Trusting the Data

Since our company’s solutions source data for our customer’s reporting & activity decisions, I’m a huge proponent of trustworthy data. You would think that understanding the reference “trustworthy data” would be relatively straightforward. The reality is that those two words have created a life of their own recently with the availability social media and the mass of information on the internet then add more traditional sources like the national media into the mix.

It seems that everyone today has some position and/or skepticism on how “trustworthy” the information they’re reading or hearing really is. So what is “trustworthy data”? The definition is a little more broad than just “is it true?”

I was very excited earlier early this month that my St. Louis Cardinals were Division Leaders in the Central Division. Naturally, I immediately sent that update to all (both) of my Cubs friends to let them know that 2017 is a new year! Of course our Division lead only lasted 3 days until the Cubs completed winning the final 2 games of the opening series. Now my Cardinals are in last place and already 4 games behind the Reds.  Grr…at least it’s only April…

While my data for this excitement with the Cardinal leadership came from a trusted source (ESPN) – and was true – it wasn’t exactly data that I should use to place a call to Vegas and take action. If the driving purpose for that data was to help me determine if my Cardinals would be in the Playoffs come October, it was a little too early.

One of the keys to any useful data is its age in relationship to its purpose. In the case above, the excitement with 2 games of data against a 162 game season was a little premature. The data was true – at the beginning of the month. But that data shouldn’t be trusted for things like placing bets on the Playoffs.

So when you’re looking at whether data is “trustworthy”, you need to look at the purpose for the data and information – and then the age of the data. Because depending on how you are going to use those facts, age can have a pretty influential impact. But that age has a different level of impact based on the purpose that you have for it.

For example, when we’re leveraging source data collection with a warehouse operation, we’re making real-time decisions based on the data captured. During asset inventory activities, we’re generally using the data for verification and information based on a certain place in time for reporting or planning.

In earlier posts, I’ve talked before about the importance of getting the purposes and goals of the data locked down – and how they can determine the path. The path being the how and why portion of the project that creates the “trustworthy data”. Trustworthy data is then created when you combine accurate (barcodes, RFID etc.) data harvesting with verifiable sources – completed in the right timeframe – and suitable to how the data will be used.

  • In the Warehouse I need the forklift driver to tell me ASAP when my material is now ready for action.
  • In Asset Management it may be OK with the end-of day, week, month or year depending on the use.

While I would love to see my Cards in the Playoff’s come October, the only data that will be meaningful in predicting that won’t be showing up until September when they’re leading the division or have a chance based on the WCGB# (Wild Card Games Behind).

Yes, you can trust your data. Just make sure it is the right data, captured without errors and shared in the timely manner required for how you’re going to use it.

It sounds more complicated than it really is. Interested in looking at your data? Let’s talk.

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