Most organizations are in the process of building a data-driven culture that allows them to analyze or experiment with any volume, variety, or velocity of data and derive valuable insights from it. The key to achieving this is with a data strategy map, a visual representation of an enterprise’s data strategy that illustrates the variety of data channels throughout the company. With this in place, organizations can ensure their data strategy aligns with their business needs and make fact-based decisions on how to achieve the next wave of profitability.
A well-constructed data strategy map is similar to a city’s metro map. Just as a metro map is essential for understanding transportation routes across a city for future development, a data strategy map would enable an enterprise to better understand its data workflows.
A Wipro Data Strategy Map offers a unified approach to assessing the current data estate and its maturity by combining a defensive and an offensive strategy (explained below). It ensures the integrated flow of data, as well as its uniformity, security, and enrichment, to deliver quick business benefits. Each strategy is focused on achieving specific goals: Democratize, Secure, Standardize, Monetize, Innovate, and Optimize.
A Data Strategy Map shows the pathways and elements covered by the two defensive and offensive data strategies, which help organizations identify their current data maturity and create a robust data strategy for developing further advancements. The map contains stations, which are the set of defined capabilities required along the pathway, and intersections, which depict the common capabilities required across the various lines.
A defensive data strategy focuses on minimizing downside risk, ensuring compliance, leveraging analytics to detect and limit fraud, and building systems to enable control and prevent theft. It’s developed to achieve the following beneficial tasks:
- Standardize: The standardization efforts take the form of a cyclical process and are the heart of all the other improvements to data operations. The focus is on the overall management of the availability, usability, integrity, and quality of the data employed. The KPIs measured here include data quality improvements, data policy operationalization, and critical data elements coverage.
- Optimize: The objective here is to simplify authorized users’ data access by consolidating data and eliminating redundancies to reduce the data costs per stored and processed terabytes. This optimization enables the flexibility to explore new data-driven business opportunities, and the KPIs include the speed to onboard, data insights and storage costs, and data duplication.
- Secure: Here the focus is on the security of hybrid or on-premises/cloud data assets across access points. This enables compliance with the legal obligations on data assets, including geographical restrictions and the identification of data temperature and user behavior across data assets. The KPIs include critical data incidents, General Data Protection Regulation (GDPR) risk scores, and the costs of security incidents.
An offensive data strategy is focused on driving innovation and change, conducting quick experiments, and supporting business objectives, such as increasing revenue, profitability, and customer satisfaction. This strategy gives enterprises the ability to achieve the following tasks:
- Democratize: Enterprises can evangelize the use of data domains within their organizations to generate analytical experiments and data consumption. This helps develop a data-driven culture by increasing data literacy and unleashing multiple citizen data scientists within the organization. The KPIs include the indexing and cataloging of CDEs, data literacy, information product revenue, and API traffic growth.
- Innovate: This strategic component enables an organization to understand its next-gen needs, allowing it to discover out-of-the box business opportunities and take advantage of them through data initiatives. The KPIs include data enrichment, the digitalization of assets, service automation, and crowdsourcing impact.
- Monetize: By developing business models that commercialize data, businesses can develop information products within their organization through a robust API strategy. The KPIs include data pricing and billing accuracy, product enhancement, information product revenue, and API traffic growth.
Each of the lines in the Data Strategy Map has a set of questionnaires and artifacts related to them, which helps in assessing the maturity of those lines. This provides an indication of the data strategy’s current state and is pivotal for making it more robust in the future.
The individual lines also need to be monitored through each set of defined KPIs, including input, process, and output KPIs. Dashboards and videos also demonstrate the key initiatives and their results.
Included in our Data Strategy Map offering, the Wipro Command Center periodically records the overall progress of the data strategy in achieving the key functions, such as customer satisfaction, increased revenue, reduced risk exposure, and employee efficiency. With this information on the strategy’s progress, Chief Operations Officers can track the growth of their multiple data and analytics initiatives and share it with the larger organization. Data Strategy Maps also provide enterprises with a comprehensive view of their data estates and their impact on the business.
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