LIMS Master Data
October 25, 2019
Globalization and outsourcing trends, along with technological advancements that have dramatically increased the volume, complexity and variety of data, have created significant data management challenges for modern scientific laboratories. Most laboratories have responded to these challenges by implementing a Laboratory Information Management System (LIMS) that automates business processes and data capture associated with laboratory workflows. With these systems comes vast amounts of data. Ensuring you are managing your LIMS Master Data properly begins with understanding the key terms
LIMS implementations usually demand a substantial investment of time, money and resources, typically costing hundreds of thousands to millions of dollars and requiring hundreds of person days to accomplish. Failure of a LIMS project can be a huge waste of time and resources, and a financial disaster for the organization involved. As such, it is critical to get a LIMS implementation right the first time in order to preserve your return on investment.
One important facet of any successful LIMS implementation and/or migration is the design and configuration of master data. In our experience, many companies involved in LIMS implementations tend to focus on software testing and configuration and put off dealing with master data until the end of the project. This is a huge mistake. Master data design and configuration is typically a much bigger job than anticipated and has multimillion-dollar impacts down the road on things like operational efficiency, time to market and LIMS return on investment (ROI).
In an effort to help organizations understand the importance and implications of master data and avoid project delays and cost overruns, we’ve put together a series of articles to highlight LIMS master data best practices. Some of the topics that will be covered in future articles in this series include:
- Master data configuration pitfalls
- Extrapolation of master data from your current paper records
- Master data naming conventions
- Strategies for handling master data in mergers and acquisitions (M&As)
- Designing your master data for maintainability and scalability
- Evolution of master data and change management
- Master data quality control
- Master data harmonization
In this part 1 article of our LIMS master data series, we’ll define master data and discuss the importance of developing a master data plan for your LIMS implementation. Without further ado, let’s dive into our LIMS master data series!
What is Master Data?
Master data can be thought of as the information that needs to be in place in the LIMS for users to be able to use the system as intended. Master data is core, top-level, non-transactional, static data that will be stored in disparate systems and shared across the enterprise, and possibly even beyond to external partners. As master data establishes a standard definition for business-critical data, its accuracy is very important, because it collectively represents a common point of reference and “single source of truth” for your organization. As such, everyone across the organization must agree on master data definitions, standards, accuracy, and authority.
Within most LIMS applications, there are two types of data that come into play – static (defined) and dynamic (transactional data). Dynamic data is the data users enter into the system as part of their daily activities such as test results, samples, batches or lots of a product. The master data is typically the static data that defines the structure of the system.
Master data and dynamic data are connected in the sense that the only way that dynamic data can be created is if master data already exists in the system. For example, in order to record a sample of a product for testing (transactional data) in a LIMS, the product name (master data) must exist in the LIMS so that the sample can be associated with a particular product in the system.
In most LIMS applications, various templates provide the ability to house the master data as lists/tables of values that will be used throughout the system. Master data typically includes core data entities like products, materials, specifications, sample types, analyses, lists, locations, reagents, instruments, environmental monitoring schedules, stability protocol templates and users. That said, universal specifications of master data items are not possible, as different laboratory types and/or LIMS will typically have different objects/entities identified as the master data.
Master data is foundational to business success. Even minor issues with master data can cause significant operational problems, and these problems will only be magnified as the organization scales, or reintroduced anytime new products or facilities are implemented. In order to avoid project delays and cost overruns for a LIMS implementation, it is critical to design and configure the master data properly. Towards this end, every LIMS implementation project should include a comprehensive Master Data Plan to ensure success.
Creating a Master Data Plan
In order to ensure a successful LIMS implementation, it is important to create a well thought out Master Data Plan that includes collecting all the master data that needs to be entered, deciding on a testing strategy to verify that the data has been entered accurately, creating a proper naming convention for your master data, and having an appropriate amount of time scheduled for entering the data into the system and testing it.
A Master Data Plan is a formal document that identifies the following:
- The rational for different aspects of the plan (e.g., why you have a specific naming convention)
- List of the organization’s master data that needs to be put into the system
- Schedule for when specific tasks need to be done
- The place(s) where the master data is created
- The people who will be doing the work of entering and testing the data. Note that these people need to have appropriate training for the job.
- How data is transferred into the system (e.g., the data migration plan)
One of the most important aspects of the Master Data Plan is determining what data needs to go into the system. This will involve scheduling an assessment of your data to determine what needs to be classified as master data, and also the master data entities in the LIMS being implemented to know which ones you will use and how. Note that this assessment may be utilized as an opportunity for you to do some housecleaning on your data. For example, you may decide not to add in master data for any test older than 5 years.
Another important feature of the Plan should be deciding on a naming convention. Here, it is important to get agreement on master data naming conventions amongst your user base so that they will be able to easily search for the data they need. Additionally, in organizations with multiple sites, using naming conventions that allow users to find their site-specific master data is crucial.
In a regulated environment, testing and documentation of testing may need to be included as part of your validation package. Towards this end, it is important that the person who tests the master data be different than the person who creates it. The person who does the testing must also have an understanding of the data they are testing and be trained in both the testing procedure and how the test results need to be documented. In addition, the Master Data Plan should document the procedure for updating master data in the system when necessary.
Your organization’s master data should serve to reduce the cost and time to integrate new facilities and enhance your organization’s flexibility to comply with regulations or enter new markets successfully. Over time, the master data contained in your LIMS will likely expand as your business expands with new products, facilities and regulatory bodies. Efficient master data management (MDM) will thus become critical to your operations. Be sure to tune in for the remaining parts of our master data series, where we will discuss the important best practices necessary to ensure your master data is designed and configured to deliver maximum business value for your organization.
Astrix is a laboratory informatics consulting firm that has been serving the scientific community since 1995. Our experienced professionals help implement innovative solutions that allow organizations to turn data into knowledge, increase organizational efficiency, improve quality and facilitate regulatory compliance. If you have any questions about our service offerings, or if you would like have an initial, no obligations consultation with an Astrix informatics expert to discuss your master data strategy or LIMS implementation project, don’t hesitate to contact us.