Many businesses were drowning in data even before the pandemic moved everything online. It’s been a recurring topic of interest for the entire C-suite how to maximise the value of owned data - and extract the insight and value hidden within.
Yet even for those who are investing efficiently in the data teams, systems and processes to unlock and make use of often complex datasets, there remains an issue of its ongoing hygiene. For whilst data can exist in a vacuum, the need for properly instituted data management has only grown in recent months - as both the volume of data being managed and the competitive business environment (amidst testing economic conditions for many) have also surged.
Of course, data management is a hugely broad area, but one area that’s receiving greater focus is Master Data and the data management subset of Master Data Management (MDM). So what is it - and why is it important for a business to get on top of?
Each category has its own unique attributes and characteristics. For example, for a customer’s master data, we might include: first name, last name, address, postcode, buyer type, and any contracts or SLAs they may have signed.
Factoring in each sub-category, this can result in a large amount of business-critical data. It’s not rocket science to know that keeping accurate, readily available information on customers, products and location is essential for everyone across a business, from engineers to finance, marketing and sales etc.
If Master Data’s importance is clear, it’s efficacy within many businesses isn’t. Many databases we come across, even within a single system/application, can have confusing, duplicated master data.
A customer record may have addresses that don’t match, or only include part of the name. A phone number might be stored in two different formats, with and without international dialling code for example. It becomes possible that systems this master data is being fed into can’t make use of it, if - as is likely - they don’t recognise certain formats of stored information.
One of the main issues affecting MDM is where siloed, unsynchronised systems lead to a particular customer being created, then recreated and possibly modified, leading to multiple entries for the same customer. Any missing data, inconsistent formatting, or incorrect spellings can lead to these siloed systems (CRM vs. Billing for example) creating unique customer IDs for the same customer.
The knock-on effect of this is an inability to be certain if it’s one or many customers, and it completely undermines the data analysis that can lead to a business unlocking valuable insight on that customer.
