Welcome to your As-Is Data Capability Maturity Self Assessment.

🢂 This assessment evaluates your organisation’s Data Capability Maturity across five critical areas. Each area contains five multiple-choice questions, totaling 25 questions.

🢂 Detailed criteria and results interpretation will be provided at the end of the assessment.

🢂 Upon completion, you’ll instantly receive free customised feedback and strategy.

🢂 Invest 10 minutes in this assessment, gain years of data capability wisdom.

Please select your industry. This will help us provide benchmark data for your industry-specific Data Capability Maturity Levels.

Section 1 : Data Strategy & Governance

1.1 How well-defined is your organisation's data strategy?

We have no formal data strategy

We have a basic data strategy, but it's not widely communicated or followed

We have a documented data strategy that is partially implemented

We have a comprehensive data strategy that is well-communicated and mostly followed

Our data strategy is fully integrated with our business strategy and drives decision-making at all levels

Section 1 : Data Strategy & Governance

1.2 How mature is your data governance framework?

We have no formal data governance

We have some ad-hoc data governance practices

We have a defined data governance framework, but implementation is inconsistent

We have a well-established data governance framework that is mostly followed

Our data governance is fully integrated into our operations and continuously improved

Section 1 : Data Strategy & Governance

1.3 How well does your organisation manage data ownership and stewardship?

Data ownership is unclear and not formally assigned

Some data owners are identified, but responsibilities are not clear

We have assigned data owners for critical data assets, with partially defined responsibilities

We have a comprehensive data ownership model with clear responsibilities

Data ownership and stewardship are fully embedded in our culture and operations

Section 1 : Data Strategy & Governance

1.4 How effective is your data policy management?

We have no formal data policies

We have some basic data policies, but they're not well-communicated or enforced

We have documented data policies that are partially implemented

We have comprehensive data policies that are well-communicated and mostly followed

Our data policies are fully integrated, regularly updated, and drive decision-making

Section 1 : Data Strategy & Governance

1.5 How well does your organisation manage data ethics and compliance?

We have no formal approach to data ethics or compliance

We address data ethics and compliance reactively

We have basic data ethics and compliance guidelines in place

We have a comprehensive data ethics and compliance program

Data ethics and compliance are fully integrated into our data strategy and operations

Section 2 : Data Architecture & Infrastructure

2.1 How mature is your data architecture?

We have no formal data architecture

We have a basic data architecture, but it's not well-documented or followed

We have a documented data architecture that is partially implemented

We have a comprehensive data architecture that is well-communicated and mostly followed

Our data architecture is fully integrated, scalable, and adapts to changing business needs

Section 2 : Data Architecture & Infrastructure

2.2 How well does your organisation manage data integration?

Data integration is ad-hoc and manual

We have some automated data integration processes, but they're limited in scope

We have a defined data integration framework with partial automation

We have a well-established, mostly automated data integration process

Our data integration is fully automated, real-time, and seamlessly connects all data sources

Section 2 : Data Architecture & Infrastructure

2.3 How advanced is your data storage and processing infrastructure?

We primarily use local storage and manual processing

We have some centralised data storage, but processing is mostly manual

We use a mix of on-premise and cloud storage with partially automated processing

We have a modern, mostly cloud-based infrastructure with automated processing

We have a state-of-the-art, fully scalable infrastructure with advanced processing capabilities

Section 2 : Data Architecture & Infrastructure

2.4 How well does your organisation handle data security and privacy?

We have minimal data security measures in place

We have basic data security and privacy practices, but they're not consistently applied

We have defined data security and privacy protocols that are partially implemented

We have comprehensive data security and privacy measures that are mostly followed

Our data security and privacy practices are state-of-the-art, fully integrated, and continuously improved

Section 2 : Data Architecture & Infrastructure

2.5 How mature is your metadata management?

We do not actively manage metadata

We have some basic metadata documentation, but it's inconsistent

We have a defined metadata management process that is partially implemented

We have a comprehensive metadata management system that is mostly utilised

Our metadata management is fully integrated, automated, and drives data discovery and utilisation

Section 3 : Data Quality & Management

3.1 How mature is your data quality management process?

We have no formal data quality management

We address data quality issues reactively

We have basic data quality checks in place for critical data

We have a comprehensive data quality framework that is mostly implemented

Our data quality management is proactive, automated, and continuously improved

Section 3 : Data Quality & Management

3.2 How well does your organisation manage the data lifecycle?

We have no formal data lifecycle management

We manage data lifecycle stages inconsistently

We have defined data lifecycle processes for critical data

We have a comprehensive data lifecycle management process that is mostly followed

Our data lifecycle management is fully integrated, automated, and optimised

Section 3 : Data Quality & Management

3.3 How advanced is your master data management?

We have no formal master data management

We have basic master data management for some domains

We have defined master data management processes for critical domains

We have a comprehensive master data management system that is mostly implemented

Our master data management is fully integrated, cross-functional, and drives business value

Section 3 : Data Quality & Management

3.4 How well does your organisation handle data cataloging and discovery?

We have no formal data cataloging process

We have basic data cataloging for some datasets

We have a defined data cataloging process that is partially implemented

We have a comprehensive data catalog that is mostly utilised

Our data cataloging and discovery processes are fully automated, comprehensive, and drive data utilisation

Section 3 : Data Quality & Management

3.5 How mature is your data cleansing and enrichment process?

We perform data cleansing ad-hoc, if at all

We have basic data cleansing processes for some critical data

We have defined data cleansing and enrichment processes that are partially automated

We have comprehensive, mostly automated data cleansing and enrichment processes

Our data cleansing and enrichment is fully automated, proactive, and continuously improved

Section 4 : Analytics & Insights

4.1 How advanced is your organisation's data analytics capability?

We primarily use basic reporting and spreadsheets

We use some business intelligence tools for descriptive analytics

We have capabilities for both descriptive and diagnostic analytics

We regularly perform predictive analytics in addition to descriptive and diagnostic

We have advanced prescriptive and cognitive analytics capabilities

Section 4 : Analytics & Insights

4.2 How well does your organisation leverage data for decision-making?

Decision-making is primarily based on intuition and experience

We use data to support some operational decisions

We regularly use data for operational and some strategic decisions

Data-driven decision-making is common across most of the organisation

We have a fully developed data-driven culture where all significant decisions are informed by analytics

Section 4 : Analytics & Insights

4.3 How mature is your self-service analytics capability?

We have no self-service analytics capabilities

We have limited self-service reporting for basic metrics

We have self-service capabilities for standard reports and some ad-hoc analysis

We have comprehensive self-service analytics tools available to most users

We have advanced, user-friendly self-service analytics integrated into all business processes

Section 4 : Analytics & Insights

4.4 How well does your organisation manage data visualisation?

We primarily use basic charts and tables in spreadsheets

We use some standalone data visualisation tools

We have standard dashboards and visualisation templates for key metrics

We have interactive, real-time dashboards used across the organisation

We leverage advanced, AI-driven data visualisation techniques for complex data storytelling

Section 4 : Analytics & Insights

4.5 How advanced is your organisation's use of artificial intelligence and machine learning?

We do not currently use AI or ML

We are experimenting with basic ML models in isolated use cases

We have implemented ML models for specific business problems

We regularly use AI and ML across multiple business functions

AI and ML are fully integrated into our operations and continuously driving innovation

Section 5 : Data Culture & Literacy

5.1 How would you describe your organisation's overall data culture?

Data is not considered a key asset in our organisation

Some departments recognise the value of data, but it's not organisation-wide

Data is generally recognised as valuable, but not consistently utilised

We have a strong data culture in most parts of the organisation

We have a pervasive data culture where data is considered a critical strategic asset

Section 5 : Data Culture & Literacy

5.2 How mature is your data literacy program?

We have no formal data literacy program

We offer some ad-hoc data training

We have a basic data literacy program for select roles

We have a comprehensive data literacy program available to most employees

Data literacy is fully integrated into our learning and development programs at all levels

Section 5 : Data Culture & Literacy

5.3 How well does your organisation promote data sharing and collaboration?

Data sharing is minimal and siloed

Some departments share data, but it's not organisation-wide

We have defined data sharing processes, but adoption is inconsistent

Data sharing and collaboration are common across most of the organisation

We have a fully developed data sharing culture with advanced collaboration tools

Section 5 : Data Culture & Literacy

5.4 How effective is your change management for data initiatives?

We have no formal change management for data initiatives

We use basic change management techniques reactively

We have a defined change management process for major data initiatives

We have a comprehensive change management approach for all significant data changes

Change management is fully integrated into our data strategy and continuously improved

Section 5 : Data Culture & Literacy

5.5 How well does your organisation measure and communicate the value of data?

We do not measure or communicate the value of data

We have some anecdotal evidence of data value, but it's not systematically tracked

We measure the value of data for some key initiatives

We regularly measure and communicate the value of data across the organisation

Measuring and communicating data value is fully integrated into our performance management

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Welcome to your As-Is Data Capability Maturity Self Assessment.

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