Many process manufacturing companies are on the path to digitization and have piloted analytics to improve operational performance and improve their competitive edge.
While some of those projects may have failed, the promise of digitization and the successes of peers in the industry fuel managers’ desire to make analytics-driven decision-making possible: They want smart factories. But what is a smart factory and how do you create one?
A true smart factory uses all the data available, in combination with human expertise, to improve business outcomes.
This requires the democratization of data where each user has direct access to relevant captured data. It also requires the democratization analytics where users can take information out of the available data.
When both the data (often stored in the data silos of various business applications) and analytics are put into the hands of the business users, the users can truly make data-driven decisions at scale.
This step is key to the success of a smart factory and applies throughout the entire organization. But it is often the case that the production department has already gathered years of operational data.
Big data holds a wealth of opportunities to improve operational performance—if the data is put in the hands of the process experts.
It is these people who have the production knowledge and experience to understand what it is telling.
They are the ones who know about what is happening with production and who can interpret the data if given the chance.
With today’s easy-to-use, self-service industrial analytics tools, these experts can analyze the data themselves and contribute directly to improving business outcomes, without the help of data scientists. They can contribute to achieving operational and team excellence.
One example where this is happening is within Lanxess, a global specialty chemicals company based in Cologne, Germany.
Lanxess launched its digitalization initiative in 2017 with the goal of becoming the digital leader in the chemical industry.
Its initiative was focused on digitalizing and energizing the entire company value chain and its production facilities.
This initiative included empowering its process experts with a self-service industrial analytics software.
With this tool, the company experts could make data-driven decisions that increased plant capacity, maximized resource efficiency and lowered costs.
The results? Savings of up to six figures within the first six months.
“Thus far, Lanxess has significantly increased its capacity utilization, optimized resource efficiency, and reduced maintenance costs,” said Jörg Hellwig, chief digital officer at Lanxess.
“The digital transformation also serves to further develop employees,” he added. “Competences in the field of digital data analytics will be essential for chemists and chemical engineers in the future.”
Process manufacturing plants can make the best out of their big data by letting the people who understand this data analyze and interpret it. It’s efficient and valuable.
Building a smart factory is not done overnight. In some cases, it is a journey that can take years.
But as many companies have shown, starting with the use of self-service analytics within the production side of your organization is an excellent way to kick things off.
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