An analysis of IBMs new approach to customer management

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Omdia was invited to attend a business innovation open day at IBM’s London Innovation Studio, for existing customers, prospective customers, and industry analysts. Highlights included a supply chain use case for blockchain, the investigation of fully homomorphic encryption (FHE) for the banking industry, data visualization for supply chain delivery failures at a major high street retailer, and making AI applications trustworthy. These projects are described below, but first a brief introduction to IBM’s new approach to customer engagement.

IBM’s approach to customer engagement 

IBM has honed its customer engagement with a dedicated customer engineering team comprising deep experts for demonstrating how IBM products can help customers and solve any challenges in adopting new technology. This pre-sale team hands over to the customer success team for continuing support in post-sales, and the two teams work together to ensure a seamless transition. These teams show clients how to build a minimum viable product (MVP) and base their methodology on IBM’s value engineering method (VEM). VEM uses IBM garage method as its foundation and builds on top a scoping layer where the focus is to solve any challenges raised by clients and de-risk product adoption.

Benefits of Walmart’s use of IBM Blockchain

IBM has had an interest in blockchain technology from the earliest days of crypto technology. Its blockchain is based on Hyperledger, a Linux Foundation open source project to which IBM is a major contributor. There were doubts about blockchain being a technology looking for a problem to solve (other than its use in cryptocurrencies), but the adoption of IBM Blockchain for the supply chain by Walmart, for example, shows real-world benefits. First of all, this use of the technology is for a private permissioned network of participants, so Walmart only invites its supply chain and their supply chain members to participate, ensuring a level of trust and security. Visibility of data stored in the ledger is governed by the owner who can ensure need to know access by any particular member of the network. Any groups of participants can also create sub-networks for sharing data if they wish. Data in the blockchain is immutable ensuring tamper proofing, and digital keys are stored and used securely. The key benefit for Walmart is fast traceability of food items through its supply network. If a food-borne disease breaks out, it typically takes days or weeks to trace the source, and without pin-point information a whole region of producers could be implicated in a sale ban. The blockchain technology, with bar coding of all produce, allows individual items to be traced to a precise source, such as an individual farm. This approach prevents waste, where a whole food category may be removed from shelves due to lack of precise information.

FHE is being tested in the banking industry

FHE is a highly mathematical algorithm for computing with encrypted data (which is never decrypted), plugging the gap that exists today where data can be encrypted in storage and in flight but has to be decrypted to perform computation. The disadvantage of FHE is that it is notoriously slow but algorithm optimizations and hardware performance improvements, including use of hardware accelerators (similar to those in use in artificial intelligence), are bringing the possibility of computing with FHE in real-time nearer. This technology is being assessed by the banking industry as a means of securing sensitive data and this industry is taking early steps to ensure it is conversant with it, as it is a question of time before it begins to be adopted.

Making AI applications trustworthy

As the use of AI increases across all industries and has a greater impact on individuals in all walks of life, it is essential that these applications are fair, unbiased and trustworthy. So far too many examples of badly designed AI applications exist, for example biased job application screening, so that governments and the EU are planning to legislate on the matter. When this happens there will be a shock for unprepared organizations that will find themselves falling under the new regulations and having to demonstrate their use of AI is compliant. IBM has a range of tools designed to ensure trustworthy AI, falling under categories such as: AI testing, explainable AI, fairness and transparency, and uncertainty quantification. 

Supply chain data visualization at a major high street retailer

A major UK high street retailer has a lot of data and wants to exploit it to help manage its supply chain, whether it is understanding revenue across the UK to delivery failures across supply hubs. IBM engaged with the retailer and built an MVP to visualize the items of concern with a heat map shown across a map of the UK. The project has a long term benefit in ensuring the retailer creates a mature data retention and governance regime, making use of the data easier to consume by data science tools and applications.