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February 14 ∙ 4 min read

Here's Why Most Start-Ups Fail in the First 5 Years



Data Management

Data Quality


why most start-ups fail

Ever seen dead wood? 

Chances are you have, unless you’ve been living under a very big rock. Dead wood refers to branches or parts of a tree that have decayed and shrivelled up.  

Now if they stay on the tree, they cover the parts of it that are still alive. Not to mention, they’re probably adding a lot of unnecessary weight. 

So it’s no surprise that dead wood is also used to describe objects or processes that are no longer useful or productive to an organisation. As Marie Kondo once said: if it does not bring joy, get rid of it! 


And to draw that connection between dead wood and your business, dead wood data has some serious effects: 

  • It’s costing a lot of money. Yep, those dead bytes aren’t just sitting there; they’re burning through the budget by affecting the accuracy and speed of marketing campaigns, threatening customer satisfaction, and skewing strategic insights. 
  • It’s messing with everyone’s head. Trying to make sense of data when half of it is useless is like trying to read a book where every other page is blank! 
  • It’s killing the vibe. In any business struggling with dead wood is a bunch of people who could be doing better stuff, like maybe their actual job…but instead, they’re wading through all that data sludge. 

So while it’s much easier to detect out in the real world, how does one identify dead wood in a database? And what are some tips and tricks, or best practices, to getting rid of all that unnecessary weight? 

The curse of dead wood data

You’re reading the right blog if one of the following descriptions of data applies to your database: 

  1. It’s somehow incomplete, like it has a Name, but no Address and Phone.  It could have an Initial + Surname + Address, but since your organisation only attempts outbound calls, the record is ineffective at meeting your organisation’s goals. 
  2. It could be a record that for all intents and purposes is complete but has been marked as Disconnected by the Phone Room/Dialler, and/or marked as Return to Sender (RTS) by the mail house. 
  3. You could’ve been advised that the person you’re attempting to correspond with is deceased. 
  4. A record that is more current, which makes another record redundant. 
  5. Basic duplication of data, such as multiples of the same person at the same address and/or phone number 

Another example of dead wood data is information that isn’t dead but becoming less relevant: 

  1. Customers that you haven’t had interactions with, within the last five years 
  2. Transactional records, even for existing customers, that are more than 10 years old 
  3. Prospects that don’t meet your target criteria in any way.  

Once a business decides they’re finally sick of running their team raw and spending thousands of dollars on marketing campaigns that don’t reach the right audience, insights that are more stress-inducing than strategic, and pissed-off teammates who must turn into impromptu data specialists on top of their actual jobs…they’re finally ready to start losing all that dead weight. 

And that means investing in a good data management and maintenance system! 

Turning lean seasons into clean seasons

Now, when’s a good time to carve out all that extra weight? 

Think of when “low” seasons are for business and work back from that date. This date differs from one business to another. The point is that the project needs to begin and end in a time frame that won’t make it too difficult for business continuity.  

Some organisations may even need to run everything in the data cleansing process twice. While it may sound like overkill, this makes perfect sense for a database that needs to be accessed nearly 24/7. Bringing the whole thing down to perform serious maintenance can be a nightmare. But if the update is performed in a sandbox, then the team can work on all the heavy-duty debugging they need to do.  

And then once they’re satisfied with the update, then it can be moved to the live, actual database at a time that won’t affect business activities too much. That’s all the maintenance needed for the system completed at a fraction of the time, effort, and money required. 

A database that sparks joy

A clean database means better decisions, faster moves, and ultimately, more cash in the pocket. But the real challenge is in making sure that it’s maintained regularly. Quarterly? Annually? Twice a year? Frequency will depend on the kind of business you run, the volumes of data you work with, and your budget for the whole operation.  

It’s time to suit up and turn all that dead wood into dead meat.  

Let’s figure out how all this work can be made easy for your business here.  

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