From Automation to Intelligence: How Siemens Energy Uses Alteryx and AI to Power the World's Energy Future

At Siemens Energy, data is everywhere. Across factories, procurement teams, and operational functions, it drives decisions that affect supply chains, production, and ultimately the delivery of energy around the world.

But turning that data into action required enormous manual effort. What began as one team’s push to make analytics more accessible has grown into a broader transformation powered by Alteryx — one that helped Siemens Energy build a network of smarter factories, empower thousands of users, and create a culture of automation.

Siloed data, spreadsheet overload

The teams at Siemens Energy were working with data across a fragmented environment that included SAP, Salesforce, AWS, factory-level systems, and local databases.

In the Power Transmission business alone, geographically distributed factories were generating large volumes of production, logistics, and financial data, often stored separately and managed manually. That fragmentation made it difficult to move quickly, get timely visibility, or scale insights across the business.

Ensuring data quality, visibility, and trust was also a challenge. “If the data quality does not reach a certain level, we cannot trust our dashboards,” said Max Johann, Data and Process Analyst at Siemens Energy.

And as digitalization efforts accelerated, the business needed a way to democratize access to trusted data and reduce its dependency on labor-intensive reporting.

Building a citizen development engine with Alteryx

To break the cycle of manual reporting and fragmented data, Siemens Energy turned to Alteryx and started with practical wins. One of the first Alteryx projects automated a weekly cash-in report. From there, the team moved into more advanced workflows, automating forecasting reports for up to 30 projects and a group of commercial project managers at a time.

“With Alteryx, domain expertise becomes more important than IT skills,” says Kessler. “The business user can build their own workflows and solutions at high speed based on their needs, and then it can be made available to everyone.”

Very quickly, Alteryx proved it could become the foundation for a more scalable analytics model. That model took shape through what Siemens Energy calls Citizen Development: enabling nontraditional coders to build solutions using low-code analytics tools.

Siemens Energy paired that mindset with stronger access to data through the SE Data Center, an Alteryx macro connected to Snowflake that replicates raw SAP data every 20 minutes.

Instead of waiting on requests or exporting massive reports, users could work with near real-time data inside a governed environment with row-level security. This combination of self-service access, automation, and guardrails made it possible to scale from a few use cases to hundreds.

Automating procurement end-to-end

A standout example is the Procurement Cockpit, an end-to-end dashboard suite powered by Snowflake, Alteryx, and Tableau. It gives operational buyers and procurement teams real-time visibility into the procurement lifecycle. “For each main step in the procurement process, from the initial demand to goods received, we have a tailored solution for our network of factories, all supported by Alteryx,” said Ana-Maria Cuciuc, Senior Domain Data & Process Analyst at Siemens Energy.

Alteryx workflows automate the data preparation and process triggers behind the scenes, including the automatic sending of 600 supplier emails every week. The solution replaced dozens of manual reports with one intuitive interface and helped improve SAP data hygiene, monitoring, and decision-making at scale.

AI-powered document intelligence

Siemens Energy extended that same Alteryx-centered approach into AI. By integrating Alteryx with Snowflake and LLMs, the team developed an AI-powered chatbot that allows users to query full document repositories, including technical manuals, handwritten notes, and other non-digitized content. Reading through these 723,000 pages of documentation would take an employee over 36,000 hours of full-time reading — more than four years.

What started as a shop-floor application is now being used across finance. The underpinning AI solution is the same; it’s simply the training data for their internal LLMs that was swapped out, unlocking even more efficiencies.

From time savings to a company-wide analytics movement

What began as a single automated cash report has grown into one of the more far-reaching analytics transformations in the energy industry. In just a few years, Siemens Energy scaled from 100 users to 2,500 and from a handful of workflows to 350 automated solutions that saved more than 500,000 hours in just a few years.

The procurement cockpit now runs across 20 factories in nine countries, saving more than 150,000 hours annually. That solution also became a blueprint the organization can adapt across more factories and more functions.

Scaling adoption and pushing further into AI

The team continues to scale automation across the business, with hundreds of use cases still in the pipeline and a clear focus on making analytics more accessible to more people.

That future includes broader reuse of proven solutions, more co-creation across functions, and more experimentation with low-code and AI-powered tools. The team is especially optimistic because these technologies lower the barrier to entry.

The Siemens Energy story is proof that with the right tools, the right mindset, and the right community, the scale of transformation is unlimited.

You can learn more about the Siemens Energy success story in this e-book: Transforming with Data: The Siemens Energy Analytics Journey