Like a scene from the Jetsons, robots are starting to roam the factory floors and warehouses of some of the world’s biggest manufacturers.
“We’re seeking to automate the world’s dullest, dirtiest and deadliest jobs,” said Ryan Gariepy, CTO and co-founder of the robotics company, OTTO Motors, at a recent ITWC webinar.
The robots use big data and machine learning to do repetitive tasks like moving materials in a warehouse. They also collect a vast amount of data.
It’s an example of how using big data effectively is “the key to productivity in our country,” said Gariepy. “It can have a very real impact right now on industrial manufacturing and warehousing.”
How data analytics transforms organizations
“Data can do so much more than anyone ever realized,” said Erin Banks, a big data and analytics specialist with Dell EMC. Dell EMC works with OTTO Motors to help the company capitalize on the power of big data.
Organizations want to understand why their productivity is not improving, said Gariepy. “Data allows us to answer that question. The key is to make decisions based on as much knowledge about your facility as possible,” he said. The data will tell organizations about the health of their systems so they can do data-driven preventative maintenance. It also provides information about how the system is working. “Previously, factories would put people with stopwatches in critical areas,” said Gariepy. “Now, the analytic systems open up the promise of always understanding what’s going on in your operations.”
For OTTO Motors, data has transformed the business by allowing its staff to have a different dialogue with customers. “When we talk to them, we are more knowledgeable about what we’re contributing to their organization,” said Gariepy. “We don’t want to put a burden on clients to understand where they’re coming from.”
OTTO Motors has also experienced improvements in its own efficiency as a result of data analytics For example, data systems allow it to easily track how many people are using a certain version of its software. “It’s very powerful to give people a new view of their business,” said Gariepy. “It allows them to look at material flow in new ways.”
Getting it right
Many organizations are struggling with how to develop insights based on the vast amounts of data available. The first step is to understand what problem they are trying to solve, said Banks.
“Analytics is a continuous journey,” said Banks. Initially, businesses should focus on generating data from their digital customer interactions, she said. The data should be stored in a single repository so that it can be analyzed as a whole to develop actionable insights. Organizations need to make decisions based on those insights, follow through with action, and make ongoing adjustments, as needed, she added. Finally, they shouldn’t forget about securing their data, so that it is built-in rather than bolted on later.
A change in culture is usually necessary to develop the ability to make decisions based on data, said Banks. Gariepy suggests a two-pronged approach. “Start by building a small amount of data to use as a proof point with the engineering team,” he said. “They will spread the gospel on how to do it.” At the same time, the executives should stress that they want decisions based on data. “It meets in the middle,” said Gariepy.
It’s important to get business and IT to the table to ensure that everyone has a clear understanding of the problem to be solved, said Banks. “If IT doesn’t understand the requirement, there will never be ROI, or, as we call it, return on information.”
To learn more about the importance of analytics in industry, check out the case studies on the Dell EMC Agile Business partner content hub.
