Episode 34: Data analysis tools
- Embedded IT
- Apr 14, 2025
- 3 min read
Updated: Jan 16
Once data has been collected, stored, and processed, the next step is analysis. This is where the real value of data emerges. Analysis tools help organisations uncover trends, spot patterns, and turn raw information into meaningful insight. For procurement teams, choosing the right analytical tools is usually a straightforward software licensing decision, but understanding what each category does makes it easier to support IT teams and ensure the right outcomes.
This builds on our explanation of what data is and how it’s used across organisations.
The importance of data analysis
After all the effort spent gathering and preparing data, the purpose is to generate insights. Data analysis tools make that possible. They vary based on the type of data involved, but the goal is always the same: provide clear, reliable outputs that inform decisions.
There are three broad categories of analysis tools: statistical analysis, business intelligence tools, and emerging AI-driven approaches.
Statistical analysis tools
Statistical analysis focuses on identifying trends, forecasting, and understanding volumes or patterns across datasets. Several established tools dominate this space.
SAS is one of the most recognised names, known for robust, long-standing analytical products. It is typically straightforward from a licensing perspective and widely used across industries. IBM’s SPSS offers similar statistical functionality and is also well regarded.
Some organisations take a different route and build their own analytical solutions using common programming languages. R is a widely used language designed for statistics and data analysis. Python is another popular choice, especially where teams want more control or wish to tailor functionality to their needs.
For procurement teams, the decision is often whether to buy an established product or support internal teams in building something bespoke. Input from IT specialists is essential to ensure the right fit.
Business intelligence tools
Business intelligence, or BI, tools help visualise data and communicate insights in accessible ways. While spreadsheets still get used, modern BI tools offer far richer capabilities.
Power BI from Microsoft is one of the most common options. It is intuitive, licensed per user, and integrates smoothly with both Microsoft and third-party systems. Other major players include Tableau, now owned by Salesforce, and Qlik (including QlikView), which provide similar functionality with different interfaces.
User experience plays a big part in BI tool selection. Trial versions are often the best way to determine whether teams feel comfortable with the interface and workflow.
Where analysis meets artificial intelligence
The final category touches on artificial intelligence and machine learning. These tools move beyond traditional analysis by applying rules or learning patterns to generate deeper insights or automate decisions.
Frameworks such as TensorFlow support the development of machine learning models, allowing organisations to identify trends or predict outcomes in more sophisticated ways. The details sit closer to AI, and choosing these tools often depends heavily on IT teams’ technical requirements.
Data analysis tools are often a stepping stone rather than an end point. Once organisations can reliably analyse and interpret data, the next challenge is using that insight to support better, faster decisions, something we explore further in AI in procurement.
What procurement teams should focus on
At this stage of the data lifecycle, the priority is functionality. Licensing terms still need reviewing, but the bigger question is whether the tool provides the outputs the organisation actually needs. Collaboration between procurement and IT is key to ensuring the right tool is selected.
For organisations looking to improve their approach to technology procurement and select the right data analysis tools, get in touch.
