Here is a list of the top 10 tips: 

1. Focus on Value Drivers

Action: Start by identifying the key value driver for your analysis. 

Whether it's 

• Growth
• Quality 
• Speed
• Risk
  
  

Ensure your analysis is centered on this focus. 

Research shows that companies that clearly define and concentrate on their value drivers—such as revenue growth, profit margins, or customer satisfaction—are better at aligning their strategic objectives with operational performance. 

This focus allows for more targeted insights, ensuring that your analysis remains relevant and impactful.

2. Target Comparisons

Action:   Always compare actual values to set targets. Understanding variances, whether positive or negative, helps in assessing performance effectively.

Research indicates that using visual aids like "rag" (Red, Amber, Green) indicators in charts can significantly enhance the understanding of performance metrics. A better decision can be made by identifying and addressing discrepancies between expected and actual outcomes using this method.

3. Monitor Growth

Action: Analyse the growth or decline between equivalent periods—be it monthly, yearly, or even hourly. 

Monitoring growth over time is essential for understanding business trends. Tools like bar charts and waterfall graphs are particularly effective in visualising these trends. 

Research emphasises the importance of comparing equivalent periods to account for seasonality and other temporal factors, which is crucial for accurate strategic planning and identifying areas of expansion or contraction.

4. Track Trends

Action: Keeping an eye on trends over multiple time horizons provides a deeper understanding of your data. 

Trend analysis, which involves examining data over different periods, is widely used in financial markets and business intelligence. By setting up charts that track daily, weekly, monthly, and yearly trends, you can uncover patterns that might otherwise go unnoticed. 

Research suggests that combining multiple time horizons provides a more comprehensive view, enabling more accurate forecasting and decision-making.

5. Data Ranking and Sorting

Action: To get the most out of your data, always rank and sort it from the most important to the least.

Research supports that sorting data by significance, rather than alphabetically, helps prioritise issues and focus on the most impactful areas. This approach is particularly useful in dashboards, where presenting the most critical information first can improve decision-making efficiency and help stakeholders quickly address key issues.

6. Understand the Mix

Action: Recognising the mix or composition of your data is crucial, especially in areas like sales analysis. 

Shifts in product or market mix can significantly impact overall performance. 

Research shows that stacked charts and treemaps are highly effective in visualising these changes, allowing analysts to quickly identify shifts in composition and their effects on performance. Understanding these shifts helps in making more informed decisions about product lines, market focus, and resource allocation.

7. Make Comparisons

Action: Comparing similar items—such as two sales reps in the same region—can reveal stories that explain performance differences. 

Comparative analysis is a fundamental technique in data analysis, often used to benchmark performance across different entities. 

Research indicates that visual comparison tools like butterfly bar charts and scatter plots enhance the ability to identify performance discrepancies and underlying causes, making this approach particularly valuable in competitive analysis.

8. Leverage the 80/20 Principle

Action: Analyse your data to identify the top 20% of factors driving 80% of your results, and prioritise these areas for focused improvement efforts.

The 80/20 rule, also known as the Pareto Principle, is a powerful tool in data analysis. This principle suggests that 80% of your results come from 20% of your efforts. 

Research validates its application across various domains. In data analysis, applying the 80/20 rule helps prioritise efforts and resources where they will have the most impact. By focusing on the critical 20%, you can quickly identify the most important areas to address, leading to significant performance improvements.

9. Correlate Data

Action: Analyse your data to uncover correlations, both positive and negative, that could reveal key insights and drive informed decision-making.

Correlation analysis is used to identify relationships between variables.
 

Research highlights the importance of identifying outliers during this process. These outliers often lead to unexpected insights, revealing relationships that might not be immediately apparent. Tools like correlation coefficients are useful for quantifying these relationships and guiding further investigation.

10. Analyse the Spread

Action: Don’t forget to look at the median, mode, and range of your data. 

Analysing the spread of data is crucial for understanding distribution patterns. 

Research shows that tools like histograms and box plots are effective for visualising data spread, helping analysts identify central tendencies and variations. This understanding is vital for making informed decisions, especially when dealing with skewed data or outliers. By examining the spread, you can gain deeper insights into the underlying structure of your data and identify areas for improvement.

In conclusion

No matter what tools you’re using—whether it’s Excel, Power BI, or something else—these tips are designed to work for you. By weaving these research-backed strategies into your data analysis process, you’ll be better equipped to uncover meaningful insights and make confident, well-informed decisions that move you closer to your goals.