Manufacturers know they need to boost production efficiency and improve performance, and that the most promising route is investing in technology that unlocks the power of production data collected from IoT sensors on the shop floor. Their typical approach, though, is problematic. Companies embark on a campaign of numerous small pilot projects, followed by POCs for the most promising. After that, the initiative generally stalls out, entering a kind of death spiral in which nothing at all gets deployed at meaningful scale. Hoped-for benefits don’t materialize, frustration ensues, pressure mounts to do something, and the process begins again — leading to the same dead-end conclusion. Sound familiar? This demoralizing “doom cycle” is more fully described in my previous blog titled The Death of Pilots.
To replace this unproductive cycle with one that breeds success, we first have to uncover the motivation behind it. What exactly propels companies to undertake drawn-out piloting odysseys to nowhere? The root cause is a pair of plain but not-so-simple apprehensions: fear and risk.
These linked concerns are legitimate. Even so, continuing to tread water in the face of risk is no way to make continuous improvements and move forward to Manufacturing 4.0. After investing careful consideration and due technical diligence, manufacturers need to choose one or more technology solutions and implement them at a scale that can actually move the needle on performance. Practically speaking, this requires “de-risking” the decision process.
When you look closely at risk, three facets reveal themselves. The first is financial: the chance that you won’t realize a good return on your investment in licensing and deploying technology. Second comes organizational risk, the team demoralization that sets in if an analytics initiative should fail. And lastly, there’s personal risk. To get initiatives off the ground, project champions stake their names, reputations, and careers. They are understandably concerned about the negative repercussions failure can have on all three.
At Sight Machine, we’ve had seven years of experience successfully deploying our data-and- AI-powered manufacturing analytics platform for hundreds of leading enterprises. After thinking long and hard about risk, we’ve created a very specific, targeted, and highly effective counter-strategy. This strategy replaces the three risk factors with a well-grounded framework that guides you safely away from the piloting merry-go-round and lets you embrace game-changing technology in a meaningful way. Our approach combines financial incentives, innovative means of sharing best practices, and a blend of training, change management, and data adoption services from experts who’ve achieved dramatic success. In future blogs we’ll delve deeply into each type of risk and how we alleviate it.
So watch this space. Or better yet, engage with us now for an honest, realistic, and in-depth discussion about risk. I promise to show you a set of compelling risk-centric remedies and resources you haven’t encountered before. To learn all about them, please contact me personally at firstname.lastname@example.org.