Down and Dirty with Data

Have you heard of dirty data before?  At the most basic level, dirty data impacts the integrity of an entire dataset.  Think spelling mistakes (typos), duplicates, out of date, inaccurate, or often entirely unnecessary records, to name a few.

Dirty data is real, and if you think your MSP doesn't have any, take a look at the contacts in your PSA. See how many of them no longer work for their associated clients.  If you passed that test, maybe review the list of your products and services and notice how many you no longer offer – or no longer even exist from the vendor.

It's something that naturally accumulates over time if not managed, and while it's usually innocent and unintentional – dirty data carries a heavy burden. There are numerous research studies available on data management that have collectively created "the 1-10-100 rule".  The rule states that it costs $1 to maintain a clean record, $10 to clean a dirty record, and $100 to keep a dirty record.

You're probably thinking, "How is that possible?!".  But think about how inaccurate data can influence averages and actuals in reporting by emphasizing red herrings that can impact critical decisions you make for your business. 

Like the butterfly effect, small (but dirty) records can drive wrong decisions, costing money or wasting effort across your team.  After all, you wouldn't try navigating a city you've never been to with a map from a decade previous.  Much like the construction of new communities and transportation infrastructures, the dynamic shifts in your business are constant from clients, users, offerings, suppliers, and pricing.

Here are a few ways you can get a handle on dirty data for your MSP to mitigate the inherent costs:

1)  Review PSA contacts semi-annually

Semi-annually reviewing PSA contacts to ensure they are still employees of your clients. You don't want to be sending invoices to the wrong person, do you?

2)  Review products and services annually

Review all products and service items in your PSA annually to ensure there are no outliers that mislead your financial reporting.

3)  Update product costs regularly

Ensure you update your costs on each current product and service as margins may change depending on price increases or achievement of volume discount tiers.

4)  Review "ticket type" usage annually

Removing unnecessary or duplicate ticket types will help ensure your reporting indicates where time is spent as accurately as possible and where you can mitigate burden for you and your clients.

It’s not the easiest or most enjoyable job.  That’s why so many businesses have lots of dirty data, and why the average cost to clean it is so high.

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