Many companies now recognize the need to have a dedicated chief data officer, whose main task is to effectively leverage data – a powerful asset of an organization. The journey to become a data driven organization is long and painful, but a clear data strategy can serve as a powerful guide during this journey. Here are 10 steps to build an enterprise data strategy:
Step 1 – Understand the company’s business strategy
An enterprise business strategy is a prerequisite for building an enterprise data strategy. A business strategy defines how an organization plans to leverage its assets to achieve various business goals. A good understanding of the enterprise business strategy is necessary to to build an ‘aligned’ enterprise data strategy.
Step 2: Identify opportunities to leverage data
There are several ways to leverage data to help business to achieve their goals. It is important to understand how data can be a useful tool to achieve many of the business goals. A good knowledge of various business goals and data science capabilities are necessary to identify opportunities to leverage data.
Step 3: Understand the market dynamics
The opportunities to leverage data to achieve business goals can be classified into two distinct categories – push opportunities and pull opportunities. Pull opportunities are those where the request originates from the business, while push opportunities are those that need to be pushed onto the business. Understanding these market dynamics helps us channelize the efforts effectively.
Step 4: Articulate the value proposition
Articulating the value proposition involves doing deep analysis of the opportunity at hand, explaining how data can help and what it will take in terms of time and investments. It also involves getting all stakeholders on board with the proposed initiatives, and involving them right from the beginning.
Step 5: Build an enterprise data architecture
An enterprise data architecture allows breaking up of various technology solutions into standard enterprise architectural components to ensure re-usability and standardization of data across businesses. This may typically involve building a common data repository or a data warehouse or a data lake, or all of them, depending on the specific business requirements and long term business goals of the organization. It may also involve defining data policies and various data management solutions like maintaining data dictionary, standards, policies etc and ensuring compliances to regulations.
Step 6: Build an Implementation Roadmap
Enterprise data strategies can quickly get very ambitious, and not everything can be achieved immediately. There has to be a long term vision and roadmap of how the data strategy needs to be implemented, with clearly defined milestones. We need to also leverage the existing data capabilities within the organization, and construct the roadmap accordingly.
Step 7: Put together a cost structure
Various milestones in the data strategy roadmap needs to be accompanied with a cost structure. This involves estimating the cost to design, build and manage the solutions, and identifying how this cost should be shared by various business within the organization.
Step 8: Build a Target operating model
A target operating model should be defined for every milestone identified within the enterprise data strategy, to ensure clarity of how various solutions will be managed and governed on an ongoing basis.
Step 9: Build a Data Governance framework
A data governance framework defines ownership of data and associated responsibilities towards its management and compliances. A typical framework defines the roles and responsibilities of data stewards for provisioning enterprise data to businesses, ensuring data integrity and quality across enterprise data, managing data security and privacy issues etc.
Step 10: Build a go-to market strategy
Every milestone within the data strategy will cater to requests from multiple businesses, and as an enterprise function, the data strategy should include a detail plan to on-board each business requirement, depending on the business urgency and priority.
Individual businesses within the organization are the future sponsors of the implementation of the data strategy. Hence, it is necessary to constantly communicate the plan among all business stakeholders and build awareness and curiosity.