In the 21st century, data is the lifeblood of supply chain management, because this is the vehicle to harvest your savings, rein in your utilization misalignments and monitor your contract compliance. However, if your data is corrupted, disorganized and messy it is useless for analytics. Here are three rules you should follow to standardize, normalize and guarantee clean data across your healthcare supply chain:
- Limit free-form entries to an absolute minimum. Free-form entries of products, services and technologies into your MMIS that are supposed to be “one off” are too often listed as such because the person making the freeform entry either doesn’t know the category into which the item fits or is too lazy to find out. If this practice is permitted (free-form entries) to continue, as we have seen it at some healthcare organizations, it will destroy the integrity of your data.
- Establish standards for your data. Without standards or accepted protocols for your data it would be just like the wild west, everyone making their own rules. As you can imagine, this would be total chaos. So, we need rules, like not mingling alphanumeric descriptions together for any reason, or, abbreviation of product, service or technology descriptions in a different way on every entry. Much of this is in common sense, but it needs to be in writing.
- Centralize your data entry under one person or team of people, so you have consistent classifications, categorization and spelling. It is easy to classify, categorize and spell the descriptions of your products, services and technologies differently on every entry, yet, impossible to fix when these entries have been made. Therefore, establish guidelines for your data entry and have them followed to the tee by your data entry person, so that your data is always consistent, reliable and absent of errors.
These are just a few rules to improve the standardization of your data in no time, which is now mission critical to your healthcare supply chain organization. Without pristine data, it is impossible for you to harness the power of your data, statistics, and numbers into effective decision driven information. And if that happens, you are effectively out of business.