Given data's importance, both as a creator of value and as an enterprise risk, having a strategy for its use and management is imperative.
This post, the first in a weekly series on data strategy for network utilities outlines five steps to develop a strategy (and a couple of tips to make sure it sticks).
But first a definition. Let me propose the following:
An enterprise data strategy is a 3-to-10-year roadmap of initiatives designed to advance an organization's data maturity to an agreed target state.
Tip 1: Criticality, the target state must be one that delivers value to the business. Invest time in speaking to stakeholders, documenting their pain points and priority use cases and bring them together to build a collective vision.
Typically, data strategy development exercise takes ~8 weeks. That will allow sufficient time for the following steps.
1. Start-Up: Identify and schedule meetings with key stakeholders throughout the business and within the technology team. Review existing materials related to overall business and technology strategy. Begin to think about how the data strategy will align with existing efforts and objectives.
2. Current State Assessment: Understand and document the organization's current state data maturity. Different frameworks exist to aid in this assessment (EY's data capabilities framework identifies 15 capabilities grouped into 4 areas: Govern & Manage, Strategize, Operate, and Deliver). The important thing is that (a) it is done in a structured way, and (b) involves key business stakeholders.
3. Target State Development: Define the future state of the data and analytics environment in each aspect of the framework used in step 2. Link strategy to use case, to technology activation and settle on an agreed data architecture.
4. Gap Analysis: Completing steps 2 & 3 in a methodical way according to a data capabilities framework will allow you to identify the gaps that needs to be closed in each aspect of your organization's data maturity. These gaps will drive the final step.
5. Roadmap Development: The final step in strategy development is to transform your gap analysis into tangible prioritized projects, and then design and communicate a delivery schedule for implementing these projects. Bonus points for estimating the effort/cost associated with each project.
Tip 2: If you have not done so already, prioritize the use cases identified via business engagement and place them on the roadmap. Some data initiatives will be foundational, but many can be delivered via use cases. For example, roll out Data Governance for each use case rather than at an enterprise level. Doing so, ties implementation of the data strategy directly to business priorities and value.
From Customer Service to Asset Management, Finance, and Operations, data is the lifeblood of the modern utility. Effective data management requires a substantial ongoing investment and the first step in ensuring that investment delivers value is a clear and reasoned data strategy tied to business objectives.
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The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organization or its member firms.