This post discusses a specific aspect of Jobs to be Done. If you haven’t already done so, we suggest starting with the post—What is Jobs To Be Done. This will give you a broad overview of JTBD concepts with links to other posts that take a deeper dive into those concepts.
Recall that a complete set of value targets for any given job applies to ALL individuals and organizations trying to get that job done regardless of job circumstance and solutions-in-use. Now, with a complete set of value targets in hand, if you try to develop a new product or service for all of those job executors, you’ll end up with a solution that doesn’t offer best value to any of them. Simply put, the new solution will likely disappoint for reasons I’ll discuss shortly.
Also recall that it’s job circumstance and the limitations of a solution-in-use that cause job executors to struggle to get a job done well. Each moment of struggle (MoS) is indicated by a corresponding undershot value target and it represents the additional value that job executors want from solutions to get that job done better.
When moments of struggle reach a threshold of unacceptability, job executors become very motivated to hire another solution that can mitigate or eliminate those struggles. A solution that can satisfy those needs better than competing alternatives at a price that customers are willing to pay is the key to demand creation.
Let’s say you’ve identified an important job that’s not getting done well with solutions-in-use. You’ve determined that your company has the capabilities to create a product or service that can help customers get that job better. But to create customer demand, your product or service must offer customers the best value vis-à-vis those other solutions. With this in mind, let’s work backwards in our reasoning.
If an entire group of customers, which could be very large, perceives a particular solution to be the best value, then they must have something in common that shapes their perception of value. Since these job executors have determined that solution eliminates their moments of struggle better than competing alternatives, then one thing they have in common is their moments of struggle. But just because they share the same MoS doesn’t mean they have the same hiring criteria. There must be something more fundamental at work that explains customer choice.
Now, customers are oriented around their experiences. They’re keenly aware of the specific circumstances that are causing their struggles and these are the problems they’re trying to solve for. As such, they look for solutions that offer features they believe will eliminate, accommodate or resolve those circumstances.
Therefore, the customers’ hiring criteria is based on the circumstance of struggle, not moments of struggle, per se. In a customer’s mind, a moment of struggle is the problem and the circumstance are the cause. Therefore, customers evaluate solutions based on how well they perceive solution features will address the circumstance of struggle.
For this reason, grouping job executors that share common moments of struggle into a single segment is not sufficient to develop a solution that offers best value to all those potential customers. That’s because a single moment of struggle can potentially be caused by different circumstances unique to certain job executors. Stated another way, different job circumstances can cause the same moment of struggle.
Think about the implication. The customers’ hiring criteria is based on how well they perceive a solution can address circumstances of struggle. But if there’s more than one circumstance that can cause a moment of struggle, then there could be significant variation in the hiring criteria within a group that share the same MoS.
If so, the segment would not be sufficiently aligned around the same set of value targets. As such, there would be significant differences in the value those customers want from a solution to get a job done better. This will make it difficult to satisfy all those needs without making trade-offs for the sake of profitability that result in undershooting some customers in that segment and overshooting others.
This results in two crippling consequences. First, the cost structure of a solution will be high relative to the value offered because the solution is burdened with features that certain customers in the segment don’t value. Second, trade-offs can result in a solution design that doesn’t help certain customers in the group get a job done better than the competing alternatives. Either way, a solution plagued by these problems will not do well.
If the intention is to create a best value product or service, that solution will have to be designed in such a way that eliminates moments of struggles better than competing solutions for all customers in a segment. This is only possible if job executors are segmented based on common moments of struggle AND common circumstance of struggle. Otherwise, a customer segment could have too much variation around value targets and this will comprise your ability to create a best value solution at the lowest cost.
The great thing is that once you’ve identified the circumstance of struggle for a group of customers, it becomes much clearer how to design solution features that can resolve the obstacles, barriers, situations, conditions, and other contextual factors that are causing moments of struggle.
Once the association is made between undershot value targets, moments of struggle and circumstance of struggle for a group of job executors, the overshot, must-be and indifferent value targets associated with those customers fall into place. Now you have a customer segment that has a high degree of uniformity around the value they want from a solution to get a particular job done better.
When you know in advance the criteria that ALL customers in a segment will use to evaluate your product or service vis-à-vis competing alternatives, you have a precise blueprint for designing a solution that removes moments of struggle at the lowest possible cost. If your solution can do this better than competing offerings at a price the customers are willing to pay, then your solution will create customer demand. This is the rationale behind jobs-based segmentation.
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