Three Steps to Extracting Value from Legacy EAM Systems

SAP professionals understand the enormous power and investment required to implement an enterprise asset management (EAM) system. Yet, with the current technology landscape, many professionals in the manufacturing industry face the pressure of wringing more value from their assets, boosting production, and reducing costs without resorting to expensive and risky rip-and-replace projects. The question remains; how do you unlock new value from the system you already have?

According to Robert Hancock, Global VP of Sales at Sigga Technologies, the answer lies in a new strategy. In a recent webinar, Hancock identified three critical, often-overlooked hurdles that derail digital projects. Overcoming them is the key to breathing new life into a legacy SAP EAM.

1. The Human Factor

The costliest mistake many plants make is treating a technology rollout as a simple IT task. Hancock shared the example of a shingle manufacturer that deployed a mobile solution, only to find out six months later that technicians weren’t using it.

“Somebody showed up one day and said, ‘Here’s your mobile device, and here’s this mobile solution, here’s the training we expect you to use it,’” Hancock explained. “And so [the technicians] felt like it was dropped on them at the last moment and were very ill-prepared.”

The fix for this issue means a fundamental shift in approach. Hancock urged leaders to get those users engaged at an early stage. “Advertise that you’re thinking about these things, collect feedback from them and then socialize those solutions,” he said.

2. The One-Size-Fits-None Trap

All plants have different equipment, different processes, and different levels of digital maturity. However, many companies design a single, standardized solution and expect it to work everywhere. This is the lowest common denominator trap, according to Hancock.

He warned that plants are expected not only to adopt new technology, but also to implement new and more mature processes. “This is a recipe for failure,” Hancock said. Conversely, designing for the least mature plant will underwhelm and frustrate high-performers.

The solution is flexibility. Start by grouping sites by maturity or function. Then, leverage modern tools to tailor the experience to the needs. Hancock advocated for no-code platforms that enable personnel within those plant environments to adjust those solutions on their own. This empowers local champions to configure a user interface that fits their specific workflow, turning a rigid, top-down mandate into a flexible, ground-up tool.

3. The Data Dilemma

Before a plant can leverage powerful technologies like AI and advanced analytics, it must confront its data quality. Hancock recalled an oil and gas client struggling to understand why 60% of its scheduled jobs failed to finish on time. When the team analyzed the data, they found over 1,000 unique reasons in the system.

After cleansing the data, the company discovered that 80% of the failures were due to multiple entries, such as “parts,” in the free text field. This insight was impossible to glean from the messy, disorganized free-text entries. Thus, to truly leverage advanced technology, Hancock noted:

1. Understand exactly what data you need to achieve your goal.
2. Assess the health and structure of your existing data.
3. Standardize messy fields into a uniform format.
4. Replace free-text fields with structured dropdowns and mandatory fields to ensure clean data going forward.

Hancock concluded, “By focusing on your people, embracing flexible processes, and ensuring data integrity, you can stop chasing expensive new systems and start extracting the immense value that’s been waiting there all along.”

What This Means for SAPinsiders

Embrace no-code to empower your team. The difference between low-code and no-code is significant. Low-code still requires a developer. However, no-code platforms are designed for business users. For SAP-specific maintenance processes, a no-code solution enables the team to rapidly configure and deploy a mobile app that exactly meets its needs without waiting in an IT queue.

Use Mobile EAM as the cure for bad data. Hancock argued that paper-based processes are the primary source of bad data. Technicians scribble illegible notes or provide vague, free-text reasons for failures. A well-designed mobile EAM solution like Sigga forces data discipline at the source. By replacing free-text fields with structured dropdowns and mandatory inputs, a team ensures that clean, accurate, and consistent data enters the SAP system from the moment the work is performed.

Start small and be patient to succeed with AI. Select one specific, high-value problem, such as predicting failures for a single critical asset type. Then, gather a deep and relevant dataset for that problem alone. SAP professionals require sufficient clean data over an extended period for the AI to learn accurately. Prove the concept on a small scale, demonstrate the ROI, and then expand AI initiatives from there.