MaximoWorld 2022: It's Music to our Ears

The Uptake team will be at Booth 507 at this year's issue of MaximoWorld 2022, held in the live music capital of the world on Austin 9-11.

Here's ReliabilityWeb’s Publisher and CEO, Terrence O’Hanlon, on what to expect at the show this year.

MaximoWorld 2022

We like what O’Hanlon said about the conversation at MaximoWorld. “The conversation will revolve around cloud, connected data, IoT, AI, machine learning, and digital twins to enhance maintenance, reliability and advance asset management.”

That’s music to our ears. Our products improve maintenance and reliability while helping IBM Maximo users advance asset management. We accomplish this with products that extract data from on-premise environments like historians and SCADA systems and then transfer the data to the cloud for AI, machine learning, digital twins, and other advanced analytics applications.

That’s easier said than done. There are a few challenges with data and the cloud. There are also ways to steer around them.

EAM and APM Require Quality Data

As a Maximo user, having quality data is essential to Enterprise Asset Management (EAM) and Asset Performance Management (APM). Many issues related to bad historian configuration require SMEs and data scientists to validate context. This is especially true with advanced applications like Maximo that run on quality data.

To illustrate, Chevron was challenged by cloud data that was often inconsistent or incomplete. It lacked quality and standardization across business units. Providing Chevron data scientists and engineers with easily retrievable operational data facilitated the continuous improvement of data quality, context, and standardization. Once all the data, time-series data in this case, was in Chevron’s data lake, it was easier to make the data readily available enterprise-wide for analytics, AI, and machine learning, driving smarter decisions for multiple use cases.

It all starts with having quality data, not unlike Papa John’s mantra, “better ingredients, better pizza.” You need quality data for better outcomes with Maximo.

Clarity Comes from Data Granularity

One of the key challenges with data transferred from on-premise to the cloud is a loss in granularity. Time-series data, including years, months, weeks, days, and hours, can arrive in the cloud missing or jumbled. With transactional data, loss in granularity of information can encompass items such as purchase orders and line items.

Come to our booth and chat with Uptake's Jerry Hillard, Joe Becker, and Tia Haggart. They’ll clear things up for you. We’ll demo how to extract not just time-series data but also the associated metadata. Metadata is critical to classifying, organizing, and labeling data. As such, data can be as granular in the cloud as it is on-premise. In fact, you can organize data in your cloud tenant using the same data structure as the source system.

Gaining Equal Access to Complete Datasets

The goal of having clean, complete data in the cloud is the capability of providing equal access to it, whether it’s your Maximo users, other stakeholders, or external resources. All use the same data set to perform advanced analytics. Data that is clean and complete, as well as accessible, accelerates group work and business decision-making.

The issue of data access challenged Enerplus, one of Canada’s largest independent oil and gas producers. Enerplus needed equal access to 22,000 data-producing assets. Having all the asset data stored in the cloud accessible anytime, anywhere increased coordination and collaboration across the organization. As a result, Enerpus is equipped to make data-driven decisions that greatly improve connectivity, efficiency, and scalability, as well as achieve time and cost savings.

We look forward to coming to MaximoWorld and meeting attendees at our booth. We might even take in some of that live music Austin is known for, but the real music to our ears will be conversations around data and cloud that give Maximo users what they need to improve asset maintenance and reliability.

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