Risky Robots

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Are you managing an automation project? Better get ready to up your risk management game. Whether it is robotic manufacturing or analysis of large amounts of data, project managers must be extra careful about errors that might be magnified in deployment.

One of the severest consequences of an automation problem happened in Britain when an algorithm failure in an automated health service system prevented women from receiving a digital reminder to schedule their mammograms. Some 450,000 patients in England missed breast-cancer screenings.

The cover story in October PM Network® will tell you how to anticipate the worst in automation projects. It also goes into what happens when you don’t take care to thoroughly plan, test and execute. Project managers quoted in the article recommend sitting with workers who perform tasks that will be automated to check whether their actions align with what was previously documented.

Leaving something out is a big, big risk. A telecom project team failed to fully integrate the operations and business support systems, resulting in customers receiving services but not getting billed for them. Uh-oh. A 20 percent budget increase was needed to fix the problem.

Testing is key to identifying unknown risks and ensuring effective deployments. The testing phase must be well-planned and comprehensive. But project teams need to balance the testing need with the reality of potential post-deployment problems. Having good data and documentation will help mitigate those risks and ensure the automation project delivers long-term benefits.

Finally, do not ignore the human risk. That refers to team members and other workers losing their jobs as a result of automation.

What is your experience with automation projects and the associated risks?


Posted on: October 02, 2018 09:55 AM | Permalink

Comments (5)

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Encountered data privacy and security issues, as well as resistance to change.
A strong foundation of network infrastructure is central to a secured database.
Employee engagement and training are fundamentals to prevent or manage resistance to technology.

I think risk in automation projects is particulary related to scope definition. It can be difficult to fully translate what a human does into a sequence/recipe for a machine and to go a step further into the specific ways that machine can fail that do not really apply to human operators. I was project manager on an automation project for a visual inspection process (egg candling). The startup of the equipment showed us the many small things a human does that the machine does not and the many ways the machines could fail that we had not anticipated. It was a steep learning curve. To solve our problems and anticipate any further ones, we performed a FMEA on the machines and the process to list all potential failures and come up with mitigations. This is an exercise we should have performed in design and that we might have come up with during a thorough and formal project risk analysis. Then again, maybe not, hindsight is 20/20.

The biggest risk with automation are the edge cases, or rather, scenarios the machine has not encountered yet. There may be a catchall safety net for when the machine does not recognize a scenario and those one-off scenarios are routed to a human.

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