How to navigate propositions?
Shifting to validating fast and often

The pace of change in today’s world is picking up: COVID-19, climate change, civil movement, technological abilities, and the Millennial generation impact the way we see the world and the way things work or do not work. This constant change requires business to continuously evaluate their propositions to match customer needs and demands. At the same time, it offers the opportunity to introduce new propositions fulfilling customer needs. 

 

In the area of proposition development, it is fairly easy to experiment. “Fail fast and fail often” is a slogan that is often vocalized. Many times, it is actually fail late or do not fail. The most brilliant ideas come forth from a brilliant mind or a group of people inside the company. Focus is on the solution, instead of on a customer need. Before one knows a new concept is launched in the market. And? Nothing happens. Energy leaks away and organization burns the brilliant idea. Many times, without learnings of the failure. Lost effort, energy and resources. 

 

An example we have witnessed, is about data. Data is hot and many companies focus on monetizing data (propositions). In our example the data proposition is a predictive information product, which is used to optimize specific logistical processes. Savings add up quick due to the large(r) volumes and makes up a promising business case. It is the signal to start burning effort to solve the problem. The data team starts to collect, clean and work the data. Hours are spent to get to a working predictive model. Once the data science part is done, the promising business case is validated. Now it is time to reach out to the potential customers to sell the solution. A range of issues arise. The sample data and the customer data differ, and the numbers do not add up. The implementation of the data proposition in the customer’s IT landscape takes a long time or takes a lot of effort. The customers see the impact on their own work and are hesitant.

 

Technology driven innovation is another challenge. In these cases, a new technology or capability are a solution for self-defined challenges. In 2016 chatbots were the upcoming trend. Chatbots were going to transform customer service, reducing cost, whilst improving experience. In the processes it turned out that the technology needed further growth, but more important customers were not ready yet for computer aided support. The insights were valuable, but there are more efficient ways to get the same insights. 

 

In practice, the data proposition often does not resonate with the customer needs. However, taking the proper steps to include the customer will reduce the risk of failure, extensive rework or long lead times. 

 

The examples show that propositions that are based on an internal perspective often do not fully align with the needs of your customers. Therefore, it is important to take the people-centered perspective into account throughout the development of a proposition to ensure that there is a customer base willing to pay for it.

 

In order to help you with people-centered proposition development, we created the Proposition Development Map. This map can help business teams, leaders and innovation groups to navigate the people-centered development or re-engineering of propositions.  

 


Please contact Wolter Buma or Roy Scheerder for an open dialogue on proposition development.