Framework for Creating an Enterprise Data and Analytics Roadmap:
Because of an apparent conflict, many data strategy teams struggle to create an enterprise data and analytics plan: If they concentrate solely on near-term data requirements without taking into account the larger company requirements – both known and unknown – the data will be deployed in a way that exacerbates proliferation, inconsistency, and incoherence However, if they opt to deploy data as an enterprise "base" – separate from specific business goals - data delivery efforts will inflate in scale, with no clear mechanism to evaluate which data items are required other than a vague feeling of "importance."
However, this conundrum stems from a false choice between two extremes; there is a healthy middle ground. It is possible to address the needs of business activities while also contributing to a coherent data foundation with the proper methodology.
It can be difficult to create a roadmap for a large, complex company. Breaking down the process into its constituent parts makes it easier to manage the complexity, avoid frequent mistakes, and steer the data and analytics programme in the proper direction. Any data and analytics team, including business and IT members, can use the methodology below to establish an effective roadmap, either from scratch or to re-examine and re-work an existing one.
Frameworks:
- Driver: The reason and explanation for the rest of the roadmap is provided by the drivers. They also put in place an important scoping mechanism. Every data piece deployed, every data quality issue resolved, and every data governance policy implemented should have a clear link to a business driver in scope.
- nitiatives and Use Cases in Business: While introducing new initiatives based on business value is a good idea, the most important step here is to simply identify the enterprise's already planned and funded business initiatives. Data and analytics are required for almost every major company endeavour to succeed. As a result, because every action on the roadmap underlies the company's most important activities, this initial move sets the roadmap to be strategic. To narrow the focus even more, the team identifies use cases within these initiatives, which could include planned delivery of packaged or custom applications with an embedded analytical component, or analytic use cases that will make use of standard reporting and analytic tools ranging from basic to advanced.
- The Company's Goals: The team searches for themes and directions that impact various projects in addition to documenting the objectives of the in-scope business efforts and use cases. Some of these instructions may be related to business, such as a lean management style or a "going green" campaign. Others, such as a cloud migration or an overarching digitalization strategy, may be more technical in nature.
- Prioritization of business use cases: The team then determines which use cases to include on the roadmap by prioritising them based on a combination of business priority and organisational preparedness.
Influencers:
Influencers assist the drivers by identifying information, architecture, and capability gaps that must be addressed to meet the requirements of the in-scope business activities and use cases.
- Prioritization of data: While identifying information requirements to support business efforts and use cases, the team will discover that some of the data is required by numerous business initiatives and use cases within them. As a result, the team prioritises and plans the distribution of that data so that it can be shared while also providing direct value in support of critical business goals.
- Architecture as it stands now: No large company can afford to start from scratch when it comes to data strategy. The team learns about the status of technology, data, and other elements that affect the design in this section. Rather than studying every aspect, the team collects coarse-grained data from across the ecosystem while conducting more fine-grained analysis in areas that would have a direct impact on the in-scope efforts.
- Assessment on Capability: Data governance, analytic skills, organisational processes, training, and other technical and non-technical capabilities are all required to properly deploy shared, enterprise data. The goal, like with all other components of the roadmap, is to plan only what is required at the time it is required, while constantly increasing shared capabilities with each action.
Decisions:
Decisions are taken to define the future vision and design a practical plan to get there.
- Roadmap for Data and Analytics: The final roadmap is divided into "swim lanes" that specify the intended business initiatives, information to be delivered, applications and analytic use cases to be enabled, system-level infrastructure services to be provisioned, and enabling capabilities to support the other swim lanes.
- The Architecture of the Future State: The team creates a vision for the future state data and analytics architecture after making judgments. The vision should spell out how the architecture will support the selected initiatives and use cases while also being scalable enough to meet the needs of future initiatives and use cases in the most cost-effective way possible.
- Alternatives for Implementation: There will be options to consider at many levels while imagining a future state. First, there are broad picture judgments to make, such as the degree of independence and interdependence across business domains, which leads to decisions on the level of integration needed. Then there are decisions to be made about how the ecosystem's components will interact and interact with one another. Finally, there are product-level options, which are geared on providing near-term, in-scope business requirements.
Conclusion:
The roadmap is comprehensive in that it covers all actions necessary to support focused business initiatives with data and analytics, but it is not meant to cover all data deployment for the firm. Some efforts may be better suited to a single business domain, or it may simply be unrealistic to include all significant business activities in the roadmap, particularly early in the process of building an enterprise strategy. Furthermore, some businesses may require numerous roadmaps, especially if shared and integrated data across unit boundaries is only marginally beneficial.
While each company's plan will differ in substance, any company can get started right now. In concept, it's straightforward: identify the company's most critical business objectives and demonstrate how they'll be backed up by the data and skills they'll need to succeed. You may really begin creating your own plan right now.
No Comments