We rely on data every day but getting to the point of truly relevant data is a process. Relevant customer data is more than who buys from me. It is all of the information that describes the people and companies that you care about, and it is everything related to who made it, who buys it, who uses it, who holds the contract and more.
That breadth of data and the job of maintaining relevancy is met with more than enough obstacles -- one being that collecting and maintain the data is often “a project”, a one-and-done task. When a request to clean up a data base or spreadsheet ends up on the to-do list, most people will start with the easiest questions to answer — update the information on businesses that you transact with on a regular basis, very familiar territory. But what about the ones you don’t regularly engage? Immediately the questions start, wasn’t there a merger between A and B? But then maybe C acquired that entity? Where are they located now, and I’m not sure the contact information is correct?
Sometimes it is just assumed that data is reliable, but obviously just because the data is stored on a computer doesn’t make it valid and correct. The reality is that data is a point in time. Supply chain data has high relevance because it reflects current business transactions, however it is also very time sensitive and starts to erode immediately. Mergers and acquisitions, as referred to above, are happening all the time and information is shifting even while you are in the process of trying to bring your data current. The real world is moving ahead and it impacts your data right away. A percentage of your spreadsheet will be outdated before you can finish.
The cost of trying to keep data relevant is higher than it appears on the surface. So, how do you know if the data you are looking at is relevant?
Here is one methodology for testing the relevancy of your data.
Start with asking questions about your information source. How close is your source to the true reality of the source? Is it coming through a second or third party? How capable is this source of delivering complete and accurate information?
The second question centers around timeliness. Is the data fresh? Is it updated on a regular occurrence and do you know that cadence.
And third, how do you make sure that the data is actually valid in the context of use? Corroboration settles the fact by validating against other data feeds. An item master is a good example, it being things you (in theory) intend to buy or bought at some point. You can corroborate your item master data for source validity and timeliness by looking at PO history, cross referencing contract data and confirming recent purchases.
Investing in quality source data is usually the least challenging obstacle but maintaining fresh data and validating through corroboration are where the real struggle lies. Time and resources aren’t available to update the data as frequently as changes occur and lack of information is the likely obstacle to corroborate data.
We help you keep your data up to date through our network by tapping into a network of relevant information — with real-time feeds from a direct source, corroborated across many connection points and feedback to update your data and keep it accurate and fresh.
What are ways that we can leverage our network of data for you?