How to transform metals data into actionable insights

Andy Suhy, Justin Chambers, Alexander Kujalowicz
| 3/22/2024
How to transform metals data into actionable insights

Metals leaders recognize the value of data and the importance of making their companies strategic, data-driven businesses. To that end, they’ve built IT teams within their companies with the goal of producing valuable insights to help inform future decisions.

Integrating such teams is a step in the right direction. However, turning to data analytics for strategic decision-making can be a complex process – one that requires extensive experience and an advanced skill set in addition to advanced technology. Many metals companies soon realize they’re in over their heads as they try to accomplish this task internally, and they fail to see the results executives are looking for.

When metals leaders understand the process, personnel, and tools needed to extract value from their metals data, they can deploy their IT teams and realize the benefits of data-driven decision-making.

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6 steps to transforming metals data into actionable insights

Transforming raw data into actionable insights is a multifaceted process that involves six steps, all of which are bundled together in our turnkey analytics solution: Crowe Metals Accelerator Analytics.

Step 1: Define end goals

Start by clearly stating what stakeholders want to achieve with data analytics. Identify the problems to be solved.

Step 2: Identify key analytics

Outline the key performance indicators and analytics that decision-makers can use to solve the problems and reach the end goals.

Step 3: Determine the necessary data points

Begin building the model behind the analytics by defining the scope of metals data necessary to generate the analytics and the relationships between these data points.

Step 4: Create technical architecture

Create infrastructure that can efficiently extract metals data, centralize, contextualize, and transform it into the desired analytics. Keep in mind that producing an optimal architecture that incorporates all factors and one that is cost-effective, scalable, extensible, agile, and built for the future requires deep specialization.

Step 5: Generate reports

Develop easy-to-read reports that display the relevant metals data. Tailor these reports to different parts of the business so everyone has access to the insights and can understand how they bring value to each specific area.

Step 6: Train end users

Work toward companywide buy-in, remembering that a data-driven future takes time and effort. Support end users, who typically have their own way of solving problems, by providing specific training as necessary to unleash the potential of the analytics tool and scale it to solve future problems.

Roles, skills, and technology needed for metals data

These six steps comprise a brief overview of the process Crowe specialists use to extract business intelligence and operational analytics from metals data. Companies that want to build their own analytics function can consider the following roles and skills to help fill any gaps existing teams might have.

Analytics visualization architect

The details of each step can get lost without an appointed person who oversees what needs to be done. An analytics visualization architect designs end-state data visualizations that tell a story to lead decision-makers to a solution. This person is creative and understands how end-state analytics can help solve problems.

Data transformation engineer

Moving metals data and changing its format requires someone to confirm accuracy. When data is formatted to connect one piece of information to another, a data transformation engineer can verify that interactions are working properly. This person can also make sure data is organized and accurate, fits together, and can be used easily.

Data integration engineer

When metals data has been moved and reformatted in a useful way, someone needs to make sure it’s being moved around and used properly, especially in big systems. In contrast to the data transformation engineer, who makes sure the data has been moved and connected properly, the data integration engineer confirms that the transformed data is being applied correctly.

Cloud solutions architect

Transforming metals data into actionable insights requires a cloud solutions architect with strong technical skills to oversee the full scope of the process. This person verifies that everything is secure and runs smoothly and is also responsible for the precise architecture described in step four.

Let Crowe help with metals data so you can focus on metals innovation 

These steps, roles, and skill sets can help provide greater clarity and insight into what it takes to transform metals data into actionable insights. With these resources, your metals company can empower leaders to be more strategic and make better business decisions faster.

If you need help at any point in the process, someone to help fill in a knowledge gap, or a better understanding of the technology you need, we’re here to help. We have decades of combined experience working with metals companies, and we’ve built industry-specific systems like Crowe Metals Accelerator Analytics to help companies like yours get the most out of your metals data. Don’t hesitate to reach out with any questions.

Contact us

people
Andy Suhy
Principal, Consulting
Justin Chambers
Justin Chambers
Consulting
Alexander Kujalowicz
Alexander Kujalowicz
Consulting