CD: To what extent are more manufacturing companies turning to technology and data analytics to help to mitigate the cost of product recalls and reduce future incidents? Are you seeing growing awareness and increased demand in this area?

Petrie: Many companies are under increasing pressure to more quickly detect and respond to manufacturing quality and safety issues. This, of course, is a very challenging ask. Though damaging when product quality issues ultimately manifest, they can be hard to proactively discover before they reach that stage. A product quality signal can be buried in the data collected and generated by the company and, often, that signal will only truly be detectable by cross-correlating a number of disparate data sources. Often the only way to successfully and proactively detect a signal – a signal comprised of faint, unusual patterns across multiple data sets – is with a series of sophisticated algorithms. There is really no other way around it, so we are certainly seeing that growing awareness.

Swinehart: As companies understand the benefits of an analytically-driven approach, they are increasingly adopting such approaches. Many companies are engaged in broader digital transformations and they sometimes start with product safety and quality as a relevant use case.

Oct-Dec 2018 issue

Deloitte Financial Advisory Services

Sidley Austin LLP

Deloitte Transactions and Business Analytics LLP