Learning the Machine: Anovo Ibérica Introduces AI in Operations

  • Reference: SI-207-E

  • Number of pages: 24

  • Geographic Setting: España

  • Publication Date: Jul 21, 2021

  • Source: IESE (España)

  • Type of Document: Case

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Description

In 2018, Anovo, a service provider for technology products, began studying the possibility of introducing AI to improve the efficiency of its operations. In 2020, it was already piloting its first implementation - a new automated diagnostics process that employed machine learning (ML) to optimize the company's smartphone repair business. So far, the results of the pilot had been encouraging: aftersales service was a low-margin business, which made efficacy and efficiency key factors for achieving customer satisfaction while maintaining low costs. The new automated diagnostics system, developed by tech provider Novaquality Consulting, made repair operations simpler and faster. Furthermore, if this first project was successful, the company was already considering further possible applications of ML inside Anovo's smartphone operations. The case takes a look at the history of how the AI-driven diagnostics project was conceived, developed, and implemented, analyzing the challenges and decisions that Anovo and Novaquality faced at every point of the process. At the end of the case, the results of the pilot are presented, advancing several questions: Was the project ready to be scaled up to the whole company? Was the improvement in Anovo's operations tangible enough? Was the system accurate enough? Was the chosen integration process the best one possible?

Learning Objective

The case presents the opportunities and challenges facing a medium-sized enterprise aiming to introduce AI projects in their operations. Through Anovo and its project with Nova Quality, the case aims to illustrate 3 main teaching objectives: 1) AI-driven innovation is not only something available to large corporations like Amazon or Google, but a tool from which small and medium-sized companies can also greatly benefit. 2) Understanding the stages of developing and implementing a company-wide AI project. In particular, the challenges of scaling a project. Bringing a successful pilot to production is more complex than just doing the same, but larger: Internal and external stakeholders need to be aligned and integrated, potential technical pitfalls need to be identified and the quality of the data ensured throughout the life of the project. 3) The role of the provider: what should the relationship between the AI solutions provider and the company be? To what degree should companies like Anovo develop their own data and AI capabilities?

Keywords

AI algorithm Data machine learning servicing smartphone