Skip to content

Data analytics · Data science · Africa

Data analytics and data science for the questions you'll need to answer again.

Understand performance, anticipate demand and decide where to act. We take on the hard analytical questions, then turn the ones that keep coming back into tools your team keeps using.

Discuss a projectSee our work

South African retail sales: the year ahead

Monthly, R billion at constant 2019 prices. Observed to July 2026, then our 12-month outlook with its planning range.

  • Observed (Stats SA)
  • 12-month outlook
  • 95% range
  • 80% range
80100120140202220232024202520262027Outlook

The retail outlook

R1,232.6 bn of retail sales expected over the next 12 months, with December 2026 alone at R138.8 bn.

Get the outlook report
Supermarket shelves stacked with tinned soups and packaged food

Every month, the same review is rebuilt from scratch.

Most organisations have the data. What they lack is analysis they can rely on, and repeat.

The hard part is rarely producing a number once. It is producing a sound answer every month, from data that doesn't line up, without depending on one person's spreadsheet.
The same analysis is rebuilt every cycle
The monthly sales review is pieced together from spreadsheets again, by whoever has time, with definitions that drift between versions.
Dashboards say what moved, not why
Volumes fell in two regions. The dashboard shows it clearly. It can't tell you whether it was price, range, distribution or a reporting change.
The plan is last year plus a percentage
There is a forecast somewhere, but nobody can show it beats last year's pattern, so the plan falls back on a guess.
The method leaves with the study
A one-off analysis answers the question once. Next quarter it comes back and the method has to be rebuilt from the slides.

Services

What you can commission. And what your team gets.

Five kinds of work, often combined around one problem. Each ends in something your team can use, not a slide deck that ages.

Case studies

See the work. Findings from our analysis of South African markets.

Explore the charts and request any full report. Each one is an analysis we can build for your market.

All case studies

Understand competitive shifts

Who is gaining ground in South Africa's vehicle market?

Jetour added +2.25 pp of market share in a year: more than GWM/Haval and Chery combined.

Chinese brands now sell 19.6% of new light vehicles. The biggest seller is rarely the biggest mover, and knowing who is taking share tells you where to focus.

Request the full reportDiscuss a project

SA Informatics analysis of naamsa monthly new-vehicle sales. Explore it on the site

Chinese brands' share of new light-vehicle sales
0%5%10%15%20%25%202420252026

Biggest contributors to the gain

  • Jetour+2.25 pp
  • BYD+0.80 pp
  • Omoda & Jaecoo+0.75 pp

Separate price from volume

Sales are growing. What is happening to volume?

Food specialists' sales rose +4.9% in rands while the volume they sold fell −1.9%.

Rand growth can hide shrinking demand. Separating price from volume shows whether a category is really growing, and whether it needs a volume plan or a pricing plan.

Request the full reportDiscuss a project

SA Informatics analysis of Stats SA retail trade sales. Explore it on the site

Last 12 months: growth in rands against growth in volume
Growth in rands+4.9%
Growth in volume−1.9%
Price effect: the gap between the two+7.0%

Food and drink specialists sold less, for more: rand sales rose +4.9% while volume fell −1.9%. Revenue is being carried by price.

1 / 2

Capabilities

Three ways we help. Explain what is happening, estimate what comes next, or hand the repeat work to an application.

The problem decides which you need. Often it is more than one.
A supermarket aisle stocked with packaged snacks and chocolate

Data Analytics

Explain what is happening: which changes are real, where they come from, and which need attention.

  • “Is this region's sales growth real once price increases are stripped out?”
  • “Which categories account for the fall in volume while revenue held up?”
  • “Which competitors are taking share, and how fast?”
Explore Data Analytics
A car's headlight on a dealership showroom floor

Data Science

Estimate what comes next: a forecast you can plan on, with its range and the assumptions behind it.

  • “What will demand look like next year, and what range should we plan around?”
  • “How much of the year will December carry?”
  • “What happens to the plan if sales run 1% below expectations?”
Explore Data Science
A long warehouse aisle with racking stacked with boxes

Applied AI

Hand repeat work to an application: it reads what arrives, applies your rules and prepares the result for review.

  • “Can enquiries arrive with a quotation already drafted?”
  • “Can applications reach us complete, with the gaps already chased?”
  • “Can the answer come from our own product knowledge and policies?”
Explore Applied AI

When the question keeps coming back, the method should become a system your team keeps using.

One team takes the work from the question to the system: framing the problem, building the data, doing the analysis or modelling, and, where the question recurs, engineering it into software that reruns on new data.

  1. Frame

    Agree the decision and what counts as an answer.

  2. Structure

    Assemble, reconcile and validate the data. Keep its lineage.

  3. Analyse

    Describe, compare and diagnose what moved and why.

  4. Model

    Forecast or test scenarios, only where the question needs it.

  5. Communicate

    Give the answer with its uncertainty and limits.

  6. Operationalise

    Where the question recurs, build the method into a system.

Three typical paths

  • “Why did volume fall in two regions while revenue held up?”

    1. Frame
    2. Structure
    3. Analyse
    4. Communicate

    Ends in an explanation

  • “What will monthly sales look like over the next year, and how sure can we be?”

    1. Frame
    2. Structure
    3. Model
    4. Communicate

    Ends in a forecast

  • “Every month the same question: are we really growing, once prices are taken out? Can the answer arrive without rebuilding the spreadsheet?”

    1. Frame
    2. Structure
    3. Analyse
    4. Communicate
    5. Operationalise

    Ends in a system the team keeps using

How an engagement runs

Is this our kind of problem? Hard, and recurring.

Our strongest fit is a hard question you'll keep asking. For a simple or one-off question, we'll point you to the quickest route to an answer.

Routine question

Answer needed once

An analyst and a spreadsheet

A one-off question with clean data rarely needs outside help.

Answer needed repeatedly

Your BI tool or off-the-shelf software

A standard report that recurs is what reporting tools are built for.

Complex question

Answer needed once

A focused analytical study

A hard question you'll ask once needs rigour, not a system. We do these too.

Answer needed repeatedly

Our strongest fit

A hard question you'll keep asking: we answer it, then build the method into something your team keeps using.

Who does the work. SA Informatics is a founder-led firm. You work directly with the people doing the analysis.

About SA Informatics
The Johannesburg skyline at golden hour

Tell us the question you need to keep answering.

Describe the question, the data you have, and whether you'll need the answer again. We'll tell you whether we're the right fit.

Start a conversation