New Country Entry: Maximizing Success and Profits
In taking various licensed concepts to some 70 countries, we have seen numerous approaches to how licensors evaluate new countries. These approaches can be classified into three basic categories: the reactive approach, the shotgun approach and the predictive approach. In general, these three approaches can be described as follows:
The reactive approach - Some licensors wait for a prospective licensee to contact them about a given country. If the licensee is "qualified," they begin to negotiate a deal, often based largely upon their typical U.S. license agreement and royalty.
The shotgun approach - These licensors take a slightly more proactive approach. They may place an ad in trade journals or license publications, post a notice on their web site, or hire a broker to try to find a licensee in certain countries. However, they elect to enter countries based largely upon gut instinct rather than quantitative reasons for believing that the country is particularly well-suited for their concept.
In our experience, both of these approaches lead to licensors entering new countries without an understanding of why the country makes sense for their concept, or what kind of opportunity the country presents for the right licensee. As a result, selection of an appropriate license partner is problematic, at best.
The predictive approach - The predictive approach is a systematic approach for ranking and measuring country opportunity based on the unique characteristics of the country and the particular license concept.
Of these three methods, companies that employ the predictive approach produce growth and returns well in excess of industry norms.
In a recent engagement, we worked with a large international licensor that wanted to expand its international operations through licensing. In the past, the client had experienced impressive results in some countries, while struggling in or even withdrawing from others. While management had several hypotheses on success and failure, they had limited empirical evidence. As a result of our work, the organization has re-focused its international licensing efforts around the highest potential countries. Employing the predictive model has allowed them to more fully understand the reasons for past successes and failures and prioritize new country entry by focusing on the countries with the highest likelihood of future success.
In this article we provide an overview of the predictive approach for ranking country opportunity and look more closely at how to develop a tool for evaluating what countries to enter.
Country ranking is a quantitative method for evaluating the relative opportunity for a license concept in multiple countries. Each country receives an overall ranking based on a weighting of critical success factors. The overall grade provides direction in evaluating the viability and priority for franchising the countries.
Country ranking employs the following six-step process to identify countries of maximum opportunity.
Step 1 - Critical Success Factor Identification - A Critical Success Factor (CSF) is an internal, external, strategic, or economic factor that has historically contributed to the success of the business. Examples of CSFs include: consumption ability, market size, market growth, labor cost, real estate cost, country infrastructure, natural resources, and product acceptance. While CSFs will be different for each business, several categories of CSFs should be included in any CSF evaluation. These categories include the size of the market opportunity, the consumptive ability of people in the country, the existence of critical infrastructure, any key cost structures, and cultural norms that are likely to impact a concept's success. The process of identifying a concept's CSFs begins with discussions with management and identifying things that are critical to the concept's success. This is followed by conversations with domain experts inside and outside the organization, who provide additional perspective on each issue. Once potential CSFs have been defined, they can be tested by applying them against the historic performance of the business in particular markets, thereby empirically testing the impact of each CSF on the success or failure of the concept.
Great effort must be taken to identify only those success factors that are truly critical to the business. In our experience, various management disciplines see their functions as critical to the business; however, a more rigorous analysis may conclude that they are not so critical as to warrant inclusion in the analysis. In a recent engagement, our client strongly believed that real estate cost was a CSF. As we began to test the CSF, the historic data showed no meaningful correlation between the cost of real estate and the financial success of the business in a market. Rather, high real estate markets proved to be the most profitable markets. The data showed that the higher consumptive ability associated with higher real estate cost markets more than offset the negative impact of high real estate costs. While real estate was an important part of the international equation, it was not a CSF.
There is often a tendency to include too many CSFs. In our experience, most businesses have 4-6 CSFs. Being able to boil the business down to its core CSFs increases the likelihood that a meaningful model can be developed. Overcomplexity can result in the analysis going into a drawer and never being used. Therefore, we strongly suggest that only the most critical success factors be included in the analysis.
Step 2 - Proxy Identification - Once the CSFs have been identified, the next step is to locate a quantitative data measure, or proxy, for each CSF. These proxies allow an "apple for apple" comparison of various countries. In a past engagement, the tendency of the population to "dine out" was identified as a CSF. In considering appropriate proxies, the following quantitative measures were examined:
- annual per person spending on food, beverages and tobacco;
- annual per person spending in restaurants;
number of multi-unit restaurant chains in the country; and
- number of McDonalds' in the country.
Any one of these measures might make a good proxy for the CSF. The question is, which makes the best proxy? In other words, which proxy is most highly correlated to the CSF, and is also available for all the countries being evaluated?
There are numerous third party companies who provide country data. These data items range from the number of cable TV subscribers, to the price of a Big Mac, or the per capita protein consumption for a particular country. To eliminate personal bias from the ranking, quantitative data is used and proxies must be available on a consistent basis for each of the countries being evaluated.
The difficulty with the proxy process is two-fold. First, you must identify data that reasonably approximates the CSF. Second, the data must be widely available. For each CSF, multiple proxies must be evaluated and compared in order to determine the best measure. Often, we expect to find the best correlations in one proxy only to realize that another more closely approximates the CSF. Recently, one of our clients identified consumptive ability as a CSF. Per person income was examined as a potential proxy and when contrasted with historical results, the regression analysis showed a modest level of correlation. Further research identified a different data proxy more closely related to our client's product offering. When compared with historical results, a 95% correlation was found. The data was then used as a proxy for consumptive ability in the country ranking analysis, and was later used by the client for accurately projecting unit sales for new countries.
Step 3 - Proxy Indexing - Next, an index must be developed from the raw data that comprises each proxy. The index standardizes the items on a scale of 1 to 100, and allows for the direct comparison of variables with different distributions (e.g. indexed population can be compared to indexed income growth rates). Without this process, it would be impossible to examine a number of CSFs and appropriately weight those CSFs for an individual business. The failure to index items results in items that have a higher raw score (e.g. population) being overly emphasized in comparison to those items that have a lower raw score (e.g. per person spending on eating out).
Step 4 - CSF Weighting - At this point in the process, a weighted average score is developed by applying weights to each of the CSFs. The weighting for each CSF is based on management's judgment and is tested by comparing the ranking to historical results. The desired result is to develop a weighted average that ranks a country's potential based upon historic successes and failures.
In determining the weights it is important to understand the interplay between CSFs. Failure to do so can result in over or under emphasizing certain CSFs. For example, if total population is used as a proxy for market size and GDP as the proxy for consumptive ability, one must account for the fact that both, in some measure, reflect market size (i.e. GDP is not only reflective of consumptive ability but a market's size). To provide each equal weight would result in market size being given more overall weight than consumptive ability, thus skewing the model toward one CSF (market size). For this reason the analyst must thoroughly understand the drivers behind each proxy and adjust the weights accordingly.
Step 5 - Testing - Once an overall equation for ranking has been achieved; it should be tested against the business's historical successes and failures to see if it accurately predicts success. If there are already international operations, this process is relatively straightforward. However, if the client does not operate in markets outside the U.S., the equation needs to be tested against U.S. markets. This requires some creativity, as the proxies will be more applicable to entire countries than sub-markets in the U.S. Once a final equation is developed, it is time to complete the final step of the process.
Step 6 - Results - The final step is to populate the analysis with data for all the countries being evaluated, and review the ranking that is produced. It is essential that management scrutinize the results. If anomalies cannot be explained, then the CSFs and proxies must be further scrutinized and alternative iterations of weighting must be tested until the results are sound.
Adopting the predictive approach requires work and discipline, but when implemented by management, the success rate for new country entry is greatly increased. Not only is a ranking of new countries produced, but the licensor also has a clear understanding of what it takes for its concept to be successful in foreign markets.
In our experience developing country risk models, a number of unexpected benefits are often realized. In the past, country ranking has resulted in:
Identifying a high correlation between the client's unit sales and certain macroeconomic data that allows the client to forecast average unit sales with a very high degree of accuracy. As a result, they forecast sales before entering a country and are able to use the data to help their existing licensees identify stores that are performing below expectation.
Computing what kind of population is required to support a profitable store/unit. As a result, the client's real estate selection process now includes not only typical traffic pattern work, but also an accurate understanding of how the trade area affects store performance.
Focusing of the client's license sales efforts on key markets that provide the best opportunity for their concept. Efforts are focused on the markets where financial returns are expected to be the greatest and management is prepared to invest to realize those returns.
Determining what markets should be "bundled" with others to create overall opportunities that are attractive for potential licensees.
Possessing the quantitative assessment necessary for the development staff to defend against pet projects that distract from more meaningful opportunities.
While this list is by no means exhaustive, it does provide some idea of the benefits that a company can expect to receive by adopting a predictive approach to new country entry.
In conclusion, as a result of employing the predictive approach to new country entry, licensors can accelerate growth and maximize the returns they receive from franchising. These benefits result from the licensor understanding the CSFs for the concept and identifying the markets where those CSFs are present. By employing a disciplined approach to new country entry, a licensor can focus its efforts where market opportunity warrants maximum returns.
Ainsworth and Anders are partners with Guidant Capital LLC, a middle market investment bank focusing on international franchising. Mr. Anders leads the firm's franchise practice and Mr. Ainsworth heads its financial studies group. Guidant Capital LLC, 214.746.8801.
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