Skills and data foundations for analytics

1 · Core competencies

Strategic workstreams

What an analytics team knows how to do.

The core methods for turning data into answers.

Business analytics: Using data and statistical analysis to make decisions, solve problems and optimise operations.
Product analytics: Understanding how users interact with a product, to improve performance and experience.
Finance analytics: Analysing financial data to understand performance, forecast and support financial decisions.
Predictive analytics: Using historical data and statistical algorithms to predict future outcomes and trends.
Business intelligence: Turning raw data into actionable insight with the right tools.
Forecasting: Estimating future trends or outcomes from historical data.
A/B & hypothesis testing: Comparing two versions to see which performs better, and drawing inferences from data.

Choosing what to do, and checking it works.

Planning: Setting objectives and strategies for specific goals, informed by data.
Strategy: Developing plans and tactics for long-term goals, grounded in data and analysis.
Market research: Gathering information on markets, customers and competitors to inform strategy.
Continuous improvement: Making ongoing improvements to processes, products and services.

Getting the insight understood and acted on.

Visualisation: Graphical representations of data that make it easier to understand.
Reporting: Summarising and presenting data in a structured form for decision-makers.
Presentation: Conveying data and information to an audience, with visuals and clear speaking.
Storytelling: Using data to tell a compelling narrative that is relatable and easy to follow.

Making it repeatable, on time and tied to the P&L.

Automation: Using technology to run tasks and data processing without manual effort.
Documentation: Keeping records, reports and manuals on data, processes and procedures.
Program management: Overseeing related projects so they meet strategic objectives.
Project management: Planning, executing and monitoring projects against goals, deadlines and budgets.
P&L management: Monitoring and optimising a company's financial performance.

2 · Effectiveness skills

The habits that turn analysis into action.

How an analyst approaches a problem.

Analytical mindset: Approaching problems logically, breaking them into smaller parts.
Attention to detail: Being thorough, so nothing important is missed.
Problem-solving: Finding solutions to complex issues with critical thinking and creativity.
Strategic thinking: Weighing long-term goals while making decisions and plans.
Critical thinking: Judging information and arguments objectively, on the evidence.
Business acumen: Understanding how a business works: financial, operational and market.
Risk assessment: Spotting risks and judging their likelihood and impact.

How insight turns into shared action.

Effective communication: Conveying ideas clearly and persuasively, in speech and in writing.
Stakeholder management: Engaging the people with a stake in a project and keeping the relationship positive.
Collaboration & teamwork: Working well with others towards common goals.
Emotional intelligence: Recognising and managing your own emotions and others', for better relationships.
Ethical conduct: Working with integrity and honesty, by professional principles.

What keeps an analyst effective over time.

Results-driven: Focusing on specific goals and tangible outcomes.
Time management: Using time well to complete tasks and meet deadlines.
Entrepreneurial mindset: Thinking creatively, taking initiative and staying open to new opportunities.
Continuous learning: Committing to new knowledge and skills throughout a career.
Agility & adaptability: Adjusting quickly to change and embracing new ways of working.

3 · Data foundations

Without these, every dashboard is a guess.

Data management: Collecting, storing, organising and maintaining data so it stays accurate and accessible.
Data modelling: A structured representation of data that supports database design and analysis.
Data governance: Managing data policies, standards and practices to ensure quality, security and compliance.
Metadata management: Maintaining data about data, so information can be found and managed.
Data instrumentation: Capturing data from sources and sensors for analysis and monitoring.
Data policies & standards: The rules for how data is used, stored and secured in an organisation.
Process excellence: Improving and optimising business processes for efficiency, guided by data.

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