Enterprise resource planning (ERP) systems are rarely designed with scientists in mind, but that doesn’t mean lab managers should ignore them. They can provide data across the organization to help lab managers make decisions, and when connected to lab software platforms like LIMS, they can automate menial processes, in turn eliminating errors and accelerating workflows. Understanding how and when to bridge these systems can help labs improve operations without overwhelming teams or budgets.

What is an ERP?

In short, “ERP software helps businesses track the quantity and status of various materials and components within a company,” says Caleb Short, a software engineer with expertise in developing ERP systems. Just as an LIMS enables scientists to track samples across the lab, ERPs enable users from across the organization to track manufacturing materials and project statuses. With this data, users can make more effective decisions and understand where their work fits into the overall picture. In short, the ERP acts as a single source of truth.

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The value of an ERP changes depending on the user. Individual contributors add, read, and update records in it, managers use it to track project statuses, and executive leaders use it to make high-level, data-driven business decisions.

To draw an example:

Let’s say the executive leadership at a large corporation wants to make more effective decisions around laboratory priorities, so they consult the ERP. The ERP pulls valuable data from several departments:

• Finance sends payroll info, time to fulfill invoices, and revenue tracking metrics    .
• Production sends throughput data, quotas met, rate of errors, and manufacturing equipment maintenance and downtime information.
• The research lab sends time spent on projects, consumables consumption rate, and equipment maintenance/downtime data.

Armed with this information, the company’s leadership is equipped to forecast operational needs, allocate resources more effectively, and project the effects of their decisions across the organization.

In a similar vein, lab managers can use the ERP in resource planning, project prioritization, and more. Staff benefit from the ease of communication and having a single source of truth for projects.

Additionally, the visibility that an ERP offers can help lab managers justify budget requests, align spending with strategic goals, and clearly communicate the lab’s financial status to organizational leadership.

Furthermore, an ERP enhances project management by offering a centralized platform for tracking project timelines, resource allocation, and team workloads. Lab managers and staff alike can gain real-time insights into project statuses, improving communication with stakeholders and enhancing overall lab productivity.

All of these benefits are compounded if labs bridge their LIMS with the organization’s ERP. Connecting the platforms more than streamlines communication; it automates communication.

Integrating the LIMS and the ERP

Tina Yauger, principal LIMS consultant at Clarkston Consultants, worked with a gene therapy company to tie together their ERP and LIMS. When staff in one department created orders in the ERP, the integration would automatically send the order to the LIMS for lab staff to start working on.

Once implemented, this integration automated a small but significant step in the process. The risk of communication breakdowns leading to missed orders and dissatisfied clients was now negated. “With any automation,” Yauger says, “it’s going to benefit efficiency in the lab, productivity in the lab . . . It’s going to take some risk of error out of the way.”

Yauger and her team then took the integration a step further. Because the ERP and the LIMS were bridged by a custom API, they were able to configure the connection to automatically import the sample plan as well, associating the order with the proper tests and other specifications needed to fulfill it. This configuration further reduced back-and-forth communication between departments, allowing ERP data to remain current with real-time lab operations.

When to integrate the LIMS and ERP

One of the best times to integrate a LIMS and ERP “is when you’re on the cusp of going commercial,” Yauger says. She explains that once an organization switches from R&D to commercial offerings, it consumes more raw materials and produces end products at a higher, but more consistent, rate. The variability of R&D is what complicates integrating LIMS and ERPs initially, but commercial production will be consistent enough to justify the time and expense of integration. For labs embedded in organizations that have long since gone commercial, this endeavor may be overdue.

Regardless of whether your organization is on the cusp or has already gone commercial, there are some hurdles you may encounter when integrating your LIMS with the ERP.

The challenges of integrating LIMS and ERP

Integrating an ERP will necessitate standardizing processes across departments. For organizations acclimated to working in a flexible R&D mode, driving this change may prove difficult. “[Lab managers] definitely need to have key stakeholders of the organization involved,” Yauger says. Key stakeholders may include:

• Leadership, who will fund the project,
• Lab staff, whose jobs will be affected, and
• IT personnel, who will execute the project.

Depending on your organization’s workflows, you may need to secure buy-in from other departments.

Budget, Yauger adds, is another significant factor to consider, particularly if you need a custom API developed like her client did. The projected ROI must justify the cost of investment. Your business case to leadership may hinge on this factor.

The integration itself will depend on the specific ERP and LIMS platforms in use. Some pairings may be able to communicate natively. Others may offer official APIs for a relatively pain-free way to connect them. Different situations, like in Yauger’s case, may require custom APIs to be built by contracted software developers.

Integrating a LIMS with an ERP is a strategic move that can help labs scale effectively, reduce errors, and improve visibility across departments. While the transition demands careful planning, collaboration, and investment, the long-term benefits can transform a lab from an isolated data source into a key source of insight.