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Increasing Data Scope with Your Quality Systems Implementation

Last week, I shared some of the most common reasons that our clients find they aren’t getting the value they had hoped for from their quality systems, but I made a serious omission. Ironically, my omission was omission. Omitting data conversion, incomplete data migration, and partial load of record types leaves incomplete systems and underwhelming value. In this piece, I want to share the importance of increasing data scope with your quality systems implementation. 

It’s understandable that projects take a minimum viable product approach to system implementation. It’s cost-conscious, efficient, and frequently helps with usability and long-term adoption. That said, quality systems get their value from two aspects. First, functional scope. Functional scope is made up of the business processes that the system helps enable. Second, is the data scope – the types of documents, products, analyses, equipment and so on that the system includes. It’s possible to have the first and only part of the second. For example, you could implement document management, but only have SOPs in scope and not work instructions or forms. Or you could implement product management in your ERP and LIMS, but only include final product specifications and not raw materials. 

What’s the Impact of Data Scope Omissions? 

We’ve partnered with a lot of clients to help make these scope decisions. There are several trade-offs to consider with regards to where your business needs the most value. Sometimes, it makes sense to reduce functional scope and increase data scope. Other times, we find the inverse. Either way, at the end of the implementation, most companies have compromised and omitted some level of data scope that they commit to come back to later.   

The best analogy for this may be building a house. You decide to build a dining room (your functional scope) even though you don’t have the furniture yet and maybe you mostly eat in the kitchen. But, at some point, you plan to buy the furniture for the dining room (expand the data scope) and use it to its fullest. Unfortunately, without the furniture, the dining room is an expensive empty box. 

The systems most commonly impacted by data scope omissions are laboratory informatics systems. They can be expensive, empty boxes without the relevant data. The most common data types that the clients may have previously compromised on but would now see value from investing in are: 

  • Product Specifications and Analyses 
  • Additional Sample Types (Training, Validation, Cleaning) 
  • Instruments 
  • Standards and Reagents 

Increasing Your Data Scope: Quality Systems Implementation

If this all sounds very familiar, maybe it’s time to invest in increasing your data scope. There are a few ways to go about it. 

  1. Invest in data conversion. Frequently this data isn’t just on paper; instead, it’s in a legacy system. Instead of re-building everything in the target system, work with a partner that can help with data conversion and migration. While there’s some upfront work on technical build and validation, the return on investment is very high. Clarkston takes best practices from years of massive ERP implementations and applies them to quality systems to create tremendous efficiencies and very high data quality. 
  2. Outsource master data build. Master data build can be tedious. It takes laboratory knowledge, high attention to detail, and technical expertise. Consider using a partner that specializes in this type of data building. It can be an efficient and effective way to increase data scope without burning out your team. 
  3. Reevaluate data. Sometimes data objects themselves have automation or functionality built in that is adding complexity, slowing data load, and increasing implementation cost. For example, maybe analyses are taking a long time to build because of all of the calculations that are automated and the different pick lists that help the users navigate. It’s important to evaluate if all that functionality that’s adding complexity to data load and also slowing the value realization is coming at a cost that your organization isn’t willing to pay. 

If you compromised before, what’s the reason to invest now? There are some leading reasons. It’s worth it to go ahead and buy the dining room furniture, or in this case, expand the data scope, which can help you: 

  • Increase data integrity and prepare for audit or inspection: Whether you’re closing data integrity gaps or preparing for inspection, your system may not be addressing the risks or gaps you’re claiming unless you’re using it for all of your products and sample types.  
  • Address labor shortages: Vacancies still exist in quality departments and hiring is still tough.  One of the ways to do more with less is by increasing the scope of enabling systems through completing the data load. 
  • Make cost-conscious improvements: IT budgets are limited for many clients right now for a variety of reasons. Increasing the data scope is a cost-effective improvement that will have real business value – often much more tangible value than an upgrade or the few functionality enhancements that a limited budget might otherwise cover. 
  • Data transparently and availability: By completing the load of your data, you’ll finally have full transparency to your data and the availability for reporting, trending, and decision-making. 

If you’re thinking of increasing your data scope, our team at Clarkston Technology Solutions has the experience with master data building to help.  

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Tags: Data Quality, Quality Management Systems