When I was younger my father bought me a book to organize pennies from different years to keep in a collection. The book had a specific slot to hold one penny from each year in the collection. When you had completed the collection, you could see an example of each and how the design had changed over the years.
Upon receiving this book, I started pouring over the pennies I already had to begin filling out the collection. I quickly realized I had some problems to deal with.
When I evaluated what I had to work with, I realized I had 3 different categories of pennies. The first were pennies that were in great shape for which I could easily identify the year they were made. The second were pennies that were either worn or dirty to the point where I couldn’t even identify the year. The third category were the pennies I did not yet have that I simply couldn’t add to the collection yet.
After having grouped my pennies into these categories, I got to work building my collection because I knew what I needed to do for each. Group 1 could be added now, group 2 would need to be cleaned, identified then added and group 3 would need to be found first.
Interesting story, but what does this have to do with accounting automation?
Just like the collection I was building, to leverage automation at your firm, you need access to quality data. Today, this data typically falls into one of three categories: available, dark and null.
Available data is accessible and usable. Dark data is data you know you have but isn’t easily accessible (dirty pennies). Null data is the data you know you need in the future, but don’t currently have.
What does this mean our firm will have to do regarding data?
The data you have is immediately available to be used as input to build models and extract information.
Dark data will likely need to be modified (cleaned pennies) before you can use it for this purpose.
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Null data will need to be identified and then found.
How would our firm go about gaining access to the data it doesn’t have?
You firm will need to develop a strategy for sourcing data that it needs but doesn’t have. This might mean purchasing data from external sources or installing sensors so that your firm can start collecting the data. A good first step is to identify the questions you need answered then working backwards from there to determine what data you need but are still missing.
Accounting firms have access to lots of data. This data is going to be a critical element to streamlining your operation AND providing your clients with significantly more value than you do today with the help of automation technologies. The first step in realizing this future vision is ensuring you have all the data in a format that you can use.
Read more about dark data.