Don’t start cleansing data yet!

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Data is a fickle beast.

One minute, you have amazing dashboards and reports… your finance nerds are seeing into the future with clarity a weather man can only wish to have…the next minute, you have gremlins everywhere causing chaos in the most basic of processes and you can only give accurate forecasts for five minutes in the past.

Don't feed data analysts after midnight!

All your data are belong to us!

I suspect this has been happening since mankind developed the first CRM, which was on Oracle Clay Tablets.

Oracle V1

You should see the servers needed for this!

Having been on many data cleansing projects in the past, with many more in my future, I decided to sketch out some ideas I have picked up along the way. Don’t worry, I will go back to my techie salesforce nerd stuff next week!

“It is a never ending story”

Cleansing data is not a project with a start and an end, it is a process that needs to be ongoing. If you have data coming in, you will have data that needs to be cleaned. Build it into your budget, chant the mantra, do whatever it takes, but embrace the fact that as long as you are around any CRM you will be doing data clean up.

“Business Involvement”

Even though dirty data and data cleansing will never go away, it will become a smaller task once you get your users sold on the idea of clean data. At the very least, you need your users to care about the system at the best they will become advocates of clean data. Boeing used to have a program called “FOD FREE”. FOD is “Foreign Object Damage” and it prompted their employees to be active in keeping the work environment clean. It was a huge success through marketing and  engagement, AKA, Business Involvement.

“Clean with a Purpose”

There are two methods to getting business involvement in data cleansing, carrot and stick. Personally, I prefer the carrot approach. Know why you are doing it, and be able to explain that to the business. Tell them in “What’s In It For Me” (WIFM) terminology why their data is changing and what outcomes they can expect. Have them involved in any process modifications or validation rule building. If you get them at least interested in clean data the process will be much less contentious.

“Know your Data”

Seriously, run some DANG reports. Know the numbers because someone will ask. Know the up and downstream impacts of dirty data. Know use cases. Have a really nice power point set explaining this things, and gear the presentations to different user levels. If you do not  know your data, how can you clean it???

On a side note, I swear by “You suck at powerpoint” as a great learning aid around presentations!

“Classify your Data”

Classifying data is just chunking up your data into sound bite groupings. The key here is “Sound Bite”. You can say something awesome like “Customers with an account that has at least 3 contacts that all have been sent an email in the past three years”, but after the first couple words, all anyone will hear is “blah blah blah”. Instead, have sound bite ready classifications. Thinking in “Sound Bite” terms will also help with reporting and formula writing, covered next week!

Here are some suggestions for accounts:

Primary = Customer, Non Customer

Secondary = Active (Open Pipeline), Non Active (No Pipeline)

Tertiary = Marketable (Contacts with Email), Non Marketable (Contacts without Email)

It’s looking a lot like Christmas (Sigh)

What really gets me excited about classifications is that it helps you NOT boil the ocean. It is not unrealistic to have hundreds of thousands of account records, and if you were to set about trying to clean them ALL, you would be wasting time and money on records that really are the equivalent to that fruitcake you got last year. It is just taking up space, but you don’t want to throw it out because someday you might have a reason to use (re-gift) it.

fruitcake

Yes, I did just compare your data to an old fruitcake

The above tips are not the end all be all, just things I have picked up along my career. But, if you are rolling into the discussion on data clean up just keeping these in mind you will be at a point where you have the business engaged in the ongoing process of data cleansing on a known set of data that involve a set of agreed upon classifications…or, in other words, you will be setup for success!

Oh, and now that this stuff is out of the way, we can get back to more techie stuff next week!

 

Andrew

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