Building an Analytics Foundation that provides Business Value and Data Integrity
By Kim Burky, V3iT Business Transformation
December 18, 2018
Analytical insights are critical to business operations and strategy. However, there are several recent surveys that reveal that many decision makers don’t have confidence in the information they are receiving. Today’s business intelligence market offers a plethora of analytics tools both on-premise and in the cloud that extend capabilities to provide both traditional and self-service analytics. In addition, digital tools offer the enticing prospect of being able to chug through volumes of data to find the proverbial “needle in a haystack” and determine patterns for powerful predictive and prescriptive capabilities. There are increasing data business roles evolving in many organizations such as data officers and data scientists. These offer great possibilities for data advancements but, if an organization doesn’t have a solid data management strategy and a workforce that is ready for these changes, it all becomes “lipstick on a pig”-colorful visualizations, dashboards and reports that could provide irrelevant or inaccurate data or sometimes both.
It can be overwhelming to figure out where to begin but it is often helpful to start with Covey’s quote “Begin with the end in mind”. The Holy Grail of any implementation is to achieve alignment between business and technical strategy and resources, so the first step of the data journey is to pull those resources together and collaboratively create an organizational data vision that embraces diverse perspectives. When you determine the ultimate destination that is best for your unique organizational data requirements, the strategy becomes the roadmap that gets you there (with everyone in the same vehicle). Your data vision strategy should include the following:
- The North Star: A mission statement of the organization and what types of insights are most critical to achieving that mission. This is helpful in creating alignment across business entities on priorities. This is also helpful in determining where there should be common analytics assets where data is validated and properly secured that leads the organization to a shared view.
- Types of Data: There should be a high-level definition of the types of data in the organization that includes definitions for sensitive data and the granularity at which it must be protected, as well as transparent data (often defined by law/policy in industries such as public sector). It should strive to identify and define all relevant data, regardless of the source.
- Types of Users: What are your user personas? What data do they need? How do they interact with it? How data savvy are they? What frequency do they need it? What do they consider relevant?
- Governance: How will your organization be structured and what processes will be in place to resolve conflicts arising from data usage, ensure data security, relevance and accuracy, and appropriate access?
- Workforce Readiness: What is the communication, change management strategy and processes to ensure that users are properly trained and collaboratively included?
- Integration: Focusing on the end destination and the desired information outcomes to provide information with proper harmonization and defined and validated data sources with minimal redundancy.
About Us
V3iT’s mission is to deliver IT Services with a quick Value, clear Vision and at a high Velocity. We leverage our technology talent, experience and portfolio of tools with the use of design principles to achieve the sweet spot at the intersection of what is technically feasible, viable from a business perspective and desirable from a user perspective. This holistic approach creates your data journey roadmap with a focus on the desired informational outcomes and a platform that is constructed in a sustainable, scalable fashion. The end goal is to ensure that what you get out of your analytics provides meaningful, accurate insights across your enterprise.
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