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A model of analytical maturity measures your organization's level of maturity in analyzing and leveraging its data. The higher your organization's maturity level, the greater its ability to use data to drive business outcomes.
In a scenario where two organizations have the same data, the more mature organization will make better pricing decisions, improve marketing performance, increase forecast accuracy, among other benefits.
Alteryx proposes these five levels (also called stages) of analytical maturity:
Analytical Novice
Localized Analysis
Analytical Aspirations
Analytical Enterprises
TOP ANALYTICS COMPANY
Stage 1: Analytical Novice
If your organization is at stage 1, you're at the beginning of your analytical journey. You lack the necessary data to answer questions, or if you have them, you can't easily use them yet, and the data quality is poor. Despite the lack of analytical maturity, you have a fantastic opportunity to establish best practices from the start.
In stage 1, the data is:
Isolated or cannot be queried.
Inaccessible or requires permissions.
Disorganized and incorrectly labeled.
Unprepared for analysis by anyone.
In stage 1, analytics are:
Isolated by departments.
Shared only during meetings.
Never used to make decisions.
Descriptive and mainly used for ad-hoc reporting.
Stage 2: Localized Analysis
In this stage, your organization uses analysis for general business intelligence, such as dashboards and visualizations for reporting. Data sets are available but trapped in silos or limited to departmental access. You may have predictive analysis capabilities, but most data analysis occurs in spreadsheets.
In stage 2, the data is:
In functional or process silos.
Managed by department or require permission to access.
Both organized and disorganized.
Both unprepared and prepared for use by data analysts.
In stage 2, analytics are:
Isolated by departments.
Shared as needed.
Rarely used to make decisions.
Mainly descriptive and used for ad-hoc reporting.
Stage 3: Analytical Aspirations
In stage 3, your organization is making appropriate changes to use data but needs to align data analytics across all departments. Initiatives are underway to centralize data sources, workflows, and assets, but adoption and daily usage must progress.
In stage 3, the data is:
Becoming centralized and organized.
In the process of being governed and assigned access permission levels.
Becoming organized and discoverable.
Mostly prepared and ready for analysis by most people.
In stage 3, analytics are:
Becoming centralized.
Becoming shareable and self-service.
Partially used to drive decision-making.
Expanding beyond descriptive to predictive.
Stage 4: Analytical Enterprises
If your organization is at stage 4, you have the data and tools to make decisions. Your organization is implementing solutions that everyone can use and benefit from, including automation. However, you may need to take additional steps to achieve adoption and full usage across the organization.
In stage 4, the data is:
Centralized, organized, and enhanced with third-party data sets.
Governed with established access controls.
Discoverable by anyone with permissions to use them.
Prepared and ready for analysis by anyone.
In stage 4, analytics are:
Centralized and accessible.
Shareable and self-service.
Mainly used to make decisions.
Increasingly driven by machine learning and artificial intelligence.
Stage 5: TOP ANALYTICS COMPANY
If you're at stage 5, congratulations! Organizations at this stage successfully use analytics throughout the organization and implement best practices for data management and governance. Analytics serves as a competitive differentiator for you and guides your business strategy.
In stage 5, the data is:
Centralized, organized, and enhanced with third-party sources.
Governed with established access controls.
Discoverable by anyone with permissions to use them.
Prepared and used for analysis by everyone.
In stage 5, analytics are:
Centralized and accessible.
Shareable and transparent.
Used to drive all decisions.
Data science, machine learning, and artificial intelligence are widely used.
Regardless of the phase you're in, at Keyrus, we guide you throughout the data journey, helping you overcome the different challenges you'll encounter at different maturity stages.