Data analytics & business intelligence
Finding the insights others miss.
We help businesses turn scattered data into clear, confident decisions — through analytics, dashboards, automation, and business intelligence.
Services
Twelve ways to get unstuck
Not a menu of packages — a description of the work. Most projects touch several of these before they're done.
Power BI Dashboards
Live dashboards built around the numbers you actually check every week.
Business Intelligence
Turning scattered systems into one dependable source of truth.
Data Analytics
Digging past the headline number to find what's actually driving it.
SQL Analysis
Querying the data where it lives instead of exporting yet another CSV.
Python Analytics
Custom analysis and modelling for questions spreadsheets can't answer.
Excel Automation
Replacing hours of manual copy-paste with a workbook that updates itself.
Data Cleaning
Messy exports and half-documented systems, turned into a dataset you can trust.
Statistical Analysis
Hypothesis testing, regression, and segment analysis with the confidence interval attached.
Forecasting
Demand, revenue, and trend projections you can actually plan around.
KPI Dashboards
The handful of metrics that matter, always visible, never stale.
Reporting Automation
Recurring reports that build themselves the following month.
Data Visualization
Charts built to be understood in five seconds, not five minutes.
Industries
Work that travels across sectors
The tools change less than people expect — clean data and a clear question matter more than the industry label.
Healthcare
Retail
Finance
Manufacturing
Hospitality
Logistics
Education
E-commerce
About
Helping businesses make better decisions with data.
Mean N Outlier Analytics is a small consultancy firm. That's not a limitation we're working around — it's the pitch.
No account manager relaying your question to someone else. No junior analyst learning the fundamentals on your dataset. When you hire Mean N Outlier Analytics, you get direct access to whoever is actually running the numbers, from the first email to the final file.
We started this practice because most data work gets diluted somewhere between the person asking the question and the person answering it. Here, there's no in-between — just close attention to your data, and an honest read of what it actually says.
Process
How a project runs
Seven stages, no account handoffs in between — you're working with the same person the whole way through.
Discovery
Understand the question behind the request, and whether it's answerable with what you have.
Collect Data
Pull data from wherever it actually lives — exports, databases, or half-documented systems.
Clean Data
Fix inconsistencies and gaps so the analysis stands on solid ground.
Analyze
Test assumptions, chase down anomalies, and check the work before it reaches you.
Build Dashboard
Turn the findings into something you'll actually open again next month.
Deliver Insights
Plain-English findings and the method behind them, not just a slide with a headline.
Support
Ongoing help as the questions — and the data — keep changing.
Contact
Have a dataset that's bugging you?
Tell us what's going on and what you're trying to find out. We'll reply with an honest read on whether we can help — no sales call required.