Pragmatic considerations in progressing your Enterprise Data Strategy

Modis Posted 22 August 2022

Every organisation needs a data strategy to navigate the process of using data to get ahead. After people, data is fast becoming the most valuable business asset, often referred to as the ‘new oil’. Successful and forward-looking enterprises are now harnessing their data asset to make strategic business decisions and leave their competition behind.

This involved six key components of an Enterprise Data Strategy which you can see here. But beyond these, we find that there are several key pragmatic considerations in progressing your Enterprise Data Strategy:

  • Enterprise Data Strategies frequently involve cultural change throughout the organisation – and this takes time. Becoming a data-led organisation is quickly emerging as a top priority at board level and is critical to driving sustainable growth. It enables the business to become rapidly responsive, with an innovative culture and processes that reinvent the organisation based on increased awareness of its data.  To do this, the Enterprise Data Strategy should encourage a philosophy of ‘good data beats opinions’, with the premise that any data asset can be continually improved, thereby adding to its utility in decision-making.
  • The second is to choose the right enterprise data platform to support your data-driven processes. The platform’s future direction needs to be in line with your own, as the ever-increasing volume of Platform as a Service (PAAS) data services feeds into strategic decisions. What may seem suitable today may not meet the needs of the Enterprise Data Strategy in the future. It needs to match the skills profile of your workforce. Balancing the adoption of best of breed technology with staff capability is an ongoing battle for many organisations.
  • The third is to develop shared data assets independently. To move forward with the implementation of an Enterprise Data Strategy, shared data assets must be developed separately from other initiatives. With finite resources to provision consumable data sets, a shared data set needs to be given the appropriate attention, priority, and support by all departments who will use it. Existing projects can then be migrated to use the shared data set once it has been successfully implemented. For example: to create a primary address list from multiple separate address lists in each department and business, technical resources need to be allocated to create and populate the main list, along with all the governance and data processes to test, support, and provision a list that will be useful for all departments. Being mindful of any updates and changes to this main list will require agreement from all who use it.
  • Lastly, recognise the need to continually adjust your Enterprise Data Strategy to cater for upcoming technological advancements. Whether they be in the short, medium, or long term, they can drastically influence your approach.

A smart Enterprise Data Strategy is one that involves incremental learning and adaptation. Over time, this helps the organisation to embrace a data-driven culture and use its ‘new oil’ data asset to its maximum potential. It is the best bet to achieve success in the near-to-medium term and to continually position your organisation to realise the benefit of current and future technologies.

To learn more about developing a smart data strategy download our whitepaper here.

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