is sometimes seen as an oversight within an organisation, often getting lost in the overall business strategy or being confused with a business case to solve a specific need. A comprehensive data strategy, like other strategies, is key to focusing your efforts on where it matters most for the business. The world of technology and data moves at a rapid pace, and current financial situations mean that priorities often change within a business. You always need to go back to the question; does our data align with our business objectives and are we getting the most out of our data?
That’s why you need a data strategy. A strategy will set out the principles of how you want to use the data, how you want to prioritise the data and how can we get to our end goal, ensuring that we always have the right people and technology along the way to support us. You wouldn't embark on a business venture without a strategy, so why treat data any differently?
Data and Analytics leaders see data strategy as one of the key concepts to any successful data program. It gives focus and meaning to any initiative and outlines key business and technical concepts.
You can look to summarise data strategy by asking yourself the Why, Who, What and How. Why are we doing this, Who are we doing this for, What are we doing and, How are we going to do it?
- Taking a Data Governance Programme to Maturity
- Is Your Data Worth Managing?
- How to Get a Data Governance Programme Underway... Quickly
For more information on the Rittman Mead Data Governance Assessment Framework, please feel free to contact us.