Why we don’t trust AT Kearney’s Global Retail Development Index and you shouldn’t too

The problem is retail development rankings are useless. Worse than useless, actually. We explain why we don’t trust AT Kearney’s Global Retail Development Index when it comes to Africa.

A few years ago we wanted to build a retail market attractiveness model. We knew AT Kearney had a successful model it used to showcase its retail practice, called the Global Retail Development Index. But at the time it didn’t cover Africa. So we went and built one to cover the grocery retail market. And while we were doing that AT Kearney released an Africa-specific index. Great.

We really liked the idea of a retail market attractiveness/development index. It provides order where there is chaos. As they say, in the Land of the Blind, the one eyed man is king. Helpfully, AT Kearney lets you have a look at their methodology and their weightings so you can have a go at building a similar model.

AT Kearney splits its retail index into four components: market attractiveness, country risk, market saturation and time pressure. Each section neatly accounts for 25% of the overall score, which seems fair enough. It’s a slick, innovative exercise that is textbook management consultancy. Lots of data sources wrangled in a clever way to deliver a decision support tool.

This year the leading African market AT Kearney are highlighting is Ghana. In 2017 it was Algeria. In 2016 it was Morocco. In 2015’s African Retail Development Index it was Gabon and Botswana.

The problem is these rankings are useless. Worse than useless, actually.

No retailer rushed into Gabon after AT Kearney flagged it as a market to watch. In fact, at the time the country’s leading retailer, Ceca Gadis, was having severe financial problems.

Morocco is an attractive market, but it’s highly saturated by African standards.

Algeria is a nightmare to do business in and a graveyard for retailers. French supermarket chain Auchan has famously spent a decade trying to find a partner and open there.

Ghana has lots of recommend but it’s not for everyone: we have seen well run retail chains like Shop n Save open there and close down within the past five years.

At this point we should say that we cover 50 retail markets in Africa, including providing data on their size and growth prospects. We track hundreds of grocery retailers in those 50 countries, including every chain. We map the exact locations of tens of thousands of supermarkets, who owns them, how big they are, who they compete with and more. We do the same for fast food chains – of which there are hundreds. We track hundreds of distributors, and speak to them almost daily: these are the companies that survive or die based on knowing their markets.

So anyway, what happened when we built our own market development index, but using our own data?

Like AT Kearney, we wanted to keep things simple, not muck about with the weightings too much. We pumped in lots of data and we stood back and assessed the results against what we could see happening in these markets.

We found that no combination of data or weightings produced a satisfactory result which chimed with what we knew. If you put too much emphasis on market size, then big but challenging markets like DRC or Algeria shot up the index. If you put too much emphasis on avoiding risk then safe but small countries like Botswana and Mauritius shot up. Market saturation was little better: most of African markets are overwhelmingly dependent on traditional channels. It’s not a meaningful metric to use without context: Algeria and DRC are not saturated, for good reasons. The opposite of “saturated” is not “open”.

Our rankings, which we never released publicly, were useless. Worse than useless. Dangerous. Because taken without proper context they give rise to terrible decisions.

Generally speaking, retailers know this, which is why they haven’t rushed into Gabon or Algeria.

If you want to see where retailers are investing look at Egypt, Côte d’Ivoire, Cameroon, Kenya. Way more so than Ghana, Botswana or Algeria.

Why are retailers so cautious about Nigeria or Angola, both otherwise large markets with lots of wealth? Because they are so oil dependent and oil prices are likely to be soft for the next few years. Why has Shoprite, the most successful retailer in Africa, just made a bet to expand in DRC? Because they’ve looked at cobalt prices (cobalt is a key element used in electric vehicle batteries) and forecasts for the growth of electric vehicles.

Any market development index needs to account for what drives the economy.

Why does Ethiopia have so little interest from foreign retailers despite strong economic growth and a large, young population? Because it is nearly impossible to get hold of the foreign currency (FX) needed to import goods. If you go there, it is the number one concern every retailer and distributor mentions.

FX availability, which is an issue in several countries including Algeria, Ethiopia, Sudan and Zimbabwe, is a market killer when it comes to retail investment.

We still use market attractiveness models because they are useful tools to do what AT Kearney does: create order from chaos. But we always share them with clients with a massive caveat that they have to be supported with real world insight about how markets operate.

This isn’t just a case of saying use better data, or different data, although we think AT Kearney could be using better data for Africa. We actually really admire what AT Kearney has done and think its way of thinking about retail markets is interesting and insightful.

Our point is that any of these models involves a compromise between the factors such as size, growth, risk, saturation, ease of doing business. The end result is often an unsatisfactory compromise.

Trendtype’s key takeaways

– Market development / attractiveness models often produce ‘middle ground’ results.

– Nice, neat weightings are pleasant to look at but are not necessarily statistically useful.

– Data quality for Africa is frequently poor or incomplete. Models based on poor data will yield poor outcomes.

– Data models that don’t account for factors which are relevant for African markets won’t help you for African markets.

– Data is useful, of course. But where data is poor or incomplete other evidence may be much more useful.

– Context matters. It really matters.