Market Development Models to inform Portfolio Go-To Market Strategy
The Challenge
Sometimes it's hard to figure out what products should go into what geographies. This often leads to shotgun and/or one-size-fits-all plans which don't recognize the intricacies of culture and consumer behavior on demand. This is especially true when you add in the complexity of emerging vs developed markets and have platforms & products existing at different price and quality tiers.
Such is the case here. The management team of a global portfolio of brands asked, "how should we plan entry and phasing of different platforms across multiple geographies over the next 3-5 years to ensure we are set up for success?" The decisions would impact manpower, and manufacturing capabilities, investments funding required, and organizational structure.
Building "Science" Into Market Expansion Strategy
The team working on this problem had little experience addressing this question. Like so many, they had started with the business when it was a purely domestic play, and they had "grown with it" as the business expanded. Very few of the team members understood the consumers or cultures of these new markets. They had not worked on a global scale-up like this before.
Decisions were usually made on an "opt-in" basis, whereas country leaders of the business would subjectively choose which products they wanted to bring into their geography. This form of unscientific approach, while simple enough to execute, had delivered unpredictable results in the past. The business was looking to incorporate a planning design that increased the probability of success more consistently.
Thinking differently about this required an innovative approach. It required thinking creatively about what factors even should be considered as part of the analysis. The team classified these considerations into four broad buckets:
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demographics (specifically income and expenditure attributes)
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economic conditions
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category dynamics
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brand propositions
After aligning on the categories within consideration, the analytics team outsourced at least some of the number-crunching to an off-shore partner to support the manual exercise of gathering and integrating several disparate data streams. The analytics manager (in this case, me) spent time to determine which factors to include, assess whether the data was good enough to use, and then, reviewing early models to make sure they made sense, added insight, and could be used by the management team to make decisions. Another task, and one that is often overlooked, was to manage the off-shore partner to ensure they clearly understood expectations and could deliver the right outcome.
The fun came once the data had been cleaned and prepared--the development of a predictive clustering solution that organized markets based on the above parameters. Indeed, there was some fuzzy math as well, so it required exercising both the logical, data-driven part of the brain and the creative, intuitive part--no model is perfect.
The Outcome: A Model to Use Now; A Model for the Future
It was time to communicate results and give direction to the business. Clustering methodologies are often hard to explain and digest to end-users, as business managers are most often accustomed to two-axes, four-quadrant solutions, whereas clustering can work on three or more dimensions. Analytical models of the future certainly work on levels of complexity that the human mind simply cannot understand. Overcoming this obstacle will be a challenge as machine learning and AI continue to flow into business activities.
Acknowledging that this complex solution required focused stakeholder engagement, workshops were created for the team to explore, discuss, and describe the solution in a methodical, sequenced way. By taking the solution in chunks and workshopping it with full discussion, it was more palatable for the audience.
The final "Market Development Model" was incorporated into the Global Product Team's long-term plan and was regularly referenced in C-Level conversations. This helped the company align future revenue streams and identify potential challenges along the way.
