Taiger AI: Unbundling the Business Value of NLP

Set in April 2020, the case talks about TAIGER, a software-as-a-service (SaaS) company providing natural language processing (NLP) solutions in a rapidly growing market where demand and competition for such solutions are high. TAIGER solutions could process and digitise large amounts of physical data, perform search and extract functions on data, and make appropriate recommendations. The algorithms and tools were bundled under three packages, and were customised for every client. Client companies were mainly large organisations and government entities. Despite a growing customer base, Arroyo and his team found it increasingly difficult to service new clients, who demanded more customisation and services. TAIGER's solution packages were bundled together with customisation and post-implementation support services based on contract licenses. The downside of this model was that it used many resources and limited the delivery of the products to a per project basis. The monetisation of the model was also complicated and project costs were difficult to control. Administering customised solutions was time consuming and expensive for both TAIGER and its clients; it also lacked flexibility and quick scalability for large-scale implementation. Arroyo realised that he needed more than just efficient solutions, given the expanding opportunities for NLP in the market and the constraints of TAIGER's existing solution packaging. He wondered if designing a new business model was the right way forward. Would he also need to devise a new pricing strategy and rebundle solution offerings? How could he unbundle the business value of TAIGER's NLP solutions?