What is business analytics and why do employers need it?

Data is growing faster than most organisations can handle. Every interaction, transaction, and process generates information. The challenge is not collecting data. It is knowing what to do with it.

This is where business analytics comes in. Organisations that can turn data into clear, timely decisions move faster, reduce risk, and spot opportunities earlier. Those that cannot often fall behind.

In many sectors, data is now treated as a core business asset. Companies invest heavily in systems that capture and store information, but without the ability to interpret it, that investment delivers limited value. Business analytics bridges that gap by turning data into direction.

This guide explains what business analytics is, why employers value it, and how you can build the skills to use it in your own career. 

What is business analytics?

Business analytics is the process of turning raw data into insights that inform decisions. It combines data analysis, technology, and business understanding to answer real-world questions.

At its core, business analytics helps organisations move from instinct-led decisions to evidence-based ones. Rather than relying on assumptions or past habits, teams can use data to guide their actions with greater confidence.

Typical questions business analytics can answer include:

• Which products are performing best, and why?

• Where are we losing customers in the journey?

• What will demand look like next quarter?

• How can we improve efficiency without increasing costs?

Business analytics is often confused with related terms, so it helps to clarify the differences.

Key distinctions:

• Business intelligence focuses on reporting past performance through dashboards and summaries.

• Data analytics is a broader term that covers analysing data across many contexts, not always tied to business decisions.

• Business analytics sits between the two. It focuses on using data specifically to guide business strategy and operations.

Another way to think about it is in terms of action. Business intelligence tells you what has happened. Data analytics explores patterns in data. Business analytics goes a step further by connecting those insights directly to decisions and outcomes.

In practice, business analytics is not just about numbers. It is about translating data into actions that make a measurable difference. This might mean improving a process, refining a strategy, or identifying a new opportunity for growth.

The main types of business analytics

Business analytics can be broken into four main types. Each builds on the last, moving from understanding the past to shaping the future.

Together, these approaches form a progression. Organisations typically start with descriptive insights and gradually develop more advanced capabilities such as predictive and prescriptive analytics.

Descriptive analytics: What happened

Descriptive analytics looks at historical data to understand what has already occurred.

Examples include:

• Monthly sales reports.

• Website traffic summaries.

• Customer churn rates.

Key benefits:

• Provides a clear picture of performance.

• Helps identify patterns and trends.

• Forms the foundation for deeper analysis.

Descriptive analytics is often the starting point for organisations. It creates visibility and ensures that teams are working from a shared understanding of performance. Without this foundation, it is difficult to move into more advanced forms of analysis.

Diagnostic analytics: Why it happened

Diagnostic analytics digs deeper to explain the reasons behind outcomes.

Examples include:

• Identifying why sales dropped in a specific region.

• Analysing customer feedback to understand dissatisfaction.

• Exploring operational bottlenecks.

Key benefits:

• Identifies root causes rather than symptoms.

• Supports more targeted problem-solving.

• Helps teams avoid repeating mistakes.

This stage often involves comparing datasets, identifying correlations, and asking more detailed questions. It requires both analytical skill and business understanding to interpret findings correctly.

Predictive analytics: What is likely to happen

Predictive analytics uses historical data and statistical models to forecast future outcomes.

Examples include:

• Sales forecasting.

• Predicting customer churn.

• Demand planning.

Key benefits:

• Enables proactive decision-making.

• Improves planning and resource allocation.

• Reduces uncertainty.

Predictive analytics allows organisations to move from reactive to proactive. Instead of responding to events after they occur, businesses can prepare in advance and allocate resources more effectively.

Prescriptive analytics: What to do about it

Prescriptive analytics recommends actions based on data insights.

Examples include:

• Optimising pricing strategies.

• Recommending marketing actions.

• Suggesting supply chain adjustments.

Key benefits:

• Supports decision-making with clear recommendations.

• Improves efficiency and outcomes.

• Bridges the gap between insight and action.

This is the most advanced stage of business analytics. It often involves optimisation models or decision frameworks that suggest specific actions. When used effectively, prescriptive analytics can significantly improve business performance.

Why employers need business analytics

Business analytics is no longer a niche function. It is central to how modern organisations operate.

Employers rely on analytics to make faster, more confident decisions. In competitive markets, the ability to act quickly on reliable information can be the difference between growth and stagnation.

Faster, more confident decision-making

• Reduces reliance on guesswork.

• Provides evidence to support strategic choices.

• Enables quicker responses to changing conditions.

Data-backed decisions are easier to justify and communicate. This is particularly important in senior roles, where decisions can have significant financial or operational impact.

Identifying growth opportunities and cutting costs

• Highlights underperforming areas.

• Reveals untapped markets or customer segments.

• Improves operational efficiency.

Analytics can uncover opportunities that are not immediately visible. For example, customer data may reveal a new segment with strong growth potential or highlight inefficiencies in a supply chain.

Managing risk and forecasting trends

• Anticipates potential disruptions.

• Supports financial planning and budgeting.

• Improves resilience in uncertain environments.

Organisations use analytics to prepare for uncertainty. This might include forecasting demand fluctuations, identifying financial risks, or modelling different scenarios.

Improving customer experience and retention

• Analyses behaviour and preferences.

• Personalises products and services.

• Identifies pain points in the customer journey.

Customer expectations continue to rise. Analytics helps organisations understand those expectations and respond with more tailored experiences.

Competitive advantage

• Enables organisations to act on insights faster than competitors.

• Supports innovation through data-backed experimentation.

• Strengthens long-term strategic positioning.

For example, a retailer using predictive analytics can forecast demand more accurately, reduce excess stock, and improve customer satisfaction by ensuring popular products are available.

As more organisations adopt analytics, it is becoming a baseline expectation rather than a differentiator. Those that fail to invest risk falling behind.

Why employers need people with business analytics skills

The demand for data skills is growing rapidly, but supply is struggling to keep up. The UK Government’s 2021 report ‘Quantifying the UK Data Skills Gap’ found that 46% of business have struggled to recruit for roles requiring hard data skills and that the supply of graduates with specialist data skills is limited. 

This creates a clear opportunity for professionals who can combine business understanding with analytical thinking.

Common roles that use business analytics skills:

• Business analyst.

• Data analyst.

• Business intelligence analyst.

• Operations analyst.

• Marketing analyst.

These roles exist across industries, including healthcare, finance, retail, and the public sector.

The value of business analytics skills is also highly transferable.

Functions that benefit include:

• Marketing, through customer insights and campaign optimisation.

• Finance, through forecasting and performance analysis.

• HR, through workforce planning and retention analysis.

• Operations, through efficiency and process improvement.

This means you do not need to move into a technical role to use these skills. You can apply them within your existing field to increase your impact.

Another important factor is decision influence. Professionals with analytics skills are often more involved in strategic discussions because they can provide evidence to support recommendations. This can lead to greater responsibility and career progression.

Key skills great business analysts possess 

Strong business analysts combine technical capability with business awareness and communication skills.

Employers increasingly look for well-rounded candidates who can move between data analysis and strategic thinking.

Technical skills

These skills allow you to work with data and extract insights.

Key skills include:

• Data interpretation and analysis.

• Basic statistics and modelling.

• Using tools such as Excel, SQL, and data visualisation platforms.

• Building dashboards and reports.

Technical skills provide the foundation for working with data. They enable you to collect, clean, analyse, and present information in a structured way.

Soft skills

These are often what set top candidates apart.

Key skills include:

• Critical thinking and problem-solving.

• Clear communication of complex ideas.

• Stakeholder management.

• Commercial awareness.

Soft skills are essential for ensuring that insights lead to action. Being able to explain findings clearly and align stakeholders is a key part of the role.

Why the combination matters

Employers value people who can not only analyse data but also explain what it means and what should happen next.

A technically strong analyst who cannot communicate insights has limited impact. Equally, someone with strong business knowledge but no analytical skills may struggle to support decisions effectively.

The most valuable professionals sit at the intersection of both. They understand the data, the business context, and the practical implications of their recommendations.

How to build business analytics skills

There are multiple ways to develop business analytics skills, depending on your starting point and career goals.

A combination of structured learning and practical experience is often the most effective approach.

Formal study

Structured learning provides a comprehensive foundation.

Options include:

• Postgraduate degrees such as an MBA with Business Analytics.

• Short courses focused on specific tools or techniques.

• Professional certifications.

Benefits of formal study:

• Builds both technical and strategic understanding.

• Provides recognised credentials.

• Offers structured progression and support.

Formal education can also help you build confidence. It provides a clear pathway through complex topics and ensures that you develop a well-rounded skill set.

If you are balancing work and study, flexible learning can make a significant difference. 

On-the-job experience

Practical experience is essential for applying what you learn.

Ways to gain exposure:

• Take on data-related tasks within your current role.

• Support reporting or analysis projects.

• Work with colleagues in analytics teams.

Applying your skills in real scenarios helps reinforce learning and demonstrates your value to employers.

Self-directed learning

You can also build skills independently.

Approaches include:

• Learning tools such as Excel or Power BI.

• Practising with real datasets.

• Following industry resources and case studies.

Self-directed learning allows you to progress at your own pace and focus on areas that are most relevant to your goals.

Why an online MBA can give you an advantage

An online MBA with Business Analytics combines technical skills with broader business understanding.

This combination is particularly valuable for professionals looking to progress or change direction. It allows you to develop both analytical capability and strategic thinking in a single programme.

Key advantages:

• Flexible study that fits around your job and commitments.

• Immediate application of learning in your current role.

• Development of leadership and strategic thinking alongside analytics.

Online learning also enables you to continue earning while you study. This can make it a more accessible option for professionals with existing responsibilities. 

Plus, an MBA can support career progression. For those aiming to move into roles where data informs strategy, this type of qualification provides both credibility and capability.

FAQs

What is the difference between business analytics and data analytics?

Business analytics focuses specifically on using data to inform business decisions. Data analytics is a broader field that includes analysing data in any context, not always linked to business strategy.

Do you need a degree to work in business analytics?

Not always, but a degree can significantly improve your prospects. Many roles require evidence of both analytical skills and business understanding, which formal study can provide.

What industries use business analytics?

Almost all industries use business analytics, including:

• Healthcare.

• Finance.

• Retail.

• Manufacturing.

• Public sector organisations.

As data becomes more central to operations, the use of analytics continues to expand across sectors.

Is business analytics a good career path?

Yes. It offers strong demand, cross-industry opportunities, and clear progression. As organisations become more data-driven, these skills are becoming increasingly valuable.

It also offers flexibility, as the skills can be applied in many different roles and industries.

What tools do business analysts use?

Common tools include:

• Excel.

• SQL.

• Power BI or Tableau.

• Python or R for more advanced analysis.

The specific tools you use will depend on your role and organisation, but the underlying analytical skills remain consistent.

Take the first step towards a future-proofed career

Business analytics is a core capability for modern organisations. It enables better decisions, stronger performance, and a clear competitive edge.

For professionals, it offers a way to increase your influence, open new career paths, and stay relevant in a changing job market. As demand for these skills continues to grow, investing in them can provide long-term benefits.

Whether you are looking to progress in your current role or move into a new field, developing business analytics skills is a practical and future-focused step. Studying a flexible online MBA with Business Analytics with Queen Margaret University can help you build those skills while continuing to work.