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Clarity is the key to successful data strategies

Data strategies are most successful when complemented by clear objectives, but the hard part is ensuring clarity.
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What it needs 

Very simply, a data strategy must have a clear mission that aligns with:

  • The business strategy.
  • The technology strategy.
  • A digital transformation agenda (if one exists).

This mission must be aligned to answer the fundamental question of how customer, employee and supplier data will be used and for what purpose, which itself must be measurable with clear indicators of success. This needs to be examined and scrutinised by different players in the organisation before finally being agreed upon by the top level.  

“Work must be undertaken to ensure the data strategy and data policies are aligned,” said Tim Bowes, associate director consulting, Dufrain. “The data strategy sets out how data will be used to meet business objectives, and data policy provides the rules and guidelines for the organisation to adhere to when using data.” 

In a nutshell, the data strategy framework should serve as the foundation for all data initiatives and enable the organisation to remain agile under pressure. It can be helpful to provide examples of scenarios where this agility will be used to ease bottlenecks and react to market changes. Data leaders will need to incorporate a large amount of storytelling to be able to get other business decision makers onboard, particularly if they have a non-data background.  

“A data strategy sets out how an organisation is going to use data to achieve its strategic vision and business objects,” said Joseph George, chief executive officer, Dufrain. “It is therefore imperative that an organisation has taken the time and effort to provide clarity on its strategic objectives, which can be used when creating a data strategy.” 

Furthermore, a data strategy needs to be set by the highest level of the business and driven by the CDO (or equivalent). It is important as a data leader to guide business leaders to consider:

  • What employees need for empowerment to effectively utilise data.
  • The processes required to ensure data is accessible and high quality.
  • Any technology required for storage, sharing and analysis of data.

“Above all else, a data strategy must be pragmatic and reflect the organisations appetite and ambitions so that tangible implementation action can be taken to achieve the objectives set out in the data strategy,” said George. 

Ambition is pivotal to the progression of a data strategy as the purpose is to drive the operation forward and seize opportunities – this is not possible without a level of ambition. However, there is a balance, and the ambition of the data strategy needs to not outrun the business strategy.  

Ultimately, the creation of a data strategy is a tightrope. Data leaders must ensure they are being ambitious enough to demonstrate drive and change, communicative enough to align with other strategies and pragmatic enough to demonstrate the journey. However, they must also show realistic understandings of true potential, a grip on financial considerations and not be dictating the journey to non-data teams. This is possible to achieve with the correct preparation and a strong focus on clarity for the long-term.  

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