Can you conduct a whitespace analysis?

When retailers approach Kalibrate for support with their location strategy, there’s a handful of questions we hear again and again.

In this blog series, we look at the most popular, give our take on why the answers are important, and explore the best practice approach.

This edition looks at whitespace analyses, one of many applications of a forecasting model.

What is a whitespace analysis?

There’s a couple of ways of framing whitespace analysis. Firstly, whitespace analyses may help an operator identify opportunities to ‘infill’ an existing market with viable new openings. Whitespace analyses are also used to assess new markets where the operator has no presence today – which may also be referred to as a greenfield analysis. Often that’s on a national level to identify markets of greatest opportunity. Analysts may also refer to ‘supportable store’ analyses to describe the same exercise.

We might talk about whitespace analysis being part of a market optimization analysis. However, this exercise would consider both whitespace infill opportunities as well as any market repositioning, which would include closures or relocations – a true rightsizing of the network rather than purely new opportunities.

Who’s it for?

The questions whitespace analyses answer are typically executive level strategic challenges – ‘what is my total buildout potential?’ For executives, the answer is critical to effective investment, resource allocation, and budgeting,

Downstream, the results of a whitespace analysis are guidance and a framework for operational teams – market researchers and analysts. The analysis provides their areas of priority to exploring available real estate followed by situational analysis of one prospective location over another.

Whitespace analyses are also conducted on behalf of private equity (PE) firms. Their use cases are often due diligence related, i.e., how big could this concept be, what investment is required, and at what valuation? The PE firm may also use the analysis to guide the operator’s direction and rate of expansion.

When’s the right time to conduct whitespace analysis?

Very few operators are just ‘throwing darts’ at a market when growing. The vast majority, if not all, will have a strategy. But the sophistication of the company and their short and long-term goals will impact the most appropriate type of analysis.

When we speak to new clients, some will want to conduct a national whitespace analysis – to see all their opportunities – when they’re a relatively local brand and the level of internal data is several years away from being able to inform that type of expansion. Going ahead would lead to a less robust model and, more than likely, a reduction in the quality of opportunities identified.

In this example, the risk is conducting whitespace analyses without proper inputs. Instead, an operator of this maturity should look at their three- and five-year goals and infill existing markets or assess neighboring markets at the first expansion priorities. For these operators, hot spot analysis, which looks at the type of customer and competitors impacting performance, may be more appropriate. Then, once the footprint grows and the number of observations we can make about what’s really driving performance increases, a larger whitespace analysis becomes more viable.

What’s the best practice approach?

The best practice approach would be to ask yourself difficult questions. For example, what’s your appetite for risk? That’s important because a whitespace analysis requires performance, cannibalization, and other optional attributes depending on the concept. Each of these qualification criteria impacts on the number of viable opportunities any analysis generates. If you’re risk averse, fewer ‘good stores’ are probably better than a higher ‘potentially viable’ unit count in the output.

Risk adverse operators will have higher minimum sales thresholds and a lower tolerance for cannibalization. Here, the whitespace opportunities might be very marginal – because the operator may have effectively set the expectation that all opportunities fit into the top tenth percentile of existing stores.

“Generally speaking, when I’m consulting with clients, I lean towards a five to one ratio. That means if you want to open a hundred stores in the next five years, you’d want to set your whitespace criteria to yield around 500 opportunities. That’s because real estate is hard! We must be realistic in acknowledging the numerous challenges dealmakers face in their attempts to execute against a strategy. Too few deals to work will quickly leave you with a frustrated team!”

Bill McKeogh, Director of Consulting

If you conduct a national analysis, there will be significant variation in the minimum sales threshold for profitability across markets. Operators should consider differing thresholds by DMA or, at a minimum, urbanicity to gain a more realistic picture of opportunities.

What does the end whitespace deliverable look like?

When Kalibrate delivers a whitespace analysis, the underlying work is a batch processing of tens (or even hundreds) of thousands of points on a national screening. We then apply the qualification criteria against all those points and eliminate points that don’t pass the threshold which determines viable units.

In essence, a whitespace deliverable is going to be a set of latitudes and longitudes. These points equate to target areas – i.e., based on what we know, you should look for real estate which serves those underlying trade areas. We will usually see clusters of opportunities within the target areas.

Then, as the pipeline of opportunities becomes reality, the underlying forecast model can be used on a specific piece of real estate, and you can compare it to the batch reports of opportunity identified in the whitespace analysis.

At this point, an operator might find a slight variation – because the whitespace analysis was evaluating map points, rather than an actual piece of physical piece of real estate with all the features of that site. Analysts will need to consider how the assumptions of forecast model interact with the specific site’s characteristics and adjust their final forecasts accordingly.

What are the benefits?

The benefits of a whitespace analysis fit into the categories of efficiency and strategy.

When you’ve built a forecasting model to evaluate sites, the whitespace or supportable analysis is just another opportunity to extract value from the model. The quantity of effort to apply the model to an existing market, new market, or across the country for the purposes of whitespace analysis is minimal. But the efficiency generated can be significant. Ultimately, the output provides a roadmap for analysts to focus their attention, which greatly reduces the amount of heavy lifting in assessing market by market where the best opportunities might be.

On the strategic side, an understanding of whitespace opportunity allows for effective budgeting. For example – how many units are we expecting to open? Where are we opening? What’s the potential revenue upside if we achieve these goals? Each of these questions is equally applicable to a private equity operator assessing an acquisition or planning expansions for brands in its portfolio.

Overall, a high-quality whitespace analysis also ensures capital investment works harder, because teams are assessing the best opportunities in the areas of greatest potential. From executives to analysts, every stakeholder’s time is better spent allowing the model and analysis focus attention, rather than starting with a vast number of potential opportunities to evaluate.

What questions should you ask next?

Once you have your forecast model and your whitespace analysis, there are a range of obvious next questions. One could be – if the macro-economic picture changes, how does that impact the assumptions of your whitespace? For example, some concepts are a lot more exposed to changes in the employment and recruitment market, others struggle to find opportunities when retail availability plummets.

If you’re opening a high volume of units or making significant optimizations to the portfolio, you should consider the optimum frequency to refresh your whitespace analysis. It’s unlikely that every suggested opportunity was hit at the prime location suggested. How does the analysis change when we introduce a new opening between two favored points?

“At a minimum, we would recommend that every time you recalibrate or rebuild your model, you should rerun your whitespace analysis. But if you are a highly active, let’s say you’re opening 75 or 150 units per year – which is not unheard of – it’s going to make sense to update your supportable unit analysis every year.”

Bill McKeogh, Director of Consulting

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