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Data Integrity - the Gatekeeper to Automation

August 29, 2018

I’m on a mission. This mission is simply to do more fulfilling work, not just for us but also the businesses I work with.  The problem is that not enough people understand some of the tasks that are holding them back, and one of those that I am most passionate about getting rid of is routine, non-value-added work.

 

Now everyone wants to get rid of the work they don’t like doing, and there are whole industries built on convenience, but when it comes to our day-to-day tasks, we put up with the time-wasting ones because we don’t know how to automate them.

 

So in comes a shining knight selling you a product that will automate a process, a task, an anything you don’t like doing. It sounds good, it looks good, and it performs well … for a while.  The problem is that most automation tasks rely on one underlying principle. That your data is clean and consistent, that the automation tool can run the same way every time and it is getting quality input .. until it doesn’t! 

 

 

 

The foundation of automation is Data Integrity

We do a lot of work in the accounting and finance industries and I will tell you something right now -  most of the systems we have seen are anything but clean! In one firm with around 100 staff there were over 140,000 issues with client details and matters/assignments, and this was only for their current clients!  

 

This is not uncommon at all. Every time we show how big the issue is (and then prove by showing all the dirty data), firms are genuinely astonished.

 

In fact, there has not been a single firm that we have worked with yet that has 100% accuracy on being able to automate a basic letter (e.g. mail names, postal addresses and salutations 100% correct for all their clients).  No wonder people aren’t automating at the rate they should, their data simply won’t let them!

 

 

 

So what do you do when you are faced with this issue?

Normally we see one of the following five responses:

  • Stick your head in the sand and respond, “It’s not affecting us at the moment!” or even worse, “We don’t have time to clean it at the moment [and we won’t ever find the time]”.

  • The businesses that say, “This is all too hard, let’s get a new system … it will all be better next time … promise!”

  • Produce massive spreadsheets when you are quiet and have your team go through your list, starting from A and making their way through the list. But things got busy when you got to “C”, so you start from “A” again next year!

  • You get a tool that helps you identify your missing data and start cleaning the exceptions throughout the year.

  • You take a look at your data strategy, looking at the ways and types of data you use to eliminate “useless data” and magnify “good data”, then use a tool to help you manage the data exceptions in your practice.

 

Only two of these responses are going to help you move forward, the other three will simply make you keep sliding backwards!

 

Build a plan

So to get started you need to build a plan on how you address this issue. So here are the key steps we look at to build a data integrity plan:

  • Do a map of your management system, splitting it into three categories:

    • Important data that you can’t function without (e.g. client names, addresses, phone numbers);

    • Data that you have in the system in case you want to track something for a client (industry codes etc); and

    • A “what the hell are we tracking that for” list (yep, you know you have something that fits into this list!)

  • Seriously look at the data in categories B & C and decide how much of this data is necessary, and how much of it is nice to have.

  • Look at your business strategy, and your data strategy (you have one of them don’t you??) and figure out where does your data fit in with your business.

  • Look at the waste in your data, how much time does your team spend looking at this data and updating it.

  • Do a comparison of how often you use it and the time it takes to maintain.

  • Focus on finding where this data is missing or incorrect - this is the tricky bit and the hardest part to do well.

  • Clean the exceptions rather than the whole database - clean the important information rather than try and clean everything.

  • Find a way to repeat this daily, not yearly. Data issues happen hourly, so don’t clean once a year and expect results.

 

Get someone to help!

If you don’t have time or the skills in-house get someone to help you, someone who has worked on numerous data integrity initiatives, someone like PT 2.0 (click here to schedule some time to chat about your data integrity strategy).

 

We’ve worked with many firms across Australia and New Zealand to help them see the quality of their data and where it is inconsistent!

 

In fact, we spend so much time helping firms with data integrity issues that we actually wrote an application that works with Reckon APS and MYOB AE (but we can port it to other practice management systems as well) that identifies dodgy data and then highlights what needs to be addressed, in real-time (not hourly, not daily, not weekly, but this instant).

 

Finally,  if you don't have a data and information strategy that fits in with your business strategy please get in contact. Honestly, the biggest impediment to future automation and growth in value is not having your data and strategy aligned!

 

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