In this chapter, we will discuss the use of data to understand our customer requirements. We need to translate those requirements into goals during the defined phase in the DMAIC cycle. There are many purposes for collecting the data. We would like to identify customer preferences and needs and any urgent problems that require immediate attention. It would also be helpful to know how we can gain a competitive advantage with innovation in our product or service. What are the desired levels of quality and functionality that customers care about most? And how can we measure customer satisfaction more effectively? There are many dimensions we need to think about. Collecting customer data may inform us about the unmet needs for a product and service. Or if there are other products and services we could provide that we aren’t providing today. What are the shifts and preferences in the marketplace that we should track in order to stay competitive? We can collect data from a number of different important sources. Data sources can be derived from direct interaction or through indirect sources that already exist. On the direct interaction side one technique is to direct observations. This could include literally standing in a retail store and paying attention to behaviors. Or maybe capturing data from cash register receipts as customers exit an establishment. Another direct interaction technique is interviews. This is a very powerful technique to get one on one input and feedback from folks. We also have focus groups and Delphi groups and the use of surveys both in person and online.
There are also indirect sources of data collection. These indirect sources often already exist. For example, we may have outputs from other projects that we are doing. There are industry experts, like the Gartner Group or JD Powers for quality satisfaction surveys in the auto industry. We also have market watchers like consumers reports. And we can leverage things like big data, and data from trade associations and published consulting studies. It’s important to recognize that once we have collected accurate and reliable data, we need to convert that data through a process. This process allows us to convert that raw data into useful information that can be acted upon. We may use this information to take a different approach in product development. In the way that we deliver the product good or service or with the implementation of improvements. They key here is that this needs to be actionable. We must clearly identify and state what we need to do as a result of having this information. The customer feedback process is also critical. We determine the method we’re going to use to gather the input of the customer feedback. Whether it is surveys, end of service, data collection, paying visits to the field, making observations, or talking to the customers. We then convert that feedback into a process that results in an output of information that we can use to act upon. After we have made changes is when establishing a feedback loop is critical. We must go back to the customer and validate that the change had the desired effect on the customer. Are we noticing that something has changed in the marketplace by what the customers are now telling us? Are there shifts in demands or are there shifts in preferences? Do we have competition entering the market? Are we observing competitors exiting the market? And do we need to react to that as well? It’s often the customer feedback loop that keeps us informed about these changes. So the benefits to creating the feedback loop are many. We can validate customer data and learn new information to support ongoing continuous improvement process in the practice of Lean Six Sigma.