Fail fast and return to the buffet
Throughout the years, we have built countless pieces of technology for clients. From streamlined, low latency databases to AI chatbots and predictive machine learning models. In many instances, the packaging and presentation of the product play just as much a role in the success of the product as the underlying technology.
That last statement might seem obvious, but we often see the most successful customers are ones that actually fail the most. By this I mean companies that package and repackage the technology via different offerings to customers to provide value often are the most successful. If the underlying data schema is properly constructed, this will be easy! In my recent post, I discussed the concept of building an information buffet instead of a la carte meals. Information buffets allow users to create many different products from one source of data, while a la carte data warehouses only service one product at a time. This concept of an information buffet fits hand in glove with business owners who have been told to “fail fast”. Preparing a fresh steak dinner takes time for the kitchen staff, but it is very easy to quickly grab something off the buffet. If you do not like what you grabbed from the buffet, then go get something else! It does not cost more!
By building an information buffet instead of an a la carte menu, “failing” is not a problem. The underlying data serving the product that is not resonating with customers can quickly be repackaged and repurposed into a new offering for customers. The core technology has not changed at all. Instead, the company has repackaged the technology for a more palatable option for customers.
What does this look like in practice?
Consider a company with a database of stock prices and dates for every publicly traded company going back to 2000. The initial packaging could be a simple dashboard that allows users to get real time stock quotes. Feedback from customers might be that the platform is too similar to what they can get on Yahoo Finance or other similar services. One option might be to allow users to interact with the app via an AI chatbot. The chatbot answers questions for the users like “how much did the stock of Amazon rise in 2021?”. Perhaps customers want the ability to more easily compare companies side by side, so the company designs a direct comparison page of data across two companies. In order to generate value for customers, our hypothetical company does not need to redesign anything about their backend infrastructure. Instead, their packaging and the way users interact with the app completely changes the customer experience. The technology and data has not changed much, but the product feels and presents very differently to the user and provides a unique value proposition.
In short, a well structured data product offers maximal flexibility. With this flexibility comes a great opportunity and that is to fail fast and often. It allows for a very short feedback loop from customers. We often see companies get into trouble because they dig their heels in when presented with feedback from the marketplace. Successful companies are often willing to admit a miss, quickly pivot, and grab a new item from the information buffet. This takes a forward thinking data infrastructure and a humble leadership team willing to pivot when necessary. The line between success and failure is thinner than it may appear.
