FREE Data and Business Analytics Audit

Data Driven Business and data Analytics

Effective data and business analytics enables you to identify and utilise key business opportunities
for optimisation, growth, and diversification.

Data and Business Analytics Framework

By using data and analytics you create a direct impact on your business and benefit from higher revenue, cost reduction with opportunities for more robust business analytics, and automation.

What Is An Analytics Audit?

An analytics audit gives you the opportunity to know exactly where your business is positioned in relation to your analytics capabilities.

The business analytics self-evaluation audit is created specifically to help you evaluate your business analytics set-up, strategy, tools, and practices that you are currently implementing. It encompasses all the aspects of business analytics through three separate sections of perception, action, and optimisation.

By completing this audit you will have the information to determine the next steps your business needs to take to upgrade how your business considers its analytics

Benefits of This Audit

The analytics audit provides you with a deep understanding of the state of business analytics within your organisation.

By understanding your business needs, this audit serves as the foundation which underpins the perfect data and analytics solution that will help achieve your desired business outcome.

You will be able to find out the gaps or inefficiencies within your analytics strategy and processes.

Business analytics is a critical and crucial element for your business growth and it is important to get a sense of where you currently stand.

How Robust is Your Business Analytics Architecture?

Take this FREE Analytics Audit to get a sense of your current state of business analytics!

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Perception

1 = Beginner
2 = Intermediate
3 = Advanced
4 = Leader
BeginnerIntermediateAdvancedLeader

Business Knowledge and Data
  • Try to evaluate Business Intelligence (BI) needs.
  • Access to a few business data points.
  • Have specific needs and goals.
  • Access to current business data points on production, sales, and marketing.
  • Achieve objectives with business analytics.
  • Access to current and historic business data points.
  • Conduct need-based data reporting with business intelligence solutions.
  • Have an actionable database.
  • Continuously achieve objectives with business analytics.
  • Consolidate data from multiple sources, including customer data.
  • Processes in place to optimize data quality and enrich data.

BeginnerIntermediateAdvancedLeader
Business Performance
  • Attempt to evaluate business performance through data analytics.
  • Process in place to determine financial performance and employee performance metrics.
  • Ability to identify internal and external events impacting business performance.
  • Have an actionable database containing chronological performance metrics on all sectors.
  • Ability to attribute external and internal activities on target business outcomes.
  • Continuously improve performance through consolidated databases and BI solutions.
  • Forecast and manipulate external events for target business outcomes.
  • Ability to apply automated attribution models to different events and outcomes.

BeginnerIntermediateAdvancedLeader
Reporting
  • Access to basic data reporting skills and tools.
  • Understand key performance metrics.
  • Ability to need-based data reporting and custom metrics.
  • Business performance reporting mart available.
  • Conduct need-based data reporting with business intelligence solutions.
  • Automatically generate live reports and custom metrics without IT interventions.
  • Share reports with all the stakeholders, drill into different views for informed strategies.
  • Ability to forecast reporting on business activities and strategies.
  • Conduct need-based data reporting with business intelligence solutions.
  • Automatically generate live reports and custom metrics without IT interventions.
  • Share reports with all the stakeholders, drill into different views for informed strategies.
  • Ability to automatically forecast results of business initiatives and strategies.
  • Use predictive models to support reporting and strategies.

BeginnerIntermediateAdvancedLeader
Machine Learning
  • Generate basic reports to understand key success metrics.
  • Understand descriptive modeling for business analysis.
  • Bespoke processes to create data marts from data warehouse.
  • Dedicated data science workspace from analytical processing.
  • Ability to execute descriptive and predictive model processing.
  • Feature and analytical record data artefacts are centralised and shared.
  • Ability to automate analytical workflows for ongoing business analysis.
  • Machine learning models self-evaluate and automatically re-calibrate over time.
  • Ability to monitor and alert machine learning model performance.
  • Feature and analytical record data artefacts are continuously updated and re-computed.

BeginnerIntermediateAdvancedLeader
Optional Strategy
  • Analytics campaigns are need-based, reacting to incidents and events.
  • Business analytics is not a separate business unit.
  • Analytic efforts are considered as expenditure rather than investment.
  • Analytics campaigns are need-based, reacting to incidents and events.
  • Analytics is a separate business unit.
  • Budgetary consideration is non-existent.
  • Analytic efforts are considered as expenditure rather than investment.
  • Business analytics is goals-oriented and continuous.
  • Business analytics works independently as a separate business unit.
  • Have a clear understanding of the impact of data analytics on business performance.
  • Have a defined strategy for investment in business analytics.
  • Business analytics is growth-oriented, continuous, and proactive.
  • Business analytics works independently as a separate business unit.
  • Separate data team.
  • Have clear demonstrations of the impact of data analytics on business performance.
  • Have a defined strategy for investment in business analytics.

Action

1 = Beginner
2 = Intermediate
3 = Advanced
4 = Leader

BeginnerIntermediateAdvancedLeader
Data Collection
  • Data collected from manual inputs of a few sources.
  • Decentralized data silos and analytics.
  • Data collected from manual inputs from dedicated sources from each department.
  • Decentralized data silos and analytics.
  • Automated data mining and reporting in place from all the business units.
  • Centralized data warehouse and analytics platform.
  • Automated reporting and data mining in place to collect structured and unstructured data sets.
  • Centralized data warehouse and analytics platform with access to all stakeholders.

BeginnerIntermediateAdvancedLeader
Orchestration & Automation
  • Scheduled manual reporting from all business units.
  • Ability to execute need-based and targeted reporting in all business units.
  • Ability to create automated reports on business units and initiatives to garner insights.
  • Ability to execute need-based and targeted reporting across and integrating business units.
  • Execute analytics combining business units to monitor and inform all teams on performance.
  • Ability to create automated reports on business units and initiatives to garner insights.
  • Execute continuous targeted reporting across and integrating business units.
  • Automated performance monitoring of all business units and teams.
  • Chart performance improvement strategies and inform all teams.
  • Proactive growth strategies through ceaseless reporting on business units and initiatives.
  • Automation in place to share reports and notify stakeholders on issues and progress.

Optimisation

1 = Beginner
2 = Intermediate
3 = Advanced
4 = Leader

BeginnerIntermediateAdvancedLeader
Data Preparation & Integration
  • Data discovery tools and processes are reviewed on ad-hoc basis.
  • All the components, units, or subsystems (CMMS, CRM, social, supply chain, etc) are not integrated.
  • Data discovery, analytics, and visualisation tools and processes are reviewed regularly.
  • A few units or subsystems are integrated.
  • Ability to understand state of analytics and develop improvement strategies.
  • Constantly monitor, manage, and improve data discovery, analytics, and visualisation tools and processes.
  • All major units or subsystems are integrated.
  • Constantly monitor state of analytics and develop improvement strategies.
  • Optimisation efforts on data analytics compliment overall business optimisation.
  • Constantly monitor, manage, and improve data discovery, analytics, and visualisation tools and processes.
  • All units or subsystems are integrated and take part in decision-making.
  • State of analytics is up to date, most advanced tools and solutions are in place.
  • Processes in place to integrate analytical updates into business operations as they happen.

BeginnerIntermediateAdvancedLeader
Real-time Engagement
  • Real-time analysis with up-to-date data is not possible
  • Real-time analysis with up-to-date data is possible.
  • Automatic and real-time sharing with stakeholders not possible.
  • Significant delay between analytical results and operational implementation.
  • Constant real-time analysis with up-to-date data is in place.
  • Automatic and real-time notification systems in place for all stakeholders.
  • Industry-average delay between analytical results and operational implementation.
  • Constant real-time analysis with up-to-date data is in place.
  • Automatic and real-time notification systems in place for all stakeholders.
  • Lowest possible delay between analytical results and operational implementation.
  • Business analytics and operations go hand-in-hand.

BeginnerIntermediateAdvancedLeader
Business Optimisation
  • Data and analytics are used on an ad hoc basis to support business deals.
  • Business intelligence and basic analytics are in place to guide business optimisation.
  • Data and analytics are in place to fully optimise the business values but it's not embedded into the business operation.
  • It needs executive approval for the strategies suggested by the data and analytics.
  • Data and analytics are embedded as part of the business operation to optimise the business.
  • A complete loop between customers and business is created with the support of data and business analytics.
  • Business analytics and operations go hand-in-hand.

Self Evaluation

Please note any comments or concerns that you may have on your business, data and analytics.